From b7817ef95fe5fbda1d171c4ab1378397070cb65e Mon Sep 17 00:00:00 2001 From: Fred Thomas Date: Fri, 5 Jan 2024 18:00:57 +0000 Subject: [PATCH 1/5] Add rules to calculate return periods for people affected by storms --- config/config.yaml | 5 + workflow/Snakefile | 14 ++ .../exposure/electricity_grid/disruption.smk | 198 ++++++++++++++++++ 3 files changed, 217 insertions(+) diff --git a/config/config.yaml b/config/config.yaml index f3864472..f11d1213 100644 --- a/config/config.yaml +++ b/config/config.yaml @@ -122,6 +122,11 @@ wind_grid_resolution_deg: 0.1 # approx 11km latitude # Failure thresholds m/s. These values are the thresholds at which the network assets # are expected to fail based on available literature. transmission_windspeed_failure: [20., 22.5, 25., 27.5, 30., 32.5, 35., 37.5, 40., 42.5, 45., 47.5, 50., 52.5, 55.] +# when plotting, mark this threshold as the central value +best_estimate_windspeed_failure_threshold: 32.5 + +# return periods at which to report +return_period_years: [2, 5, 10, 20, 50, 100, 200, 500, 1000] # whether to plot maximum wind fields and storm track animations for each storm plot_wind: diff --git a/workflow/Snakefile b/workflow/Snakefile index 2e7497f8..5c6c5b88 100644 --- a/workflow/Snakefile +++ b/workflow/Snakefile @@ -14,6 +14,7 @@ import math import os.path from glob import glob +import numpy as np import requests from open_gira.assets import Assets @@ -60,6 +61,19 @@ else: # will raise ValueError in case of mismatch Assets.valid_selection(requested_asset_damage_types) +# check tropical cyclone / grid workflow return period array is valid +TC_RPs = np.array(config["return_period_years"]) +if not np.all(np.diff(TC_RPs) > 0): + raise ValueError("config.return_period_years should be monotonically increasing") +if not np.all(TC_RPs > 0): + raise ValueError("config.return_period_years values must be strictly positive") + +# check transmission wind speed damage thresholds +if not config["best_estimate_windspeed_failure_threshold"] in config["transmission_windspeed_failure"]: + raise ValueError( + "config.transmissions_windspeed_failure must contain config.best_estimate_windspeed_failure_threshold" + ) + # Constrain wildcards to NOT use _ or / wildcard_constraints: DATASET="[^_/]+", diff --git a/workflow/rules/exposure/electricity_grid/disruption.smk b/workflow/rules/exposure/electricity_grid/disruption.smk index c9e12300..92a0cf53 100644 --- a/workflow/rules/exposure/electricity_grid/disruption.smk +++ b/workflow/rules/exposure/electricity_grid/disruption.smk @@ -114,6 +114,204 @@ snakemake --cores 1 -- results/power/by_country/PRI/disruption/IBTrACS/pop_affec """ +rule disruption_pop_affected_return_periods: + """ + Calculate how many people are affected by storms corresponding to given + return periods. Also output the estimated recurrence time for the largest + event of every year in the storm set. + """ + input: + per_event = rules.aggregate_per_event_disruption_across_samples.output, + tracks = "{OUTPUT_DIR}/storm_tracks/{STORM_SET}/tracks.geoparquet", + params: + return_periods = config["return_period_years"] + output: + return_periods_raw = "{OUTPUT_DIR}/power/by_country/{COUNTRY_ISO_A3}/disruption/{STORM_SET}/pop_affected_RP_raw.pq", + return_periods_interpolated = "{OUTPUT_DIR}/power/by_country/{COUNTRY_ISO_A3}/disruption/{STORM_SET}/pop_affected_RP.pq", + run: + import pandas as pd + import numpy as np + + # read in the number of people affected by each event (event rows, threshold columns) + pop_affected = pd.read_parquet(input.per_event) + thresholds: np.ndarray = pop_affected.columns.values.copy() + + tracks = pd.read_parquet(input.tracks, columns=["track_id", "year"]) + tracks: pd.DataFrame = tracks.drop_duplicates("track_id").set_index("track_id") + n_years: int = tracks.year.max() - tracks.year.min() + 1 + + # bring in year data for the storms (common event_id index) + pop_affected: pd.DataFrame = pop_affected.join(tracks) + + # year index, threshold columns, values are event_ids of max pop affected that year + event_ids_of_annual_max: pd.DataFrame = pop_affected.groupby("year").idxmax() + + data_by_threshold: list[pd.DataFrame] = [] + for threshold in thresholds: + + # index into pop_affected data with event_ids of largest disruption per year, sort ascending + df = pd.DataFrame(pop_affected.loc[event_ids_of_annual_max[threshold], threshold]) + + # move speed threshold from column name into vales of new `threshold` column + df = df.rename(columns={threshold: "pop_affected"}) + + # add zero-valued entries for years with no record in the time span + years_with_no_data = pd.DataFrame( + index=pd.Index([f"no_data" for i in range(n_years - len(df))], name="event_id"), + data={"pop_affected": np.zeros(n_years - len(df))} + ) + # sort to ascending pop_affected + df = pd.concat([df, years_with_no_data]).sort_values("pop_affected") + + # store threshold as data (will be set as index later) + df["threshold"] = threshold + + # calculate recurrence intervals using 'plotting position' formula + # most impactful event gets rank 1 + df["rank"] = range(n_years, 0, -1) + + # T = n + 1 / m, where T is expected value of return period, n is number of observations and m observation rank + # for a derivation of this formula, see Gumbel 1958, ยง2.1.4 or Makkonen 2006 + # N.B. this is valid for any underlying distribution + df["return_period_years"] = (n_years + 1) / df["rank"] + + # the Annual Exceedance Probability, AEP, is 1 / T + + df = df.reset_index().set_index(["threshold", "event_id"]) + + data_by_threshold.append(df) + + # write out raw return periods as calculated for the largest event in each year + data = pd.concat(data_by_threshold) + data.to_parquet(output.return_periods_raw) + + # interpolate between the raw events to find population affected for a given set of return periods + interpolated_RP_by_threshold = [] + for threshold in thresholds: + df = pd.DataFrame( + { + "threshold": threshold, + "return_period_years": params.return_periods, + # note that numpy interp expects the x grid, i.e. + # return_period_years data to be monotonically increasing + "pop_affected": np.interp( + params.return_periods, + data.xs(threshold, level="threshold")["return_period_years"], + data.xs(threshold, level="threshold")["pop_affected"] + ) + } + ) + interpolated_RP_by_threshold.append(df) + + interpolated_RP = pd.concat(interpolated_RP_by_threshold).set_index(["threshold", "return_period_years"]) + interpolated_RP.to_parquet(output.return_periods_interpolated) + +""" +Test with: +snakemake -c1 -- results/power/by_country/PRI/disruption/STORM-constant/pop_affected_RP.pq +""" + + +rule plot_pop_affected_return_periods: + """ + Plot population affected as a function of return period. + """ + input: + return_periods = rules.disruption_pop_affected_return_periods.output.return_periods_raw + params: + best_estimate_threshold = config["best_estimate_windspeed_failure_threshold"] + output: + plot = "{OUTPUT_DIR}/power/by_country/{COUNTRY_ISO_A3}/disruption/{STORM_SET}/pop_affected_RP.png", + run: + import matplotlib + import matplotlib.pyplot as plt + import numpy as np + import pandas as pd + + matplotlib.use("Agg") + + f, ax = plt.subplots(figsize=(12,6)) + + data_by_threshold = pd.read_parquet(input.return_periods) + thresholds = np.array(list(map(float, data_by_threshold.index.get_level_values(level="threshold").unique()))) + max_delta = np.max(np.abs(thresholds - params.best_estimate_threshold)) + + cmap = matplotlib.colormaps["magma"] + for threshold in thresholds: + + delta = np.abs(threshold - params.best_estimate_threshold) + + threshold_str = f"{threshold:.1f}" + df = data_by_threshold.xs(threshold_str, level="threshold") + + if threshold == params.best_estimate_threshold: + line_style = "--" + else: + line_style = "-" + ax.step( + df["return_period_years"], + df["pop_affected"], + label=f"{threshold_str}", + color=cmap(delta / max_delta), + ls=line_style, + ) + + ax.set_xscale("log") + ax.set_xlabel("Return period [years]", labelpad=10) + + ax.set_ylabel(f"Population affected", labelpad=10) + + ax.grid(alpha=0.4, which="both") + plt.subplots_adjust(right=0.8) + ax.legend( + title="Threshold [ms-1]", + fontsize=8, + bbox_to_anchor=(1.02, 1.0), + loc='upper left' + ) + ax.set_title(f"{wildcards.COUNTRY_ISO_A3}: {wildcards.STORM_SET}") + + f.savefig(output.plot) + +""" +Test with: +snakemake -c1 -- results/power/by_country/PRI/disruption/STORM-constant/pop_affected_RP.png +""" + + +def pop_affected_return_periods_plot_path(wildcards) -> list[str]: + """ + Return a list of paths, one for each country. + """ + import json + + country_set_path = f"{wildcards.OUTPUT_DIR}/power/by_storm_set/{wildcards.STORM_SET}/countries_impacted.json" + with open(country_set_path, "r") as fp: + countries = json.load(fp) + + return expand( + "{OUTPUT_DIR}/power/by_country/{COUNTRY_ISO_A3}/disruption/{STORM_SET}/pop_affected_RP.png", + OUTPUT_DIR=wildcards.OUTPUT_DIR, + COUNTRY_ISO_A3=countries, + STORM_SET=wildcards.STORM_SET, + ) + +rule plot_pop_affected_return_periods_storm_set: + """" + Target rule for population affected as a function of return period plots for + all countries affected by STORM_SET. + """ + input: + plot_paths = pop_affected_return_periods_plot_path, + output: + flag = touch("{OUTPUT_DIR}/power/by_storm_set/{STORM_SET}/pop_affected_RP_plots.flag") + +""" +Test with: +snakemake -c1 -- results/power/by_storm_set/STORM-constant/pop_affected_RP_plots.flag +""" + + def disruption_per_target_sample_files(wildcards) -> list[str]: """ Return a list of paths, one for each sample. From 14ff6df343afeff1d345136e0bbb403463424c36 Mon Sep 17 00:00:00 2001 From: Fred Thomas Date: Mon, 22 Jan 2024 16:45:43 +0000 Subject: [PATCH 2/5] Remove validation work from this repository --- validation/compare_wind_models.ipynb | 15055 ---------------- validation/iso_codes.csv | 257 - validation/map_outages.ipynb | 1044 -- validation/observed_outages/2005236N23285.csv | 2 - validation/observed_outages/2005261N21290.csv | 2 - validation/observed_outages/2005289N18282.csv | 2 - validation/observed_outages/2008238N13293.csv | 2 - validation/observed_outages/2008245N17323.csv | 3 - validation/observed_outages/2011028S13180.csv | 2 - validation/observed_outages/2011233N15301.csv | 2 - validation/observed_outages/2012296N14283.csv | 2 - validation/observed_outages/2013018S14138.csv | 2 - validation/observed_outages/2013306N07162.csv | 2 - validation/observed_outages/2014092S11159.csv | 2 - validation/observed_outages/2014190N08154.csv | 2 - validation/observed_outages/2015293N13266.csv | 2 - validation/observed_outages/2016242N24279.csv | 2 - validation/observed_outages/2016253N13144.csv | 3 - validation/observed_outages/2016273N13300.csv | 3 - validation/observed_outages/2017228N14314.csv | 3 - validation/observed_outages/2017242N16333.csv | 5 - validation/observed_outages/2017260N12310.csv | 2 - validation/observed_outages/2018073S09129.csv | 2 - validation/observed_outages/2018242N13343.csv | 2 - validation/observed_outages/2018280N18273.csv | 2 - validation/observed_outages/2018292N14261.csv | 2 - validation/observed_outages/2020136N10088.csv | 2 - validation/observed_outages/2020211N13306.csv | 2 - validation/observed_outages/2022255N15324.csv | 3 - validation/observed_outages/2022263N10313.csv | 2 - validation/outage_model_validation.csv | 241 - validation/outage_model_validation.ipynb | 1166 -- .../undesa_pd_2022_hh-size-composition.xlsx | Bin 342176 -> 0 bytes 33 files changed, 17825 deletions(-) delete mode 100644 validation/compare_wind_models.ipynb delete mode 100644 validation/iso_codes.csv delete mode 100644 validation/map_outages.ipynb delete mode 100644 validation/observed_outages/2005236N23285.csv delete mode 100644 validation/observed_outages/2005261N21290.csv delete mode 100644 validation/observed_outages/2005289N18282.csv delete mode 100644 validation/observed_outages/2008238N13293.csv delete mode 100644 validation/observed_outages/2008245N17323.csv delete mode 100644 validation/observed_outages/2011028S13180.csv delete mode 100644 validation/observed_outages/2011233N15301.csv delete mode 100644 validation/observed_outages/2012296N14283.csv delete mode 100644 validation/observed_outages/2013018S14138.csv delete mode 100644 validation/observed_outages/2013306N07162.csv delete mode 100644 validation/observed_outages/2014092S11159.csv delete mode 100644 validation/observed_outages/2014190N08154.csv delete mode 100644 validation/observed_outages/2015293N13266.csv delete mode 100644 validation/observed_outages/2016242N24279.csv delete mode 100644 validation/observed_outages/2016253N13144.csv delete mode 100644 validation/observed_outages/2016273N13300.csv delete mode 100644 validation/observed_outages/2017228N14314.csv delete mode 100644 validation/observed_outages/2017242N16333.csv delete mode 100644 validation/observed_outages/2017260N12310.csv delete mode 100644 validation/observed_outages/2018073S09129.csv delete mode 100644 validation/observed_outages/2018242N13343.csv delete mode 100644 validation/observed_outages/2018280N18273.csv delete mode 100644 validation/observed_outages/2018292N14261.csv delete mode 100644 validation/observed_outages/2020136N10088.csv delete mode 100644 validation/observed_outages/2020211N13306.csv delete mode 100644 validation/observed_outages/2022255N15324.csv delete mode 100644 validation/observed_outages/2022263N10313.csv delete mode 100644 validation/outage_model_validation.csv delete mode 100644 validation/outage_model_validation.ipynb delete mode 100644 validation/undesa_pd_2022_hh-size-composition.xlsx diff --git a/validation/compare_wind_models.ipynb b/validation/compare_wind_models.ipynb deleted file mode 100644 index b88e66e2..00000000 --- a/validation/compare_wind_models.ipynb +++ /dev/null @@ -1,15055 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "ff0b1de4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'\\nCompare the output of our wind model (Holland, downscaled with local surface roughness)\\nagainst the footprints of Done et al. (Willougby with numerical boundary layer simulation)\\n'" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "\"\"\"\n", - "Compare the output of our wind model (Holland, downscaled with local surface roughness)\n", - "against the footprints of Done et al. (Willougby with numerical boundary layer simulation)\n", - "\"\"\"" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "837f092b", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_868937/4090681641.py:2: UserWarning: Shapely 2.0 is installed, but because PyGEOS is also installed, GeoPandas will still use PyGEOS by default for now. To force to use and test Shapely 2.0, you have to set the environment variable USE_PYGEOS=0. You can do this before starting the Python process, or in your code before importing geopandas:\n", - "\n", - "import os\n", - "os.environ['USE_PYGEOS'] = '0'\n", - "import geopandas\n", - "\n", - "In a future release, GeoPandas will switch to using Shapely by default. If you are using PyGEOS directly (calling PyGEOS functions on geometries from GeoPandas), this will then stop working and you are encouraged to migrate from PyGEOS to Shapely 2.0 (https://shapely.readthedocs.io/en/latest/migration_pygeos.html).\n", - " import geopandas as gpd\n" - ] - } - ], - "source": [ - "import pandas as pd\n", - "import geopandas as gpd\n", - "import xarray as xr\n", - "import matplotlib\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.ticker as ticker\n", - "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", - "import numpy as np\n", - "import shapely\n", - "\n", - "import os\n", - "from glob import glob" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "f03f2f12", - "metadata": {}, - "outputs": [], - "source": [ - "def grid_point_data(point_speeds: gpd.GeoDataFrame, col_name: str, agg_func_name: str, delta: float = 0.1) -> gpd.GeoDataFrame:\n", - " \"\"\"\n", - " Bin data on a regular grid. Grid will snap to integer number of `delta` from CRS reference.\n", - " \n", - " Args:\n", - " point_speeds: Table of data at point locations\n", - " col_name: Data column to rebin\n", - " agg_func: Name of function to apply to multiple points within a bin, e.g. max, mean\n", - " delta: Width and height of output raster pixels in decimal degrees\n", - " \"\"\"\n", - " \n", - " def n_cells(start: float, end: float, width: float) -> int:\n", - " return round((end - start) / width)\n", - "\n", - " # create grid\n", - "\n", - " # unpack and snap extrema to integer number of cells from CRS reference\n", - " min_x, min_y, max_x, max_y = map(lambda x: np.ceil(x / delta) * delta, point_speeds.total_bounds)\n", - "\n", - " cells = []\n", - " for x0 in np.linspace(min_x, max_x, n_cells(min_x, max_x, delta) + 1):\n", - " x1 = x0 + delta\n", - " for y0 in np.linspace(min_y, max_y, n_cells(min_y, max_y, delta) + 1):\n", - " y1 = y0 + delta\n", - " cells.append(shapely.geometry.box(x0, y0, x1, y1))\n", - "\n", - " grid = gpd.GeoDataFrame({\"geometry\": cells})\n", - "\n", - " # associate points with grid\n", - " raster = grid.sjoin(point_speeds, how=\"inner\")\n", - "\n", - " # take aggregate of arbitrary number of rows (points) grouped by cell\n", - " agg_func = getattr(raster.groupby(raster.index), agg_func_name)\n", - " aggregated = agg_func(col_name)\n", - " \n", - " # merge geometry back in, how=\"right\" for every grid cell, empty or not\n", - " rebinned = aggregated.merge(grid[[\"geometry\"]], left_index=True, right_index=True, how=\"right\")\n", - " rebinned = rebinned.drop(columns=[\"index_right\"])\n", - " \n", - " # cast to GeoDataFrame again (merge reverted to DataFrame) and return\n", - " return gpd.GeoDataFrame(rebinned)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "daf9c8f8", - "metadata": {}, - "outputs": [], - "source": [ - "def to_xarray(cells: gpd.GeoDataFrame) -> xr.Dataset:\n", - " \"\"\"\n", - " Given table of polygon cells, export to xarray\n", - " \"\"\"\n", - " to_export = cells\n", - " to_export[\"longitude\"] = to_export.geometry.centroid.x\n", - " to_export[\"latitude\"] = to_export.geometry.centroid.y\n", - " to_export = to_export.drop(columns=[\"geometry\"])\n", - " to_export = to_export.set_index([\"longitude\", \"latitude\"])\n", - " return to_export.to_xarray()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "77bc16b2", - "metadata": {}, - "outputs": [], - "source": [ - "def read_kw01(name_year: str, delta: float) -> gpd.GeoDataFrame:\n", - " \"\"\"\n", - " Read the KW01 data, wrangle as points in GeoDataFrame\n", - " \n", - " Args:\n", - " name_year: Storm identifier, e.g. IRMA_2017 or IKE_2008\n", - " delta: Grid resolution to return at in decimal degrees\n", - " \"\"\"\n", - " \n", - " data = pd.concat(\n", - " [\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - " for path in glob(f\"/home/fred/projects/WRN_TC_footprints/footprints/regions/*/{name_year}/*.txt\")\n", - " ]\n", - " )\n", - " point_speeds = gpd.GeoDataFrame(\n", - " {\n", - " \"max_wind_speed\": data[\"wind(m/s)\"],\n", - " \"geometry\": gpd.points_from_xy(data.lon, data.lat)\n", - " }\n", - " )\n", - "\n", - " return to_xarray(grid_point_data(point_speeds, \"max_wind_speed\", \"max\", delta=delta))" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "2b78df95", - "metadata": {}, - "outputs": [], - "source": [ - "def fig_size(\n", - " min_x: float,\n", - " min_y: float,\n", - " max_x: float,\n", - " max_y: float,\n", - " max_width_in: float = 16,\n", - " max_height_in: float = 9\n", - ") -> tuple[float, float]:\n", - " \"\"\"\n", - " Given bounding box, calculate size of figure in inches for equal aspect ratio.\n", - " \n", - " Returns:\n", - " width in inches, height in inches\n", - " \"\"\"\n", - " x_span = max_x - min_x\n", - " y_span = max_y - min_y\n", - " aspect_ratio = y_span / x_span\n", - " max_plot_width_in = 16\n", - " max_plot_height_in = 9\n", - "\n", - " if max_plot_width_in * aspect_ratio < max_plot_height_in:\n", - " # tall\n", - " x_in = max_plot_width_in\n", - " y_in = max_plot_width_in * aspect_ratio\n", - "\n", - " else:\n", - " # wide\n", - " x_in = max_plot_height_in / aspect_ratio\n", - " y_in = max_plot_height_in\n", - " \n", - " return x_in, y_in" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "1468f85a", - "metadata": {}, - "outputs": [], - "source": [ - "def name_year_from_id(tracks: gpd.GeoDataFrame, storm_id: str) -> str:\n", - " \"\"\"\n", - " Given IBTrACS storm ID, return name_year.\n", - " e.g. \"2017242N16333\" -> \"IRMA_2017\"\n", - " \"\"\"\n", - " storm_track = tracks[tracks.track_id==storm_id]\n", - " track_point = storm_track.iloc[0]\n", - " name = track_point[\"name\"]\n", - " year = track_point[\"year\"]\n", - " return f\"{name}_{year}\"\n", - "\n", - "def id_from_name_year(tracks: gpd.GeoDataFrame, name_year: str) -> str | None:\n", - " \"\"\"\n", - " Given name_year, return IBTrACS storm ID.\n", - " e.g. \"IRMA_2017\" -> \"2017242N16333\"\n", - " \"\"\"\n", - " try:\n", - " name, year = name_year.split(\"_\")\n", - " except ValueError:\n", - " print(f\"skipping {name_year}...\")\n", - " return None\n", - " track = tracks[(tracks.name==name) & (tracks.year==int(year))]\n", - " try:\n", - " storm_id, = set(track.track_id)\n", - " except ValueError:\n", - " print(f\"{name_year} is ambiguous: {set(track.track_id)}, skipping...\")\n", - " return None\n", - " return storm_id" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "3dbcc465", - "metadata": {}, - "outputs": [], - "source": [ - "def clip_field_to_buffered_points(\n", - " points: gpd.GeoDataFrame,\n", - " field: xr.DataArray,\n", - " buffer_radius_km: float = 0,\n", - ") -> xr.Dataset:\n", - " \"\"\"\n", - " Clip `field` to spatial extent of a buffer around `points`.\n", - " \n", - " Args:\n", - " points: Must include `geometry` column of points.\n", - " field: Longitude latitude data array to clip extent of.\n", - " buffer_radius_km: Only return field within this proximity to points.\n", - " \"\"\"\n", - " \n", - " # make a buffer around the points\n", - " # N.B. using web mercator as geographic CRS, so extremely wrong for non-tropical latitudes\n", - " points_m = points.to_crs(3857)\n", - " buffer = points_m.buffer(buffer_radius_km * 1000).to_crs(4326)\n", - " \n", - " # get the unary_union of point buffers\n", - " aoi = gpd.GeoDataFrame(geometry=[buffer.unary_union])\n", - "\n", - " # get the field as geopandas points\n", - " field_pandas = field.to_dataframe().reset_index()\n", - " field_geopandas = gpd.GeoDataFrame(\n", - " {\n", - " field.name: field_pandas[field.name],\n", - " \"geometry\": gpd.points_from_xy(\n", - " field_pandas.longitude,\n", - " field_pandas.latitude\n", - " )\n", - " } \n", - " ).set_crs(4326)\n", - "\n", - " # find the field values within the AOI \n", - " clipped_field = field_geopandas.sjoin(aoi, how=\"inner\")[[field.name, \"geometry\"]].copy()\n", - " \n", - " # recast as xarray field\n", - " #clipped_field.geometry = clipped_field.geometry.drop_duplicates() # shouldn't be necessary?\n", - " clipped_field[\"latitude\"] = clipped_field.geometry.y\n", - " clipped_field[\"longitude\"] = clipped_field.geometry.x\n", - " clipped_field = clipped_field.drop(columns=[\"geometry\"])\n", - " clipped_field = clipped_field.set_index([\"longitude\", \"latitude\"])\n", - " \n", - " return clipped_field.to_xarray()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "6f408a65", - "metadata": {}, - "outputs": [], - "source": [ - "def plot_error(\n", - " errors: np.ndarray,\n", - " buffer_km: float,\n", - " filepath: str\n", - ") -> None:\n", - " \"\"\"\n", - " Plot distribution of wind speed errors w.r.t Done et al.\n", - " \n", - " pooled_ratio: 1D array of ratios to bin.\n", - " \"\"\"\n", - "\n", - " f, ax = plt.subplots(figsize=(8, 5))\n", - "\n", - " mean = np.nanmean(errors)\n", - " median = np.nanmedian(errors)\n", - " n = len(errors)\n", - "\n", - " ax.set_title(\n", - " (\n", - " \"Wind model validation against Done et al.\\n\"\n", - " f\"for pixels < {buffer_km}km from eye\\n\"\n", - " f\"$n_{{pixels}}={n}, \\ \\mu={mean:.2f} $ms$^{{-1}}, \\ q_{{50}}={median:.2f}$ms$^{{-1}}$\"\n", - " ),\n", - " pad=15\n", - " )\n", - " ax.set_xlabel(\"Errors: downscaled Holland $-$ Done et al. [ms$^{-1}$]\", labelpad=10)\n", - " ax.set_ylabel(\"Frequency\", labelpad=10)\n", - "\n", - " frequency, bin_edges, _ = ax.hist(\n", - " errors,\n", - " bins=np.linspace(-100, 100, 201),\n", - " color=\"g\",\n", - " alpha=0.5,\n", - " density=True,\n", - " label=\"PDF\"\n", - " )\n", - "\n", - " ax.axvline(mean, color=\"r\", ls=\"--\", label=\"Mean\", alpha=0.5)\n", - " miny, maxy = ax.get_ylim()\n", - " for probability_level in [0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95]:\n", - " quantile = np.quantile(errors, probability_level)\n", - " ax.axvline(quantile, color=\"pink\", ls=\"--\", alpha=0.6)\n", - " ax.text(\n", - " quantile,\n", - " 0.07 * maxy,\n", - " f\"$\\mathrm{{q}}_{{{probability_level:.2f}}}$\",\n", - " rotation=-90,\n", - " ha=\"center\",\n", - " size=9\n", - " )\n", - "\n", - " ax.set_xlim(-20, 20)\n", - " ax.grid(alpha=0.3)\n", - " ax.legend()\n", - " plt.subplots_adjust(top=0.8, bottom=0.15)\n", - "\n", - " f.savefig(filepath)\n", - " plt.close(f)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "94156616", - "metadata": {}, - "outputs": [], - "source": [ - "def plot_wind_speed_errors(\n", - " name_year: str,\n", - " storm_id: str,\n", - " buffer_km: str,\n", - " holland: xr.Dataset,\n", - " clipped_error: xr.Dataset,\n", - " plot_dir: str,\n", - ") -> None:\n", - "\n", - " model_arr = holland.sel(\n", - " dict(\n", - " longitude=clipped_error.longitude,\n", - " latitude=clipped_error.latitude\n", - " )\n", - " ).max_wind_speed.values.ravel()\n", - " error_arr = clipped_error.error.values.ravel()\n", - "\n", - " f, (ax_scatter, ax_hist) = plt.subplots(2, 1, sharex=True, gridspec_kw={'height_ratios': [3, 1]})\n", - " ax_scatter.scatter(error_arr, model_arr, s=0.1, c=\"k\")\n", - " ax_scatter.set_ylabel(\"Model wind speed [ms$^{-1}$]\")\n", - " ax_scatter.grid(alpha=0.3)\n", - " x_min = -20\n", - " x_max = 20\n", - " ax_scatter.set_xlim(x_min, x_max)\n", - " ax_scatter.axvline(0, color=\"k\", ls=\"--\", alpha=0.8)\n", - "\n", - " frequency, bin_edges, patches = ax_hist.hist(\n", - " error_arr,\n", - " bins=np.linspace(-50, 50, 150),\n", - " density=True,\n", - " alpha=1,\n", - " color=\"black\"\n", - " )\n", - " \n", - " ax_hist.axvline(0, color=\"k\", ls=\"--\", alpha=0.8)\n", - " ax_hist.set_xlim(x_min, x_max)\n", - " ax_hist.set_ylabel(\"PDF\", labelpad=20)\n", - " ax_hist.set_xlabel(\"Thomas et al. 2023 - Done et al. 2020 [ms$^{-1}$]\")\n", - " ax_hist.spines['top'].set_visible(False)\n", - " ax_hist.spines['right'].set_visible(False)\n", - " ax_hist.spines['left'].set_visible(False)\n", - " ax_hist.get_yaxis().set_ticks([])\n", - "\n", - " f.suptitle(f\"{name_year.replace('_', ' ')} / {storm_id}\\nError within {buffer_km}km of eye over land\")\n", - " f.savefig(os.path.join(plot_dir, f\"{storm_id}_error_distribution.png\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "9214b29e", - "metadata": {}, - "outputs": [], - "source": [ - "def plot_wind_speed_maps(\n", - " name_year: str,\n", - " storm_id: str,\n", - " holland: xr.Dataset,\n", - " kw01: xr.Dataset,\n", - " error: xr.Dataset,\n", - " plot_dir: str,\n", - ") -> None:\n", - "\n", - " f, (ax_h, ax_kw, ax_error) = plt.subplots(1, 3, figsize=(12,5))\n", - "\n", - " vmax = max(holland.max_wind_speed.max(), kw01.max_wind_speed.max()).values\n", - " vmin = min(holland.max_wind_speed.min(), kw01.max_wind_speed.min()).values\n", - "\n", - " xr.plot.pcolormesh(\n", - " error,\n", - " x=\"longitude\",\n", - " ax=ax_error,\n", - " cbar_kwargs={'label': \"Thomas $-$ Done [ms$^{-1}$]\"},\n", - " )\n", - " ax_error.set_title(\"Thomas et al. 2023 - Done et al. 2020\")\n", - " xmin, xmax = ax_error.get_xlim()\n", - " ymin, ymax = ax_error.get_ylim()\n", - "\n", - " xr.plot.pcolormesh(\n", - " holland.max_wind_speed,\n", - " x=\"longitude\",\n", - " ax=ax_h,\n", - " vmax=vmax,\n", - " vmin=vmin,\n", - " cbar_kwargs={'label': \"Max wind speed [ms$^{-1}$]\"}\n", - " )\n", - " ax_h.set_title(\"Thomas et al. 2023\\nSurface roughness downscaling\")\n", - " ax_h.set_xlim(xmin, xmax)\n", - " ax_h.set_ylim(ymin, ymax)\n", - "\n", - " xr.plot.pcolormesh(\n", - " kw01.max_wind_speed,\n", - " x=\"longitude\",\n", - " ax=ax_kw,\n", - " vmax=vmax,\n", - " vmin=vmin,\n", - " cbar_kwargs={'label': \"Max wind speed [ms$^{-1}$]\"}\n", - " )\n", - " ax_kw.set_title(\"Done et al. 2020\\nKepert & Wang physical boundary layer\")\n", - " ax_kw.set_xlim(xmin, xmax)\n", - " ax_kw.set_ylim(ymin, ymax)\n", - "\n", - " for ax in (ax_h, ax_kw, ax_error):\n", - " ax.set_xlabel(\"Longitude\")\n", - " ax.set_ylabel(\"Latitude\")\n", - "\n", - " f.suptitle(f\"{name_year.replace('_', ' ')} / {storm_id}\")\n", - " plt.subplots_adjust(left=0.05, right=0.9, wspace=0.4, top=0.85, bottom=0.1)\n", - " f.savefig(os.path.join(plot_dir, f\"{storm_id}_max_wind_speed_maps.png\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "9cfebae6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "skipping NOT_NAMED_2006...\n", - "TOMAS_2010 is ambiguous: {'2010069S12188', '2010302N09306'}, skipping...\n", - "skipping NOT_NAMED_2011...\n", - "skipping NOT_NAMED_2005...\n", - "skipping NOT_NAMED_2010...\n", - "skipping NOT_NAMED_2017...\n", - "skipping NOT_NAMED_2007...\n", - "skipping NOT_NAMED_2003...\n", - "skipping NOT_NAMED_2014...\n", - "skipping NOT_NAMED_2013...\n", - "HARVEY_2005 is ambiguous: {'2005215N28291', '2005035S14136'}, skipping...\n", - "skipping NOT_NAMED_2016...\n", - "JOYCE_2018 is ambiguous: {'2018007S13130', '2018255N37320'}, skipping...\n", - "skipping NOT_NAMED_2002...\n", - "PODUL_2019 is ambiguous: {'2019237N08140', '2019236N08143'}, skipping...\n", - "len(holland_storms_name_year)=1236\n", - "len(wrn_storms_name_year)=743\n", - "len(common_storms)=586\n" - ] - } - ], - "source": [ - "tracks = gpd.read_parquet(\n", - " \"/home/fred/projects/open_gira/open-gira/results/storm_tracks/IBTrACS/tracks.geoparquet\"\n", - ")\n", - "holland_storms_id = {\n", - " path.split(\"/\")[-1] for path in\n", - " glob(\"/home/fred/projects/open_gira/open-gira/results/power/by_storm_set/IBTrACS/by_storm/*\")\n", - "}\n", - "holland_storms_name_year = {\n", - " name_year_from_id(tracks, storm_id) for storm_id in\n", - " holland_storms_id\n", - "}\n", - "wrn_storms_name_year = {\n", - " path.split(\"/\")[-2] for path in\n", - " glob(f\"/home/fred/projects/WRN_TC_footprints/footprints/regions/*/*/*.txt\")\n", - "}\n", - "common_storms_name_year = holland_storms_name_year & wrn_storms_name_year\n", - "common_storms_id = [\n", - " id_from_name_year(tracks, name_year)\n", - " for name_year in common_storms_name_year\n", - "]\n", - "common_storms = sorted(filter(bool, common_storms_id))\n", - "\n", - "print(f\"{len(holland_storms_name_year)=}\")\n", - "print(f\"{len(wrn_storms_name_year)=}\")\n", - "print(f\"{len(common_storms)=}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "7d44d9a7", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ALLISON_2001\n", - "ALLISON_2001 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "YUTU_2001\n", - "YUTU_2001 has 38.22004631968363, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TORAJI_2001\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BARRY_2001\n", - "BARRY_2001 has 30.863999999999997, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PABUK_2001\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DEAN_2001\n", - "DEAN_2001 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FITOW_2001\n", - "FITOW_2001 has 20.956774554577542, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DANAS_2001\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NARI_2001\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GABRIELLE_2001\n", - "GABRIELLE_2001 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LEKIMA_2001\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IRIS_2001\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAREN_2001\n", - "KAREN_2001 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MICHELLE_2001\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LINGLING_2001\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BERNIE_2002\n", - "BERNIE_2002 has 26.226606060606056, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TAPAH_2002\n", - "TAPAH_2002 has 21.47117455457754, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHRIS_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GUILLAUME_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HARY_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BONNIE_2002\n", - "BONNIE_2002 has 26.09995454545454, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KESINY_2002\n", - "KESINY_2002 has 37.08940909090909, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOGURI_2002\n", - "NOGURI_2002 has 38.9168371782115, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHATAAN_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RAMMASUN_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HALONG_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NAKRI_2002\n", - "NAKRI_2002 has 21.812298946294167, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FENGSHEN_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FUNG-WONG_2002\n", - "FUNG-WONG_2002 has 37.696098520219415, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAMMURI_2002\n", - "KAMMURI_2002 has 28.903328210230892, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "VONGFONG_2002\n", - "VONGFONG_2002 has 25.622069434876895, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RUSA_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SINLAKU_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EDOUARD_2002\n", - "EDOUARD_2002 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FAY_2002\n", - "FAY_2002 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAGUPIT_2002\n", - "HAGUPIT_2002 has 25.374433639494832, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GUSTAV_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HANNA_2002\n", - "HANNA_2002 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ISIDORE_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MEKKHALA_2002\n", - "MEKKHALA_2002 has 23.778423809159328, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KYLE_2002\n", - "KYLE_2002 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LILI_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HIGOS_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JULIO_2002\n", - "JULIO_2002 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KENNA_2002\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DELFINA_2002\n", - "DELFINA_2002 has 28.847318181818178, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FARI_2003\n", - "FARI_2003 has 28.847318181818178, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GRAHAM_2003\n", - "GRAHAM_2003 has 21.978909090909088, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JAPHET_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CRAIG_2003\n", - "CRAIG_2003 has 24.726272727272725, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "INIGO_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MANOU_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LINFA_2003\n", - "LINFA_2003 has 28.137470014032402, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SOUDELOR_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CARLOS_2003\n", - "CARLOS_2003 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BILL_2003\n", - "BILL_2003 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CLAUDETTE_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IMBUDO_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KONI_2003\n", - "KONI_2003 has 32.6474124633244, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ETAU_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MORAKOT_2003\n", - "MORAKOT_2003 has 24.169393073096057, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KROVANH_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ERIKA_2003\n", - "ERIKA_2003 has 33.436, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "VAMCO_2003\n", - "VAMCO_2003 has 20.75984708933963, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IGNACIO_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DUJUAN_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAEMI_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HENRI_2003\n", - "HENRI_2003 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ISABEL_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARTY_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LARRY_2003\n", - "LARRY_2003 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NORA_2003\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OLAF_2003\n", - "OLAF_2003 has 33.436, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MINDY_2003\n", - "MINDY_2003 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MELOR_2003\n", - "MELOR_2003 has 30.556493596121953, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NEPARTAK_2003\n", - "NEPARTAK_2003 has 35.26281885954841, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CELA_2003\n", - "CELA_2003 has 36.47563636363637, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ODETTE_2003\n", - "ODETTE_2003 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DEBBIE_2003\n", - "DEBBIE_2003 has 35.71572727272727, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ELITA_2004\n", - "ELITA_2004 has 35.501393939393935, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FRITZ_2004\n", - "FRITZ_2004 has 24.52752727272727, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MONTY_2004\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GAFILO_2004\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NIDA_2004\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHARLEY_2004\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FRANCES_2004\n", - "FRANCES_2004 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ERNEST_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FELAPI_2005\n", - "FELAPI_2005 has 20.459090909090907, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "INGRID_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ADRIAN_2005\n", - "ADRIAN_2005 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ARLENE_2005\n", - "ARLENE_2005 has 30.863999999999997, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DORA_2005\n", - "DORA_2005 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CINDY_2005\n", - "CINDY_2005 has 33.436, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DENNIS_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EMILY_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAITANG_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BANYAN_2005\n", - "BANYAN_2005 has 30.34216026278862, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GERT_2005\n", - "GERT_2005 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WASHI_2005\n", - "WASHI_2005 has 23.364474205893607, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MATSA_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SANVU_2005\n", - "SANVU_2005 has 30.118818859548412, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAWAR_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JOSE_2005\n", - "JOSE_2005 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KATRINA_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TALIM_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NABI_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KHANUN_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OPHELIA_2005\n", - "OPHELIA_2005 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "VICENTE_2005\n", - "VICENTE_2005 has 23.835579364714885, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RITA_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DAMREY_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LONGWANG_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OTIS_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "STAN_2005\n", - "STAN_2005 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TAMMY_2005\n", - "TAMMY_2005 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WILMA_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ALPHA_2005\n", - "ALPHA_2005 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BETA_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAI-TAK_2005\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TEMBIN_2005\n", - "TEMBIN_2005 has 23.014352681039245, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BOLAVEN_2005\n", - "BOLAVEN_2005 has 33.81906854190585, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GAMMA_2005\n", - "GAMMA_2005 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FANOOS_2005\n", - "FANOOS_2005 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DARYL_2006\n", - "DARYL_2006 has 28.847318181818178, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LARRY_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GLENDA_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MONICA_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MALA_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHANCHU_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ALBERTO_2006\n", - "ALBERTO_2006 has 30.863999999999997, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EWINIAR_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BILIS_2006\n", - "BILIS_2006 has 30.23312997065952, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAEMI_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BERYL_2006\n", - "BERYL_2006 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PRAPIROON_2006\n", - "PRAPIROON_2006 has 37.39129076412807, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHRIS_2006\n", - "CHRIS_2006 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SAOMAI_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARIA_2006\n", - "MARIA_2006 has 35.80005483352468, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BOPHA_2006\n", - "BOPHA_2006 has 26.537114458476843, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WUKONG_2006\n", - "WUKONG_2006 has 26.251336680699065, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ERNESTO_2006\n", - "ERNESTO_2006 has 33.436, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JOHN_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LANE_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "XANGSANE_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PAUL_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CIMARON_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHEBI_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DURIAN_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "UTOR_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BONDO_2006\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NELSON_2007\n", - "NELSON_2007 has 27.47363636363636, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FAVIO_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JACOB_2007\n", - "JACOB_2007 has 39.429539393939386, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "INDLALA_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KARA_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JAYA_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "AKASH_2007\n", - "AKASH_2007 has 33.436, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BARBARA_2007\n", - "BARBARA_2007 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GONU_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BARRY_2007\n", - "BARRY_2007 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAN-YI_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "USAGI_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PABUK_2007\n", - "PABUK_2007 has 34.17686330399285, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SEPAT_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DEAN_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FITOW_2007\n", - "FITOW_2007 has 39.62509852021942, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HENRIETTE_2007\n", - "HENRIETTE_2007 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FELIX_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GABRIELLE_2007\n", - "GABRIELLE_2007 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NARI_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HUMBERTO_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WIPHA_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FRANCISCO_2007\n", - "FRANCISCO_2007 has 20.66918783518306, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LORENZO_2007\n", - "LORENZO_2007 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LEKIMA_2007\n", - "LEKIMA_2007 has 34.533512986350296, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KROSA_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOEL_2007\n", - "NOEL_2007 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PEIPAH_2007\n", - "PEIPAH_2007 has 39.10595743079474, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SIDR_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAGIBIS_2007\n", - "HAGIBIS_2007 has 39.05354296466386, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MITAG_2007\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OLGA_2007\n", - "OLGA_2007 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HELEN_2007\n", - "HELEN_2007 has 26.889090909090907, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FAME_2008\n", - "FAME_2008 has 38.98918181818182, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IVAN_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JOKWE_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NEOGURI_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NARGIS_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HALONG_2008\n", - "HALONG_2008 has 33.31952997065952, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ALMA_2008\n", - "ALMA_2008 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FENGSHEN_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KALMAEGI_2008\n", - "KALMAEGI_2008 has 38.086277055746905, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CRISTOBAL_2008\n", - "CRISTOBAL_2008 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DOLLY_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FUNG-WONG_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAMMURI_2008\n", - "KAMMURI_2008 has 26.998593073096053, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EDOUARD_2008\n", - "EDOUARD_2008 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NURI_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FAY_2008\n", - "FAY_2008 has 30.863999999999997, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JULIO_2008\n", - "JULIO_2008 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GUSTAV_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HANNA_2008\n", - "HANNA_2008 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IKE_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LOWELL_2008\n", - "LOWELL_2008 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SINLAKU_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAGUPIT_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JANGMI_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KYLE_2008\n", - "KYLE_2008 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MEKKHALA_2008\n", - "MEKKHALA_2008 has 21.94944603138155, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NORBERT_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARCO_2008\n", - "MARCO_2008 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ODILE_2008\n", - "ODILE_2008 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RASHMI_2008\n", - "RASHMI_2008 has 21.43333333333333, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PALOMA_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOUL_2008\n", - "NOUL_2008 has 20.726343390738613, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NISHA_2008\n", - "NISHA_2008 has 24.00533333333333, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BILLY_2008\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHARLOTTE_2009\n", - "CHARLOTTE_2009 has 23.34284848484848, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ERIC_2009\n", - "ERIC_2009 has 23.34284848484848, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FANELE_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ELLIE_2009\n", - "ELLIE_2009 has 20.69290909090909, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IZILDA_2009\n", - "IZILDA_2009 has 32.89821818181818, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JADE_2009\n", - "JADE_2009 has 33.37754545454545, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BIJLI_2009\n", - "BIJLI_2009 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KUJIRA_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHAN-HOM_2009\n", - "CHAN-HOM_2009 has 39.130301038397754, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "AILA_2009\n", - "AILA_2009 has 30.863999999999997, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LINFA_2009\n", - "LINFA_2009 has 34.262056907768844, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ANDRES_2009\n", - "ANDRES_2009 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NANGKA_2009\n", - "NANGKA_2009 has 21.240743390738615, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MOLAVE_2009\n", - "MOLAVE_2009 has 37.91994684270953, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GONI_2009\n", - "GONI_2009 has 23.65497666794234, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MORAKOT_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BILL_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CLAUDETTE_2009\n", - "CLAUDETTE_2009 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KROVANH_2009\n", - "KROVANH_2009 has 32.862285526215075, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JIMENA_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KOPPU_2009\n", - "KOPPU_2009 has 39.22171055491771, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KETSANA_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PARMA_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MELOR_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PATRICIA_2009\n", - "PATRICIA_2009 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RICK_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MIRINAE_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IDA_2009\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PHYAN_2009\n", - "PHYAN_2009 has 24.00533333333333, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAGDA_2010\n", - "MAGDA_2010 has 35.93006060606061, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OLGA_2010\n", - "OLGA_2010 has 26.18763636363636, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FAMI_2010\n", - "FAMI_2010 has 25.05751515151515, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HUBERT_2010\n", - "HUBERT_2010 has 28.720666666666666, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ULUI_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PAUL_2010\n", - "PAUL_2010 has 37.64472727272727, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LAILA_2010\n", - "LAILA_2010 has 29.14933333333333, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JOEL_2010\n", - "JOEL_2010 has 33.3190909090909, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "AGATHA_2010\n", - "AGATHA_2010 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PHET_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ALEX_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CONSON_2010\n", - "CONSON_2010 has 38.90167881617553, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHANTHU_2010\n", - "CHANTHU_2010 has 38.98209852021942, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BONNIE_2010\n", - "BONNIE_2010 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DIANMU_2010\n", - "DIANMU_2010 has 28.117834685546626, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MINDULLE_2010\n", - "MINDULLE_2010 has 29.046612463324404, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EARL_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LIONROCK_2010\n", - "LIONROCK_2010 has 27.474439321342008, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KOMPASU_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MALOU_2010\n", - "MALOU_2010 has 25.16538112514351, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HERMINE_2010\n", - "HERMINE_2010 has 30.863999999999997, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MERANTI_2010\n", - "MERANTI_2010 has 32.67172326061998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FANAPI_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KARL_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MATTHEW_2010\n", - "MATTHEW_2010 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NICOLE_2010\n", - "NICOLE_2010 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PAULA_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MEGI_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GIRI_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RICHARD_2010\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JAL_2010\n", - "JAL_2010 has 30.006666666666668, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TASHA_2010\n", - "TASHA_2010 has 21.511272727272726, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BIANCA_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ANTHONY_2011\n", - "ANTHONY_2011 has 27.74642424242424, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "YASI_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BINGIZA_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ERROL_2011\n", - "ERROL_2011 has 32.383818181818185, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "AERE_2011\n", - "AERE_2011 has 22.93580753922694, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SONGDA_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAIMA_2011\n", - "HAIMA_2011 has 20.211943390738615, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BEATRIZ_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ARLENE_2011\n", - "ARLENE_2011 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MA-ON_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOCK-TEN_2011\n", - "NOCK-TEN_2011 has 28.627493596121955, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DON_2011\n", - "DON_2011 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EMILY_2011\n", - "EMILY_2011 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HARVEY_2011\n", - "HARVEY_2011 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NANMADOL_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IRENE_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TALAS_2011\n", - "TALAS_2011 has 29.341938040566397, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LEE_2011\n", - "LEE_2011 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARIA_2011\n", - "MARIA_2011 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NATE_2011\n", - "NATE_2011 has 33.436, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ROKE_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NESAT_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NALGAE_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JOVA_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RINA_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KEILA_2011\n", - "KEILA_2011 has 21.0904, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WASHI_2011\n", - "WASHI_2011 has 25.16538112514351, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GRANT_2011\n", - "GRANT_2011 has 30.895175757575757, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "THANE_2011\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHANDA_2012\n", - "CHANDA_2012 has 20.653939393939392, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HEIDI_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DANDO_2012\n", - "DANDO_2012 has 24.726272727272722, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FUNSO_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IRINA_2012\n", - "IRINA_2012 has 30.33790909090909, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LUA_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BUD_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BERYL_2012\n", - "BERYL_2012 has 30.863999999999997, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GUCHOL_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CARLOTTA_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TALIM_2012\n", - "TALIM_2012 has 26.251336680699065, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DEBBY_2012\n", - "DEBBY_2012 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DOKSURI_2012\n", - "DOKSURI_2012 has 21.64980753922694, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KHANUN_2012\n", - "KHANUN_2012 has 26.765736680699064, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "VICENTE_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SAOLA_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DAMREY_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ERNESTO_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAIKUI_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HELENE_2012\n", - "HELENE_2012 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAI-TAK_2012\n", - "KAI-TAK_2012 has 36.91972462048731, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TEMBIN_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ISAAC_2012\n", - "ISAAC_2012 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SANBA_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JELAWAT_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NORMAN_2012\n", - "NORMAN_2012 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "couldn't calculate the error or ratio for GAEMI_2012, skipping...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PAUL_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SON-TINH_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SANDY_2012\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NILAM_2012\n", - "NILAM_2012 has 24.00533333333333, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "couldn't calculate the error or ratio for SONAMU_2013, skipping...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OSWALD_2013\n", - "OSWALD_2013 has 21.031945454545454, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PETA_2013\n", - "PETA_2013 has 22.48551515151515, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HARUNA_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RUSTY_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ZANE_2013\n", - "ZANE_2013 has 34.95581818181818, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAHASEN:VIYARU_2013\n", - "MAHASEN:VIYARU_2013 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BARBARA_2013\n", - "BARBARA_2013 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ANDREA_2013\n", - "ANDREA_2013 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BARRY_2013\n", - "BARRY_2013 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BEBINCA_2013\n", - "BEBINCA_2013 has 20.92064603138155, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RUMBIA_2013\n", - "RUMBIA_2013 has 30.20878636305651, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SOULIK_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CIMARON_2013\n", - "CIMARON_2013 has 20.29193492027044, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JEBI_2013\n", - "JEBI_2013 has 29.17998636305651, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MANGKHUT_2013\n", - "MANGKHUT_2013 has 22.559061543564233, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "UTOR_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TRAMI_2013\n", - "TRAMI_2013 has 36.54347241995152, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KONG-REY_2013\n", - "KONG-REY_2013 has 28.194625569587956, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FERNAND_2013\n", - "FERNAND_2013 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JULIETTE_2013\n", - "JULIETTE_2013 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TORAJI_2013\n", - "TORAJI_2013 has 25.67978112514351, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GABRIELLE_2013\n", - "GABRIELLE_2013 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LORENA_2013\n", - "LORENA_2013 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "INGRID_2013\n", - "INGRID_2013 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAN-YI_2013\n", - "MAN-YI_2013 has 33.148063303992856, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MANUEL_2013\n", - "MANUEL_2013 has 33.436, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "USAGI_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WUTIP_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FITOW_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAREN_2013\n", - "KAREN_2013 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PHAILIN_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NARI_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OCTAVE_2013\n", - "OCTAVE_2013 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KROSA_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SONIA_2013\n", - "SONIA_2013 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAIYAN_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HELEN_2013\n", - "HELEN_2013 has 30.863999999999997, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LEHAR_2013\n", - "LEHAR_2013 has 37.72266666666666, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ALESSIA_2013\n", - "ALESSIA_2013 has 23.26490909090909, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHRISTINE_2013\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DELIWE_2014\n", - "DELIWE_2014 has 26.012272727272723, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DYLAN_2014\n", - "DYLAN_2014 has 29.69490909090909, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GILLIAN_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HELLEN_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ITA_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BORIS_2014\n", - "BORIS_2014 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAGIBIS_2014\n", - "HAGIBIS_2014 has 20.76389642811583, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ARTHUR_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NEOGURI_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RAMMASUN_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MATMO_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HALONG_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NAKRI_2014\n", - "NAKRI_2014 has 27.165825569587955, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BERTHA_2014\n", - "BERTHA_2014 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ISELLE_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DOLLY_2014\n", - "DOLLY_2014 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ODILE_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KALMAEGI_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FUNG-WONG_2014\n", - "FUNG-WONG_2014 has 26.19838248501084, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PHANFONE_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "VONGFONG_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HUDHUD_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TRUDY_2014\n", - "TRUDY_2014 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SINLAKU_2014\n", - "SINLAKU_2014 has 25.955504184207168, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAGUPIT_2014\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MEKKHALA_2015\n", - "MEKKHALA_2015 has 35.219379653016965, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHEDZA_2015\n", - "CHEDZA_2015 has 29.453296969696964, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FUNDI_2015\n", - "FUNDI_2015 has 28.720666666666666, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LAM_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARCIA_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NATHAN_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAYSAK_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOUL_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ANA_2015\n", - "ANA_2015 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BLANCA_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CARLOS_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BILL_2015\n", - "BILL_2015 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KUJIRA_2015\n", - "KUJIRA_2015 has 23.79364779181018, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHAN-HOM_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LINFA_2015\n", - "LINFA_2015 has 37.657923727516255, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NANGKA_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HALOLA_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "couldn't calculate the error or ratio for CLAUDETTE_2015, skipping...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KOMEN_2015\n", - "KOMEN_2015 has 21.43333333333333, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SOUDELOR_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GONI_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ERIKA_2015\n", - "ERIKA_2015 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ETAU_2015\n", - "ETAU_2015 has 26.989078083939276, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DUJUAN_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MUJIGAE_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KOPPU_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PATRICIA_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHAPALA_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MEGH_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SANDRA_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MELOR_2015\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "STAN_2016\n", - "STAN_2016 has 31.916181818181816, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ROANU_2016\n", - "ROANU_2016 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BONNIE_2016\n", - "BONNIE_2016 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "COLIN_2016\n", - "COLIN_2016 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DANIELLE_2016\n", - "DANIELLE_2016 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NEPARTAK_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ABELA_2016\n", - "ABELA_2016 has 27.74642424242424, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MIRINAE_2016\n", - "MIRINAE_2016 has 28.80424108177063, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NIDA_2016\n", - "NIDA_2016 has 36.052876297997194, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EARL_2016\n", - "EARL_2016 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JAVIER_2016\n", - "JAVIER_2016 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHANTHU_2016\n", - "CHANTHU_2016 has 27.19392923842327, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DIANMU_2016\n", - "DIANMU_2016 has 21.94944603138155, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MINDULLE_2016\n", - "MINDULLE_2016 has 34.234018859548414, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LIONROCK_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HERMINE_2016\n", - "HERMINE_2016 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NAMTHEUN_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NEWTON_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MERANTI_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MALAKAS_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JULIA_2016\n", - "JULIA_2016 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MEGI_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CHABA_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MATTHEW_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "AERE_2016\n", - "AERE_2016 has 29.131950432453117, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SARIKA_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAIMA_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OTTO_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TOKAGE_2016\n", - "TOKAGE_2016 has 28.25178112514351, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NADA_2016\n", - "NADA_2016 has 21.43333333333333, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "VARDAH_2016\n", - "VARDAH_2016 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOCK-TEN_2016\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DINEO_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ALFRED_2017\n", - "ALFRED_2017 has 26.889090909090907, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BLANCHE_2017\n", - "BLANCHE_2017 has 29.706599999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ENAWO_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DEBBIE_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAARUTHA_2017\n", - "MAARUTHA_2017 has 22.290666666666667, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MORA_2017\n", - "MORA_2017 has 34.29333333333334, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BEATRIZ_2017\n", - "BEATRIZ_2017 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MERBOK_2017\n", - "MERBOK_2017 has 28.289841081770632, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CALVIN_2017\n", - "CALVIN_2017 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BRET_2017\n", - "BRET_2017 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CINDY_2017\n", - "CINDY_2017 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NANMADOL_2017\n", - "NANMADOL_2017 has 30.98516026278862, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TALAS_2017\n", - "TALAS_2017 has 26.251336680699065, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NORU_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SONCA_2017\n", - "SONCA_2017 has 21.337811591614578, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NESAT_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAITANG_2017\n", - "HAITANG_2017 has 22.806779364714885, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EMILY_2017\n", - "EMILY_2017 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FRANKLIN_2017\n", - "FRANKLIN_2017 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HARVEY_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HATO_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PAKHAR_2017\n", - "PAKHAR_2017 has 30.976152192881745, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IRMA_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LIDIA_2017\n", - "LIDIA_2017 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAWAR_2017\n", - "MAWAR_2017 has 25.736936680699063, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KATIA_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TALIM_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DOKSURI_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAX_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARIA_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PILAR_2017\n", - "PILAR_2017 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NATE_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KHANUN_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LAN_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DAMREY_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAI-TAK_2017\n", - "KAI-TAK_2017 has 23.236587830080367, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TEMBIN_2017\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HILDA_2017\n", - "HILDA_2017 has 27.34893333333333, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KELVIN_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARCUS_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ELIAKIM_2018\n", - "ELIAKIM_2018 has 32.60594545454545, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NORA_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ALBERTO_2018\n", - "ALBERTO_2018 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EWINIAR_2018\n", - "EWINIAR_2018 has 20.935363094782495, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BUD_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GAEMI_2018\n", - "GAEMI_2018 has 21.469365612960836, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CARLOTTA_2018\n", - "CARLOTTA_2018 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PRAPIROON_2018\n", - "PRAPIROON_2018 has 37.5299454828422, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARIA_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BERYL_2018\n", - "BERYL_2018 has 36.007999999999996, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "couldn't calculate the error or ratio for SON-TINH_2018, skipping...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "AMPIL_2018\n", - "AMPIL_2018 has 26.960039321342006, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JONGDARI_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SHANSHAN_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "YAGI_2018\n", - "YAGI_2018 has 22.497593073096056, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BEBINCA_2018\n", - "BEBINCA_2018 has 27.48438248501084, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LEEPI_2018\n", - "LEEPI_2018 has 27.027170850873834, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RUMBIA_2018\n", - "RUMBIA_2018 has 24.30804779181018, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SOULIK_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CIMARON_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "JEBI_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FLORENCE_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OLIVIA_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GORDON_2018\n", - "GORDON_2018 has 30.863999999999997, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MANGKHUT_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BARIJAT_2018\n", - "BARIJAT_2018 has 21.94944603138155, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TRAMI_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ROSA_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KONG-REY_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SERGIO_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LUBAN_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MICHAEL_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TITLI_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TARA_2018\n", - "TARA_2018 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "VICENTE_2018\n", - "VICENTE_2018 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WILLA_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "YUTU_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "USAGI_2018\n", - "USAGI_2018 has 35.64804631968363, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GAJA_2018\n", - "GAJA_2018 has 37.72266666666666, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OWEN_2018\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PHETHAI_2018\n", - "PHETHAI_2018 has 28.291999999999998, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PENNY_2018\n", - "PENNY_2018 has 28.75963636363636, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DESMOND_2019\n", - "DESMOND_2019 has 21.031945454545454, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TREVOR_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "VERONICA_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KENNETH_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FANI_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "couldn't read kw01 for ANN_2019, skipping...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BARRY_2019\n", - "BARRY_2019 has 33.436, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DANAS_2019\n", - "DANAS_2019 has 23.321179364714887, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WIPHA_2019\n", - "WIPHA_2019 has 23.835579364714885, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FRANCISCO_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LEKIMA_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KROSA_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BAILU_2019\n", - "BAILU_2019 has 29.475279129991073, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DORIAN_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FAXAI_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LINGLING_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FERNAND_2019\n", - "FERNAND_2019 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LORENA_2019\n", - "LORENA_2019 has 38.58, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "IMELDA_2019\n", - "IMELDA_2019 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAREN_2019\n", - "KAREN_2019 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MITAG_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NARDA_2019\n", - "NARDA_2019 has 23.148, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HAGIBIS_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NESTOR_2019\n", - "NESTOR_2019 has 25.72, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PRISCILLA_2019\n", - "PRISCILLA_2019 has 20.576, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NAKRI_2019\n", - "NAKRI_2019 has 34.94272150019135, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KALMAEGI_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "KAMMURI_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BELNA_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PHANFONE_2019\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "BLAKE_2020\n", - "BLAKE_2020 has 25.06530909090909, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FRANCISCO_2020\n", - "FRANCISCO_2020 has 23.440272727272724, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DAMIEN_2020\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ESTHER_2020\n", - "ESTHER_2020 has 23.779309090909088, skipping plotting...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n", - "/tmp/ipykernel_868937/987684252.py:12: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", - " pd.read_csv(path, delimiter=r',\\s+')\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HEROLD_2020\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/fred/micromamba/envs/open-gira/lib/python3.10/site-packages/geopandas/geodataframe.py:2061: UserWarning: CRS mismatch between the CRS of left geometries and the CRS of right geometries.\n", - "Use `to_crs()` to reproject one of the input geometries to match the CRS of the other.\n", - "\n", - "Left CRS: EPSG:4326\n", - "Right CRS: None\n", - "\n", - " return geopandas.sjoin(left_df=self, right_df=df, *args, **kwargs)\n" - ] - } - ], - "source": [ - "buffer_km = 200\n", - "\n", - "plot_dir = (\n", - " \"/home/fred/projects/open_gira/open-gira/validation/wind_model_comparison/error_by_model_speed\"\n", - ")\n", - "os.makedirs(plot_dir, exist_ok=True)\n", - "\n", - "errors_by_storm = {}\n", - "holland_by_storm = {}\n", - "kw01_by_storm = {}\n", - "for i, storm_id in enumerate(common_storms):\n", - "\n", - " name_year = name_year_from_id(tracks, storm_id)\n", - " storm_track = tracks[tracks.track_id == storm_id]\n", - "\n", - " try:\n", - " kw01 = (\n", - " read_kw01(name_year, delta=0.1)\n", - " .interpolate_na(dim=\"longitude\", method=\"linear\")\n", - " .interpolate_na(dim=\"latitude\", method=\"linear\")\n", - " )\n", - " kw01_by_storm[storm_id] = kw01.max_wind_speed\n", - " except ValueError:\n", - " print(f\"couldn\\'t read kw01 for {name_year}, skipping...\")\n", - " continue\n", - " \n", - " try:\n", - " holland = xr.open_dataset(\n", - " (\n", - " \"/home/fred/projects/open_gira/open-gira/\"\n", - " f\"results/power/by_storm_set/IBTrACS/by_storm/{storm_id}/wind_field.nc\"\n", - " )\n", - " )\n", - " holland_by_storm[storm_id] = holland.max_wind_speed\n", - " except FileNotFoundError:\n", - " print(f\"couldn\\'t find holland for {name_year}, skipping...\")\n", - " continue\n", - "\n", - " try:\n", - " error = (holland - kw01).max_wind_speed.rename(\"error\")\n", - " ratio = (holland / kw01).max_wind_speed.rename(\"ratio\")\n", - " except ValueError:\n", - " print(f\"couldn\\'t calculate the error or ratio for {name_year}, skipping...\")\n", - " continue\n", - "\n", - " # make a buffer around the on-land track \n", - " print(name_year)\n", - " storm_track_over_land = storm_track[storm_track.landfall == True]\n", - " clipped_error = clip_field_to_buffered_points(storm_track_over_land, error, buffer_km)\n", - " errors_by_storm[storm_id] = clipped_error\n", - " \n", - " \n", - " # don't plot the weak storms (for brevity)\n", - " if storm_track.max_wind_speed_ms.max() < 40:\n", - " print(f\"{name_year} has {storm_track.max_wind_speed_ms.max()}, skipping plotting...\")\n", - " continue\n", - "\n", - " #plot_wind_speed_maps(name_year, storm_id, holland, kw01, error, plot_dir)\n", - " #plot_wind_speed_errors(name_year, storm_id, buffer_km, holland, clipped_error, plot_dir)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "a232d2d7", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2001157N28265 (104,) (104,)\n", - "2001204N19127 cannot retrieve model data\n", - "2001206N14134 (220,) (220,)\n", - "2001215N26275 (144,) (144,)\n", - "2001225N18146 (1620,) (1620,)\n", - "2001235N18296 cannot retrieve model data\n", - "2001239N19116 (693,) (693,)\n", - "2001246N19156 (936,) (936,)\n", - "2001248N23125 (810,) (810,)\n", - "2001255N26276 (285,) (285,)\n", - "2001264N21126 (285,) (285,)\n", - "2001278N12302 (144,) (144,)\n", - "2001284N28297 (399,) (399,)\n", - "2001303N13276 (408,) (408,)\n", - "2001309N10130 (1029,) (1029,)\n", - "2001365S12138 cannot retrieve model data\n", - "2002008N07141 (378,) (378,)\n", - "2002033S13121 (528,) (528,)\n", - "2002045S18049 cannot retrieve model data\n", - "2002063S11066 (266,) (266,)\n", - "2002098S07133 (252,) (252,)\n", - "2002122S07063 (80,) (80,)\n", - "2002155N20112 cannot retrieve model data\n", - "2002178N04155 (425,) (425,)\n", - "2002178N10139 (220,) (220,)\n", - "2002187N11160 cannot retrieve model data\n", - "2002189N21116 (198,) (198,)\n", - "2002195N11172 cannot retrieve model data\n", - "2002200N21150 cannot retrieve model data\n", - "2002214N19120 (315,) (315,)\n", - "2002227N14115 (338,) (338,)\n", - "2002234N14164 (462,) (462,)\n", - "2002240N16155 (442,) (442,)\n", - "2002245N29281 (128,) (128,)\n", - "2002249N28266 (220,) (220,)\n", - "2002252N20121 (252,) (252,)\n", - "2002252N29289 (150,) (150,)\n", - "2002255N26273 (375,) (375,)\n", - "2002258N10300 (1632,) (1632,)\n", - "2002264N13114 (532,) (532,)\n", - "2002264N28308 (735,) (735,)\n", - "2002265N10315 (4446,) (4446,)\n", - "2002268N15163 (1600,) (1600,)\n", - "2002268N15258 (500,) (500,)\n", - "2002295N11261 (768,) (768,)\n", - "2002364S16045 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"2007297N18300 (1078,) (1078,)\n", - "2007306N18133 (490,) (490,)\n", - "2007314N10093 (377,) (377,)\n", - "2007323N09128 (1410,) (1410,)\n", - "2007324N10140 (735,) (735,)\n", - "2007345N18298 (1470,) (1470,)\n", - "2007365S15134 (2170,) (2170,)\n", - "2008023S10050 (1995,) (1995,)\n", - "2008037S10055 (1947,) (1947,)\n", - "2008062S10064 (722,) (722,)\n", - "2008104N08128 (368,) (368,)\n", - "2008117N11090 (1700,) (1700,)\n", - "2008135N12116 (665,) (665,)\n", - "2008150N10274 (273,) (273,)\n", - "2008169N08135 (4158,) (4158,)\n", - "2008193N20126 (900,) (900,)\n", - "2008201N32280 cannot retrieve model data\n", - "2008203N18276 (1485,) (1485,)\n", - "2008206N22133 (540,) (540,)\n", - "2008217N19120 (312,) (312,)\n", - "2008217N28273 (8,) (8,)\n", - "2008229N13147 cannot retrieve model data\n", - "2008229N18293 (19092,) (19092,)\n", - "2008237N18253 (162,) (162,)\n", - "2008238N13293 (15470,) (15470,)\n", - "2008241N19303 (4088,) (4088,)\n", - "2008245N17323 (4623,) (4623,)\n", - "2008251N15256 (220,) (220,)\n", - "2008252N16128 (261,) (261,)\n", - "2008262N16142 (736,) (736,)\n", - "2008268N12140 (279,) (279,)\n", - "2008269N21290 (520,) (520,)\n", - "2008272N15113 cannot retrieve model data\n", - "2008278N13261 (864,) (864,)\n", - "2008280N18268 (420,) (420,)\n", - "2008283N12271 cannot retrieve model data\n", - "2008298N16085 cannot retrieve model data\n", - "2008311N14278 (363,) (363,)\n", - "2008320N08122 (490,) (490,)\n", - "2008329N09082 (1170,) (1170,)\n", - "2008351S11128 (2079,) (2079,)\n", - "2009011S16140 (350,) (350,)\n", - "2009017S15059 cannot retrieve model data\n", - "2009017S20043 cannot retrieve model data\n", - "2009031S16147 (868,) (868,)\n", - "2009082S16039 cannot retrieve model data\n", - "2009093S12062 (1224,) (1224,)\n", - "2009104N13088 cannot retrieve model data\n", - "2009121N13124 (456,) (456,)\n", - "2009123N10111 (651,) (651,)\n", - "2009143N17089 (510,) (510,)\n", - "2009164N10131 (612,) (612,)\n", - "2009171N15264 cannot retrieve model data\n", - "2009173N10132 (756,) (756,)\n", - "2009196N14129 (242,) (242,)\n", - "2009213N16130 cannot retrieve model data\n", - "2009215N20133 (616,) (616,)\n", - "2009227N12328 cannot retrieve model data\n", - "2009228N27277 (40,) (40,)\n", - "2009238N20151 cannot retrieve model data\n", - "2009239N12270 (176,) (176,)\n", - "2009254N14130 (300,) (300,)\n", - "2009268N14128 (638,) (638,)\n", - "2009270N10148 (1566,) (1566,)\n", - "2009272N07164 (825,) (825,)\n", - "2009282N16252 cannot retrieve model data\n", - "2009288N07267 (160,) (160,)\n", - "2009299N12153 (1620,) (1620,)\n", - "2009308N11279 (682,) (682,)\n", - "2009313N11072 (432,) (432,)\n", - "2010019S11123 (952,) (952,)\n", - "2010022S12160 (2624,) (2624,)\n", - "2010032S20042 (368,) (368,)\n", - "2010066S19050 (256,) (256,)\n", - "2010070S15168 (884,) (884,)\n", - "2010084S09138 (525,) (525,)\n", - "2010137N10090 (560,) (560,)\n", - "2010143S20035 cannot retrieve model data\n", - "2010149N13266 (437,) (437,)\n", - "2010151N14065 (714,) (714,)\n", - "2010176N16278 (391,) (391,)\n", - "2010191N12138 (1456,) (1456,)\n", - "2010198N15123 (544,) (544,)\n", - "2010203N22286 (176,) (176,)\n", - "2010218N20127 (608,) (608,)\n", - "2010233N17119 (459,) (459,)\n", - "2010236N12341 (782,) (782,)\n", - "2010239N15118 (171,) (171,)\n", - "2010240N15142 (570,) (570,)\n", - "2010243N12146 cannot retrieve model data\n", - "2010247N15266 (1376,) (1376,)\n", - "2010249N24125 (160,) (160,)\n", - "2010256N17137 (495,) (495,)\n", - "2010257N16282 (990,) (990,)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2010267N14285 (2325,) (2325,)\n", - "2010271N19276 (390,) (390,)\n", - "2010284N14278 (888,) (888,)\n", - "2010285N13145 (1353,) (1353,)\n", - "2010293N17093 cannot retrieve model data\n", - "2010293N17277 (726,) (726,)\n", - "2010305N06105 (375,) (375,)\n", - "2010358S13152 (1085,) (1085,)\n", - "2011021S16129 (1225,) (1225,)\n", - "2011023S16147 cannot retrieve model data\n", - "2011028S13180 (1938,) (1938,)\n", - "2011038S11062 (2640,) (2640,)\n", - "2011103S12126 (406,) (406,)\n", - "2011126N11129 (1634,) (1634,)\n", - "2011140N08142 (442,) (442,)\n", - "2011167N08129 (1127,) (1127,)\n", - "2011170N12263 cannot retrieve model data\n", - "2011179N20267 (552,) (552,)\n", - "2011192N18158 (814,) (814,)\n", - "2011205N12130 (2184,) (2184,)\n", - "2011208N22274 (143,) (143,)\n", - "2011214N15299 (189,) (189,)\n", - "2011231N15278 (2640,) (2640,)\n", - "2011233N12129 (1408,) (1408,)\n", - "2011233N15301 (5780,) (5780,)\n", - "2011236N15143 (700,) (700,)\n", - "2011245N27269 (360,) (360,)\n", - "2011250N12324 cannot retrieve model data\n", - "2011250N20266 (240,) (240,)\n", - "2011253N20145 (1176,) (1176,)\n", - "2011266N13139 (2639,) (2639,)\n", - "2011270N18139 (2584,) (2584,)\n", - "2011279N10257 (117,) (117,)\n", - "2011295N13279 (276,) (276,)\n", - "2011302N13062 (630,) (630,)\n", - "2011346N03156 (525,) (525,)\n", - "2011358S11132 (500,) (500,)\n", - "2011360N09088 (322,) (322,)\n", - "2012006S15043 cannot retrieve model data\n", - "2012009S12121 (575,) (575,)\n", - "2012010S24049 cannot retrieve model data\n", - "2012018S16041 cannot retrieve model data\n", - "2012056S13057 (1932,) (1932,)\n", - "2012070S17112 (690,) (690,)\n", - "2012142N09262 cannot retrieve model data\n", - "2012147N30284 (408,) (408,)\n", - "2012162N06150 (2257,) (2257,)\n", - "2012166N09269 (675,) (675,)\n", - "2012168N19112 cannot retrieve model data\n", - "2012176N26272 (410,) (410,)\n", - "2012177N11135 (247,) (247,)\n", - "2012196N19144 (805,) (805,)\n", - "2012201N15129 (989,) (989,)\n", - "2012209N11131 (312,) (312,)\n", - "2012209N25149 (360,) (360,)\n", - "2012215N12313 (1311,) (1311,)\n", - "2012215N23146 (1012,) (1012,)\n", - "2012223N14317 (4176,) (4176,)\n", - "2012225N16133 (1909,) (1909,)\n", - "2012230N21126 (1034,) (1034,)\n", - "2012234N16315 (4154,) (4154,)\n", - "2012254N09135 (1715,) (1715,)\n", - "2012263N15141 (2623,) (2623,)\n", - "2012272N22251 (289,) (289,)\n", - "2012288N14248 (180,) (180,)\n", - "2012296N06135 (4165,) (4165,)\n", - "2012296N14283 (1892,) (1892,)\n", - "2012301N11087 (306,) (306,)\n", - "2013018S14138 (1368,) (1368,)\n", - "2013020S17124 (1254,) (1254,)\n", - "2013046S20042 cannot retrieve model data\n", - "2013052S13126 (630,) (630,)\n", - "2013117S10155 cannot retrieve model data\n", - "2013130N04093 (448,) (448,)\n", - "2013149N14264 (399,) (399,)\n", - "2013157N25273 (2214,) (2214,)\n", - "2013167N12279 (989,) (989,)\n", - "2013171N15117 (1702,) (1702,)\n", - "2013178N09133 (2133,) (2133,)\n", - "2013187N20156 (540,) (540,)\n", - "2013196N14128 (253,) (253,)\n", - "2013210N13122 (1386,) (1386,)\n", - "2013217N11118 (744,) (744,)\n", - "2013220N12137 (2752,) (2752,)\n", - "2013228N23124 (611,) (611,)\n", - "2013237N11129 cannot retrieve model data\n", - "2013238N19266 (260,) (260,)\n", - "2013241N19254 cannot retrieve model data\n", - "2013243N26122 (560,) (560,)\n", - "2013248N16294 cannot retrieve model data\n", - "2013248N17255 cannot retrieve model data\n", - "2013255N19268 (162,) (162,)\n", - "2013255N20148 (726,) (726,)\n", - "2013257N15259 (2021,) (2021,)\n", - "2013259N17132 (585,) (585,)\n", - "2013269N15118 (672,) (672,)\n", - "2013272N10135 (437,) (437,)\n", - "2013276N21273 cannot retrieve model data\n", - "2013281N12098 (1120,) (1120,)\n", - "2013282N14132 (1748,) (1748,)\n", - "2013286N15251 (66,) (66,)\n", - "2013301N13142 (918,) (918,)\n", - "2013305N16252 (95,) (95,)\n", - "2013306N07162 (1800,) (1800,)\n", - "2013322N13090 (638,) (638,)\n", - "2013324N07103 (525,) (525,)\n", - "2013324S11113 (2790,) (2790,)\n", - "2013360S12124 (315,) (315,)\n", - "2014015S16043 (676,) (676,)\n", - "2014024S13160 (1190,) (1190,)\n", - "2014066S09138 cannot retrieve model data\n", - "2014086S10041 cannot retrieve model data\n", - "2014092S11159 (957,) (957,)\n", - "2014153N12267 cannot retrieve model data\n", - "2014164N19116 (396,) (396,)\n", - "2014180N32282 (2193,) (2193,)\n", - "2014184N08147 (456,) (456,)\n", - "2014190N08154 (5136,) (5136,)\n", - "2014197N10137 (768,) (768,)\n", - "2014209N12152 (792,) (792,)\n", - "2014209N16134 cannot retrieve model data\n", - "2014210N10323 (504,) (504,)\n", - "2014212N11242 cannot retrieve model data\n", - "2014245N19268 (294,) (294,)\n", - "2014253N13260 (704,) (704,)\n", - "2014254N10142 (3164,) (3164,)\n", - "2014260N13135 (2135,) (2135,)\n", - "2014271N10160 (550,) (550,)\n", - "2014275N06166 (2754,) (2754,)\n", - "2014279N11096 (1107,) (1107,)\n", - "2014290N14261 (200,) (200,)\n", - "2014329N08131 (660,) (660,)\n", - "2014334N02156 (1475,) (1475,)\n", - "2015012N09146 (1075,) (1075,)\n", - "2015013S18038 (950,) (950,)\n", - "2015036S20038 cannot retrieve model data\n", - "2015045S12145 (1080,) (1080,)\n", - "2015047S15152 (1160,) (1160,)\n", - "2015068S12151 (3100,) (3100,)\n", - "2015085N06162 (650,) (650,)\n", - "2015122N07144 cannot retrieve model data\n", - "2015126N27281 (1225,) (1225,)\n", - "2015152N12258 (195,) (195,)\n", - "2015162N12262 (243,) (243,)\n", - "2015167N27266 (2132,) (2132,)\n", - "2015171N15112 (1288,) (1288,)\n", - "2015180N09160 cannot retrieve model data\n", - "2015183N13130 (2449,) (2449,)\n", - "2015184N08172 (756,) (756,)\n", - "2015188N08194 (546,) (546,)\n", - "2015207N22091 (352,) (352,)\n", - "2015211N13162 (760,) (760,)\n", - "2015226N12151 cannot retrieve model data\n", - "2015237N14315 cannot retrieve model data\n", - "2015249N18142 (400,) (400,)\n", - "2015263N14148 (966,) (966,)\n", - "2015273N12130 (3526,) (3526,)\n", - "2015285N14151 (570,) (570,)\n", - "2015293N13266 (1131,) (1131,)\n", - "2015301N11065 (560,) (560,)\n", - "2015309N14067 (300,) (300,)\n", - "2015328N11260 cannot retrieve model data\n", - "2015344N07145 (900,) (900,)\n", - "2016027S13119 (910,) (910,)\n", - "2016138N10081 (576,) (576,)\n", - "2016148N27288 (228,) (228,)\n", - "2016158N22272 (140,) (140,)\n", - "2016171N19268 (240,) (240,)\n", - "2016185N08145 (512,) (512,)\n", - "2016195S06076 cannot retrieve model data\n", - "2016207N17116 (1550,) (1550,)\n", - "2016212N12127 (1113,) (1113,)\n", - "2016215N16283 (1134,) (1134,)\n", - "2016220N18258 (663,) (663,)\n", - "2016225N16138 (784,) (784,)\n", - "2016228N22117 (1148,) (1148,)\n", - "2016230N15138 (3127,) (3127,)\n", - "2016230N25160 cannot retrieve model data\n", - "2016242N24279 (5822,) (5822,)\n", - "2016244N21123 (528,) (528,)\n", - "2016248N15255 (210,) (210,)\n", - "2016253N13144 (551,) (551,)\n", - "2016256N12146 (558,) (558,)\n", - "2016257N27280 (2244,) (2244,)\n", - "2016266N11144 (645,) (645,)\n", - "2016269N15165 cannot retrieve model data\n", - "2016273N13300 (1558,) (1558,)\n", - "2016279N19130 (105,) (105,)\n", - "2016287N13130 (3496,) (3496,)\n", - "2016288N07145 (1944,) (1944,)\n", - "2016323N13279 (5,) (5,)\n", - "2016328N09130 (660,) (660,)\n", - "2016335N07088 (143,) (143,)\n", - "2016341N08092 (880,) (880,)\n", - "2016355N07146 (532,) (532,)\n", - "2017043S19040 (400,) (400,)\n", - "2017046S17137 (1365,) (1365,)\n", - "2017060S09139 (1584,) (1584,)\n", - "2017061S11063 (1508,) (1508,)\n", - "2017082S14152 (980,) (980,)\n", - "2017104N08085 (315,) (315,)\n", - "2017147N14087 (819,) (819,)\n", - "2017152N14262 (364,) (364,)\n", - "2017161N13119 (552,) (552,)\n", - "2017163N14265 (170,) (170,)\n", - "2017170N08310 (644,) (644,)\n", - "2017171N24271 (1770,) (1770,)\n", - "2017182N15132 (1440,) (1440,)\n", - "2017195N16114 (779,) (779,)\n", - "2017200N26162 (875,) (875,)\n", - "2017202N16116 (559,) (559,)\n", - "2017206N13129 (602,) (602,)\n", - "2017209N19118 (432,) (432,)\n", - "2017212N28275 (546,) (546,)\n", - "2017219N16279 (2130,) (2130,)\n", - "2017228N14314 (7704,) (7704,)\n", - "2017232N19130 (1430,) (1430,)\n", - "2017236N15129 (1827,) (1827,)\n", - "2017242N16333 (3212,) (3212,)\n", - "2017242N17253 (612,) (612,)\n", - "2017242N19122 (100,) (100,)\n", - "2017249N22263 (270,) (270,)\n", - "2017252N14147 (2226,) (2226,)\n", - "2017253N14130 (1008,) (1008,)\n", - "2017257N16258 (114,) (114,)\n", - "2017260N12310 (609,) (609,)\n", - "2017265N17257 cannot retrieve model data\n", - "2017277N11279 (25380,) (25380,)\n", - "2017284N15134 (2665,) (2665,)\n", - "2017288N09138 (782,) (782,)\n", - "2017304N11127 (980,) (980,)\n", - "2017347N11129 (1562,) (1562,)\n", - "2017354N08134 (760,) (760,)\n", - "2017360S15124 (1170,) (1170,)\n", - "2018044S10133 (2700,) (2700,)\n", - "2018073S09129 (2923,) (2923,)\n", - "2018073S12057 (225,) (225,)\n", - "2018079S08137 (638,) (638,)\n", - "2018146N19273 (517,) (517,)\n", - "2018153N12113 (992,) (992,)\n", - "2018161N12260 (88,) (88,)\n", - "2018165N22117 (8,) (8,)\n", - "2018166N15260 cannot retrieve model data\n", - "2018179N19134 cannot retrieve model data\n", - "2018184N10147 (1083,) (1083,)\n", - "2018186N10325 cannot retrieve model data\n", - "2018199N18128 (1400,) (1400,)\n", - "2018204N15137 (2544,) (2544,)\n", - "2018214N19153 cannot retrieve model data\n", - "2018218N18134 (1938,) (1938,)\n", - "2018221N17112 (1755,) (1755,)\n", - "2018222N16147 (624,) (624,)\n", - "2018226N23128 (1118,) (1118,)\n", - "2018227N11145 (1189,) (1189,)\n", - "2018229N11160 (1508,) (1508,)\n", - "2018239N11161 (442,) (442,)\n", - "2018242N13343 (5586,) (5586,)\n", - "2018244N14252 cannot retrieve model data\n", - "2018246N22283 (570,) (570,)\n", - "2018250N12170 (4508,) (4508,)\n", - "2018251N20122 (125,) (125,)\n", - "2018263N12146 (3139,) (3139,)\n", - "2018268N14253 (238,) (238,)\n", - "2018271N06154 (726,) (726,)\n", - "2018273N12259 (150,) (150,)\n", - "2018279N11069 (338,) (338,)\n", - "2018280N18273 (2295,) (2295,)\n", - "2018281N14088 (924,) (924,)\n", - "2018288N17257 cannot retrieve model data\n", - "2018292N13269 (70,) (70,)\n", - "2018292N14261 (196,) (196,)\n", - "2018294N08161 (714,) (714,)\n", - "2018311N07179 (288,) (288,)\n", - "2018314N12093 (476,) (476,)\n", - "2018334S08156 (1980,) (1980,)\n", - "2018347N07089 (374,) (374,)\n", - "2018362S13147 (770,) (770,)\n", - "2019018S24033 cannot retrieve model data\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2019074S08151 (4340,) (4340,)\n", - "2019077S13123 cannot retrieve model data\n", - "2019112S10053 (640,) (640,)\n", - "2019116N02090 (940,) (940,)\n", - "2019192N29274 (1440,) (1440,)\n", - "2019195N13136 (960,) (960,)\n", - "2019210N16117 (1254,) (1254,)\n", - "2019213N17155 (1353,) (1353,)\n", - "2019214N15134 (1260,) (1260,)\n", - "2019216N16147 (640,) (640,)\n", - "2019231N13135 (442,) (442,)\n", - "2019236N10314 (912,) (912,)\n", - "2019242N14180 (589,) (589,)\n", - "2019243N06136 (1024,) (1024,)\n", - "2019246N24266 (357,) (357,)\n", - "2019260N12262 (1632,) (1632,)\n", - "2019261N28264 (81,) (81,)\n", - "2019265N12301 cannot retrieve model data\n", - "2019268N10155 (620,) (620,)\n", - "2019272N14261 (3248,) (3248,)\n", - "2019278N16165 (714,) (714,)\n", - "2019291N22264 (1575,) (1575,)\n", - "2019293N17257 (247,) (247,)\n", - "2019308N13114 (578,) (578,)\n", - "2019314N14136 (1204,) (1204,)\n", - "2019329N09160 (561,) (561,)\n", - "2019336S06055 (1332,) (1332,)\n", - "2019354N05151 cannot retrieve model data\n", - "2020004S14122 (2256,) (2256,)\n", - "2020034S13063 (396,) (396,)\n", - "2020034S17129 (1610,) (1610,)\n", - "2020052S13140 (4104,) (4104,)\n", - "2020072S14054 cannot retrieve model data\n" - ] - } - ], - "source": [ - "model = []\n", - "error = []\n", - "for storm_id, clipped_error in errors_by_storm.items():\n", - " holland = holland_by_storm[storm_id]\n", - "\n", - " try:\n", - " model_arr = holland.sel(\n", - " dict(\n", - " longitude=clipped_error.longitude,\n", - " latitude=clipped_error.latitude\n", - " ),\n", - " method=\"nearest\",\n", - " tolerance=1E-3\n", - " ).values.ravel()\n", - " error_arr = clipped_error.error.values.ravel()\n", - " print(storm_id, model_arr.shape, error_arr.shape)\n", - " except ValueError:\n", - " print(storm_id, \"cannot retrieve model data\")\n", - "\n", - " if len(model_arr) == len(error_arr) and len(model_arr) != 0:\n", - " model.append(model_arr)\n", - " error.append(error_arr)\n", - " \n", - "pooled_model = np.concatenate(model)\n", - "pooled_error = np.concatenate(error)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "ace2e35b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 0.98, 'Wind model comparison (error within 200km of eye over land)\\n$n_{pixels}=442728, \\\\ \\\\mu=0.35 $ms$^{-1}, \\\\ q_{50}=0.22$ms$^{-1}$')" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "vmin = 10\n", - "vmax = 90\n", - "\n", - "df = pd.DataFrame({\"error\": pooled_error, \"model\": pooled_model})\n", - "df = df[df.model > vmin]\n", - "\n", - "f, (ax_scatter, ax_hist) = plt.subplots(2, 1, sharex=True, gridspec_kw={'height_ratios': [3, 1]})\n", - "\n", - "stride = 1\n", - "ax_scatter.scatter(\n", - " df.error[::stride],\n", - " df.model[::stride],\n", - " s=0.05,\n", - " c=\"k\",\n", - " alpha=0.2\n", - ")\n", - "ax_scatter.set_ylabel(\"Model wind speed [ms$^{-1}$]\")\n", - "ax_scatter.grid(alpha=0.3)\n", - "x_min = -30\n", - "x_max = 30\n", - "ax_scatter.set_xlim(x_min, x_max)\n", - "ax_scatter.axvline(0, color=\"k\", ls=\"--\", alpha=0.8)\n", - "\n", - "frequency, bin_edges, patches = ax_hist.hist(\n", - " df.error,\n", - " bins=np.linspace(-50, 50, 150),\n", - " density=True,\n", - " alpha=1,\n", - " color=\"black\"\n", - ")\n", - "ax_hist.axvline(0, color=\"k\", ls=\"--\", alpha=0.8)\n", - "ax_hist.set_xlim(x_min, x_max)\n", - "ax_hist.set_ylabel(\"PDF\", labelpad=20)\n", - "ax_hist.set_xlabel(\"Thomas et al. 2023 $-$ Done et al. 2020 [ms$^{-1}$]\")\n", - "ax_hist.spines['top'].set_visible(False)\n", - "ax_hist.spines['right'].set_visible(False)\n", - "ax_hist.spines['left'].set_visible(False)\n", - "ax_hist.get_yaxis().set_ticks([])\n", - "\n", - "n = len(df)\n", - "mean = df.error.mean()\n", - "median = df.error.median()\n", - "\n", - "f.suptitle(\n", - " f\"Wind model comparison (error within {buffer_km}km of eye over land)\\n\"\n", - " f\"$n_{{pixels}}={n}, \\ \\mu={mean:.2f} $ms$^{{-1}}, \\ q_{{50}}={median:.2f}$ms$^{{-1}}$\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "0bd3933d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "vmin = 10\n", - "vmax = 80\n", - "\n", - "df = pd.DataFrame({\"error\": pooled_error, \"model\": pooled_model})\n", - "df = df[df.model > vmin]\n", - "\n", - "f, (ax_box, ax_hist) = plt.subplots(2, 1, sharex=True, gridspec_kw={'height_ratios': [3, 1]})\n", - "\n", - "ax_box.set_ylabel(\"Model wind speed [ms$^{-1}$]\")\n", - "ax_box.grid(alpha=0.3)\n", - "xticks = np.linspace(-30, 30, 13) \n", - "ax_box.set_xticks(xticks, labels=[f\"{int(x):d}\" for x in xticks])\n", - "\n", - "step = 10\n", - "speed_bands = np.linspace(vmin, vmax, int((vmax - vmin) / step + 1))\n", - "errors_by_band = []\n", - "for i, lower_bound in enumerate(speed_bands[:-1]):\n", - " upper_bound = speed_bands[i + 1]\n", - " mid_point = (lower_bound + upper_bound) / 2\n", - " span = upper_bound - lower_bound\n", - " band_errors = df.loc[df.model.between(lower_bound, upper_bound), \"error\"]\n", - " # boxplot routine can't handle NaN values, mask them out\n", - " errors_by_band.append(band_errors[~np.isnan(band_errors)])\n", - " \n", - "ax_box.boxplot(\n", - " errors_by_band,\n", - " vert=False,\n", - " positions=speed_bands[:-1] + step / 2,\n", - " widths=[step * 0.8] * len(errors_by_band),\n", - " whis=[5, 95], # percentiles\n", - " flierprops=dict(alpha=0.1)\n", - ")\n", - "yticks = [10, 20, 30, 40, 50, 60, 70, 80]\n", - "ax_box.set_yticks(yticks, labels=yticks)\n", - "\n", - "n = len(df)\n", - "mean = df.error.mean()\n", - "\n", - "frequency, bin_edges, patches = ax_hist.hist(\n", - " df.error,\n", - " bins=np.linspace(-50, 50, 150),\n", - " density=True,\n", - " alpha=0.8,\n", - " color=\"black\"\n", - ")\n", - "ax_hist.set_xlim(x_min, x_max)\n", - "ax_hist.set_ylabel(\"PDF\", labelpad=20)\n", - "ax_hist.set_xlabel(\"Thomas et al. 2023 $-$ Done et al. 2020 [ms$^{-1}$]\")\n", - "ax_hist.spines['top'].set_visible(False)\n", - "ax_hist.spines['right'].set_visible(False)\n", - "ax_hist.spines['left'].set_visible(False)\n", - "ax_hist.get_yaxis().set_ticks([])\n", - "ax_hist.axvline(mean, color=\"orange\", lw=1.5)\n", - "\n", - "f.suptitle(\n", - " f\"Wind model errors within {buffer_km}km of eye\\n\"\n", - " f\"$n_{{pixels}}={n}, \\ \\mu_{{error}}={mean:.2f} $ms$^{{-1}}$\"\n", - ")\n", - "\n", - "f.savefig(\n", - " os.path.join(\n", - " \"/home/fred/projects/open_gira/open-gira/validation/wind_model_comparison/\",\n", - " \"thomas_vs_done.png\"\n", - " )\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.8" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/validation/iso_codes.csv b/validation/iso_codes.csv deleted file mode 100644 index 4a210a16..00000000 --- a/validation/iso_codes.csv +++ /dev/null @@ -1,257 +0,0 @@ -"Country","Alpha-2 code","Alpha-3 code","Numeric code","Latitude (average)","Longitude (average)" -"Afghanistan", "AF", "AFG", "4", "33", "65" -"Albania", "AL", "ALB", "8", "41", "20" -"Algeria", "DZ", "DZA", "12", "28", "3" -"American Samoa", "AS", "ASM", "16", "-14.3333", "-170" -"Andorra", "AD", "AND", "20", "42.5", "1.6" -"Angola", "AO", "AGO", "24", "-12.5", "18.5" -"Anguilla", "AI", "AIA", "660", "18.25", "-63.1667" -"Antarctica", "AQ", "ATA", "10", "-90", "0" -"Antigua and Barbuda", "AG", "ATG", "28", "17.05", "-61.8" -"Argentina", "AR", "ARG", "32", "-34", "-64" -"Armenia", "AM", "ARM", "51", "40", "45" -"Aruba", "AW", "ABW", "533", "12.5", "-69.9667" -"Australia", "AU", "AUS", "36", "-27", "133" -"Austria", "AT", "AUT", "40", "47.3333", "13.3333" -"Azerbaijan", "AZ", "AZE", "31", "40.5", "47.5" -"Bahamas", "BS", "BHS", "44", "24.25", "-76" -"Bahrain", "BH", "BHR", "48", "26", "50.55" -"Bangladesh", "BD", "BGD", "50", "24", "90" -"Barbados", "BB", "BRB", "52", "13.1667", "-59.5333" -"Belarus", "BY", "BLR", "112", "53", "28" -"Belgium", "BE", "BEL", "56", "50.8333", "4" -"Belize", "BZ", "BLZ", "84", "17.25", "-88.75" -"Benin", "BJ", "BEN", "204", "9.5", "2.25" -"Bermuda", "BM", "BMU", "60", "32.3333", "-64.75" -"Bhutan", "BT", "BTN", "64", "27.5", "90.5" -"Bolivia, Plurinational State of", "BO", "BOL", "68", "-17", "-65" -"Bolivia", "BO", "BOL", "68", "-17", "-65" -"Bosnia and Herzegovina", "BA", "BIH", "70", "44", "18" -"Botswana", "BW", "BWA", "72", "-22", "24" -"Bouvet Island", "BV", "BVT", "74", "-54.4333", "3.4" -"Brazil", "BR", "BRA", "76", "-10", "-55" -"British Indian Ocean Territory", "IO", "IOT", "86", "-6", "71.5" -"Brunei Darussalam", "BN", "BRN", "96", "4.5", "114.6667" -"Brunei", "BN", "BRN", "96", "4.5", "114.6667" -"Bulgaria", "BG", "BGR", "100", "43", "25" -"Burkina Faso", "BF", "BFA", "854", "13", "-2" -"Burundi", "BI", "BDI", "108", "-3.5", "30" -"Cambodia", "KH", "KHM", "116", "13", "105" -"Cameroon", "CM", "CMR", "120", "6", "12" -"Canada", "CA", "CAN", "124", "60", "-95" -"Cape Verde", "CV", "CPV", "132", "16", "-24" -"Cayman Islands", "KY", "CYM", "136", "19.5", "-80.5" -"Central African Republic", "CF", "CAF", "140", "7", "21" -"Chad", "TD", "TCD", "148", "15", "19" -"Chile", "CL", "CHL", "152", "-30", "-71" -"China", "CN", "CHN", "156", "35", "105" -"Christmas Island", "CX", "CXR", "162", "-10.5", "105.6667" -"Cocos (Keeling) Islands", "CC", "CCK", "166", "-12.5", "96.8333" -"Colombia", "CO", "COL", "170", "4", "-72" -"Comoros", "KM", "COM", "174", "-12.1667", "44.25" -"Congo", "CG", "COG", "178", "-1", "15" -"Congo, the Democratic Republic of the", "CD", "COD", "180", "0", "25" -"Cook Islands", "CK", "COK", "184", "-21.2333", "-159.7667" -"Costa Rica", "CR", "CRI", "188", "10", "-84" -"Cรดte d'Ivoire", "CI", "CIV", "384", "8", "-5" -"Ivory Coast", "CI", "CIV", "384", "8", "-5" -"Croatia", "HR", "HRV", "191", "45.1667", "15.5" -"Cuba", "CU", "CUB", "192", "21.5", "-80" -"Cyprus", "CY", "CYP", "196", "35", "33" -"Czech Republic", "CZ", "CZE", "203", "49.75", "15.5" -"Denmark", "DK", "DNK", "208", "56", "10" -"Djibouti", "DJ", "DJI", "262", "11.5", "43" -"Dominica", "DM", "DMA", "212", "15.4167", "-61.3333" -"Dominican Republic", "DO", "DOM", "214", "19", "-70.6667" -"Ecuador", "EC", "ECU", "218", "-2", "-77.5" -"Egypt", "EG", "EGY", "818", "27", "30" -"El Salvador", "SV", "SLV", "222", "13.8333", "-88.9167" -"Equatorial Guinea", "GQ", "GNQ", "226", "2", "10" -"Eritrea", "ER", "ERI", "232", "15", "39" -"Estonia", "EE", "EST", "233", "59", "26" -"Ethiopia", "ET", "ETH", "231", "8", "38" -"Falkland Islands (Malvinas)", "FK", "FLK", "238", "-51.75", "-59" -"Faroe Islands", "FO", "FRO", "234", "62", "-7" -"Fiji", "FJ", "FJI", "242", "-18", "175" -"Finland", "FI", "FIN", "246", "64", "26" -"France", "FR", "FRA", "250", "46", "2" -"French Guiana", "GF", "GUF", "254", "4", "-53" -"French Polynesia", "PF", "PYF", "258", "-15", "-140" -"French Southern Territories", "TF", "ATF", "260", "-43", "67" -"Gabon", "GA", "GAB", "266", "-1", "11.75" -"Gambia", "GM", "GMB", "270", "13.4667", "-16.5667" -"Georgia", "GE", "GEO", "268", "42", "43.5" -"Germany", "DE", "DEU", "276", "51", "9" -"Ghana", "GH", "GHA", "288", "8", "-2" -"Gibraltar", "GI", "GIB", "292", "36.1833", "-5.3667" -"Greece", "GR", "GRC", "300", "39", "22" -"Greenland", "GL", "GRL", "304", "72", "-40" -"Grenada", "GD", "GRD", "308", "12.1167", "-61.6667" -"Guadeloupe", "GP", "GLP", "312", "16.25", "-61.5833" -"Guam", "GU", "GUM", "316", "13.4667", "144.7833" -"Guatemala", "GT", "GTM", "320", "15.5", "-90.25" -"Guernsey", "GG", "GGY", "831", "49.5", "-2.56" -"Guinea", "GN", "GIN", "324", "11", "-10" -"Guinea-Bissau", "GW", "GNB", "624", "12", "-15" -"Guyana", "GY", "GUY", "328", "5", "-59" -"Haiti", "HT", "HTI", "332", "19", "-72.4167" -"Heard Island and McDonald Islands", "HM", "HMD", "334", "-53.1", "72.5167" -"Holy See (Vatican City State)", "VA", "VAT", "336", "41.9", "12.45" -"Honduras", "HN", "HND", "340", "15", "-86.5" -"Hong Kong", "HK", "HKG", "344", "22.25", "114.1667" -"Hungary", "HU", "HUN", "348", "47", "20" -"Iceland", "IS", "ISL", "352", "65", "-18" -"India", "IN", "IND", "356", "20", "77" -"Indonesia", "ID", "IDN", "360", "-5", "120" -"Iran, Islamic Republic of", "IR", "IRN", "364", "32", "53" -"Iraq", "IQ", "IRQ", "368", "33", "44" -"Ireland", "IE", "IRL", "372", "53", "-8" -"Isle of Man", "IM", "IMN", "833", "54.23", "-4.55" -"Israel", "IL", "ISR", "376", "31.5", "34.75" -"Italy", "IT", "ITA", "380", "42.8333", "12.8333" -"Jamaica", "JM", "JAM", "388", "18.25", "-77.5" -"Japan", "JP", "JPN", "392", "36", "138" -"Jersey", "JE", "JEY", "832", "49.21", "-2.13" -"Jordan", "JO", "JOR", "400", "31", "36" -"Kazakhstan", "KZ", "KAZ", "398", "48", "68" -"Kenya", "KE", "KEN", "404", "1", "38" -"Kiribati", "KI", "KIR", "296", "1.4167", "173" -"Korea, Democratic People's Republic of", "KP", "PRK", "408", "40", "127" -"Korea, Republic of", "KR", "KOR", "410", "37", "127.5" -"South Korea", "KR", "KOR", "410", "37", "127.5" -"Kuwait", "KW", "KWT", "414", "29.3375", "47.6581" -"Kyrgyzstan", "KG", "KGZ", "417", "41", "75" -"Lao People's Democratic Republic", "LA", "LAO", "418", "18", "105" -"Latvia", "LV", "LVA", "428", "57", "25" -"Lebanon", "LB", "LBN", "422", "33.8333", "35.8333" -"Lesotho", "LS", "LSO", "426", "-29.5", "28.5" -"Liberia", "LR", "LBR", "430", "6.5", "-9.5" -"Libyan Arab Jamahiriya", "LY", "LBY", "434", "25", "17" -"Libya", "LY", "LBY", "434", "25", "17" -"Liechtenstein", "LI", "LIE", "438", "47.1667", "9.5333" -"Lithuania", "LT", "LTU", "440", "56", "24" -"Luxembourg", "LU", "LUX", "442", "49.75", "6.1667" -"Macao", "MO", "MAC", "446", "22.1667", "113.55" -"Macedonia, the former Yugoslav Republic of", "MK", "MKD", "807", "41.8333", "22" -"Madagascar", "MG", "MDG", "450", "-20", "47" -"Malawi", "MW", "MWI", "454", "-13.5", "34" -"Malaysia", "MY", "MYS", "458", "2.5", "112.5" -"Maldives", "MV", "MDV", "462", "3.25", "73" -"Mali", "ML", "MLI", "466", "17", "-4" -"Malta", "MT", "MLT", "470", "35.8333", "14.5833" -"Marshall Islands", "MH", "MHL", "584", "9", "168" -"Martinique", "MQ", "MTQ", "474", "14.6667", "-61" -"Mauritania", "MR", "MRT", "478", "20", "-12" -"Mauritius", "MU", "MUS", "480", "-20.2833", "57.55" -"Mayotte", "YT", "MYT", "175", "-12.8333", "45.1667" -"Mexico", "MX", "MEX", "484", "23", "-102" -"Micronesia, Federated States of", "FM", "FSM", "583", "6.9167", "158.25" -"Moldova, Republic of", "MD", "MDA", "498", "47", "29" -"Monaco", "MC", "MCO", "492", "43.7333", "7.4" -"Mongolia", "MN", "MNG", "496", "46", "105" -"Montenegro", "ME", "MNE", "499", "42", "19" -"Montserrat", "MS", "MSR", "500", "16.75", "-62.2" -"Morocco", "MA", "MAR", "504", "32", "-5" -"Mozambique", "MZ", "MOZ", "508", "-18.25", "35" -"Myanmar", "MM", "MMR", "104", "22", "98" -"Burma", "MM", "MMR", "104", "22", "98" -"Namibia", "NA", "NAM", "516", "-22", "17" -"Nauru", "NR", "NRU", "520", "-0.5333", "166.9167" -"Nepal", "NP", "NPL", "524", "28", "84" -"Netherlands", "NL", "NLD", "528", "52.5", "5.75" -"Netherlands Antilles", "AN", "ANT", "530", "12.25", "-68.75" -"New Caledonia", "NC", "NCL", "540", "-21.5", "165.5" -"New Zealand", "NZ", "NZL", "554", "-41", "174" -"Nicaragua", "NI", "NIC", "558", "13", "-85" -"Niger", "NE", "NER", "562", "16", "8" -"Nigeria", "NG", "NGA", "566", "10", "8" -"Niue", "NU", "NIU", "570", "-19.0333", "-169.8667" -"Norfolk Island", "NF", "NFK", "574", "-29.0333", "167.95" -"Northern Mariana Islands", "MP", "MNP", "580", "15.2", "145.75" -"Norway", "NO", "NOR", "578", "62", "10" -"Oman", "OM", "OMN", "512", "21", "57" -"Pakistan", "PK", "PAK", "586", "30", "70" -"Palau", "PW", "PLW", "585", "7.5", "134.5" -"Palestinian Territory, Occupied", "PS", "PSE", "275", "32", "35.25" -"Panama", "PA", "PAN", "591", "9", "-80" -"Papua New Guinea", "PG", "PNG", "598", "-6", "147" -"Paraguay", "PY", "PRY", "600", "-23", "-58" -"Peru", "PE", "PER", "604", "-10", "-76" -"Philippines", "PH", "PHL", "608", "13", "122" -"Pitcairn", "PN", "PCN", "612", "-24.7", "-127.4" -"Poland", "PL", "POL", "616", "52", "20" -"Portugal", "PT", "PRT", "620", "39.5", "-8" -"Puerto Rico", "PR", "PRI", "630", "18.25", "-66.5" -"Qatar", "QA", "QAT", "634", "25.5", "51.25" -"Rรฉunion", "RE", "REU", "638", "-21.1", "55.6" -"Romania", "RO", "ROU", "642", "46", "25" -"Russian Federation", "RU", "RUS", "643", "60", "100" -"Russia", "RU", "RUS", "643", "60", "100" -"Rwanda", "RW", "RWA", "646", "-2", "30" -"Saint Helena, Ascension and Tristan da Cunha", "SH", "SHN", "654", "-15.9333", "-5.7" -"Saint Kitts and Nevis", "KN", "KNA", "659", "17.3333", "-62.75" -"Saint Lucia", "LC", "LCA", "662", "13.8833", "-61.1333" -"Saint Pierre and Miquelon", "PM", "SPM", "666", "46.8333", "-56.3333" -"Saint Vincent and the Grenadines", "VC", "VCT", "670", "13.25", "-61.2" -"Saint Vincent & the Grenadines", "VC", "VCT", "670", "13.25", "-61.2" -"St. Vincent and the Grenadines", "VC", "VCT", "670", "13.25", "-61.2" -"Samoa", "WS", "WSM", "882", "-13.5833", "-172.3333" -"San Marino", "SM", "SMR", "674", "43.7667", "12.4167" -"Sao Tome and Principe", "ST", "STP", "678", "1", "7" -"Saudi Arabia", "SA", "SAU", "682", "25", "45" -"Senegal", "SN", "SEN", "686", "14", "-14" -"Serbia", "RS", "SRB", "688", "44", "21" -"Seychelles", "SC", "SYC", "690", "-4.5833", "55.6667" -"Sierra Leone", "SL", "SLE", "694", "8.5", "-11.5" -"Singapore", "SG", "SGP", "702", "1.3667", "103.8" -"Slovakia", "SK", "SVK", "703", "48.6667", "19.5" -"Slovenia", "SI", "SVN", "705", "46", "15" -"Solomon Islands", "SB", "SLB", "90", "-8", "159" -"Somalia", "SO", "SOM", "706", "10", "49" -"South Africa", "ZA", "ZAF", "710", "-29", "24" -"South Georgia and the South Sandwich Islands", "GS", "SGS", "239", "-54.5", "-37" -"South Sudan", "SS", "SSD", "728", "8", "30" -"Spain", "ES", "ESP", "724", "40", "-4" -"Sri Lanka", "LK", "LKA", "144", "7", "81" -"Sudan", "SD", "SDN", "736", "15", "30" -"Suriname", "SR", "SUR", "740", "4", "-56" -"Svalbard and Jan Mayen", "SJ", "SJM", "744", "78", "20" -"Swaziland", "SZ", "SWZ", "748", "-26.5", "31.5" -"Sweden", "SE", "SWE", "752", "62", "15" -"Switzerland", "CH", "CHE", "756", "47", "8" -"Syrian Arab Republic", "SY", "SYR", "760", "35", "38" -"Taiwan, Province of China", "TW", "TWN", "158", "23.5", "121" -"Taiwan", "TW", "TWN", "158", "23.5", "121" -"Tajikistan", "TJ", "TJK", "762", "39", "71" -"Tanzania, United Republic of", "TZ", "TZA", "834", "-6", "35" -"Thailand", "TH", "THA", "764", "15", "100" -"Timor-Leste", "TL", "TLS", "626", "-8.55", "125.5167" -"Togo", "TG", "TGO", "768", "8", "1.1667" -"Tokelau", "TK", "TKL", "772", "-9", "-172" -"Tonga", "TO", "TON", "776", "-20", "-175" -"Trinidad and Tobago", "TT", "TTO", "780", "11", "-61" -"Tunisia", "TN", "TUN", "788", "34", "9" -"Turkey", "TR", "TUR", "792", "39", "35" -"Turkmenistan", "TM", "TKM", "795", "40", "60" -"Turks and Caicos Islands", "TC", "TCA", "796", "21.75", "-71.5833" -"Tuvalu", "TV", "TUV", "798", "-8", "178" -"Uganda", "UG", "UGA", "800", "1", "32" -"Ukraine", "UA", "UKR", "804", "49", "32" -"United Arab Emirates", "AE", "ARE", "784", "24", "54" -"United Kingdom", "GB", "GBR", "826", "54", "-2" -"United States", "US", "USA", "840", "38", "-97" -"United States Minor Outlying Islands", "UM", "UMI", "581", "19.2833", "166.6" -"Uruguay", "UY", "URY", "858", "-33", "-56" -"Uzbekistan", "UZ", "UZB", "860", "41", "64" -"Vanuatu", "VU", "VUT", "548", "-16", "167" -"Venezuela, Bolivarian Republic of", "VE", "VEN", "862", "8", "-66" -"Venezuela", "VE", "VEN", "862", "8", "-66" -"Viet Nam", "VN", "VNM", "704", "16", "106" -"Vietnam", "VN", "VNM", "704", "16", "106" -"Virgin Islands, British", "VG", "VGB", "92", "18.5", "-64.5" -"Virgin Islands, U.S.", "VI", "VIR", "850", "18.3333", "-64.8333" -"Wallis and Futuna", "WF", "WLF", "876", "-13.3", "-176.2" -"Western Sahara", "EH", "ESH", "732", "24.5", "-13" -"Yemen", "YE", "YEM", "887", "15", "48" -"Zambia", "ZM", "ZMB", "894", "-15", "30" -"Zimbabwe", "ZW", "ZWE", "716", "-20", "30" \ No newline at end of file diff --git a/validation/map_outages.ipynb b/validation/map_outages.ipynb deleted file mode 100644 index 94d64692..00000000 --- a/validation/map_outages.ipynb +++ /dev/null @@ -1,1044 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "835aff35", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3187746/637195552.py:5: UserWarning: Shapely 2.0 is installed, but because PyGEOS is also installed, GeoPandas will still use PyGEOS by default for now. To force to use and test Shapely 2.0, you have to set the environment variable USE_PYGEOS=0. You can do this before starting the Python process, or in your code before importing geopandas:\n", - "\n", - "import os\n", - "os.environ['USE_PYGEOS'] = '0'\n", - "import geopandas\n", - "\n", - "In a future release, GeoPandas will switch to using Shapely by default. If you are using PyGEOS directly (calling PyGEOS functions on geometries from GeoPandas), this will then stop working and you are encouraged to migrate from PyGEOS to Shapely 2.0 (https://shapely.readthedocs.io/en/latest/migration_pygeos.html).\n", - " import geopandas as gpd\n" - ] - } - ], - "source": [ - "import os\n", - "from glob import glob\n", - "import multiprocessing\n", - "\n", - "import geopandas as gpd\n", - "import matplotlib.pyplot as plt\n", - "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", - "from matplotlib.lines import Line2D\n", - "import numpy as np\n", - "import pandas as pd\n", - "import xarray as xr\n", - "from shapely.geometry import box, Polygon" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "8dd0c11d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import display, HTML\n", - "display(HTML(\"\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "66c9459c", - "metadata": {}, - "outputs": [], - "source": [ - "def plot_outage_maps(\n", - " event_id: str,\n", - " plot_dir: str,\n", - " thresholds: list[float | int],\n", - " exposure: xr.Dataset,\n", - " aoi: Polygon,\n", - " aoi_targets: gpd.GeoDataFrame,\n", - " borders: gpd.GeoDataFrame,\n", - " track: gpd.GeoDataFrame\n", - ") -> None:\n", - " \"\"\"\n", - " Plot target outage maps for a given storm and set of thresholds.\n", - " \"\"\"\n", - " \n", - " event_dir = os.path.join(plot_dir, event_id)\n", - "\n", - " if not os.path.exists(event_dir):\n", - " os.makedirs(event_dir)\n", - " \n", - " plot_paths = []\n", - " for threshold in thresholds:\n", - " \n", - " threshold_str = f\"{threshold:.2f}\".replace(\".\", \"p\")\n", - " plot_filepath = os.path.join(event_dir, f\"{threshold_str}.png\")\n", - " \n", - " if not os.path.exists(plot_filepath):\n", - "\n", - " # draw map at given threshold\n", - " fig = plot_outage_map_threshold(event_id, threshold, exposure, aoi, aoi_targets, borders, track)\n", - " fig.savefig(plot_filepath)\n", - " \n", - " plot_paths.append(plot_filepath)\n", - "\n", - " # animate stack of maps\n", - " os.system(f\"convert -delay 50 {' '.join(sorted(plot_paths))} {os.path.join(plot_dir, event_id)}.gif\")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "6e5ca09d", - "metadata": {}, - "outputs": [], - "source": [ - "def plot_outage_map_threshold(\n", - " event_id: str,\n", - " threshold: float | int,\n", - " exposure: xr.Dataset,\n", - " aoi: Polygon,\n", - " aoi_targets: gpd.GeoDataFrame,\n", - " borders: gpd.GeoDataFrame,\n", - " track: gpd.GeoDataFrame\n", - ") -> plt.Figure:\n", - " \"\"\"\n", - " Plot a target outage map for a given storm and threshold.\n", - " \"\"\"\n", - "\n", - " # preprocess data\n", - " # extract supply factor\n", - " df = exposure.supply_factor.sel(dict(event_id=event_id, threshold=threshold))\n", - " df = df.to_dataframe().reset_index()[[\"target\", \"supply_factor\"]]\n", - " df = df.rename(columns={\"target\": \"id\"})\n", - "\n", - " # drop targets with NaN supply_factor\n", - " df = df[~df.supply_factor.isna()]\n", - "\n", - " # combine target information with exposure\n", - " data = gpd.GeoDataFrame(df.merge(aoi_targets, how=\"inner\", on=\"id\"))\n", - " data.geometry = data.geometry.centroid\n", - "\n", - " # categorise supply_factor\n", - " status_cmap = {\n", - " \"DISCONNECTED\": \"firebrick\",\n", - " \"DEGRADED\": \"salmon\", \n", - " \"NOMINAL\": \"lightgrey\",\n", - " \"OVERSUPPLY\": \"darkorchid\"\n", - " }\n", - " status_labels = {\n", - " \"DISCONNECTED\": r\"Disconnected: [$s < 0.2$]\",\n", - " \"DEGRADED\": r\"Degraded: [$0.2 \\leq s < 0.8$]\",\n", - " \"NOMINAL\": r\"Nominal: [$0.8 \\leq s < 1.2$]\",\n", - " \"OVERSUPPLY\": r\"Oversupply: [$1.2 \\leq s$]\"\n", - " }\n", - " status_bin_edges = np.array([-np.inf, 0.20, 0.80, 1.2, np.inf])\n", - " data[\"connection_status\"] = pd.cut(\n", - " data.supply_factor,\n", - " bins=status_bin_edges,\n", - " labels=status_cmap.keys()\n", - " )\n", - " data[\"colour\"] = data.connection_status.map(status_cmap)\n", - "\n", - " # create figure that is correct aspect ratio, but no larger than 16\" wide or 9\" tall\n", - " min_x, min_y, max_x, max_y = aoi.bounds\n", - " x_span = max_x - min_x\n", - " y_span = max_y - min_y\n", - " aspect_ratio = y_span / x_span\n", - " max_plot_width_in = 16\n", - " max_plot_height_in = 9\n", - "\n", - " if max_plot_width_in * aspect_ratio < max_plot_height_in:\n", - " # tall\n", - " x_in = max_plot_width_in\n", - " y_in = max_plot_width_in * aspect_ratio\n", - "\n", - " else:\n", - " # wide\n", - " x_in = max_plot_height_in / aspect_ratio\n", - " y_in = max_plot_height_in\n", - " \n", - " fig, ax = plt.subplots(figsize=(x_in, y_in))\n", - " \n", - " # plot landmasses and political borders\n", - " borders.plot(ax=ax, facecolor=\"none\", edgecolor=\"grey\", alpha=0.5)\n", - "\n", - " # plot supply_factor\n", - " def population_markersize(x: np.array) -> np.array:\n", - " \"\"\"Target population -> target marker size\"\"\"\n", - " return np.log10(x) ** 4 / 10\n", - " \n", - " ax.scatter(data.geometry.x, data.geometry.y, c=data.colour, alpha=0.3, marker=\"o\", s=population_markersize(data.population))\n", - " \n", - " pop_handles = [\n", - " # N.B. need the sqrt around the markersize for equality between scatter markers and legend markers\n", - " Line2D([], [], color=status_cmap[\"NOMINAL\"], lw=0, marker=\"o\", markersize=np.sqrt(population_markersize(p)), label=f\"$10^{int(np.log10(p)):d}$\")\n", - " for p in np.logspace(4, 7, 7 - 4 + 1)\n", - " ]\n", - " pop_legend = ax.legend(handles=pop_handles, title=\"Node population\", loc=\"lower left\", ncol=len(pop_handles))\n", - " ax.add_artist(pop_legend)\n", - " \n", - " # reverse the cmap order, so it's from oversupply to undersupply\n", - " cmap = dict(reversed(status_cmap.items())).items()\n", - " status_handles = [\n", - " Line2D([0], [0], marker='o', color='w', markerfacecolor=colour, label=status_labels[status], markersize=8)\n", - " for status, colour in cmap if isinstance(status, str)\n", - " ]\n", - " status_legend = ax.legend(handles=status_handles, ncol=1, title=\"Node supply factor, $s$\", loc=\"upper right\")\n", - "\n", - " # plot tracks with colourbar for wind speed intensity\n", - " track_markersize = np.exp(track.category)\n", - " divider = make_axes_locatable(ax)\n", - " cax = divider.append_axes(\"right\", size=\"3%\", pad=0.01)\n", - " ax.plot(track.geometry.x, track.geometry.y, ls=\"--\", color=\"grey\", alpha=1)\n", - " track.plot(column=\"max_wind_speed_ms\", ax=ax, cax=cax, s=track_markersize, alpha=0.4, legend=True)\n", - " cax.set_ylabel(\"Wind speed $[m s^{-1}]$\")\n", - "\n", - " # set window to AOI (track with a buffer)\n", - " ax.set_xlim(min_x, max_x)\n", - " ax.set_ylim(min_y, max_y)\n", - " ax.set_xlabel(\"Longitude [deg]\")\n", - " ax.set_ylabel(\"Latitude [deg]\")\n", - " ax.grid()\n", - "\n", - " name, = set(track.name)\n", - " year, = set(track.year)\n", - " ax.set_title(f\"{event_id}: {name}, {year:d} @ {threshold:.1f} $[m s^{{-1}}]$\")\n", - "\n", - " return fig" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "47d1e395", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/3062914548.py:40: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n", - "/tmp/ipykernel_3187746/944994308.py:25: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", - "\n", - " data.geometry = data.geometry.centroid\n" - ] - } - ], - "source": [ - "def main():\n", - " root_path = \"/home/fred/projects/open_gira/\"\n", - "\n", - " # manually created targets file with country iso codes\n", - " #ย should probably modify target creation rule to include iso code column\n", - " targets_path = os.path.join(root_path, \"archive/2023-03-03T181500+0000/power/targets_with_iso_a3.geoparquet\")\n", - " exposure_path = os.path.join(root_path, \"archive/2023-03-03T181500+0000/power/by_storm_set/IBTrACS/exposure_by_target.nc\")\n", - " tracks_path = os.path.join(root_path, \"open-gira/results/input/IBTrACS/processed/v4.geoparquet\")\n", - " validation_data_path = os.path.join(root_path, \"open-gira/validation/outage_model_validation.csv\")\n", - "\n", - " # read in data\n", - " targets = gpd.read_parquet(targets_path)\n", - " exposure = xr.open_dataset(exposure_path)\n", - " borders = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))\n", - " tracks = gpd.read_parquet(tracks_path)\n", - " validation_data = pd.read_csv(validation_data_path)\n", - "\n", - " # do the plotting\n", - " plot_dir = os.path.join(root_path, \"open-gira/validation/plots/target_status\")\n", - " os.makedirs(plot_dir, exist_ok=True)\n", - "\n", - " events_to_plot = sorted(set(validation_data.event_id) & set(exposure.event_id.values))\n", - "\n", - " # batch the work into chunks\n", - " chunk_size = 8\n", - " for chunk_start in range(0, len(events_to_plot), chunk_size):\n", - "\n", - " args = []\n", - " for event_id in events_to_plot[chunk_start: chunk_start + chunk_size]:\n", - "\n", - " # subset tracks\n", - " track = tracks[tracks.track_id == event_id]\n", - "\n", - " # find all targets within X degrees of track\n", - " track_bbox = box(*track.geometry.total_bounds)\n", - " aoi = track_bbox.buffer(5)\n", - " aoi_targets = targets[targets.within(aoi)]\n", - " \n", - " # shrink AOI to ignore track in the open ocean\n", - " track_target_aoi = box(*aoi_targets.geometry.centroid.total_bounds)\n", - "\n", - " args.append((event_id, plot_dir, exposure.threshold.values, exposure, track_target_aoi, aoi_targets, borders, track))\n", - "\n", - " with multiprocessing.Pool(processes=chunk_size) as pool:\n", - " pool.starmap(plot_outage_maps, args)\n", - " \n", - "main()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.8" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/validation/observed_outages/2005236N23285.csv b/validation/observed_outages/2005236N23285.csv deleted file mode 100644 index 85e0386b..00000000 --- a/validation/observed_outages/2005236N23285.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,2700000,,http://www.oe.netl.doe.gov/docs/HurricaneComp0508r2.pdf diff --git a/validation/observed_outages/2005261N21290.csv b/validation/observed_outages/2005261N21290.csv deleted file mode 100644 index 3cc57cf7..00000000 --- a/validation/observed_outages/2005261N21290.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,1500000,,http://www.oe.netl.doe.gov/docs/HurricaneComp0508r2.pdf diff --git a/validation/observed_outages/2005289N18282.csv b/validation/observed_outages/2005289N18282.csv deleted file mode 100644 index 3543b101..00000000 --- a/validation/observed_outages/2005289N18282.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,3500000,,http://www.oe.netl.doe.gov/docs/HurricaneComp0508r2.pdf diff --git a/validation/observed_outages/2008238N13293.csv b/validation/observed_outages/2008238N13293.csv deleted file mode 100644 index 985d35e7..00000000 --- a/validation/observed_outages/2008238N13293.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,1100000,,http://www.oe.netl.doe.gov/docs/HurricaneComp0508r2.pdf diff --git a/validation/observed_outages/2008245N17323.csv b/validation/observed_outages/2008245N17323.csv deleted file mode 100644 index de1bb2e1..00000000 --- a/validation/observed_outages/2008245N17323.csv +++ /dev/null @@ -1,3 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,2900000,,https://hurricane.egr.uh.edu/sites/hurricane.egr.uh.edu/files/files/2009/wei.pdf -USA,3900000,,http://www.oe.netl.doe.gov/docs/HurricaneComp0508r2.pdf diff --git a/validation/observed_outages/2011028S13180.csv b/validation/observed_outages/2011028S13180.csv deleted file mode 100644 index 4517a4dc..00000000 --- a/validation/observed_outages/2011028S13180.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -AUS,170000,,https://web.archive.org/web/20110204093056/http://www.smh.com.au/environment/weather/power-down-for-weeks-after-yasi-20110203-1ae4p.html diff --git a/validation/observed_outages/2011233N15301.csv b/validation/observed_outages/2011233N15301.csv deleted file mode 100644 index 198fd301..00000000 --- a/validation/observed_outages/2011233N15301.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,6690000,,http://www.oe.netl.doe.gov/docs/Northeast%20Storm%20Comparison_FINAL_041513c.pdf diff --git a/validation/observed_outages/2012296N14283.csv b/validation/observed_outages/2012296N14283.csv deleted file mode 100644 index 680ea405..00000000 --- a/validation/observed_outages/2012296N14283.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,8511251,,https://www.oe.netl.doe.gov/docs/2012_SitRep20_Sandy_11072012_1000AM.pdf diff --git a/validation/observed_outages/2013018S14138.csv b/validation/observed_outages/2013018S14138.csv deleted file mode 100644 index 990fde9a..00000000 --- a/validation/observed_outages/2013018S14138.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -AUS,283000,,https://www.couriermail.com.au/news/almost-250000-homes-without-power-as-weather-hits-seq-electricity-grid/news-story/43f96e3940d3f1d05ee09d679bcefb09 diff --git a/validation/observed_outages/2013306N07162.csv b/validation/observed_outages/2013306N07162.csv deleted file mode 100644 index 3a4dede9..00000000 --- a/validation/observed_outages/2013306N07162.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -PHL,,12000000,https://www.ucanews.com/news/power-outages-continue-in-philippines-following-typhoon/71447 diff --git a/validation/observed_outages/2014092S11159.csv b/validation/observed_outages/2014092S11159.csv deleted file mode 100644 index a299bbdf..00000000 --- a/validation/observed_outages/2014092S11159.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -AUS,46000,,https://knowledge.aidr.org.au/resources/cyclone-cyclone-ita-queensland/ diff --git a/validation/observed_outages/2014190N08154.csv b/validation/observed_outages/2014190N08154.csv deleted file mode 100644 index bb3758e1..00000000 --- a/validation/observed_outages/2014190N08154.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -PHL,,25000000,https://www.wsj.com/articles/typhoon-rammasun-death-toll-rises-to-38-in-the-philippines-1405573803 diff --git a/validation/observed_outages/2015293N13266.csv b/validation/observed_outages/2015293N13266.csv deleted file mode 100644 index db8504a1..00000000 --- a/validation/observed_outages/2015293N13266.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -MEX,,250000,https://www.vox.com/2015/10/26/9615274/hurricane-patricia-aftermath diff --git a/validation/observed_outages/2016242N24279.csv b/validation/observed_outages/2016242N24279.csv deleted file mode 100644 index c0d947d9..00000000 --- a/validation/observed_outages/2016242N24279.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,,432000,http://web.archive.org/web/20160911072502/https://abcnews.go.com/US/wireStory/hermine-hits-florida-coast-1st-hurricane-decade-41816713 diff --git a/validation/observed_outages/2016253N13144.csv b/validation/observed_outages/2016253N13144.csv deleted file mode 100644 index 6e4cc06f..00000000 --- a/validation/observed_outages/2016253N13144.csv +++ /dev/null @@ -1,3 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -TWN,1000000,,https://www.upi.com/Top_News/World-News/2016/09/15/Typhoon-Meranti-kills-one-destroys-historic-bridge-thousands-without-power/2171473936356/ -CHN,1650000,,https://www.reuters.com/article/us-asia-storm-china-idUSKCN11L03F diff --git a/validation/observed_outages/2016273N13300.csv b/validation/observed_outages/2016273N13300.csv deleted file mode 100644 index 8fa14377..00000000 --- a/validation/observed_outages/2016273N13300.csv +++ /dev/null @@ -1,3 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,1580000,,https://poweroutage.us/about/majorevents -USA,3080000,,https://www.eia.gov/todayinenergy/detail.php?id=28372 diff --git a/validation/observed_outages/2017228N14314.csv b/validation/observed_outages/2017228N14314.csv deleted file mode 100644 index 2b79be9a..00000000 --- a/validation/observed_outages/2017228N14314.csv +++ /dev/null @@ -1,3 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,309204,,https://poweroutage.us/about/majorevents -USA,2020000,,https://www.nerc.com/pa/rrm/ea/Hurricane_Harvey_EAR_DL/NERC_Hurricane_Harvey_EAR_20180309.pdf diff --git a/validation/observed_outages/2017242N16333.csv b/validation/observed_outages/2017242N16333.csv deleted file mode 100644 index 880db952..00000000 --- a/validation/observed_outages/2017242N16333.csv +++ /dev/null @@ -1,5 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,7654461,,https://poweroutage.us/about/majorevents -PRI,,900000,https://www.marketwatch.com/story/hurricane-maria-thrashes-dominican-republic-after-leaving-puerto-rico-entirely-without-power-2017-09-21 -PRI,,1000000,https://people.com/human-interest/hurricane-irma-1-million-without-power-puerto-rico-kills-10/ -CUB,,3100000,https://reliefweb.int/report/cuba/cuba-hurricane-irma-emergency-appeal-n-mdrcu004-12-month-operations-update diff --git a/validation/observed_outages/2017260N12310.csv b/validation/observed_outages/2017260N12310.csv deleted file mode 100644 index 82662ecb..00000000 --- a/validation/observed_outages/2017260N12310.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -PRI,1500000,,https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0218883 diff --git a/validation/observed_outages/2018073S09129.csv b/validation/observed_outages/2018073S09129.csv deleted file mode 100644 index 33037081..00000000 --- a/validation/observed_outages/2018073S09129.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -AUS,28500,,https://utilicom.nt.gov.au/news/2018/no-gsl-payments-relating-to-tropical-cyclone-marcus diff --git a/validation/observed_outages/2018242N13343.csv b/validation/observed_outages/2018242N13343.csv deleted file mode 100644 index fd33b825..00000000 --- a/validation/observed_outages/2018242N13343.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,1400000,,https://poweroutage.us/about/majorevents diff --git a/validation/observed_outages/2018280N18273.csv b/validation/observed_outages/2018280N18273.csv deleted file mode 100644 index ab51b08e..00000000 --- a/validation/observed_outages/2018280N18273.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,3100000,,https://poweroutage.us/about/majorevents diff --git a/validation/observed_outages/2018292N14261.csv b/validation/observed_outages/2018292N14261.csv deleted file mode 100644 index 312d4b65..00000000 --- a/validation/observed_outages/2018292N14261.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -MEX,102000,,https://apnews.com/article/caribbean-ap-top-news-international-news-hurricanes-storms-7d17de60abde4ff1997faf0dfd8c7b61 diff --git a/validation/observed_outages/2020136N10088.csv b/validation/observed_outages/2020136N10088.csv deleted file mode 100644 index 8b4f9712..00000000 --- a/validation/observed_outages/2020136N10088.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -BGD,1040000,,https://www.newindianexpress.com/world/2020/may/21/over-1-million-customers-lose-power-supply-as-cyclone-amphan-hits-bangladesh-coast-three-dead-2145936.html diff --git a/validation/observed_outages/2020211N13306.csv b/validation/observed_outages/2020211N13306.csv deleted file mode 100644 index c1d40997..00000000 --- a/validation/observed_outages/2020211N13306.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,6400000,,https://poweroutage.us/about/majorevents diff --git a/validation/observed_outages/2022255N15324.csv b/validation/observed_outages/2022255N15324.csv deleted file mode 100644 index 8411493d..00000000 --- a/validation/observed_outages/2022255N15324.csv +++ /dev/null @@ -1,3 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -DOM,,709000,https://www.reuters.com/business/environment/hurricane-fiona-slams-dominican-republic-after-leaving-puerto-rico-mostly-2022-09-19/ -PRI,1400000,,https://poweroutage.us/about/majorevents diff --git a/validation/observed_outages/2022263N10313.csv b/validation/observed_outages/2022263N10313.csv deleted file mode 100644 index 0b52ecd3..00000000 --- a/validation/observed_outages/2022263N10313.csv +++ /dev/null @@ -1,2 +0,0 @@ -country_iso_a3,customers_affected,population_affected,source -USA,4450000,,https://poweroutage.us/about/majorevents diff --git a/validation/outage_model_validation.csv b/validation/outage_model_validation.csv deleted file mode 100644 index 59405fee..00000000 --- a/validation/outage_model_validation.csv +++ /dev/null @@ -1,241 +0,0 @@ -threshold,event_id,country_iso_a3,observed,modelled,error,error_abs,ratio,error_norm,signed_ratio 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-45.0,2014092S11159,AUS,117299.99999999999,0.0,-117299.99999999999,117299.99999999999,0.0,-1.0,-0.0 -45.0,2014190N08154,PHL,25000000.0,24947841.286639474,-52158.71336052567,52158.71336052567,0.997913651465579,-0.0020863485344210266,-0.997913651465579 -45.0,2015293N13266,MEX,250000.0,141596.45169224692,-108403.54830775308,108403.54830775308,0.5663858067689876,-0.4336141932310123,-0.5663858067689876 -45.0,2016242N24279,USA,432000.0,0.0,-432000.0,432000.0,0.0,-1.0,-0.0 -45.0,2016253N13144,CHN,5577000.0,6737051.976459128,1160051.9764591279,1160051.9764591279,1.2080064508623145,0.20800645086231448,1.2080064508623145 -45.0,2016253N13144,TWN,,2801621.0394942164,,,,, -45.0,2016273N13300,USA,7669200.000000001,425853.1152500508,-7243346.88474995,7243346.88474995,0.055527710224019554,-0.9444722897759804,-0.055527710224019554 -45.0,2017228N14314,USA,5029800.0,1132803.0834181567,-3896996.916581843,3896996.916581843,0.22521831552311358,-0.7747816844768863,-0.22521831552311358 -45.0,2017242N16333,CUB,3100000.0,4161172.011268383,1061172.011268383,1061172.011268383,1.342313552022059,0.342313552022059,1.342313552022059 -45.0,2017242N16333,PRI,1000000.0,66967.06887854419,-933032.9311214559,933032.9311214559,0.06696706887854419,-0.9330329311214558,-0.06696706887854419 -45.0,2017242N16333,USA,19059607.89,474825.6833663062,-18584782.206633694,18584782.206633694,0.02491266798911602,-0.9750873320108839,-0.02491266798911602 -45.0,2017260N12310,PRI,4005000.0,2738996.174740714,-1266003.825259286,1266003.825259286,0.683894175965222,-0.31610582403477805,-0.683894175965222 -45.0,2018073S09129,AUS,72675.0,0.0,-72675.0,72675.0,0.0,-1.0,-0.0 -45.0,2018242N13343,USA,3486000.0000000005,0.0,-3486000.0000000005,3486000.0000000005,0.0,-1.0,-0.0 -45.0,2018280N18273,USA,7719000.000000001,1134417.6847038788,-6584582.315296122,6584582.315296122,0.14696433277676885,-0.8530356672232311,-0.14696433277676885 -45.0,2018292N14261,MEX,382500.0,7409491.45374268,7026991.45374268,7026991.45374268,19.371219486908966,18.371219486908966,19.371219486908966 -45.0,2020136N10088,BGD,4430400.0,,,,,, -45.0,2020211N13306,USA,15936000.000000002,0.0,-15936000.000000002,15936000.000000002,0.0,-1.0,-0.0 -45.0,2022255N15324,DOM,709000.0,0.0,-709000.0,709000.0,0.0,-1.0,-0.0 -45.0,2022255N15324,PRI,3738000.0,0.0,-3738000.0,3738000.0,0.0,-1.0,-0.0 -45.0,2022263N10313,USA,11080500.000000002,1864210.4122445772,-9216289.587755425,9216289.587755425,0.16824244503809185,-0.8317575549619082,-0.16824244503809185 diff --git a/validation/outage_model_validation.ipynb b/validation/outage_model_validation.ipynb deleted file mode 100644 index 3427393a..00000000 --- a/validation/outage_model_validation.ipynb +++ /dev/null @@ -1,1166 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "96c6c070", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'\\nValidation of open-gira power outage model\\nThis notebook compares modelled and observed customer disconnected estimates\\nObserved data are collated media and goverment reports (CSV files in validation/)\\nModelled data are exposure_by_country.nc for the whole IBTrACS storm set\\n'" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "\"\"\"\n", - "Validation of open-gira power outage model\n", - "This notebook compares modelled and observed customer disconnected estimates\n", - "Observed data are collated media and goverment reports (CSV files in validation/)\n", - "Modelled data are exposure_by_country.nc for the whole IBTrACS storm set\n", - "\"\"\"" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "9a6b87f8", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_3184390/2742257982.py:4: UserWarning: Shapely 2.0 is installed, but because PyGEOS is also installed, GeoPandas will still use PyGEOS by default for now. To force to use and test Shapely 2.0, you have to set the environment variable USE_PYGEOS=0. You can do this before starting the Python process, or in your code before importing geopandas:\n", - "\n", - "import os\n", - "os.environ['USE_PYGEOS'] = '0'\n", - "import geopandas\n", - "\n", - "In a future release, GeoPandas will switch to using Shapely by default. If you are using PyGEOS directly (calling PyGEOS functions on geometries from GeoPandas), this will then stop working and you are encouraged to migrate from PyGEOS to Shapely 2.0 (https://shapely.readthedocs.io/en/latest/migration_pygeos.html).\n", - " import geopandas as gpd\n" - ] - } - ], - "source": [ - "import os\n", - "from glob import glob\n", - "\n", - "import geopandas as gpd\n", - "import matplotlib\n", - "from matplotlib.lines import Line2D\n", - "import matplotlib.pyplot as plt\n", - "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", - "import numpy as np\n", - "import pandas as pd\n", - "import xarray as xr" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "be058577", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import display, HTML\n", - "display(HTML(\"\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "d69837a2", - "metadata": {}, - "outputs": [], - "source": [ - "# model outputs\n", - "root_path = \"/home/fred/projects/open_gira/\"\n", - "tracks_path = os.path.join(root_path, \"open-gira/results/input/IBTrACS/processed/v4.geoparquet\")\n", - "targets_path = os.path.join(root_path, \"archive/2023-03-03T181500+0000/power/targets_with_iso_a3.geoparquet\")\n", - "exposure_path = os.path.join(root_path, \"archive/2023-03-03T181500+0000/power/by_storm_set/IBTrACS/exposure_by_country.nc\")\n", - "\n", - "# validation data\n", - "# https://www.un.org/development/desa/pd/data/household-size-and-composition\n", - "household_path = os.path.join(root_path, \"open-gira/validation/undesa_pd_2022_hh-size-composition.xlsx\")\n", - "# https://gist.githubusercontent.com/tadast/8827699/raw/f5cac3d42d16b78348610fc4ec301e9234f82821/countries_codes_and_coordinates.csv\n", - "iso_codes = os.path.join(root_path, \"open-gira/validation/iso_codes.csv\")\n", - "# see source column\n", - "outage_paths = glob(os.path.join(root_path, \"open-gira/validation/observed_outages/*.csv\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "c37b9522", - "metadata": {}, - "outputs": [], - "source": [ - "# read iso numeric to alpha table\n", - "rename_dict = {\n", - " \"Country\": \"name\",\n", - " \"Alpha-2 code\": \"iso_a2\",\n", - " \"Alpha-3 code\": \"iso_a3\",\n", - " \"Numeric code\": \"iso_num\"\n", - "}\n", - "iso = pd.read_csv(iso_codes, usecols=rename_dict.keys())\n", - "iso = iso.rename(columns=rename_dict)\n", - "# strip out quotes\n", - "for c in iso.columns:\n", - " iso[c] = iso[c].str.replace('\"', \"\").str.strip()\n", - "iso.iso_num = iso.iso_num.astype(int)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "9551117c", - "metadata": {}, - "outputs": [], - "source": [ - "# read household size data\n", - "rename_dict = {\n", - " \"ISO Code\": \"iso_num\",\n", - " \"Reference date (dd/mm/yyyy)\": \"ref_date\",\n", - " \"Average household size (number of members)\": \"mean_household_pop\"\n", - "}\n", - "hh = pd.read_excel(household_path, sheet_name=\"HH size and composition 2022\", header=4, usecols=rename_dict.keys())\n", - "hh = hh.rename(columns=rename_dict)\n", - "hh.ref_date = pd.to_datetime(hh.ref_date, dayfirst=True)\n", - "\n", - "# any non-numeric value -> NaN (some '..' placeholders in excel data)\n", - "hh[\"mean_household_pop\"] = pd.to_numeric(hh[\"mean_household_pop\"], errors=\"coerce\")\n", - "\n", - "# drop any rows without a valid mean household pop\n", - "hh = hh[~hh.mean_household_pop.isna()]\n", - "\n", - "# discard all but most recent entry for each territory\n", - "hh = hh.sort_values([\"ref_date\"], ascending=False).drop_duplicates(\"iso_num\", keep=\"first\")\n", - "\n", - "# merge in iso alpha ids (will permit join with outage data)\n", - "hh = hh.merge(iso, how=\"left\", on=\"iso_num\")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "45ae7771", - "metadata": {}, - "outputs": [], - "source": [ - "# now compare population_affected with the exposure_by_country.nc data\n", - "ds = xr.open_dataset(exposure_path).rename({\"country\": \"country_iso_a3\"})\n", - "\n", - "by_threshold = {}\n", - "for threshold in ds.threshold.values:\n", - "\n", - " # storm loop\n", - " obs_data = {os.path.basename(p).split(\".\")[0]: pd.read_csv(p) for p in sorted(outage_paths)}\n", - " by_storm = {}\n", - " for event_id, obs in obs_data.items():\n", - " \n", - " try:\n", - " # select model data for given storm and threshold\n", - " mod = ds.customers_affected.sel(dict(event_id=event_id, threshold=threshold)).to_pandas()\n", - " except KeyError:\n", - " # storm has no modelled results for any threshold\n", - " continue\n", - " \n", - " # create a duplicate dataframe for modelled and derived measures (as well as obs)\n", - " by_storm[event_id] = obs.copy()\n", - " \n", - " # bring in demographic data to obs dataframe\n", - " obs = obs.rename(columns={\"country_iso_a3\": \"iso_a3\"}).merge(hh, how=\"left\", on=\"iso_a3\")\n", - "\n", - " for i in range(len(obs)):\n", - " # gap-fill the population_affected numbers where we have customers_affected only\n", - " if pd.isna(obs.loc[i, \"population_affected\"]):\n", - " by_storm[event_id].loc[i, \"population_affected\"] = \\\n", - " obs.loc[i, \"customers_affected\"] * obs.loc[i, \"mean_household_pop\"]\n", - "\n", - " # take the largest estimate for each country (we assume reports underestimate outages)\n", - " by_storm[event_id] = by_storm[event_id].groupby(\"country_iso_a3\").max()\n", - " by_storm[event_id] = by_storm[event_id][[\"population_affected\"]]\n", - " by_storm[event_id] = by_storm[event_id].rename(columns={\"population_affected\": \"observed\"})\n", - "\n", - " # modelled customers_affected (really population affected, should change this name!)\n", - " mod.name = \"modelled\"\n", - " by_storm[event_id] = by_storm[event_id].join(mod)\n", - " by_storm[event_id][\"error\"] = \\\n", - " by_storm[event_id].modelled - by_storm[event_id].observed\n", - " by_storm[event_id][\"error_abs\"] = \\\n", - " np.abs(by_storm[event_id][\"error\"])\n", - " by_storm[event_id][\"ratio\"] = \\\n", - " by_storm[event_id].modelled / by_storm[event_id].observed\n", - " by_storm[event_id][\"error_norm\"] = \\\n", - " by_storm[event_id].error / by_storm[event_id].observed\n", - " by_storm[event_id][\"signed_ratio\"] = \\\n", - " np.sign(by_storm[event_id].error) * by_storm[event_id].ratio\n", - "\n", - " concat = pd.concat(by_storm)\n", - " concat.index.names = [\"event_id\", \"country_iso_a3\"]\n", - " by_threshold[threshold] = concat\n", - "\n", - "# all data with a 3 level multi-index\n", - "data = pd.concat(by_threshold, names=[\"threshold\", \"event_id\", \"country_iso_a3\"])\n", - "\n", - "# write to disk\n", - "data.to_csv(\"outage_model_validation.csv\")" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "3ae309c5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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observedmodellederrorerror_absratioerror_normsigned_ratio
event_idcountry_iso_a3
2005236N23285USA6723000.001.349097e+076.767968e+066.767968e+062.0066891.0066892.006689
2005261N21290USA3735000.004.070329e+063.353288e+053.353288e+051.0897800.0897801.089780
2005289N18282USA8715000.007.700070e+06-1.014930e+061.014930e+060.883542-0.116458-0.883542
2008238N13293USA2739000.001.064142e+077.902419e+067.902419e+063.8851472.8851473.885147
2008245N17323USA9711000.009.470136e+06-2.408638e+052.408638e+050.975197-0.024803-0.975197
2011028S13180AUS433500.001.762983e+05-2.572017e+052.572017e+050.406686-0.593314-0.406686
2011233N15301USA16658100.006.071332e+05-1.605097e+071.605097e+070.036447-0.963553-0.036447
2012296N14283USA21193014.993.353923e+071.234622e+071.234622e+071.5825610.5825611.582561
2013306N07162PHL12000000.009.278462e+06-2.721538e+062.721538e+060.773205-0.226795-0.773205
2014092S11159AUS117300.002.470017e+03-1.148300e+051.148300e+050.021057-0.978943-0.021057
2014190N08154PHL25000000.003.524475e+071.024475e+071.024475e+071.4097900.4097901.409790
2015293N13266MEX250000.001.244851e+071.219851e+071.219851e+0749.79403648.79403649.794036
2016242N24279USA432000.009.031791e+04-3.416821e+053.416821e+050.209069-0.790931-0.209069
2016253N13144CHN5577000.001.877560e+071.319860e+071.319860e+073.3666122.3666123.366612
TWNNaN5.270656e+06NaNNaNNaNNaNNaN
2016273N13300USA7669200.007.655421e+06-1.377917e+041.377917e+040.998203-0.001797-0.998203
2017228N14314USA5029800.002.087086e+06-2.942714e+062.942714e+060.414944-0.585056-0.414944
2017242N16333CUB3100000.005.926783e+062.826783e+062.826783e+061.9118660.9118661.911866
PRI1000000.002.156092e+061.156092e+061.156092e+062.1560921.1560922.156092
USA19059607.896.808931e+06-1.225068e+071.225068e+070.357244-0.642756-0.357244
2017260N12310PRI4005000.002.738996e+06-1.266004e+061.266004e+060.683894-0.316106-0.683894
2018073S09129AUS72675.000.000000e+00-7.267500e+047.267500e+040.000000-1.000000-0.000000
2018242N13343USA3486000.001.441513e+06-2.044487e+062.044487e+060.413515-0.586485-0.413515
2018280N18273USA7719000.001.531375e+06-6.187625e+066.187625e+060.198390-0.801610-0.198390
2018292N14261MEX382500.007.470910e+067.088410e+067.088410e+0619.53179218.53179219.531792
2020136N10088BGD4430400.00NaNNaNNaNNaNNaNNaN
2020211N13306USA15936000.006.935946e+05-1.524241e+071.524241e+070.043524-0.956476-0.043524
2022255N15324DOM709000.008.141210e+051.051210e+051.051210e+051.1482670.1482671.148267
PRI3738000.001.917598e+06-1.820402e+061.820402e+060.513001-0.486999-0.513001
2022263N10313USA11080500.007.018806e+06-4.061694e+064.061694e+060.633438-0.366562-0.633438
\n", - "
" - ], - "text/plain": [ - " observed modelled error \\\n", - "event_id country_iso_a3 \n", - "2005236N23285 USA 6723000.00 1.349097e+07 6.767968e+06 \n", - "2005261N21290 USA 3735000.00 4.070329e+06 3.353288e+05 \n", - "2005289N18282 USA 8715000.00 7.700070e+06 -1.014930e+06 \n", - "2008238N13293 USA 2739000.00 1.064142e+07 7.902419e+06 \n", - "2008245N17323 USA 9711000.00 9.470136e+06 -2.408638e+05 \n", - "2011028S13180 AUS 433500.00 1.762983e+05 -2.572017e+05 \n", - "2011233N15301 USA 16658100.00 6.071332e+05 -1.605097e+07 \n", - "2012296N14283 USA 21193014.99 3.353923e+07 1.234622e+07 \n", - "2013306N07162 PHL 12000000.00 9.278462e+06 -2.721538e+06 \n", - "2014092S11159 AUS 117300.00 2.470017e+03 -1.148300e+05 \n", - "2014190N08154 PHL 25000000.00 3.524475e+07 1.024475e+07 \n", - "2015293N13266 MEX 250000.00 1.244851e+07 1.219851e+07 \n", - "2016242N24279 USA 432000.00 9.031791e+04 -3.416821e+05 \n", - "2016253N13144 CHN 5577000.00 1.877560e+07 1.319860e+07 \n", - " TWN NaN 5.270656e+06 NaN \n", - "2016273N13300 USA 7669200.00 7.655421e+06 -1.377917e+04 \n", - "2017228N14314 USA 5029800.00 2.087086e+06 -2.942714e+06 \n", - "2017242N16333 CUB 3100000.00 5.926783e+06 2.826783e+06 \n", - " PRI 1000000.00 2.156092e+06 1.156092e+06 \n", - " USA 19059607.89 6.808931e+06 -1.225068e+07 \n", - "2017260N12310 PRI 4005000.00 2.738996e+06 -1.266004e+06 \n", - "2018073S09129 AUS 72675.00 0.000000e+00 -7.267500e+04 \n", - "2018242N13343 USA 3486000.00 1.441513e+06 -2.044487e+06 \n", - "2018280N18273 USA 7719000.00 1.531375e+06 -6.187625e+06 \n", - "2018292N14261 MEX 382500.00 7.470910e+06 7.088410e+06 \n", - "2020136N10088 BGD 4430400.00 NaN NaN \n", - "2020211N13306 USA 15936000.00 6.935946e+05 -1.524241e+07 \n", - "2022255N15324 DOM 709000.00 8.141210e+05 1.051210e+05 \n", - " PRI 3738000.00 1.917598e+06 -1.820402e+06 \n", - "2022263N10313 USA 11080500.00 7.018806e+06 -4.061694e+06 \n", - "\n", - " error_abs ratio error_norm \\\n", - "event_id country_iso_a3 \n", - "2005236N23285 USA 6.767968e+06 2.006689 1.006689 \n", - "2005261N21290 USA 3.353288e+05 1.089780 0.089780 \n", - "2005289N18282 USA 1.014930e+06 0.883542 -0.116458 \n", - "2008238N13293 USA 7.902419e+06 3.885147 2.885147 \n", - "2008245N17323 USA 2.408638e+05 0.975197 -0.024803 \n", - "2011028S13180 AUS 2.572017e+05 0.406686 -0.593314 \n", - "2011233N15301 USA 1.605097e+07 0.036447 -0.963553 \n", - "2012296N14283 USA 1.234622e+07 1.582561 0.582561 \n", - "2013306N07162 PHL 2.721538e+06 0.773205 -0.226795 \n", - "2014092S11159 AUS 1.148300e+05 0.021057 -0.978943 \n", - "2014190N08154 PHL 1.024475e+07 1.409790 0.409790 \n", - "2015293N13266 MEX 1.219851e+07 49.794036 48.794036 \n", - "2016242N24279 USA 3.416821e+05 0.209069 -0.790931 \n", - "2016253N13144 CHN 1.319860e+07 3.366612 2.366612 \n", - " TWN NaN NaN NaN \n", - "2016273N13300 USA 1.377917e+04 0.998203 -0.001797 \n", - "2017228N14314 USA 2.942714e+06 0.414944 -0.585056 \n", - "2017242N16333 CUB 2.826783e+06 1.911866 0.911866 \n", - " PRI 1.156092e+06 2.156092 1.156092 \n", - " USA 1.225068e+07 0.357244 -0.642756 \n", - "2017260N12310 PRI 1.266004e+06 0.683894 -0.316106 \n", - "2018073S09129 AUS 7.267500e+04 0.000000 -1.000000 \n", - "2018242N13343 USA 2.044487e+06 0.413515 -0.586485 \n", - "2018280N18273 USA 6.187625e+06 0.198390 -0.801610 \n", - "2018292N14261 MEX 7.088410e+06 19.531792 18.531792 \n", - "2020136N10088 BGD NaN NaN NaN \n", - "2020211N13306 USA 1.524241e+07 0.043524 -0.956476 \n", - "2022255N15324 DOM 1.051210e+05 1.148267 0.148267 \n", - " PRI 1.820402e+06 0.513001 -0.486999 \n", - "2022263N10313 USA 4.061694e+06 0.633438 -0.366562 \n", - "\n", - " signed_ratio \n", - "event_id country_iso_a3 \n", - "2005236N23285 USA 2.006689 \n", - "2005261N21290 USA 1.089780 \n", - "2005289N18282 USA -0.883542 \n", - "2008238N13293 USA 3.885147 \n", - "2008245N17323 USA -0.975197 \n", - "2011028S13180 AUS -0.406686 \n", - "2011233N15301 USA -0.036447 \n", - "2012296N14283 USA 1.582561 \n", - "2013306N07162 PHL -0.773205 \n", - "2014092S11159 AUS -0.021057 \n", - "2014190N08154 PHL 1.409790 \n", - "2015293N13266 MEX 49.794036 \n", - "2016242N24279 USA -0.209069 \n", - "2016253N13144 CHN 3.366612 \n", - " TWN NaN \n", - "2016273N13300 USA -0.998203 \n", - "2017228N14314 USA -0.414944 \n", - "2017242N16333 CUB 1.911866 \n", - " PRI 2.156092 \n", - " USA -0.357244 \n", - "2017260N12310 PRI -0.683894 \n", - "2018073S09129 AUS -0.000000 \n", - "2018242N13343 USA -0.413515 \n", - "2018280N18273 USA -0.198390 \n", - "2018292N14261 MEX 19.531792 \n", - "2020136N10088 BGD NaN \n", - "2020211N13306 USA -0.043524 \n", - "2022255N15324 DOM 1.148267 \n", - " PRI -0.513001 \n", - "2022263N10313 USA -0.633438 " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# example data for a given threshold\n", - "data.loc[32.5, :, :]" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "fd567148", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# where are these tracks?\n", - "borders = gpd.read_file(gpd.datasets.get_path(\"naturalearth_lowres\"))\n", - "tracks = gpd.read_parquet(tracks_path)\n", - "tracks = tracks[tracks.track_id.isin(set(data.index.get_level_values(\"event_id\")))]\n", - "\n", - "f, ax = plt.subplots(figsize=(16, 7))\n", - "\n", - "# plot landmasses and political borders\n", - "borders.plot(ax=ax, facecolor=\"none\", edgecolor=\"grey\", alpha=0.5)\n", - "\n", - "# plot tracks with colourbar for wind speed intensity\n", - "divider = make_axes_locatable(ax)\n", - "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.15)\n", - "markersize = np.exp(tracks.category)\n", - "tracks.plot(column=\"max_wind_speed_ms\", ax=ax, s=markersize, cax=cax, legend=True, cmap=\"viridis\")\n", - "cax.set_ylabel(\"Max wind speed $[ms^{-1}]$\")\n", - "\n", - "ax.set_xlim(-130, 180)\n", - "ax.set_ylim(-60, 75)\n", - "ax.set_title(\"Tracks of storms with observed outage data\")\n", - "ax.set_xlabel(\"Longitude [deg]\")\n", - "ax.set_ylabel(\"Latitude [deg]\")\n", - "\n", - "# second legend for saffir simpson storm classification\n", - "saffir_simpson = ax.legend(\n", - " handles=[\n", - " Line2D(\n", - " [],\n", - " [],\n", - " color=plt.get_cmap(\"viridis\")(0.8),\n", - " lw=0,\n", - " marker=\"o\",\n", - " markersize=np.sqrt(b),\n", - " label=np.log(b),\n", - " )\n", - " for b in sorted(set(markersize))\n", - " ],\n", - " loc=\"lower left\",\n", - " title=\"Saffir-Simpson scale\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "75841142", - "metadata": {}, - "outputs": [], - "source": [ - "def categorical_cmap(cmap_name: str, categories: list) -> dict[str: tuple[float]]:\n", - " scalar_mappable = matplotlib.cm.ScalarMappable(matplotlib.colors.Normalize(0, 1), cmap_name)\n", - " return {code: scalar_mappable.to_rgba(i / len(categories)) for i, code in enumerate(categories)}\n", - "\n", - "# create some colourmaps and persist between plots\n", - "\n", - "# make a country colormap\n", - "countries = sorted(set(data.index.get_level_values(\"country_iso_a3\").values))\n", - "country_cmap = categorical_cmap(\"tab20c\", countries)\n", - "\n", - "# make a cmap for wind speed thresholds\n", - "thresholds = sorted(set(data.index.get_level_values(\"threshold\").values))\n", - "wind_cmap = categorical_cmap(\"plasma\", thresholds)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "2daa83eb", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# scatter plot modelled vs. observed by threshold\n", - "\n", - "n = len(thresholds)\n", - "ncols = min([n, 4])\n", - "nrows = (n // ncols) + (n % ncols)\n", - "f, axes = plt.subplots(ncols=ncols, nrows=nrows, figsize=(3 + 2.5 * ncols, 2 + 2 * nrows), squeeze=False)\n", - "\n", - "for row in range(nrows):\n", - " for col in range(ncols):\n", - "\n", - " i = col + (row * ncols)\n", - " ax = axes[row, col]\n", - " \n", - " if i < n:\n", - " threshold = thresholds[i]\n", - " df = data.loc[threshold, :, :]\n", - "\n", - " # build a list of RGBA values the same length as the data\n", - " colours = [country_cmap[value] for value in df.index.get_level_values(\"country_iso_a3\").values]\n", - "\n", - " ax.scatter(df.observed, df.modelled, marker=\"x\", c=colours)\n", - " x = np.linspace(0, 10 * max(df.observed), 100)\n", - " ax.plot(x, x, ls=\"--\", c=\"cornflowerblue\")\n", - " ax.grid()\n", - " ax.set_title(f\"$s_{{th}} = {threshold} \\ m s^{{-1}}$\", size=10)\n", - " ax.set_xscale(\"log\")\n", - " ax.set_yscale(\"log\")\n", - " ax.set_xlim(1E5, 1E8)\n", - " ax.set_ylim(1E5, 1E8)\n", - "\n", - " # disable any axes we don't need\n", - " else:\n", - " ax.set_axis_off()\n", - "\n", - "handles = [\n", - " Line2D([0], [0], marker='o', color='w', markerfacecolor=v, label=k, markersize=8)\n", - " for k, v in country_cmap.items() if isinstance(k, str)\n", - "]\n", - "f.legend(handles=handles, ncol=1, bbox_to_anchor=(0.95, 0.92), fontsize=9)\n", - " \n", - "f.supxlabel(\"Observed pop. disconnected, $p_{d,obs}$\")\n", - "f.supylabel(\"Modelled pop. disconnected, $p_{d,mod}$\")\n", - "f.suptitle(\"Population disconnected, $p_{d}(s_{th})$\")\n", - "\n", - "plt.subplots_adjust(bottom=0.11, top=0.88, left=0.08, right=0.9, hspace=0.35, wspace=0.35)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "f1197bd7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# scatter plot modelled vs. observed by threshold (same plot)\n", - "\n", - "f, ax = plt.subplots(figsize=(6, 6))\n", - " \n", - "for threshold in thresholds:\n", - " df = data.loc[threshold, :, :]\n", - " ax.scatter(df.observed, df.modelled, marker=\"x\", label=threshold, color=wind_cmap[threshold])\n", - " \n", - "x = np.linspace(0, 10 * max(data.observed), 100)\n", - "ax.plot(x, x, ls=\"--\", c=\"cornflowerblue\")\n", - "ax.grid()\n", - "ax.set_title(\"Population disconnected, $p_{d}(s_{th})$\")\n", - "ax.set_xlabel(\"Observed pop. disconnected, $p_{d,obs}$\")\n", - "ax.set_ylabel(\"Modelled pop. disconnected, $p_{d,mod}$\")\n", - "ax.set_xscale(\"log\")\n", - "ax.set_yscale(\"log\")\n", - "ax.set_xlim(1E4, 1E8)\n", - "ax.set_ylim(1E4, 1E8)\n", - "ax.legend(title=\"Wind speed\\n threshold,\\n$s_{th}$, $[m s^{{-1}}]$\")" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "5442f06a", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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rcPVoQUGBevvtt6sdOnRQvby81FGjRqm//fabOnbsWHXs2LF2z3/kkUfUTp06qRqNRgXU9evX11mR2pjXeG71XUOqXKutXr1ajY2NVd3c3NSuXbuqzzzzzHlfu8FgUO+66y41NjZW9fPzUz09PdU+ffqoTz75pFpWVmb3vP3796s33HCDGhwcbGvj1ltvVQ0GQ7O91sYcm5aWpt52221q586dVb1er4aGhqojR45Un3rqqRrXqiGvpbb3uLHtNOQ9KSkpUQH15ptvrvH8s3322WcqoG7evFmdMWOG6ufnp/r6+qqTJ09W9+/fbztu8eLF6o033mh7nJWVpXp4eKg7d+60O9/o0aPVK6+80m7bq6++qo4ePVrt0KGD6u7urnbv3l297bbb1CNHjqiqqqqVlZWqm5ubWlpaanvOiRMn1PDwcLvz9O7du8bP/7p162w/x4197apa92eh2vnel4Z+1mv7bDX0Z0tVG/Yd1Jjvmqb+vIrWR5I24RLO92UtRFv23XffqYqiqHv27Kn3uH/961+qt7e3ajKZznu+0NBQ9dixY2pOTo562WWXqXq93i4hVVVV/eKLL1StVqueOnWqwbHm5uaqer3ebmqTr7/+Wr300kttj8vKylS9Xq+Wl5fbPfeWW25RR44cWSPWhrx2IdoDGdMmhBBt3Pr167n55pttt2TrsmPHDgYOHFhrxefZLr/8cq688kpiYmIYM2YMvXv3pl+/fjXGUE2ZMoUhQ4awcOHCBscaHBzMtGnT6Nq1K0OHDgWwjSWrtm/fPnr27Imnp6dt25EjR/j0009rFCY09LUL0R4oqlrLSE8h2pm5c+cyb948cnJymq0CUYjWTFVVAgMDue2221i8eLHDzrt3715b9WFzLhq/fv16UlNT+dvf/tZsbQjR2knSJoQQQgjRBrjM7dGFCxeiKAr333+/s0MRQgghhGg0l0jatm/fzv/+9z+7MRNCCCGEEG1Ju0/aSktLmT59Ou+88w6BgYHODkcIIYQQokna/eS6c+bM4aqrruKSSy7hqaeeqvO4yspKu6VDLBYL+fn5BAcHN+uEnkIIIYRwXaqqUlJSQqdOnc5bzNOuk7ZPPvmExMREtm/fft5jFy5cyLx581ogKiGEEEIIeydPnjzvihbtNmk7efIk9913Hz/99FONhZFr88gjj/DAAw/YHhcVFdG1a1fS0tLw9fVtlhirqqpYv34948ePR6/XN0sbbZFcl9rJdamdXJe6ybWpnVyX2sl1qV1zX5eSkhK6d+/eoFyj3SZtO3fuJDs7m0GDBtm2mc1mNm7cyGuvvUZlZaXdBJPu7u41Jo4ECAoKws/Pr1lirKqqwsvLi+DgYPkBOYtcl9rJdamdXJe6ybWpnVyX2sl1qV1zX5fqczZkKFa7TdouvvhikpOT7bbNnj2b6OhoHn744fPOCC6EEEII0Zq026TN19eXAQMG2G3z9vYmODi4xnYhhBBCiNau3SZtQgghhGgZFosFo9Ho7DCaRVVVFTqdDoPBgNlsbvJ53NzcLnipN5dK2jZs2ODsEIQQQoh2xWg0kpaWhsVicXYozUJVVcLDwzl58uQFTQGm0Wjo3r07bm5uTT6HSyVtQgghhHAcVVXJzMxEq9USERFxwT1JrZHFYqG0tBQfH58mvz6LxUJGRgaZmZl07dq1ycmfJG1CCCGEaBKTyUR5eTmdOnXCy8vL2eE0i+pbvx4eHheUlIaGhpKRkYHJZGpyFWr7S4mFEEII0SKqx3hdyC0/V1F9jS5kXJwkbUIIIYS4ILLc4/k54hpJ0iaEEEII0QZI0iaEEEII0QZI0iaEEEKIFnX69Gn+8Y9/0KNHD9zd3YmIiGDSpEmsW7euReNQFIVVq1a1aJsXQqpHhRBCCNFijh07xkUXXURAQACLFi0iNjaWqqoqfvzxR+bMmcPBgwedHaKdqqoqZ4dgIz1tQgghhGgxd999N4qi8Mcff3D99dcTFRVF//79eeCBB9i6dSsAJ06cYPLkyfj4+ODn58eNN95IVlaW7Ry33nor11xzjd1577//fsaNG2d7PG7cOO69917+/e9/ExQURHh4OHPnzrXt79atGwDXXnstiqLYHs+dO5f4+Hjef/99evTogaenJx9//DGhoaFUVlbatXndddcxc+ZMh12b85GkTQghhBAtIj8/nzVr1jBnzhy8vb1r7A8ICEBVVa655hry8/P59ddfWbt2LUeOHOGmm25qdHsffPAB3t7ebNu2jUWLFjF//nzWrl0LwPbt2wFYsmQJmZmZtscAhw8f5rPPPmPlypUkJiZyzTXXYDabWb16te2Y3Nxcvv32W2bPnt3ouJpKbo8KIYQQokUcPnwYVVWJjo6u85iff/6ZPXv2kJaWRkREBAAffvgh/fv3Z/v27QwZMqTB7cXGxvLkk08C0Lt3b1577TXWrVvHxIkTCQ0NBayJYnh4uN3zjEYjH374IaGhoVgsFoqLi5k6dSpLlizhhhtuAGDFihV06dLFrnevuUlPmxBCCCFahKqqQP1zlh04cICIiAhbwgbQr18/AgICOHDgQKPai42NtXvcsWNHsrOzz/u8yMhIW1JX7Y477uCnn34iPT0dsPbQ3XrrrS06R50kbUIIIYRoEb1790ZRlHqTL1VVa02Ezt6u0WhsCWC12goGzl0uSlGUBi1sX9ut24SEBOLi4li2bBmJiYkkJydz6623nvdcjiRJmxBCCCFaRFBQEJdddhmvv/46ZWVlNfYXFhbSr18/Tpw4wcmTJ23b9+/fT1FREX379gWs63hmZmbaPXfXrl2Njkev1zdqWak77riDJUuW8P7773PJJZfY9Qa2BEnahBBCCNFi3njjDcxmM0OHDmXlypWkpqZy4MABXnnlFUaMGMEll1xCbGws06dPJzExkT/++IOZM2cyduxYBg8eDMCECRPYsWMHy5YtIzU1lSeffJK9e/c2OpZu3bqxbt06Tp8+TUFBwXmPnz59Ounp6bzzzjvcdtttjW7vQknSJoQQQogW0717dxITExk/fjwPPvggAwYMYOLEiaxbt44333zTNuFtYGAgY8aM4ZJLLqFHjx58+umntnNcdtllPP744/z73/9myJAhlJSUNGnqjRdeeIG1a9cSERFBQkLCeY/38/Pjuuuuw8fHp8aUIy1BqkeFEEII0aI6duzIa6+9xmuvvVbr/q5du/L111/Xe4558+Yxb968Ovdv2LChxrZzVz+YNGkSkyZNsts2d+5cu/nczpWZmcn06dNxd3evN77mIEmbEEIIIcR55Ofn8/PPP/PLL7/UmWw2N0nahBBCCCHOY/DgwRQUFPDss8/Sp08fp8QgSZsQQgghxHkcPXoUjca5pQBSiCCEEEII0QZI0iaEEEII0QZI0iaEEEII0QZI0iaEEEII0QZI0iaEEEIIpzJb1PMfJKR6VAghhBAtz2RR0WkUdp8s4nSxgXA/D+Ii/G3bRU3S0yaEEEKIFqWqKr+n5nLN61uYvXQnj3y5j9lLd3LN61v4PTUXVW2enrfbbrsNRVE4cOCAbdvSpUuJj4+vceytt97K/fffb3v84YcfEhMTg5+fH8HBwYwaNYrt27c3S5x1kaRNCCGEEC3GZFHZmJLLg58ncyK/wm7fifwKHvw8mY0puZgcfMu0tLSUzz77jKCgIN57771GPXfz5s3cf//9vPnmmxQVFXH8+HEeffTRFl/KSpI2IYQQQrQYnUbhxZ8PU1dOZlHhpXVHHH6L9JNPPsHb25tnn32WZcuWUVVV1eDn7ty5k4EDBzJq1CgURcHHx4crr7yS2NhYh8Z4PpK0CSGEEKLF7D5ZVKOH7VzH88rZfbLIoe2+9957TJ8+nZtvvpny8nK++eabBj936NCh/PbbbzzyyCOsX7+ekpISh8bWUJK0CSGEEKJFmC0qp4sNDTo2q9jgsKrS/fv3s3XrVmbNmoWPjw/XXntto26RDhs2jO+//57U1FRuuukmgoODuf7668nJyXFIfA0lSZsQQgghWoRWoxDu59GgY8P8PNA66Bbpe++9R1xcHHFxcQDMmjWLH3/8kfT0dPR6fa23SquqqtDr9bbHEyZM4IsvviA7O5vt27dz5MgR7rvvPofE11Ay5YcQQgghWkxchD9dgzzrvUUaGexFXIS/Q9qrqqriww8/pLS0lPDwcMBavWo2m1m6dCljx47l1KlTNZK0I0eOMHLkyNpfQ1wct912G//73/8cEmNDSU+bEEIIIVqMyaLyz0t6UVcnmkaB+y/u6bDq0dWrV1NcXExiYiK7du1i165d7N69m8cff5z333+fIUOGEBYWxmOPPUZZWRlGo5ElS5awb98+Jk+eDMB3333H8uXLbbdD09LSWLFiRZ1JXXORpE0IIYQQLUanURgTFcILN8TQNcjTbl9ksBcv3BDDmKgQh1WPvvfee0ydOpXo6GjCw8Nt/+69914yMjL4/fff+f777zl06BA9evQgPDycJUuWsGbNGrp06QJAQEAAH374If369cPHx4dx48YxZMgQXnjhBYfE2FBye1QIIYQQLUpRFC7qHcLYPqHsPllEVrGBsLNWRFAUx0338f3339e6PSQkhIqKM7doV61aVec5LrroIq644go0Guf2dUnSJoQQQogWV92TFhfhj9niZys6kCWs6ia3R4UQQgjhVI6qEm3vJGkTQgghhGgDJGkTQgghhGgDJGkTQgghhGgDJGkTQgghhGgDJGkTQgghhGgDJGkTQgghhFNZVMesftDeyTxtQgghhGhxFlVFoyhklVRSZjTh7aYjzNfdtl3UJD1tQgghhGhRqqpyqrCClXsy+P5gFr8ezeP7g1ms3JPBqcIKVAf3vI0bNw53d3d8fHzw9fWlf//+fP7557b9eXl53HfffXTv3h1vb2+6dOnCFVdcwXfffWc7Zvbs2bi5ueHr64u/vz9RUVHcddddpKWlOTTW+kjSJoQQQogWY1FVThZW8MvhXIorTXb7iitN/HI4l5OFFQ6/Zfrss89SWlpKcXExixYtYvr06Rw/fpzCwkJGjhzJ8ePH+e677yguLubw4cPce++9rF692u4cd999NyUlJRQVFfHjjz/i5uZGQkICBw4ccGisdZHbo0IIIYRoMRpFYfvJQupKyVRg+6lCugZ6NUv7iqJw1VVXERAQwKFDh9i8eTM6nY4vvvgCnc6aFmm1Wq644gquuOIKLBZLrefp3r07r7zyCikpKcydO5dPP/20WeI9m/S0CSGEEKLFZJVU1uhhO1exwUR2aWWztG+xWPj6668xGAwkJCTw448/ct1119kStsa6/vrr2bBhg2ODrIMkbUIIIYRoERZVpcxYf8JWrcxocugt0kceeYSAgAC8vb2ZMmUKjz32GKGhoeTm5tKpUyfbcampqQQEBODv74+HhwdFRUX1nrdz587k5+c7LM76yO1RIYQQQrQIjaLg7daw1MPbTefQKtKFCxdy//33A3D48GEmTZqEv78/ISEhZGRk2I7r3bs3hYWFHDt2jO7du6OqKko9caSnpxMUFOSwOOsjPW1CCCGEaDFhvu74udefuPl56Ojg495sMfTq1YurrrqKb7/9lokTJ/Lll19iNpubdK6VK1cybtw4xwZYB0nahBBCCNFiLKrKkIgA6uq7UoAhXQKadcLd48eP8/333xMTE8M///lPKisrufHGGzlw4ABmsxmj0cjmzZvPe45//vOfbNmyhblz5zZbrGeTpE0IIYQQLUajKEQEeDKhV0iNHjc/Dx0TeoUQEeDp8Al2H374YXx8fPDx8eGiiy7ikksu4YknniAwMJAtW7bQsWNHLr/8cnx9fenZsyfLli3j22+/JSAgwHaON954A19fX/z8/Lj44ospKysjMTGRvn37OjTWusiYNiGEEEK0KEVR6BLgSddAL7JLz6yI0MHHuiJCfWPImuJ81Z0hISG89tprvPbaazX2VU/5sWTJEj744AOHxtVYkrQJIYQQosVV96RZEzU322NZwqpucnu0hW1KT8RsqTnY0aJa+O3UTidEJIQQQjiXJGoNI0lbC1q2+3PuXb+QuRuet0vcLKqFhb+9wn0bnuHtHR86MUIhhBBCtFaStLUgv63fo7FY+C5jh13itnjLW6w88TuKqhKw7QcnRymEEEKI1kiSthY06Yb/8p+j2bbE7b+/vQLA1ye3oagqDx7O5LobFjo5SiGEEEK0RpK0tSBtUEeuvfcza+Kmqvx0epdt34OHM7lxzkfoOkQ6L0AhhBBCtFqStLUwbVBHJv/jE3yqzqy9pqgq1929XBI2IYQQQtRJkrYWZlEtLNr3OcVuets2VVF4at9ntVaVCiGEEEKAJG0tqrpKtLro4J69BwFqLU4QQgghXIUqv/saRJK2FvTi5jNVog8ezuS6e78A4IFjOWeKEza+5NwghRBCiBagmq3DhIyHtmHYsgrjoW1225vDpk2buOKKKwgMDCQgIIC4uDgWLVqE0WhEURR27dpld/yGDRsICgqyPb711ltRFIVvv/3W7riAgIDzrrrgCJK0taBhe3bgXVXFA9VFB6ERAFx91wf850gWnlUmhu/Z4eQohRBCiOalqiqViT+Rfd9A8h6fSOHLs8l7fCLZ9w2kMvEn1GZYLP7bb7/liiuu4LLLLiM1NZXCwkI+/fRT9u/fT2ZmZoPPExwczKOPPmpb3qolSdLWgoKG382LR830Hv4gJr8w23azdyCRox/hpaNGOo74hxMjFEIIIZqXajZRueMHCp6fhjnzsN0+c+ZhCp6fRuWOHxza46aqKvfeey8PP/ww999/PyEhIQBER0ezdOlSIiMbXgh40003UV5ezvLlyx0WX0NJ0taCevQdgPGKRyh1DyAxMZHKykoAdu/eTYnGE+Plj9Kjf7xzgxRCCCGakaLVUbz8MVDr6KlSLRQvfwxF67jl0VNTU0lLS2Pq1KkXfC69Xs+CBQt44oknbL/HW4okbS3Iw8ODgQMH4uHhgcFgYMcO663QiooK3N3dSUhIwMvLy8lRCiGEEM3HeGhbjR62c5kzD2M89IfD2szJyQGgc+fO9R43evRoAgICbP+uvvrqWo+7+eabCQ4O5s0333RYjA0hSVsLq07ctFotZvOZahlJ2IQQQrR3qsWMOfdUg4415510WFVp9e3Q9PT0eo/77bffKCwstP07t+CgmqIoLFy4kKeffpri4mKHxNgQkrQ5gaIoNbZpNPJWCCGEaN8UjRZtSJcGHasNjkDRaB3SblRUFN26deOTTz5xyPkALr30UuLi4nj++ecdds7zkUyhhVVWVpKUlGTXywaQmJiIwWBwUlRCCCFEy3DrMwxtx171HqPt2Au3PkMd1qaiKLz66qs888wzvPrqq+Tl5QGQkpLC7bffzvHjx5t03meeeYaXXnqpxX5/S9LWgqoTtvLyctzd3RkyZAgA7u7uGAwGSdyEEEK0e6rZhN8tT4FSRwqiaPC75SmHz9d29dVX88MPP/Ddd9/Rs2dPAgICuP7664mOjqZjx45NOufgwYO54oorWqwgod0mbW+++SaxsbH4+fnh5+fHiBEj+OGHH5wa05EjR2wJW0JCAp6engDEx8fbihNSU1OdGqMQQgjRnBStDvfBVxD40Ec1ety0HXsR+NBHuA++wqHVo9VGjRrFmjVrbGPW9uzZw7/+9S/c3NxQVZX4+Hi748eNG0d+fr7t8dKlS3nppZfsjvn0009RVZVx48Y5PN5zOf6KtBJdunThmWeeoVcv6wfigw8+YPLkySQlJdG/f3+nxBQVFYXZbKZnz554eXlRVVUFWHvaBg4cSGpqKtHR0U6JTQghhGgpiqLgPvBSOgy5EuOhPzDnnUQbHIFbn6GoZlOtY79FO07aJk2aZPf46aef5s0332Tr1q1OS9p0Oh0xMTG17vPw8KhznxBCCNHeVPekufUZimoZZCs6aI4etvbCJa6M2Wzm888/p6ysjBEjRtR6TGVlpd096eoS3qqqKluPmKNVn7e5zt9WyXWpnVyX2sl1qZtcm9rJdaldU65LVVUVqqpisVgucFknBdUJy0I1RPWSWtWvs6ksFguqqlJVVYVWe6YqtjHXW1GbY4GvViI5OZkRI0ZgMBjw8fHho48+4sorr6z12Llz5zJv3rwa2z/66COZP00IIYSohU6nIzw8nIiICNzc3JwdTqtmNBo5efIkp0+fxmQ6U2RRXl7OtGnTKCoqws/Pr95ztOukzWg0cuLECQoLC1m5ciXvvvsuv/76K/369atxbG09bREREeTm5p73IjZVVVUVa9euZeLEiej1+mZpo63IyMggJCQENzc3u+ui0+lIT0+nY8eOdn+ZuCL5vNROrkvd5NrUTq5L7ZpyXQwGAydPnqRbt254eHg0c4TOoaoqJSUl+Pr6XtBYO4PBwLFjx4iIiLC7VsXFxYSEhDQoaWvXt0fd3NxshQiDBw9m+/btvPzyy7z99ts1jnV3d8fd3b3Gdr1e3+w/1C3RRmt28uRJjhw5QmZmJgkJCbZrodPpbNsLCwuJj4+XwanI56Uucl3qJtemdnJdateY62I2m1EUBY1G024nia++JVr9OptKo9GgKEqN69uYz2D7vMJ1UFW1xRd3FecXHByMu7s75eXlJCUlYTQaAeukh5mZmSiKQqdOnSRhE0II4dLabU/bo48+yhVXXEFERAQlJSV88sknbNiwgTVr1jg7NHEOLy8vEhISbBMP7969G4CsrCw0Gg39+vUjLCzMyVE6h8ViqfMvu/r2CSGEaH/a7Td+VlYWM2bMoE+fPlx88cVs27aNNWvWMHHiRGeHJmpRnbi5u7tTUVFh2+7KCZvZbGbXrl2kpaXV2Gc0Gtm+fTunT592QmRCCOFYrbVytLVptz1t7733nrNDEI3k6emJp6en3VJeAQEBzgvIyXJycmyzdoN1wmiwJmzJycmUl5dz9OhRQkNDXb5IQwjR9qgWM4pGi5p3FCoKUD0DUYJ72LaLmtptT5toW1RV5eDBg7YEpVpSUpLLjkMMDw+nZ8+eAKSlpdkWNN69e7dtObT4+HhJ2IQQbY6qqpC1D8va+agbF6NuX4K6cTGWtfMhax/NNbHFpk2buOKKKwgMDCQgIIC4uDgWLVpESkoKiqLU+B20dOlSBg4caHvcrVs3PD098fHxwc/Pj8GDB7N+/fpmibU2krQJp6tO2KqLDqqX8nJzc7MVJ7hq4hYZGWlL3KqTtoqKCtv6ta46h2BOTg55eXm17ktPT6ekpKSFIxJCNJRqMcPpZNSt70Bptv3O0mzr9tPJ1uMc6Ntvv+WKK67gsssuIzU1lcLCQj799FP2799PZmZmg8/z8ccfU1paSmFhIXfccQeTJ0+2u0PUnCRpE0537NgxW8LWr18/OnToAEBcXJytqnTPnj3N9pdXaxcZGUlERITdNldO2IqKiti7dy/Jyck1ErdTp05x6NAhl070hWjtFI0Wde8qoK7vdBV17yqH3iJVVZV7772Xhx9+mPvvv5+QkBAAoqOjWbp0KZGRkY0+p0ajYebMmZSUlHDixAmHxVpvmy3SihD16NKlC76+vjWKDjw9PUlISMDb25vevXu77JQfRqOxRnKSlZXlpGicz9fXl5CQECwWC8nJyeTn5wPWCZpTUlIA6Ny5s8zOLkQrpeYdrdnDdq7SbOtxDpKamkpaWhpTp0512DlNJhNLliwhIiKCbt26Oey89Wm3hQii7dDr9QwePLjWpMzLy4uhQ4e6dMKWmJhIeXm5XRJSXVHavXt3Z4XmNBqNhv79+7Nv3z5ycnLYv38/AIcPH0ZRFCIjI+nRo4fLfmaEaM1UiwUqChp2cEUBqmpBUS68fyknJwew/kF3oaZPn45er6eiogJFUXjvvfda7I9E6WkTrUJ9v2Bd9Zfv2Qmbu7s7cXFxwJlELS0trdbpQFxBdeIWGhpqt4CzJGxCtG6KRgOegQ072DPQIQkbYLsdmp6eXuv+6lUJzl28vaqqqsaKBStWrKCwsBCDwcCWLVt46KGHWmwOWEnahGiliouL7YoOPD09AYiIiLAVJ+Tk5GA2O3awbluh0Wjw9/e32xYQECAJmxCtnBLcA3w61H+QTwfrcQ4SFRVFt27d+OSTT2rd37FjR9zc3Gr8IXzkyJE6x7spikJCQgIXXXQR3333ncNirY8kbUK0UiEhIQwYMKDWooPIyEiio6NdesqPU6dOcfjwYbtttRUnCCFaF9ViRhlwDVDXH1gKyoBrHFo9qigKr776Ks888wyvvvqq7XsiJSWF22+/nZMnTzJ16lQee+wxMjIysFgsbN68mffee49p06bVed7k5GR+++03YmJiHBZrfSRpE6IVCw0NrbNKtFOnTi472P7UqVO2ooPqytqzixMkcROi9VI0WgiPQRn+15o9bj4drNvDYxw+we7VV1/NDz/8wHfffUfPnj0JCAjg+uuvJzo6mo4dO/LKK68QHR3NiBEjCAgI4M477+SZZ57hmmuusTvP1KlT8fHxwcfHh7/85S/8/e9/569//atDY62LFCIIIdqUwsJCW8JWPR3KgQMHiI6OJiUlhZycHJKTkxkxYgTu7u5OjlYIURtFUVDD+qPpGGtbEYGzV0RopmEOo0aNqnP8mZubG6+88gqvvPKK3fazx80eO3asWeJqKEnahBBtir+/PxEREWg0Gnr06IHJZALsq0qDgoIkYROilavuSVOCe9hVicoSVnWTpE0I0aYoikKvXr1s/z+bRqNhwIABUowgRBvjqCrR9k6SNiFEmyNTxAghXJGktkII0U6oqmo3/uZsFovFZZeCE6K9kKRNCCHaAVVVOXLkCLt3764xd5/FYmH//v0cPHhQEjch2jBJ2oQQoh0wGAykp6dTUFDAnj177BK3Q4cOkZ2dzenTpyktLXVilEKICyFJmxBCtAOenp7ExcWh1WptiVt1ZW1OTg6KohATE4Ovr6+TIxVCNJUkbUII0U4EBATYJW6bN28GsCVs1esvCtHamOsYiynsSdImhBDtSEBAALGxsXbboqOjJWETrY7pz2Wqducc4ucTW9idc8huu6hJkjYhhGhHLBYL6enpdtsyMzNrFCcI4UyqqvJ7eiLXfH0vs398jEc2vcTsHx/jmq/v5ff0RIcXzIwbNw53d3d8fX3x9/dnwIABPPjgg+Tk5NiOqaqqYt68efTs2RNPT08iIiL45z//aTcOdMOGDSiKwqhRo+zOX1lZSXBwMIqiUFhY6NDYzyZJmxBCtBPVVaLZ2dkoikKXLl0A69Jf5xYnCOEsJouZjad28ODG5zlRkmm370RJJg9ufJ6Np3Y4vMft2WefpaSkhMLCQj777DPS09MZNGgQWVlZAEybNo2vvvqKzz77jNLSUtatW8fu3bu5/PLLqaqqsp3H19eXY8eO2ZbTA/j666/p0KFDjTYdTZI2IYRoB85N2GJiYujRoweAXXGCJG7C2XQaLS8mfohFrWNOQdXCS0nL0TXTclaKotCvXz+WL1+Ov78/ixcvZsOGDaxevZqvvvqKQYMGodVqiYqK4quvviIlJYXPP//c9nyNRsOMGTNYunSpbduSJUuYPXt2s8R7NknahBCiHTAajRQWFtZadDBgwAC0Wi0lJSUYDAYnRimEdQzbuT1s5zpenGEb49ZcdDodkydPZsOGDfz4448MGzaM7t272x3j7+/P5Zdfzi+//GK3ffbs2Sxbtgyz2Ux6ejo7duxg8uTJzRovyDJWQgjRLnh4eDBw4EAqKioIDg622+fv709cXBwajQZvb28nRSiEtUr0dFlug47NKsvDHGxBq2m+/qXOnTuTn59Pbm4unTp1qvWYTp06sX37drttUVFRREZG8tNPP5GUlMRNN92Eu7t7s8VZTZI2IYRoJ7y8vPDy8qp1X0BAQMsGI0QttBoN4d4Nq2QO8w5u1oQNID09naCgIEJCQjh0qPaevYyMjBp/CIG1t+39999n9+7dfPzxx80aZzW5PSqEEEKIFhMX2oeuvh3rPSbSrxNxoX2aNQ6TycTXX3/NuHHjmDhxItu2bSMtLc3umOLiYtasWcP48eNrPP+mm25izZo1eHh4MGjQoGaNtZokbUIIIYRoMSaLmX8OnIFGqT0F0Sga7k+4pVnnazt48CCzZs2iqKiIBx54gAkTJnDllVdy7bXXkpiYiNlsJiUlhWuvvZaePXtyww031DiHr68v69evtytSaG6StAkhhBCixeg0WsZ0GcwLYx6q0eMW6deJF8Y8xJgugx1ePfrwww/b5mmbMmUK4eHh7Nixg7CwMAA+/fRTJk+ezPXXX4+3tzfjx49nwIAB/Pjjj7i5udV6zsGDB9OnT/P2CJ5NxrSJVsF4eAf6brEoupo/GMZD29BHDUVRFCdEJoQQwtEUReGizgMZGzGE3TmHyCrLI8w7mLjQPpgsZod/32/YsOG8x7i5uTFv3jzmzZtnt91isVBcXAxYJ+mta/Lcbt26OXxS4HNJT5twOkPST+Q9cTkFL81GNRnt9pWtfZ+8xydS8sEjzf7DIIQQouVU96TFhfbh4q7DbWPYmmt+tvZAkjbhfIoCikLlH9/YJW7l65dT/M791mOauYJICCGE8zR3lWh7IVdJOJ1H/EQC//UR6N2p/OMbCt+8G4CSpQ8D4H31PfjOeFpujwohhHBpzZa0abXSvSka7uzEzbjjB9t2SdiEEEIIq2ZL2mT8kWgsj/iJuCdcarfNd9pcSdiEEEIIHJC0ZWdnU1FRUWO7/KIVjVW29n0q//jGblttxQlCCCGEK2py0vbQQw+RnZ3NXXfdxV//+ldHxiRcUNna921FB16X32nd+OcYN0nchBBCiAtI2oqLi1m5ciVPPPEE4eHhjoxJuJjyXz60JWzeV9+Dz82PAxBw33tnihNeuk1uuQshRDtlUS3ODqFNaHLSNmHCBMrKyoiPjycqKsqRMQkXo+8Rj+ITWKPowD1m/J/FCR64DRgjt9yFEKIdqU7UsiuyOF6SRnZFlt12UVOTk7a8vDySkpKYMWMGVVVVjoxJuBh9txhCn9tca5WoR/xEOryShPflf3NSdEIIIRxNVVXSy07yVdpnrDn5Db+dXs+ak9/wVdpnpJeddPidlXHjxqEoCj///LPd9ueeew5FUbj//vsB63h8Ly8vfHx8bP+mTJkCwLp16/D39+f48eO25584cYKAgADWrl3r0Hjr0uSkLTU1lRUrVvDhhx+SlpbmyJiEC9IGd66zJ00b3LmFoxFCCNFcLKqFU2Un2JDxMyVVxXb7SqqK2ZDxM6fKTji8x61Pnz4sWbLEbtvSpUuJjo6227Z582ZKS0tt/7788ksALr74YmbMmMHs2bNRVRVVVbntttuYOnUqEydOdGisdWnS2qPr1q0jLy+PTz/9FEVRyMnJcXRcQgghhGiHNIqGHTnbUKm9N01FZWfOH0T4RDq03ZtvvplXXnmFoqIi/P392bZtG6qqMmzYsAaf49lnnyUuLo7XXnsNgLS0NFatWuXQOOvTpJ62U6dOcckll1BZWYnBYGDChAmOjksIAVTu/x1zYVat+wyJa7AYylo4IiGEuDDZFVk1etjOVVxVZBvj5igBAQFcfvnlfPzxxwC8//77zJ49u1Hn8Pb2ZunSpTz66KM8+uijLF26FB8fH4fGWZ8mJW2zZs2iZ8+erFu3jl9++YUePXo4Oi4hXF7l3o3kP30tefOuqpG4lW9YQcGzN1HwzA2oxprzJAohRGtkUS2UVZU26NhyU5nDb5HOnj2bJUuWUFFRwcqVK5kxY0aNY0aPHk1AQIDt3/z58+32x8TE4OnpSadOnbjoooscGt/5NHlM25IlS1iyZAnvvvsuy5Ytc2RMQghAG9IFjV8w5vQUa+JWlA1AxabPKHrzblBVdF2iQe/h5EiFEKJhNIoGb33Deqa8dN5oFMcu3HTxxRdz+vRpFixYwIgRI2qdsuy3336jsLDQ9u+JJ56w23/vvfcyfPhwNBoNixcvdmh859OkMW0AVVVV5ObmoqqqVI8K0Qx04T0IfvI7a8KWnkL+MzfA6IcpfvcBtKqK16V34Hf7CzIVihCiTengGYav3q/eW6R+en86eIY5vG2NRsPMmTN5+umn+eKLLxr9/NWrV/P999+zd+9e0tLSuOSSS5g0aRJ9+vRxeKy1aXIK+/jjj7No0SKee+45HnnkEUfGJIT4U3XipgnujCXjsHWjJGxCiDbMoloYHDoMhdq/vxQUBoUObbb52v75z3/y008/MWnSpEY9Ly8vj7/97W+8/vrrhIWFMXz4cObMmcOtt96K2WxulljP1eSkrXfv3jz//PM8//zzLZZhCuGKdOE98Bo33W6bz3X/loRNCNEmaRQNXby7Mq7TJfjq/ez2+en9GdfpErp4d3X4rdFqQUFBXHLJJej1+lr3jxw50m6etuHDhwMwZ84cxowZw4033mg7dv78+RQVFfHCCy80S6znavLtUSFEyyjfsILSL58DrbttW978qwl+8ju0AY6/fSCEEM1NURQ6e0cQ4RNJdkUW5aYyvHTedPAMw6JaHP5H6YYNG+rct3TpUtv/a5vU12KxUFxczCeffIJGY59Iuru7s3//fkeFeV4OSWPXrl3LiRMnHHEqIcRZyjessBUdeF48CwAlqNOZ4oQ6pgMRQojWrronrYNnGF19utnGsDVXD1t74JArEx4ezi+//OKIUwkh/mT44xtbwuZ16R34zngagKD/fI4muLO1OGHe1TLlhxCizZNErWGadHt0xowZGAwGDAYDGo0GrVZrW+ZBCOEYbn1HoouMwS1qKH63v4DJZAJAF9bNVlXqOWEmipunkyMVQgjREpqUtH344Yc8/vjjPPHEE+h0Op5//nlHxyWEy9P4BhM87wcUD58a4zt04T0IfWEbGi+/Op4thBCivWlyIUJKSgp5eXm4ubnJeDYhmonG07fufZKwCSGES2ly0rZgwQJbD9ucOXMcFpAQQgghhKipyUlbVFRUk2+LZmdn4+vri6enjMURQgghhGiIBidtqqqycuVKNm/ejKIojBw5kilTpjRqLpWHHnqIf//739x11114eXmxfPnyJgUthBBCCOFqGlxje+edd7J8+XKGDBnC4MGDWbFiBXfeeWejGisuLmblypU88cQTtS7SKoQQDVGxeSWGP76pdV/pt69hTN3ewhEJIS6ExdI8S1a1Nw1O2rZs2cKqVauYOnUqU6dOZeXKlWzZsqVRjU2YMIHS0lLi4+OJiopqdLBCCGE8uJXCl2+n4MVZNRK30lWLKVn2KPlPXYs5P9NJEQohGsJstiZqx47msycpk2NH8+22O9K4ceNwd3fHx8eHwMBAxo4dy/bt29mwYQMBAQE1jp87dy7XXHON7XFsbCyrVq1yeFyN1eDbo7GxsezatYv4+HgAdu/ezbBhwxrV2M0332z7/9/+9rdGPVcIIQD0UUPwuOg6DJs+p+DFWfjetxSAsu9eo+KjuQB4/+VetEEdnRekEKJeqqpycF82363aR252mW17SAdvrrqmP/1iwhy+lNWzzz7L/fffj8Fg4JFHHuGaa65hxYoVDm2juTW4p23v3r0MHjyY6OhooqOjGTRoEDt37mTIkCEMHTq0Qed44403mD59OjNmzOD1119vctBCCNelaLQE3PM/PEbdAGYTha/fBUDpZwsB8LnpMXyv+7czQxRC1MNstrA/OYtl7/xhl7AB5GaXseydP9ifnNUsPW4AHh4e3H777WRkZJCXl9csbTSXBve0rV69+oIbS0lJsWW1Dz300AWfTwjhmqoTt0KgbOuZW6SSsAnR+mm1Gr5btY9a1mYHQFXh+1X76B/bPGPfy8vLeffdd4mMjCQ4OLhZ2mguDU7aIiMjL6ihdevWkZeXx6effoqiKOTk5FzQ+doiVVXhxDboMghFq7ffZzHDiT8gcrjDu4SFaI8UjRZdl2jgTNKmj+jrvICEEA1y7Gh+jR62c+Vkl3H8aD6RPYIc1u4jjzzC3Llz8fDwID4+ntWrV5Ofn09RUVGNcW0Gg4HLL7/cYW07Sout0Hrq1CkuueQSKisrMRgMTJgwoaWabjXUA9+iJi5H3fYuqrnqzHaLGXXHUtSkFajJK50YoRBtR+mqxZR+ssBuW23FCUKI1sNisVBYUNGgYwsLKrBY6uiOa4KFCxdSWFjI6dOnWbNmDbGxsQD4+/tTWFho9+8///mPw9p1pEYnbadPn25SQ7NmzaJnz56sW7eOX375hR49ejTpPG2ZEhIFGj1k7bNL3NSkjyA9CTQ6lNA+To5SiNavdNViSqqLDv68Heo+4lowmyRxE6IV02g0BAQ2bGL9gEBPNBq583S2Ridtl156aZMbW7JkCUuWLOHdd99l2bJlTT5PW6V06IMy4q4zidv2pdYdmbutCdvQ21E6xjg1RiFau8r9v9sSNp+bHsPnL/cB4P+3l23FCQUv3yZTfgibiooKTp48Weu+4uLiJndGiKbp1iOIkA7e9R4T2sHbobdGHaGqqgqDwWD7ZzQaWzyGRi9jpdY1crABqqqqyM3NRVVVqqqqzv+Edkjp0AdG3IW6+XXIPQSaztbtkrAJ0SBufUfiM+VfoHfH97p/275LqosTijQ63OMmyJQfAgCTyURiYiKVlZWYTCa6d+9u21dSUsLevXsxmUzo9fo2Nyi9rTKbLVx1TX+WvfNHrcUIigJXXtMfs9mCVttio7jO6+xpywDGjh3Lhg0bWjSGRidtFzJI/vHHH2fRokWAdUCgywrpBToPqKo8s61DtPPiEaINURQF35sfr32fRkvAPW+3cESiNdPpdHTp0oUjR46QlpYGQJcuXQBITk7GbDbj7++Pv7+/M8N0KVqthn4xYcz869Aa87SFdvDmymaYp62u5GrcuHEUFhbW2D537ly7x3v27MHPzw+NxrlJZJMXjG+K3r17N3mR+faiuuiAqnJAe2b7tndh2B01qkqFEEJcmOrZD6oTt6KiIsDaCxcQEEBcXBw6XYv+OnR5iqIQ3b8D/WPDOX40n8KCCgICPYnsEYTZbJFZFOrgtJTx559/5sSJE85q3ilsCVt10cGQ26w7ailOEEII4TiRkZH07NkTwDahqp+fnyRsTlR96zOyRxAxCZ1sY9ha0y3R1qbRV8bNzc0hDYeFhfHLL7845Fxthbrn8zMJ29DbUcL6AViTt+rELekjJ0cphBDtU2BgoN1jPz8/SdhaCakSbZhGJ207duxwSMMxMTHceuutDjlXW6H0GAOeATWKDpTQ3taqUg9/lF6uN3+dEEI0t+LiYnbt2mW37dSpU7ZxbkK0BS32J8aMGTNsZbIajQatVsuXX37ZUs23CopfJ5j4ZK3j1pQOfeDSuTKmTQghHKw6YTOZTPj7+9OvXz9++uknAFvSdnZVqRCtVYvdOP7www+Jjo7myy+/ZNWqVYwYMaKlmm5V6kvKJGETQgjHMplM7N6925awnT2GrTpRS0tLc8mlFUXb06Setqb2mqWkpJCXl4ebm1uzFyEsXLiQL7/8koMHD+Lp6cnIkSN59tln6dNHVhwQQghXodPpiIqKIj09ndjYWHQ6nW1uv4iICLRaLSUlJTJHm2gTmtTT1tReswULFvD888/z3//+lzlz5jSl6Qb79ddfmTNnDlu3bmXt2rWYTCYuvfRSysrqX6RWCCFE+xIWFkZCQkKtRQeRkZH079/f6fNvCdEQTR7TlpKSQm5ubr29ZqqqsnLlSjZv3oyiKIwcOZLnnnuuReZfWbNmjd3jJUuW0KFDB3bu3MmYMWOavX0hhBCtR32/d2ROMOdTVVXehwZoctK2YMECFi9ejKqq3HPPPTX2q6rKnXfeSXZ2NjfddBMAK1as4Mcff+R///tf0yNuourJFIOCal/LrLKyksrKMysUFBcXA9alt5prya3q87rqkl51ketSO7kutZPrUje5NrWT61K7plyXqqoqVFXFYrFgsVga2aKCRqNQWFhBZaUJd3cdAQGeWCwq0PQlMx2tevnO6tfZVBaLxbaMp1Z7ZnL9xlxvRW3iYqKbNm3inXfeAeCOO+5g9OjRdvs1Gg0DBgxgz549tm2qqhIbG0tycnJTmmwyVVWZPHkyBQUF/Pbbb7UeM3fuXObNm1dj+0cffYSXl1dzhyiEEEK0OTqdjvDwcCIiIho8j6tOp8Pb25vc3HJSD+dRUXEmafH01NO7VzAhIV6UlZVhMpkcEufVV1/N9u3b0ev16HQ6+vfvz4IFCygvL2fSpEl4e3ujKAoBAQFcf/31PP7447Zb5s888wzJycmsWLHigmIwGo2cPHmS06dP272u8vJypk2bRlFREX5+fvWeo8k9bUuWLGHJkiWoqspdd91VI2kDiI2NZdeuXcTHxwOwe/duhg0b1tQmm+yee+5hz549bNq0qc5jHnnkER544AHb4+LiYiIiIrj00kvPexGbqqqqirVr1zJx4kT0eqkcrSbXpXZyXWon16Vucm1qJ9eldk25LgaDgZMnT+Lj44OHh0cDW1LIzS1nT/LpGnsqKqrYk3ya2JhwgoO9cVSPm06n45lnnuG+++7DYDDw6KOPMmPGDD788EP8/f3Jz88H4MCBA1xyySX079+f226zrlpUnYz6+vpe0C1cg8GAp6cnY8aMsbtW1Xf2GvQ6mtp4VVUVubm5tq6+2iQnJzNo0CB69+4NQGpqKrGxsQwZMgRFUfjjjz+a2nyD/eMf/2D16tVs3LjRtkhwbdzd3XF3d6+xXa/XN/sPdUu00RbJdamdXJfayXWpm1yb2sl1qV1jrovZbEZRFDQaTaOKOVIP59W7//CRPEJDvQHHjXOrjtPLy4s77riDl19+mYKCAgBb7P3792fUqFEkJSXZtlUnatXPbyqNRoOiKDWub2M+g01O2h5//HEWLVoEWHupavPNN9/QxLuvF0xVVf7xj3/w1VdfsWHDBpk4UQghhGgFCosq7G6J1qa8vIqiIgP+/g3tvWu48vJy3n33XSIjI2tM9ZKcnMzGjRt59NFHHd6uIzQ5aevduzfPP/98nYPyFEWha9euTQ7sQs2ZM4ePPvqIr7/+Gl9fX06ftnbD+vv74+np6bS4hBBCCFelqiqVhoaNUzMYTPj5Oa6q9JFHHmHu3Ll4eHgQHx/P6tWryc/Pp6ioiICAACorKzEYDMyePZu7777bIW06WpOTtr///e+Ul5fbuvvef/99R8Z1wd58800Axo0bZ7d9yZIlLrfmqRBCCNEaKIqCu0fDUg8PD51DpwFZuHAh999/v922DRs24O/vT2FhIWazmffff59FixZRXl6Ov7+/w9p2lCYnbUFBQbbEqDVy1m1ZIYQQQtQtwN8TT099vbdIvbz0zXJrtD5arZa//vWvfPvtt8ydO5cXX3yxRdtviCaPqPPz8+Oaa65h5syZzJw505ExtWv1JZOSaAohhGjvLKpK7171LxvWq2ew034nPv7447z11lukp6c7pf36NDlpS0lJ4YsvvmDZsmUsW7bMkTG1W5WVlezcubPW8t7S0lJ27NhBRUWFEyITQgghWoZGUQgJ8SI2JhxPT/vKSS8vPbEx4YSEeDlthYTBgwczZswYnn76aae0X58m3x5VVZVvv/3WNofZhAkTHBZUe3XkyBGKi4ttc9dVF0SUlZWRnJxMVVUVhw8fJiYmxsmRCiGEEM1H+TNxCw31pqjIgMFgwsNDh7+/R7MsabVhw4Zat48bN47CwsIa23/88Ufb/5988slGzaXWnJqctI0dO5aioiLb8lDi/KKioqioqKCoqIhdu3YxYMAAAPbs2YPJZMLX15fo6GgnRymEEEI0v+rEzN/fw65KVNYgrVuTk7ZZs2Y5Mg6XoNPpiIuLY/fu3RQVFZGUlARYJyr28/MjPj5eJnoUQgjhciRRa5imT+17lp9//pkTJ0444lTtXnXiptPZ58uSsAkhhBCiPg5J2sLCwvjll18ccSqXYDAYakxKLAUIQgghhKiPQ5K2mJgYmbC2gUpLS0lKSsJisditzLBr165WM9BRCCGEEK1Pk8a0zZgxA4PBgMFgQKPRoNVq+fLLLx0dW7tTnbBVVVXh6+tL//79Wbt2LX5+fpSUlNiqSqsrcoUQQgghqjWpp+3DDz8kOjqaL7/8klWrVjFixAhHx9Uupaen2xK2s8ewDRgwAH9/f0wmEydPnnRylEIIIYRojZpcPZqSkkJeXh5ubm5ShNBAvXv3Rq/XExERgV6vp6rKuoRHdXHC8ePH6d69u5OjFEIIIVqWxWJBo3HIiK12rclJ24IFC3j++ecBmDNnjsMCas80Gg09evSodZ9Op6Nnz54tHJEQQgjhHGazGa1Wy+HDh8nPzycoKIhevXrZtouaGpy0qarKypUr2bx5M4qiMHLkSJ577jmZW0UIIVoJ1WxCrShB4xNYY5/FUIqi0aG4tewi3ELURlVVkpOT+fzzz8nKyrJtDwsL44YbbiAuLs5h+YWPj4/t/xUVFeh0OtvwpNGjR6PVaomJiWHhwoW247p06ULv3r1Zv369bdv1119Ply5deOWVV7j11lv54IMP+Oabb7j66qttxwQEBLBq1SrGjRvnkNjP1eC+yDvvvJPly5czZMgQBg8ezIoVK7jzzjubJSghhBCNo5pNFL76V/LmXYWlOM9un6WyjPz/XkfBc1NRjQYnRSiEldlsZvfu3bz++ut2CRtAVlYWr7/+Ort378ZsNjukvdLSUtu/0aNH8+yzz9oe//DDD4wfP94uOUtNTUWv17N7924MBuvPi6qq/Pbbb4wfP952XHBwMI8++miNKbyaU4OTti1btrBq1SqmTp3K1KlTWblyJVu2bGnO2IQQQjSQpSAT4/5NmI7vJW/BJLvEreD5W6g6uAVj6g5MWWlOjFII0Gq1fP7556iqWut+VVX5/PPPW+wW6fjx49m5cyclJSWAdZ3Siy++mISEBFues3//fvLz8xk7dqzteTfddBPl5eUsX768ReKERiRtsbGx7Nq1y/Z49+7dDBs2rDliEkII0UjakAiCn/wOjX8HW+JmyrFWo5tS/kDx8ifosVXoI/o6OVLh6g4fPlyjh+1cWVlZHDlypEXiiY+Px9fXl02bNgHWpG3cuHGMHTvWttD877//TlxcHEFBQbbn6fV6FixYwBNPPEFlZWWLxNrgpG3v3r0MHjyY6OhooqOjGTRoEDt37mTIkCEMHTq0OWMUQgjRALrOUQTP/f5M4vbQcOuOPxM2t16DnBugcHkWi4X8/PwGHZufn98itx41Gg1jxoyx3SL99ddfGTt2LGPHjrVt27RpU63j1G6++WaCg4N58803mz1OaEQhwurVqxt14rq6PYUQQjQfXecoAv/zGXmPjLNtC/j7a5KwiVZBo9HY9VbVJygoqMWmARk/fjzLly8nNTUVd3d3IiIiCA0NZffu3ZSVlbF582buuOOOGs9TFIWFCxcyffp0brvttmaPs8FJW2RkZKNO3JID84QQQlhZDKUUf/CI3baSzxfi1XswGr9gJ0UlxBm9evUiLCys3lukYWFhLToN1vjx43nwwQf5+uuvbePWPDw8iI+P591336WwsJAxY8bU+txLL72UuLg42zRozUlmshNCiHbCYigl/7/XUXVwC4qXP353vgyA+cT+GsUJQjiL2WzmhhtuqHNKD0VRuOGGGxxWPdoQMTExBAYG8sILL9jdBh07diyLFi067xKTzzzzDC+99JKt2rS5SNImhBDtwLkJW9Bjq/AceT0Ain9orVWlQjiDVqslLi6OOXPmEBYWZrcvLCyMOXPmEBcX16IT7CqKwtixYzl9+rRdhWj1tlGjRtX7/MGDB3PFFVc0e0FCk1dEEEII0XqolRWopQW2hM2t1yDbUnlBj3xB8YJJqOXFWAylcptUOJ2iKMTExBAfH8+RI0dsKyL07NkTs9ncbBP3V1eD1uaLL76ose3iiy/GbDZTXFxst33p0qU1jv3000/59NNPLzTEeknSJoQQ7YDWP5SgJ77Fkp+Bvke83T5dx14Ez/0e9O7oOjRufLIQzaW6J61nz550797dVnQgS1jVTZI2IYRoJ7QBHdAGdKh1n65zVAtHI0TDyWLxDdMiV0mj0TBhwgR27tzZEs0JIYQQQrQ7LZK0vf/++4wdO5Z77723JZoTQgghhGh3WuT26K233grAk08+2RLNCSGEEEK0O3ITuYXVt1KErCIhhBCOp1osmHNP1r7PaMBcWP86mEK0FhfU0/bAAw80+NjFixdfSFPtQkVFBbt376ZPnz4EBgba7SsqKuLAgQPExMTg7e3tpAiFEKJ9US0Wit65n8o/viHoyW/Rd+1/Zp+xkoKXZmDKPkbwk9+jDeroxEiFOL8LStqSkpIadFxzzbfS1hw7dozy8nJ2795NXFwcPj4+ABQXF7N3717MZjNpaWkMGDDAyZEKIUT7oFaWYTq2G0tJHvnzriboyW+ho7WStvCV2zDvXofi7oU5+7gkbU6kqqrkCg1wQUnb+vXrHRWHS4iKiqK0rIri4lx2795N//7Wv/iSk5MxWyz4+gTTt29fJ0cphBDth8bTl6D/W0X+09dQdSSJ/HlX4/PvzwAwJm9A5+5F4CNf4BY93LmBuqDqRK2oqAiDwYCHhwf+/v6SwNXD4WPa9u/fz5o1a1i9erXt3zfffOPoZtqkzMwSiou9cHcLw2yxsGfPHgBMZjPubh0oKfXh1KkiJ0cphBDti8YnkKD/W4W+ZwKWkjwK5l1l3fFnwuber/4lioTjqapKbm4uW7ZsYefOnezbt4+dO3eyZcsWcnNzHT7Gu1u3bqxatcpu27Fjx1AUhcLCQjIzM5k2bRrh4eH4+vrSo0cP/vnPf9Y4z8aNG1EUhYcfftih8TWUw6pHjx49yrXXXktycjKKotgueHW23JILv7ZWp0+fBvRUGj1QlCAsavUagH5UGj3/PCaLyMggp8UohBDtkcYnkMCHPyP7b71t23xvfFQSNieoTtiSk5Nr7KuoqCA5OZmYmBhCQkJarMdtxowZdO3alYMHD+Ln50daWhqbNm2qcdx7771HUFAQH3zwAU8//TQ6XcuuUeCwnrb77ruP7t27k5WVhZeXF/v27WPjxo0MHjy43rW+XElMTHfc9CUAqKovEPDnHn8A9LoSYmO7OSM0IYRo11SjgaLX77LbVrpqMVUn9jkpItelKAqHDx+u95gjR4606C3SrVu3Mnv2bAICAtBoNPTs2ZNZs2bZHVNcXMwXX3zBa6+9RmlpKd99912LxVfNYUnbli1bmD9/PqGhoWg0GjQaDaNGjWLhwoUyqe6f3N3d6du3C1Ddw+Z71t58oqLC8fT0dEJkQgjRfqlGAwXPTaXyz6KDgPvet24vySd/3tWSuLWwoqIiKioq6j2mvLycoqKWGy40atQo7r//fpYtW0ZKSkqtx3z88cd4e3tzww03cN111/Hee++1WHzVHJa0mc1mWzVkSEgIGRkZAERGRnLo0CFHNdOmFRUVsW/fPqAUOPt2sQqUcPDgQQoKCpwTnBBCtEPnJmyBj3yB+8DLAND1iLNVlUri1jJUVcVgMDToWIPB0GLzl3722WdMmjSJl156if79+xMZGclHH31kd8ySJUuYPn06Op2OmTNn8v3335OZmdki8VVzWNI2YMAA28D6YcOGsWjRIn7//Xfmz59Pjx49HNVMm5adnW0rOgDtWXsUW3FCVpZM8iiEEA6j0YDO7UzCdtYYtsCHPkLfMwE0WhSt3olBug5FUfDw8GjQsR4eHg67RarX66mqqrLbVv1Yr9fj5+fH3LlzSUxMpKCggHvvvZeZM2dy4MABAPbt28f27dttt0zHjx9Pp06d+OCDDxwSX0M5LGl77LHHsFgsADz11FMcP36c0aNH8/333/PKK684qpk2rWfPngT4R9qKDhSl0Lav0uiBn28kUVFRTorOuSyWuv+aqm+fEELUR9G5EfjghwQv+KlG0YHGO4Cg/1tF8Lwf0HV2ze9eZ/D39z/vUCAvLy/8/f0d1mZkZCRpaWl2244cOUJISEiNCe19fHx48MEH8ff3Z//+/QAsX74cgMsvv5zw8HA6depEdnY277//vsNibAiHJW2XXXYZU6ZMAaBHjx7s37+f3NxcsrOzmTBhgqOaadMOH8ml8M9b9HpdCUOHWOdkc9OXAlBcAodScpwVntNUVpr4Y/tJMjKKa+wrLTOyZesJ8vLLnRCZEKI9UHRu6LvF1rpP4xOIrlPvWveJ5qGqKr169ar3mJ49ezr01ugtt9zC66+/TlJSEqqqcvz4cebOncv06dMB+Ne//sWuXbswGo0YjUbeffddysrKGDRoEEajkc8++4yFCxeya9cu279t27Zx9OhRNm7c6LA4z6dZa1WDgmTqirOVluYDOvS6UoYM6WMrFR40qA+JiakYq3woLc0DwpwaZ0vLzCyhrKyKAwetCWtoqPUvsLJyI8nJORiNZtKO5hMU6CkTLgohhAOZi3PR+oXU2K6qKmpJPhq/YIe3qSgKISEhxMTEcPjwYbuiBC8vL3r27Onw6T5mzZpFSUkJ06dP59SpU4SEhHD99dczd+5cACorK7n55ptJT09Hr9fTt29fvv76a7p168Ynn3xCVVUVf//73+16/8LDw7nmmmt49913GTNmjMNirY/Dkrb58+fXu/+JJ55wVFNtVmxML/YfSKF3rz54enra7qe7ubkxdGhfDh06TN++rtdFHxkZQGVpCaeyrYmb2Wxdl3XP7tNUmcDHS0NcXEdJ2IQQwoHK1vyPkk8WEPR/X+LWe4htu6qqlHz4GBVbviJ47nfowro7vO3qxC00NLRFVkRQFIV//OMf/OMf/6h1f33DuG688UYuv/xyfH19a+z74osvHBZjQzgsafvqq6/sHldVVZGWloZOp6Nnz56StAE6nY7YmH617nN3dyc2tn+t+9q9/DR6pb2OGjiFdGM4h1JyATBWmfH1gPist9EdnQB9LndyoEII0T6oFjOGratQy4vIf+pagh77CqVbPAClnyyg8ttXATAe2NwsSRucmXzf398fPz8/22P5A71uDkvaals8vri4mFtvvZVrr73WUc2I9qiiAMVkpHfOx5QH30Z+lY9tV3zuu+gt5ailOSDr0QkhhEMoGi2B//mMgoU3YDzwO/lPXYvvIysBKF/zNlrA744X8Ro3vWXike/2BnH42qNn8/PzY/78+Tz++OPN2Yxo45Qug1AGz6JcE0yp0f7viFxtd+g6DGXgdPmhFkIIB9J4+BD4yOe49b0ItaKYgvmTbPv87ngR70tvd2J0ojbNmrQBFBYWtuisxqJtKguKZVfALVRpvPE2n6mgPeg1kcyOf0FRmv2jKoQQLqc6cTubx+ibJGFrpRx2e/TcQXyqqpKZmcmHH37I5ZfLWCRRt9IyI0lJGRjNGnyUEgaUr+ZnZSQdK/dw2iOBgwdzUVDo1MnP2aEKIUS7oqoqpZ8ttNtm2PEDxtTtdsUJDTmPqJ8jrpHDkrYXX3zR7rFGoyE0NJRZs2bxyCOPOKoZ0Q4VFlZgNJrxcTcTn/sRqJWgQM/K39D6dSTdGE52ThkdO/rKLVIhhHCQ6irRsj+LDnxufsK6qmJFsa044XyJm1ZrXd3HaDTK2tnnYTQagTPXrCkclrSdO9OwEA3VpbM/2qITBKV+iN5STlWXYZABCgq9cz7GO3wyHfuPl4RNCCEc5NyEze+OF3EbPxO+/x59n+FY9m1oUOKm0+nw8vIiJycHvV6PRtP+hrJYLBaMRiMGg6HJr89isZCTk4OXl5dtjtamaNbJdYVoCDU9ibCUJaBarEUHMTdCxhqUhGkoSR/S+fTXsCcbNWGaJG5CCOEIqgVz4WngTNFB9dyhAQ8uo/S5qRhTt2Mpya/3NIqi0LFjR9LS0jh+/Hizh+0MqqpSUVGBp+eFTfCu0Wjo2rXrBZ3jgpK2Bx54oMHHLl68+EKaEu2Zuy9odNA5wVolajIDoHROQNFqUHd8AJ4BkrAJIYSDKBotAXPexjhuOu6x9ktNaty9CXzkc0xpe3DrO/K853Jzc6N3796223/tTVVVFRs3bmTMmDHo9fomn8fNze2CeyIvKGk7d262nTt3Yjab6dOnDwApKSlotVoGDRp0Ic2Idk4J6UXliHtxC474s0rUfGZfxGAq3YPx6NA8kzsKIYSrUrS6GglbNY2HT4MSNtvxGg0eHh6OCq1V0Wq1mEwmPDw8Lihpc4QLStrWr19v+//ixYvx9fXlgw8+IDDQugxRQUEBs2fPZvTo0RcWpWjXiouL2XXgBGFhlURF2S/jlZOTw959x+hp0NK1a1cnRSiEEEI4n8NGDL7wwgssXLjQlrABBAYG8tRTT/HCCy84qhnRDpWVlWEymUhPTyclJcVWFp2bm8vevXtRVZXi4mIpKRdCCOHSHJa0FRcXk5WVVWN7dnY2JSUljmpGtEMdO3akb9++AKSnp3P48GEADhw4gKqqdOjQgX79+smYNiGEEC7NYUnbtddey+zZs/niiy84deoUp06d4osvvuD2229nypQpjmpGtFNnJ26ZmZkAdglbeywjF0IIIRrDYVN+vPXWWzz00EPccssttrJhnU7H7bffznPPPeeoZkQ71rFjR3Jzc8nOzrZtk4RNCCGEsHJY0ubl5cUbb7zBc889x5EjR1BVlV69euHt7e2oJkQ7l5OTQ25urt221NRUoqKi5NaoEEIIl+fwyXW9vb2JjY119GlFO5eTk2MrOggNDaW0tBSwjnEDJHETQgjh8i54ct0FCxbg7e193ol2ZXJdUZecnBySk5MB6NChA7179yYtLY0+ffqQkpJCeno6qqrSp08fSdyEEEK4rAueXLd6/Nq5E+2eTX7RivoUFRUBoNfr7XrUwsLCyM/PJzc3l8LCQlRVdanPkqqqHDmaT2CAJ8HBXnb7LBaVQyk5dOnsj6+vu5MiFEII0ZIcNrnu2f8XojE6dOhAeno6VVVVJCcn069fPwCOHTtmG+PWsWNHlytIOH26lOPHCzl5sojYmHD8/KwzcVssKgcPZZGdXUZubjkjR3RFq3WtayOEEK7IYd/0FRUVlJeX2x4fP36cl156iZ9++slRTYh2ys/Pj4SEBHQ6HUVFRezduxeAEydOANCrVy8iIyOdGaJThIX5EBrijcWisif5NPn5FQAcPJRNdnYZigJ9o0MlYRNCCBfhsG/7yZMns2zZMgAKCwsZOnQoL7zwApMnT+bNN990VDOinfLz8yM+Ph6dTkdxcbFte69evVx2+SqNRmHAgDBb4rZ332kAcnLKURSIjQknJESqs4UQwlU4LGlLTEy0rTH6xRdfEB4ezvHjx1m2bBmvvPKKo5oR7Zifnx/+/v522zp16uSkaFqH6sQtJNiLs1fxkoRNCCFcj8OStvLycnx9fQH46aefmDJlChqNhuHDh3P8+HFHNSPasaNHj5KXl2e3bffu3ZhMJidF1IqcU3/hSgUZQgghrByWtPXq1YtVq1Zx8uRJfvzxRy699FLAuvaon5+fo5oR7dTRo0c5duwYAD169ACwjXFz5cTNYlHZtz+L3Nxyu+17kk+Tl1dex7OEEEK0Rw5L2p544gkeeughunXrxtChQxkxYgRg7XVLSEhwVDOiHTp58qQtYevVqxddunQBICYmxpa47dmzB/Xs+4MuoDphqy46GNA/DICQYC9bcYIkbkII4ToclrRdf/31nDhxgh07dthVjF588cW8+OKLjmpGtEMhISF4eHjUKDrw9fUlPj4evV5Ply5dXO6WYFZWiS1hi40Jt83V1rdvB1txwv4D2ZjNFidHKoQQoiU4dBmr1NRU3n77bY4ePcrnn39O586dOXToEN27d3dkM6Kd8fT0ZOjQoeh0NT+Ofn5+jBgxotZ97V14uC+lZUYCAzwJCfG2TWRdXZxw8GAOXbr4y5QfQgjhIhz2bb9y5Uouu+wyPD09SUxMpLKyEoCSkhL++9//OqqZNs1gMPHR0p3k13JLq6jQwIolOykvNzohMuerLylzxYQNrMUGvXuF1FolqtEo9OvXAT8/WQ1BCCFchcOStqeeeoq33nqLd955B71eb9s+cuRIEhMTHdVMm/b158ns2pHO2y//bpe4FRdV8vbLv7N7ZzorP9rtxAidp7Kyss4xa9V/AAghhBCuzGFJ26FDhxgzZkyN7X5+fhQWFjqqmTbt8knRhIR6U5Bfwdsv/07BnzPcL3lzK7k5ZQQGeXLVtf2dHGXLKy0t5Y8//uDo0aM1Erf8/Hy2bNlCenq6k6JzrsrKSiyW2sesGQwGlyvOEEIIV+awpK1jx44cPny4xvZNmzbZpnBwdf4Bntx530hb4vbKsxsAyMu1Jmx33ncRQecsDO4KioqKqKqq4vjx43aJW0FBAXv27MFisZCXl+dyCUpFRQU7d+5k3759NRK34uJi/vjjDw4fPuxy10UIIVyVw5K2O++8k/vuu49t27ahKAoZGRmsWLGChx56iLvvvttRzTTYxo0bmTRpEp06dUJRFFatWtXiMdSmOnFzc9NiNp/5ZeuqCRtA586diYqKAqxr1lZP/1GdrAQHBzNgwACXqx6tqKjAaDSSk5Njl7iVlJSwa9cuTCYTxcXFdfbECSGEaF8cNsL73//+N0VFRYwfPx6DwcCYMWNwd3fnoYce4p577nFUMw1WVlZGXFwcs2fP5rrrrmvx9uvnWslHQ1TPzZaSksLJkycBsFgshISEEBMTg0bjehWSQUFBxMTEkJycTE5Oji05S05Oxmw24+/vT1xcHFqt1smRCiGEaAkOLct7+umn+b//+z/279+PxWKhX79++Pj4OLKJBrviiiu44oornNJ2fYoKDbz98u8YjWbc3BTA2tv29su/u3RvG1gTt/z8fHJycmzbXDVhqxYcHGxL3HJzcwEwmUwEBAQQFxfnspW1QgjhihzyjV9VVcWll17K22+/TVRUFIMHD3bEaVtUZWWlXZVicXExYH1t1fNjXajiokqWvLmVgvwygkM8mfHXwWzf8RuhHbzIyS7nnVc3MfvvwwkM8nRIe21NQUGB3dg1VVU5fPgw3bp1c7lbo2fz8/MjIiKCtLQ0wHpd+vbti6qqDvtstmXV10CuRU1ybWon16V2cl1q19zXpTHnVVQHjWIODQ1l8+bN9O7d2xGncyhFUfjqq6+45ppr6jxm7ty5zJs3r8b2jz76CC8v1+39EkIIIUTzKS8vZ9q0aRQVFZ13rXaHJW0PPvgger2eZ555xhGnc6iGJG219bRFRESQm5vrsAXvKytNrP58L5dc2YfAIE+qqqpYu3YtEydOpKLczJpvDjDpuv54ero5pL22oqCgwDbQPigoiKioKH7++WdiYmJsvUsREREu2eNWUlJCcnIyJpMJHx8fTp8+ja+vL6qqEhISQnR0tEvfPgbsfo7OniNSyLWpi1yX2sl1qV1zX5fi4mJCQkIalLQ5bECM0Wjk3XffZe3atQwePBhvb/tZ3BcvXuyoppqFu7s77u41Z5fX6/UOe5P0ej3TZg+pdbtXiBfTZw91SDttTXUiVl10YDabAWui5ubmRkpKCqqqotfrXSppKy4uJnX3NiwWHQEBQfTr14/Tp0/Tv39/Dhw4QHn2cVIUhf4DBrh84gaO/Vltb+Ta1E6uS+3kutSuua5LY87psKRt7969DBw4ELBWAJ7NlX7RisYLDQ1l4MCB+Pr6otFobEkbWIsTvL29CQgIcLnPkaYij9jiXzC4BeM74H5UjbVKNCgoiPjIALx2raJYGwVqPxw4e48QQohWymFJ2/r16x11KocoLS21m+w3LS2NXbt2ERQURNeuXZ0YmaiNv79/nfsCAwNbMJLWw1tThQUT7oZTsHMJpoGzAFDzj+G3dzlgIkhfhYJMriuEEK6g3f55vmPHDhISEkhISADggQceICEhgSeeeMKpcVnqGUJY3z7hepTQKDQj7wKtHrL2oe5YBoC67V0wGSAkCmXEXShauY0hhBCuoN0mbePGjUNV1Rr/li5d6rSYMgormPq/7ew+WVRj3/7MYm5++w9OnLWQvBBKaB+UEX8mbjkHrBvN1QnbnSi6muMwhRBCtE/tNmlrjd7emEZqdilzPtpll7gdzCrh78t3cTinjNfXH3VihKI1UkL7oPS53H7bsDtcOmE7cbKQU6dq/vGjqiqpqbnk5pY5ISohhGhekrS1oP9c0Ych3QIpN5qZ89Eu9qZbJ/B94NNkSgwm4rr488SkaCdHKVobNe8oaspa+207PkA1u+YEmAWFFaSm5nEoJdcucVNVlZTUXE6cLCJ5bxaVlSYnRimEEI4nSVsL8tRreenmWFvi9vcVuwBsCdtr0+LwdpdlicQZat5R1M1vWMewBfeybtT8OcZt27sumbgF+HvQtau1cOVQSi4ZGdY/fg4fyePUKev/+0SF4C4/S0KIduaCvtUeeOCBBh/b2udpaynVidtlL/6O8c+lKxSQhE3UoOannUnYQqJQBt8GP/2MMvQ22P6OLXFj2B0uVYygKAq9egYDcOJEEamH8wDIyChBUbT0jQ6lUyfHTIgthBCtyQVlCUlJSXaPd+7cidlspk+fPoB1vjatVsugQYMupJl2Jy23DKPJYnusAoezy4iLqHvaC+GCdB6g0Z0pOlCtHeNKSG+UEXehbnkL3Lzgz/nbXInRaKRrhC+ocPxEvm173+hQAgJ0mM1mtFrXuy5CiPbtgpK2s+dmW7x4Mb6+vnzwwQe2ebUKCgqYPXs2o0ePvrAo25H9mcX8ffkujGYLAzp6A6UAzPloF69Pi5fETdgofh1hzD/BM8BadHDWosJKaB8Y+xD4dURRXGuUQ2Vl5Z9/MCr4+Xez21dRYeDIkUP4+PgQGxsriZsQol1x2Lf9Cy+8wMKFC+0mQg0MDOSpp57ihRdecFQzbVp1wlY9hu3VqXEADOoaYCtOqG06EOG6FN+wOqtEFf/OLpewAZjNZqqqTJSVu5GZWWq379jxEoxV7phMJiwWSx1nEEKItslh3/jFxcVkZWXV2J6dnU1JSYmjmmnTvt192q7owMvN2tH5zHX9bcUJXyVlODlKIVo3T09PgoJ6An6AipvemrhpNNXTfATToUNPWTtRCNHuOGzk+7XXXsvs2bN54YUXGD58OABbt27lX//6F1OmTHFUM23ag5f2JtTXjRsHd8HbXUfVn7e7PP4sTvho20lmjpAltoSoT2GRgdNZ1kmoddoiqqoKAbBY8nF302Os8uRoWiHh4X5SQSqEaFcc9o321ltv8dBDD3HLLbfYkhGdTsftt9/Oc88956hm2jStRmH2Rd1q3eep13L7qNr3CSHOCAzwJCoqGI1GwU3vx549hYC1CjshoRunTxsIDPKShE0I0e447FvNy8uLN954g+eee44jR46gqiq9evXC29vbUU0IIQSqaqFz5ipMFpVtlT3t9h1I3sVA43Y0pr4QdHkdZxBCiLbJ4X+Kent7Exsb6+jTCiGEVX4a6qmd6FDpoc/lVMhoSktLcddr6JnzM4o5F0txOprI4SieAc6OVgghHMahpWe//fYbt9xyCyNGjCA9PR2ADz/8kE2bNjmyGSGECyv3CCfFdzgq0LHqOLGaFAAGmZMIMOdiQseBgHFUab2cG6gQQjiYw5K2lStXctlll+Hp6UlSUhKVlZUAlJSU8N///tdRzQghXJxer6fYtxdpQWNQUdCk7wRAU3gcVefB/oDxmP0i0OlkTJsQon1xWNL21FNP8dZbb/HOO+/YldqPHDmSxMRERzUjhHBxbm5uJCQkEDnyWjQJ0+z2aUbeTZ/hlxITE4NG43pz2KmFJ1FP7ax93+l9qLmpLRyREMKRHPatdujQIcaMGVNju5+fH4WFhY5qRgghcHNzQ6dYUE9ss9uuHtuMh4e7ayZsZXmom15F3b4U9eR2+31ZB1G3vYO6+U3UolNOilAIcaEc9s3WsWNHDh8+XGP7pk2b6NGjh6OaEUIIVFMl6uY3Ie8waD3+3KrAia2oiR+hqi64GoJXIHSOB1TUHcvsEjd151KwmCCsL/h2dFaEQogL5LCk7c477+S+++5j27ZtKIpCRkYGK1as4KGHHuLuu+92VDNCCBdnl7DpPFCG/w0AZeB0XDlxUxQN5gE3UhExjurEzZL0kXWnxURl+BBM8bNQNLIeqxBtlcNG6v773/+mqKiI8ePHYzAYGDNmDO7u7jz00EPcc889jmqmTTMajezbt4/evXvj4+Njt6+8vJyDBw/Sv39/3N1rX2tSCAGUZEHhCWvCdtE9KL6dgb0oneJRtBrU7Ush5xBUloKHn7OjbTEmk4U9yVlUVA4mPkLB6+R6SE8EzQSMHQayl3FodmcxMKETer0kbkK0RQ4tr3r66af5v//7P/bv34/FYqFfv341khNXdvjwYQoKCkhKSiIhIcGWnFVUVLBnzx6MRiMpKSnExMQ4OVIhWi8lsCuMnAMaLUpQN/hzBRYApcsg0OjAvzOKCyVsABaLBaPRTGWlmV3mWOI1iegt1nVZ95iHYKg04eGuw2SySNImRBvlsNujFRUVlJeX4+XlxeDBgwkLC+Pdd9/lp59+clQTbV7v3r3x9fWlqqqKpKQkysqsC1zv2rULo9GIt7c3ffr0cXKUQrR+SkhPa8JW275OcSjeIS0bUCvg5qZj4MBOeLlZqDRp2OV9A0Ua6/i1iiod7jozAwd2wtNTf54zCSFaK4clbZMnT2bZsmUAFBYWMmzYMF544QUmT57Mm2++6ahm2jS9Xk98fLwtcdu501qaX1VVhbe3NwkJCbi5uTk5SiFEW+WWf4iE/PfxMudRqfFlj88U63ZLCQn5H+CRu8u5AQohLojDkrbExERGjx4NwBdffEFYWBjHjx9n2bJlvPLKK45qps2rTty0WvvbE66esBlMlU3aJ4SwUstyUbe9g5u5hH7eR+z2Rflm4KkWWatKC044KUIhxIVyWNJWXl6Or68vAD/99BNTpkxBo9EwfPhwjh8/7qhm2oWqqipUVbXbZjQanRSN82WV5XHTdw/x6aE1NfalFBzjL1//g411TBja3p0+fdp2G/1sqqpy6tQp28ojQijeISjRV1IZPoT9yki7fSlV/SiPGA+9xkNAhJMiFEJcKIclbb169WLVqlWcPHmSH3/8kUsvvRSA7Oxs/Pxca0BwffbuOUliYiIWi8WuZy0pKYm9u13zL+A1xzZxsuQ0z25/zy5xO1x4gjvXziO3ooAP9n9dI9Ft73Jycti/f7/d+EewJmxpaWmkpKSQlJSE2Wx2YpSiNTF2m8AuZTzlFdaig4T4TtbtRjO7KgdR0eNqFEVxcpRCiKZyWNL2xBNP8NBDD9GtWzeGDRvGiBEjAGuvW0JCgqOaadM2/nKQEycP2YoOBg4cCICPjw9VVVWcykhl3Y/7nBxly5vZ7y/M6jcZgGe3v8eXqT8DcP/6ZygyljIguBcvjXvY5X7ZBAQE4OPjg9FoJCkpifLycgCOHz/OsWPHAOjUqVONW+3CNVUaTSQmZVBeXoWHu7Uowc/PWqHu6amnstJM0q4MKiqqznMmIURr5bCk7frrr+fEiRPs2LGDNWvO9JZcfPHFvPjii45qpk1TtCV4eGooKTJz4ogOnc5axZV5Qk9RgRk3dwWtW4mTo2x5iqJwb8J0W+L2YuKHABQZyxgQ3IvXL34MXzdvZ4boFHq9noSEBFvitnv3bgBOnLD2yPbq1YuuXbs6M0TRiui0GtzdtLaE7ewq0fi4cLy89Li5adHpXG+JLyHaC4fO0xYeHk54eLjdtqFDhzqyiTYtMNiTE8eL2Pm7AYMhHdUM7n6wbdNJFI3CRRd70SXC09lhOkV14pZScIydmftt2101YatWnbglJSVRUnImoZeETZxLq9UQF9eRqiozHh7203pUTweiURSZo02INuyCkrYHHniABQsW4O3tzQMPPFDvsYsXL76QptoFT09PPDw1DBvnycafyknacYrhE6z7Roz3wtNLg6enayZtAKmFx9mfZ1/19n3ab9zU53InRdQ66HQ6/P397ZK24OBgJ0YkWiutVoNWW3tPmrubQ/9Gb1PUikLIOoDSbUTNfUXpUJaH0im25QMTopEu6Kc4KSmJqj9nI09KSqrzOFcbi1QXf39/FEXB00tDwjAP9myvAKBfgjvePhoURSEgIMC5QTpJSsEx7lw7jyJjKfFBfeDPYTfPbn8PwGUTt+qig/T0dLvt1atqeHu7bi+kEA2hVlWg/vYylOWAqQKl14Qz+4ozUbe+AVXlMPLvKB36OjFSIc7vgpK29evX1/p/UbuQkBBiYmLYvXsPHTrqiBnsARjoFKFHVaF//3506NDB2WG2uLMTtgHBvXhhzL/Y+PMGpkVfydKDX7ts4ladsFUXHfTo0YM9e/bg7e1NeXm5JG5CNITOA7oMgkNrUJO/tG6LtM4pqm55G6pKIaArBEQ6MUghGkZGpLYgVVXZ9EsGOzdXYLGodOh4Jmfeta2CX9dmYLG41rQWAPvzjlJkLKVvYE9ev/gxfNy8ALgr9kZm9fsLANsyk11uyo+srCxbwtarVy+6dOkCQGxsrK04YdeuXTLlhxD1UBQFpe9V8OcffWryl1h2fWrd+WfCplx0D8qf3ztCtGYXPKatoWRMG3z/9X42bzwGgKpC9V1jVVXJOW0mK+Mker2Wa29yrbEVYZk9iEkZQ3/vKDRj9eB+Zl/X1Dj6H86jb8lQGOu8GJ0hNDSU4OBgAgMD6dq1q20oQnVxwq5du4iMjJQpP4Q4D0VRoO9VqACH1sCp7aCZAP4RKBfdLQmbaDMueExbQ8iYNqugUNDpYMQEL7RaxdZzpCgKoy/14vd15QS73t1RevQKpuf3vck9Wck7r21m9l1DAPh+1QG2/HacTkoP4i/r4nKfI61WS2xsbK2vW6/XM3jwYJe7JqJ+ZVVllJlK6eAZVmNffmUeWkWLv1tAywfWCiiKAp0TUM9eeaVDtCRsok1x2Jg2cX569wrGX+WNVmv9RRsdHc2OHTsA8PTSMOFKb9y9KpwZolOEdfTlznsv4u1XfifjVDFL3v6D7tGw7fdjKIrC9dPiGTLCNae3qC8pk4RNnK3cVM5Pp76jwlTOxZ0vJ8zrzPRLBcZ81mf+hEbRclnEVfi5+TsxUudQi9JRN71qvzF1LaqHl11xghCtmcNrwPfv38+JEyfs1tJUFIVJkyY5uqk2x83NzZawATXWlNRoFZddNL46cXvr5d/Jyiime7R1uysnbEI0hpvGDR+9DyVVxaxLX8PFnS8nSG+dGmb9qZ+oVCoJ8QjFQ+vh5Ehbni1hM/45hm3oXfCztdOhujhBEjfRFjgsaTt69CjXXnstycnJKIr9rT9ABktjnW/rbCdPnjzvMa6kQ7gPHTv7kXY4x7atX0x4Pc8QQlTTaXSM73Qp6zN+IrM8g3Xpa4gLHARApcVIiHcol3S+HDet+3nO1L6oVRWov792JmG76B4U5c/Jh3tdAod/tCZuXiEyV5to9RxWPXrffffRvXt3srKy8PLyYt++fWzcuJHBgwezYcMGRzXTpvXt25dOnTrVuT88PJwBAwa0YESth6qqfP35Xg4fyrXb/s5rmykrNdbxrPbPWGmqs2rWWGlq4WhEa1eduHX06oRJNbEz5w8Agj1CXDJhA1D0nij9/wKB3WpUiSp9LrNWlYbHQHg/J0YpRMM4LGnbsmUL8+fPJzQ0FI1Gg0ajYdSoUSxcuJB7773XUc20aYqi0KdPH/z8/Grs8/HxITo62iXHKVUnbJs3pqEocM2N1r92vX3dyDhV7LKJW0V5FW+9vJlvv9xXI3HLzyvnhf9u4Pdf05wUnWitdBod8cGD7bYNCIx1yYStmhI5AmXMP2sUHVRPB6IMuwNF47p3OUTb4bCkzWw24+PjA1gnkc3IyAAgMjKSQ4cOOaqZNu/48eMUFxfX2F5aWkpaWprLzUUGsP6nw7aE7fpp8Qwcap2PbPZdw/H5M3Fb+vY2l7s2hw/lcOpEIb+tP2qXuBXkV/D2K5spyCvn91+PUmWUoQfijPzKPH5J/9Fu2++nfyWr/LSTImodFE3tU+MoilLnPiFaG4clbQMGDGDPnj0ADBs2jEWLFvH7778zf/58evTo4ahm2rTjx49z9OjRevenpblez8mQERGEhfvWKDroEObDnfdeRGCQJxOv7ONyvZAxCZ2YcrO11/G39UdZ881BAJa8tY2CvHJCQr25896R6N3kF46wyq/MY+3J76m0WIsOru12AwAm1cy69DUun7gJ0dY5LGl77LHHsFgsADz11FMcP36c0aNH8/333/PKK684qpk2zcvLvms+LKzmXErnHuMKfP08uO8/Y2utEg3r6Mu/nriYqL4uOIEdMHxUN1vitmWjNaEvzP8zYbtvJP4Bns4Mz2ksFrXO1UPMZksLR9M6lFaV2CVsl3S+HA+d9fMR7hWOSTWxLn0NBZV5To5UtCaqoeadH7AOW6lrn3AehyVtl112GVOmTAGsayTu37+f3NxcsrOzmTBBSqnBvoK2Y8eOREVFAdgVJ1Qnvq5Gp6v7o1jfPlcwfFQ3Jlza226bqydsX3y0i1Wf7amRuBmNJt5/Yysbfj7spOicx1vnQxefSFvCdvYYttHhE+jo1YmOXp3xc9HJdUVN6uH1qGvno+bZ3wFSVRU1eSXq+mdRS7OdFJ2oTbP+NgwKCnK5W1r1qV6GqGPHjnZFBz179rStK3n2/HZCgLXoIGlnut22jeuOuNwYv2rH0/LZue0kWzcdt0vcjEYTH7z9B6mHcvn5h0MUFRqcHGnLUhSFkWGjmdjlihpFB9VVpWM6TUCryO10AapqQT29F0wG1M2v2yVu6v7VcGQDGIog/5jTYnQWVVVRT9csAANQLWbUrANOiMrKoeUyBoOBPXv2kJ2dXaPH6C9/+Ysjm2qTIiIi8Pb2JjAw0C6ZVRSF3r17ExwcTHBwsBMjFK1Nfl65reigQ5g3YJ2Q+bf11i/Yq6f0d7k/jLr3DObGGQl89mESWzcdByxoPeHjJTtJPZSPm7uW2+8ejn+A600iqygKeqX2Cbp1Uh0pzqIoGhh+J+rWtyAnxZq4Db3TujPtN+sxCdNQug51YpTOoe5fDSlrofcl0H/yme0WM2rSh5CeCPE3o3Qf1eKxOeyneM2aNcycOZPc3Nwa+xRFkcl1/xQUFFTrdkVRXDZhs1gspKam0qlTJ3x9fe32mUwmUlJS6NGjBx4ervVL+OyELSTUm9l/H8qm339h0nUDWPXZPpdO3GITwrGY4/jio91s33KC4RPgSGoebu46Zt4xiMjugc4OUYhWT9G5wfC77BI3NNbhTErCNJRuI50coXMonoGoAKk/owJq1JUAqEkfQ2YiKFrwcM5ScA67PXrPPfdwww03kJmZicVisfsnCZuVqqocO3YMk6nmpKhms5m0tDSXHNN2/Phx0tPT2bVrFyUlJbbtJpOJPXv2cPr0aZKTk13udmBeThklRQZb0YGfvzVpHTKiq6044cTxAkxVrvWZqaqqYteuXSj6HCbfYD8Z9S23JZBbcJR9+/a55M+SEI2l6NxQht9pvzFiqMsmbABKjzEocTdaH6T+jLr/G+v/M3eBorXO69cxximxOaynLTs7mwceeKDWikhhlZqayqlTp8jNzSU+Pt623Ww2k5ycTGFhIRUVFfTr51ozc3fp0oXc3FxKSkrYtWuXbVWIffv2UVxcjEajoU8f15vyo3d0KLP/PowOYT74B3jaxkSCtTjBx9edXn1CXW7Kj8rKSioqKqg0VLFnu33P/i9r99InRotGo8FkMrncWr67dqaTfrKQKyf3q/Hzsn5tKu5uOkaO7e6k6ERrpKrqmaSkWsZu1LwRKMGuO12X0mMMAOruzyBto7UHUtGiDJvttIQNHNjTdv3118tyVefRsWNHdDodxcXF7Nq1y9bjtnfvXgoLC9FqtXTu3NnJUTqHqqp4enraelEAioqK0Gg0uLm5uWyvSe8+oXVWiQ6I64iHh+uNU/Lx8WFA/1iStlWSlWlEpzuTnBw7bCBlr4W4uHiXS9jycsv45INEfv35CN9+ZT+I+rdfjvDD1wdY9Xkyp04UOi9I0apUV4lyZAMASv9rrDvMlTWKE1xSt4vsH3sFQ7hzl5p02Df+a6+9xg033MBvv/1GTEwMer3ebr8sZQW+vr4kJCSQlJRkS9zAmpzodDri4+Px93fOfXJnOnXqFKWlpQC4u7tjMJyp+tPpdBgMBlJTUxk8eLDL9baJmoxGEys/2k9ulgmtDuKHeQAV9EtwJ3mHkbTUCn74+hDX3BiLRuM6n5fgEG+uuTGGLz/Zw2+/WH/ZXna1dVqhtd8fAhQuuzqaLl0DnBekaDVqJGwJ01A6D4ED30NwL8g7ZB3jNnKOS/a4qRYz6o4P7DeWZaPu+xr6T3ba7yKHJW0fffQRP/74I56enmzYsKFGdaQkbdaxOEeOHCE6Opr9+/dTXl5u2xcdHc3Ro0fp168f7u6utUZgt27dMBgMZGZmUllZabfPaDTi5eVFbGysJGwCgKzMEo4dLcDNXct106LJLzxGaSl0itDTs2cvvv5sP/uTs7jkikrbOEBXMXxUNwBb4rb51yMM/3OazMuujubiy6OcF5xoZVQwWn8H2YoO/hyCoQy5DXa+B3lHweRaU+fAWQlburXoQBl8G+w8Zt35Z3GCsxI3hyVtjz32GPPnz+c///kPGo1rT4Zal9TUVPLz8ykuLq7xZqempmI0GklJSSEmxnn3y51BURR69epFXl5erfPURUVFuVwiK+oWERnI7L8Pw2Qykl94zG6fm2chN82IJyIyyOUStmpnJ27VLr48yqUTNkNFFSePF9I7OrTGvsKCCoqLDHTt5loVx4qigUG3QORwlFD7z4a1OOEuKDrlmr1siSvOJGzD7kAJiQaOoQyYAns/tyZuWj1K36taPDaHZVdGo5GbbrpJErZ6GL3DOF1urYo8t6LWaDSSWwEVnq5XyGEymUhOTq5zYuF9+/bZVZUK0TnCm/zCYxgMBjw9rWP+qseLWjTZBAa7ZsJWraK8yu5xeUWVy1VfV6usNPHem1t5742tJCdl2O0rKjTw9iubeee1LZw4VuCkCJ1HUTQ1EjbbPp2bSyZsAErnBNC516gSVbqNtFaV6r1QnDS2zWEZ1qxZs/j0008ddbp2af2hXMprzvZhU2GGdYdqznPX3p04cYLCwkI0Gk2NsZDVxQkHDx502V86wl5FRQVJSUkYDAa8vLyIi4sDIDY2ttZCH1ez/qdUflhtnbG9uohly69pNYoTXIVeryU42BuLRWXFkp12iduSt7aRl1OGl7cbvn7Smy+slI4xKJfOq7VKVOkxBmXiEyiBkU6IzIG3R81mM4sWLeLHH38kNja2xi/fxYsXO6qpNuuyLmZOnwaDGRQVzp6podwEET6QEOp6c9p169aN0tJSiouLMRqNeHp62goTKioq8PX1ZcCAATKmTQDYPgdeXl4kJCTYevd9fHxshT6u+lk5O2G77Opoxlzcne+//x7AVpxw9bWuNRmzRqNw44wEABK3n2LFkp1ceW00APm5ZQQGe3PXfSMJDPJyZpiilVGrqlDqyOPr29fcHNbTlpycbPsC3bt3L0lJSbZ/1VWSrq5Hjx74+PhwzBTIud+Zh43+eHv70KtnT+cE50QGg4GSkhJb0UF1z0n1nH/VCZ0QAB4eHgwcOJCEhIQaYx19fX0ZOHAgcXFx6HSuNR1KXm4ZP31/CKhZdDDpOuutnE3rj5J+ssgp8TlTdeI2cEgXLBaVH1btByAgyEsSNlGDYddasufEYEj8sca+8p+XkH1fAlVpu50QmQN72tavX++oU7VbHh4e9O/fn6pdu6ishOJKqM7dBvmX079/Al5ervflkZeXR2VlZY2ek6ioKLRaLZmZmWRkZNChQweX6iEQdatvSTMfH58WjKT1CA7xZtZfh5CZXsz4S3vb7RsyoisajRY3d53LTvmh0ShcNimaxO2nbNuGj4qUhE3UULHxE9SKYgqen07gQyvQxlhLsCs2LKfsnfsAMPzxDfrucS0em0N62qqqqhg/fjwpKSmOOF27VV5ezq5du6isrCSrHF5Ltm5PL7Vew6SkJMrKypwbpBP4+YZw/LCKxRhs13OiKAr+vh05lmrGTRcuCZsQ5xHdP6xGwlZt+KhuDBzSpYUjaj0KCyr436tb7Lb99O3BGsUJQgTc/RYeQ/8CJiMFz0+ncvc6AIqXPAyA91Vz8Lnx/5wSm0OSNr1ez969e+WX6nkcP37clrC9uRdG9O4AwJKDZxK3tLQ0J0fZ8pK2n+LAnjJWfXaALb+def1ZmcX879WtHEyu4Nefj7jkIGohxIUrLKjg7Vc2k5dTRmCwF/c/Mg6g1uIEIRSdnoD7l9gSt8LFM237vK+ag+/M/zot33HYmLaZM2fy3nvvOep07VKGGsjvmdaEbUx0GP93ZR8AJvYP56198HsmHDcHOTnKljf2kl6Mudg6lu+rT5P5Y8txAN5/6w/Ky4xERAYw+85hLvlHQamxvM5ktcToer2yQjSWoaLKLmG7676RBAVbb4nGDexsS9xSDmQ7OVLRmlQnbmfTdOzp1IQNHDimzWg08u6777J27VoGDx6Mt7e33X6pHoVThZV8dRSujAlj3l/6YTFbpyR48NLeWBQtXyZmENLZ9WafVhSFq67pB8DGdUf4duU+hk+AijIjEZGB3DFnBJ5e+vOcpf0prCzhrp/nERfah/8MucNu34mSTO5cO4+p0Vcys99fnBShEK2fu4eO+MGd2HMwjTtmW4sOqv6c+f/am2NRNSp5RcVERLrW5Lri/Co2LLd7bMk5SWXST3gMvMxJETkwadu7dy8DBw4EqDG2zRV7SGoza2Qk3UO8uahXMFqNguXP2T00isKjV/ZhdK9gxkSFODdIJ6lO3E6nF3Mk9cxfvK6asAEkZR8gteAEKQXWnscH42cBcKo0i7vXP0VWeR6rj6znxqjL8NDJHFNC1EZFxSMhg85ROZg8S4EzhQdmqggYm4muqhSTrgJwze8aUVP5z0so+p+16MBz4mzrxj/HuAU+tMJpiZtUj7awupIyjaIwtk/NJVZcyemMYk6dMx3Brp2nGDG6u5Micq7xEUOZO+Ju5m55g89TfkJjUYgmlPvWP0NWeR7d/Tvz9iVPSsImRD0sqgWD2YBJreLn9B+4pPMVBOisvWobMn4mtyoHN40bRkvtK7II13N2wuZ91Rw8ps6DH37AffCVmLZ+6dTEzaFrThUWFvLCCy9wxx138Ne//pUXX3yRoiLXmxNINF5mehFvv7KF8jIjnc+akuCrT5PtihNczaSe45g74m4UFL46/AsA2eX5dPfvzP8umUuwZ4BzAxSildNpdEzofClhnh2pslgTt9Pl1sKDXEMubho3Jna5kmAP17zLIWoyZR4BahYd+P/9DVtxgjnnhFNic1jStmPHDnr27MmLL75Ifn4+ubm5LF68mJ49e5KYmOioZkQ7dHbCFhEZwKy/DgFg5DjruneunLgZjUau6j6GO2Km2G1/+5In8dF4SkWtEA2g1+jtErf1GT8D4KbRu3zCZjDUvdxbffvaM99bFhD4709qFB1UFycE/udzvC/7q1Nic1jS9s9//pO//OUvHDt2jC+//JKvvvqKtLQ0rr76au6//35HNSPaoZPHC20J2x1zRuDhaR1XctlVfWxVpSkHclwuQTEYDOzYsYP1SZtYfWSD3b7Xd37M1q1bOXJEpkIRoiH0Gj1jOo632xYTnODSCVviHydZNG8dmek1V5z5+YdDvPLsrxQVVjghMudSFAWPwVfWOh5f0enbRyHCjh07eOedd+yWjtHpdPz73/9m8ODBjmpGtENDR0bi4aGnd3Qonl56W2VXdXFCeEdf4gd3cbmClrKyMtLLsnnj2CqKLGVE+XYFrKtofH1s/f+3d+bhdVXl/v/sM5/M89QkndI2SZMm6UhLoS0zDoAoCCqDgCiCCjig9zrgCOJVGRQEUUGuiBcF7/UnCAXagrR0ytgkTdI2YzPPZ8yZ9u+P3bOTk6kDJSfJXp/nydNmr3X2ec/K3ut897ve9110R3Rzc8SHCQQC6PX66U8mEGgcb8DDzhMetiCVfaWkRKaSbE0Jk1XhIxCQ2f12E3bbCE89tpvbv7SJpBQrADu3N7D9lSMA1B7q4pzNi8JoqWAsZ83TFhMTQ0vLxDXe1tZWoqOjz9bbCOYpq1ZnTJolKkkSa8/JxmA4q+GXcwKHycNvh15hKOAgxRDPnZkfB+Ca+K1IwB5nNa/7S9VtvwQCweR4Ax7eaPsXPe5uTDoTFy649MRxH28cf5Uel/ZqtOl0Erd8cQOZ2XE47B6eemw3XR02AN56rQGAy6/ME4JtlnHWZvtPfvKT3HrrrfzlL3+htbWVtrY2XnjhBW677Tauv/76s/U2AoFm6Hb0Y/c6yI5M44tJV+I5sUxRZFnKTekfQkKi2daBJ+ANs6UCwezFG/CGCLaLMz9EijUVgBRrqpqc0KtB4RYRYeK2u85Rhduvf/6O2nb5lXlsu3jyLdEE4eOsLY/+13/9F5IkceONN+LzKcGLRqORO+64gwcffPBsvY1AoBnWpq3kVxd+m4XR6Qx3DnDs2DG17Y7zP8Pq7iLWpOZj1pvCaKVAMLvRS3qijTEMu21clHkpiZYkNQTj/PQLeKdrBw6PA4vBGmZLw0NQuN3/jX+px4pWLxCCbZZy1kSbyWTikUce4YEHHuDIEWUtPCcnh4iIiJO8UiAQTMXqlDxsNhutra0hx+vq6tiUXyyWRgWCk6CTdKS7CqFnIZHZsSFtBslAhm0NDqcHyyLtflft3hWand9Q30PH8WHSF8SEySLBVJz1GT8iIoJVq1axatUqIdgEgveJzWajrKwMn8+nxoZKkkR3dzc1NTUEAoEwWygQzG58vgBdXXZGRgIcLG3H7R4NJ6ir66G7y4HT7mVoaCSMVoaPN16t4/V/1gFw3gVKmSXniRi3ybJKBeHlfYs2nU6HXq+f9mdsRqlAIDg1bDYbBw8exOfzERMTQ2FhIQD5+fmqcDt06JAQbgLBNBgMOlaXLMBqNeB2+0KEW1e3A0mClStTSUzUnpNhrGC7/Mo8Lv5QLgAZWaPJCVoUboGATOn+NgKBieWUvF4/5QePh8Eqhfetpl5++eUp23bv3s1jjz0W1jpSjz/+OD/72c/o6Ohg5cqVPPzww5x33nlhs0cgOFUGBwcJBAJIkkRubq768JOYmEh6ejrt7e0MDg7i9/vFMqlAMA0Wi4HVJQsoLTuOy+Vj7742AFWwpaZEhdnCmScQkGltHgRGkw6CsX433b6WZ35zkOOtg/R02zW3TPq/L1ax550mjjX0cvV1Repxr9fPn585SF1NN0MDLrZclDPjtr1v0XbllVdOOHb48GG+9a1v8Y9//INPf/rT/PCHP3y/b3NG/OUvf+Huu+/m8ccf59xzz+XJJ5/k8ssvp6amhuzs7LDYJBCcKsnJyTQ2NuLz+aisrGTVqlUAtLe3096ubMOTmpqqSU+2P+BHkiR00kSx6gv4MehE3TpBKBaLgZLiDHbvGS1NtWRxgiYFGyglP264dS21h7ooLMkIabNaleSElsYBclemhsnC8LFoSQLv/buJfbuVa+WjH88H4IVnS6mr6cVo0pM5ZrvFmeSszvbt7e1873vf49lnn+XSSy+lvLycgoKCs/kWp8UvfvELbr31Vm677TYAHn74YV577TWeeOIJHnjggVM6x4hXZsQ70VOok8BokEL6TYUkgWmSvl6vjC+gY8QrE0Cetu9UmI1n1tfjk5nOAXqmfb0+mUk8yqfVNzguYz20Xr/MdKuAJgNq8d2T9TUaQHeir88v4z9bffXKRHi2+vYN2HB7AugkZXeE8vJyArLE4fpjSCfESnfvIFkL/WpxXYMe9CfO6w/I+PxT26DXgUF/+n0DARnvB9FXlvFOs2tOsK8/4Od7ux/HKFn4xrpb8PtG7yOHz8XX3/45G9ILuG3VVQDIsoxnmvPqdGA8YcNJ+57GfX825oj329fnC22bL3NEkNO67/Uyxxr7AfAHwBfQ0dg6TEJSDBZLaI3IuTJHBBl7359OX0mvY3lB+qTfSUajkZzc0aLDc2mOOJW+0933+cUL+Lgf/vp8OXv3tOHx+oiMg4bDPRhMBj7zuQ1kLk5839pgfN9TQZLPwtrl0NAQP/nJT3jssccoLi7mpz/9adiXID0eDxEREbz44ot87GMfU49/5Stfoby8nF27doX0HxkZYWRkNBB1eHiYrKwsbvyvRkzWia7hlVl67rxsNAbi7j/Yppzsl6Xruecjo32/8Zwdu3vyYc9O0vHNj0Wqv3/7z3b67ZP3TY/T8Z1rRvv+8EUHHYOT360JURI/un70ifLBlx209E7eN8oi8dANo31/+f+cNHRMfleZDPDwZ0eLJ//6X06qW6e+Ax//3Gjf377hoqxx6rvqoU+biYpQyln8caeL9xqm7vvTz0QSbVWEzAvvunm7ZuraZT+8LpLEaKXvS3vdvFE5dd9vfzyCjARFEP2/gyO8UuqZsu83ropgUbLSd3uFh5f3TR3YfPeHrSzPUJ6ZdlV7+Mvuqfuev+AoGVHDyLLM4e5IKgZXTNn3tgstrF6ifAGVHvPy9JvuKfvesMXCxuVK36oWH0+8NvV2NZ/cZGbLSuVvUd/u4+F/Tt33Y+vNXFyk9G3q8fPQ351T9v3QahMfWWMGoL3fz4/+NnXfi1YZuXqDhaqeeu558wmW234wZd8h87s8cs0Gkqzx2FwB7vtvx5R9z1lm4MatSrmHEa/MPc/Yp+xbstjA5y4aLQ3xxd/apuw7G+aItDiJtZFvc/HFF2M0GufdHPHLm6NUkXeyOeK2DS5sg0oMW50jnrLWqb2xc22OuONSK4XZSt899V6e2zX1fa+FOQKgzxbgOy9Mfd+fn2/kunOVviebIyzDXVyUV0/pbolrbljPI29PXWbpTOaI4eFhkpKSGBoaIiZm+qXo9+1pe+ihh/jpT39KWloaf/7znyddLg0Hvb29+P1+UlNDXbupqal0dnZO6P/AAw/w/e9//5TP39PdwyuvVKu/+/2bgMkngb6+Pl55Zaf6u8dzDjCx+j8oAviVV0YFpcu1DrBM2tdmt4X0tdlXA5GT9nW5XLzyyttj3qcYmHynCo/HwyuvvDLG/kIgbtK+fr8/pG9P70ogYdK+QEjfzr5cIHnKvm+99RYGnfKl0TawHJjaTf/GG29i1isTa/PgUiBjyr47duwgwqBMgMeGFgOZU/Z95513iDYqk0TDcDawcMq+u999lxqT8oV/1LYAWDJl3/f27uWIeQiAJns6MHVshMvtwk5QSEz+9w1SWlZG5+FeANpdSUDelH0rKyoYOKIUFO1yxwNTe8Wrq6txNHcA0DsSC6yasu/hw7V4jyuBuoOeKKBkyr4NDQ280qUsQdi8EcCaKfseO9bIK31KaYIvRHyEt6aeC1llWMy+HXsAGPEbgXOm7Nt2/DivvFIPKN4XOHfKvp0dHbzyyuExR6Z+OJ0Nc4TdbodI2L59OzD/5ojXXnvtlOeI5uYKdY7on2dzxIED+2k9NABAqyMFmPrBTitzhNNnBtZP2be5uZlXho4CJ58jktKUf1dvkqlr2M/ZniOczqmF6Hjet6dNp9NhtVq56KKLpt3/8KWXXno/b3PatLe3s2DBAnbv3s3GjRvV4z/+8Y957rnnOHz4cEj/qTxtxzt6JlW+Z7L0cfjwYbq7u0FvorCgAKPRxFtvvcWmTZuoqa3B5/WRlJjIqsLRm2i6ZYfxyyRnqy+Ee3nUy1tvvcVll1yAyaQ80czn5dGTLTt0HG+lpaUJWZax2Z1YI6IwGg0UF5dgNptD+p7O8uiZ9p0tSx//OraXhw78DoNs4MtRV/Ko/X8xGg385NyvUJC89NSXPOf48uh096fP52XXjjdUT9t8mSOCnMp97/MFqK7uwuUcIS8vhZTkSFxuD9vfeIvzzttCdU0vPp+fgpVpREcr99NcmyPO1n0fnHsvuOACjEbjnJ8jznR5FJSkg7/+qZyj9b3odTLrt8js3wVFa7K49MqV6t9mwnnPYI6YUU/bjTfeOCs38k5KSkKv10/wqnV3d0/wvgGYzeYJX4AAUREmdYluOoyTPxSHkJubi9vtxmazUVd7iMLCQgy6AA111UgBH3ExkRQW5GIcc7JTOe986+v1Shh0AUwmkzoWs9ne9913mra2tjZaW5vVe0wnyRj1MpLso662itWrV2OxTO5lOQ0TTqsvwMQ75Sz1PY3NHa7MPQ+/foSH9v4egy7AiOTk0Qu/R1HyRC+D6TTOezp9Z8X1M01fr1c60cd44mfmbZgNfTesy2Jo2E1iwugStEEXID7Wysb12YyM+IiNneI+mg2f7dS7nnZfl8+J1aCMS3DujYowYTAYcPtdGE+0zcU54nT6jr3vvV4/f3mmlIaaHowmPTd9bg219XsJBGD/njYkScfV1xVNKdzGcip/Z+NpXAzvW7Q988wz7/cUHwgmk4k1a9awffv2kJi27du3h20J12g0UlxcTHl5uVqDC5Snm6ioKEpKSlTPktbo6+sjLi5uUm9tT08PSUlJs/Lh4IOkq6uL+vr6KdvdbjelpaVs2LBhWi/3fMXlc/Ovpn+HHPu/ozsoTFo2aVapQLsYDLoQwTYWi8WAxaK9DGyAmoFDVPQd5MIFl5JiTVOPy7LMvp49tNiauDTrw8SYYqc5y/zjhT+WUlfTjdGk55YvbCB7cSy19fDx64v5n/+uYN/uFiIiTHzoqvwZt21ez2z33nsvTz/9NL///e+pra3lnnvuoaWlhS984Qthsyko3MZ/yWpZsHV2dlJRUUFFRQV+f6ifvLGxkaqqKmpqasJa7y8cJCYmhnh/Fy9eDBCy00h6erpmBdtXdjzIga5qIo2Kh0QnwctH3uTHe58iIIuCwwLBdATkAG2OFrwBL2+0vUa3a3RV6mDvPuoGa3D5nfS6e8JoZXg4d8sSoqJN3PKFDSxdnqQeX7U6g+tuXE1MrIU152SFxbZ5Ldo++clP8vDDD/ODH/yA4uJi3n77bV555RUWLpw6UHQm8Hg8EwSIxzN1xtF8x2q1otfrGRwcDBFuzc3NNDYqQaVRUVGa87T19PSocZZLly4lK0uZJFatWkVkpBJM3tbWNkHozndcPjeff/X+E4LNyn+d/zUA/nPDF9BJEi8feZPv7HxUCDeBYBp0ko4LMi4hLSIDn3xCuLm7AGgYUnZJ2Jh6HktiZr6AbLhZkpPIN++/KESwBSlZl8k3vnsBqWmTJ+l80Mxr0QbwxS9+kaamJkZGRjh48CDnn39+WO1xOByUlZURCARCPGtlZWVKppcGiY2NVb2Pg4ODHDp0CFBEGyiCJdxCOxyM3Z5q7LUS3B5ufB+tUNFaS91wM2bJyHdW3kZB0jIALs4+hy8svBoJid0d5XQMdYfZUoFgdmPQGUKE25ttr6ltG1PPY1ns1Fmo8x2Teeol8+naPmjmvWibTdjtdg4cOIDH4yEyMpLVq1cDihfJ6/Vy8OBBbLZp6hjMY8YKt6GhIfW4VgUbQEZGBhkZSlmC2tpaurqUp+BDhw4xPDyMTqebdKl9vlOcnsfnk6/gc4kfwdDto61N2ZKovr6eJZ4UPhN/MfdmXUda9NSlIgQCgYJBZ2BbxsUhx5ZE52hasM1mhGibQWpqavD7ler1RUVFqvekoKAAg8GA3++nurr6JGeZf8iyzNGjRzEajcTFxYW0ZWRkUF9fr8nlY0mSWLFiBQsWLACgrk5ZshgaGkKv11NSUkJsrLYChEHxLi6zZrLIpAROHzt2DEAVtUXWpaSaEzTphRQIThdZlint3R9yrMXeFBLjJpg9CNE2gwQDyf1+Pw0NDeqXyrFjx/D5fCF9tERzczPNzc3s37+fvr6+kLY9e/bQ1tZGZWWl5hIRQBFuy5cvJy0tLeR4cXGxJgUbKIkYq1evnjJNPpiJfTpp9AKBFglmidYN1gCwJlkpRuuTfROSEwSzAyHaZpDk5GSKiorQ6XT09PRQW1sLKLXjJEmisLBw0hpy852MjAyMRqMaUB/0LAGqmF20aJHmEhGCBAIB3O7QrWZOp4L2fCQyMpKSkhJ0utApzGQyaVqwDQ4OcvxEpfnxdHV10dvbO8MWCWYr4wXbxtTzWB6bC0BqRNpocoIQbrMKIdpmmMTERAoLC5EkKcSrVFBQQHKyNmNwurq68Hq9Ib+Pp7W1VZOeNr/fT0VFBYODgyGxa7W1tXR0dITRsvAiyzKtra0TlkA9Ho9mx8XlclFeXk5dXZ0a5xeku7ub6upqKisrNRs3K5iIL6DMu+OTDs5Pu4C0iAxkAvgC02wrIJhxhGgLA/Hx8ROCxxMTE8NkTfgJ1iNbuHAhVqtV9a4BLF++HIPBQEZGhuY8beMFW2FhIaDUZgPtCjdZljl8+PCUn/3IkSO0tLTMsFXhR6fTqZ7H+vr6EOEW3LZPp9NpLnFFMDmSJLEx9TwuzfzwhKSDYFbpJZkfJiNy6n1XBTOPEG0zTCAQoLa2NkSYgLLZrlYDpyMiItiwYQOLFi3CYAhNpU5ISGDTpk2aXDbu6elRBVtxcbG6J11OTo66hHzs2DHN1WkbGhoKEWzBmnVjl0SPHTsWspewFjAYDERFRam/19fXU1FREdInIiJCs0vHgonoJB2pEemTthl0BpKtKTNskeBkCNE2gwQFW1dXF5IkkZ+vbIERjHHTsnCTJIlDhw5NWLopLS3VZOYoQFpaGr6RBDLSl4UkHUiSxLJlyxjqi2LpknzNeU4MBoPqdY2KimLVqlUAFBUVqYJkrNdJKwSz0sdmYI8tnyMSNASCuY+2ZrUw09DQoAq2goICkpKUasv5+fmqcAsuY2gJv9/PoUOH6OvrQ6fTqV/CEREReDweSktLNRl4X1Xezhv/bOH531fS2T6sHpdlmdf/Xx17dnXy3NNleD3a8rS5XC41vjEqKkr1zprNZiwWZUsrn883wZutBYLCbexWZyASNGRZxuVyTdrm9/s155UVzF2EaJtBMjIyMJlME5IOEhISKCwsxGg0hmROaoXm5mZVsI31FAS3a/J4PBw6dEhziQhLlyexICsWh93Dk4/upqtT8UK++Wo9b73eAMDGzYswmrTlaUtOTmb58uWAsm9tQ4MyFkFPrU6no6SkBKvVGk4zw0Zvb++EhxyPxzNpgo8WkGWZ2tpa9u/fP8GT7/f7qays5ODBgxMytLWAx+Pj6NG+SedWh8NDU/OA5ubd2Y4QbTNIdHQ0GzdunDRLNDExkU2bNmmy9tbChQtJSkqiqKiI+Ph49XjQOxAfH8/KlSs1l4gQEWHic1/aqAq3P/xmLwBvv3UUgCs+XsDmbUvCaWLYyMzMVMMLOjuVkgRjiw6PvY60RFdX15QFuscnJ2gFv9+P0+nE5/NRVlYWItyqq6sZGBjA6/VqztsmyzLl5R00NQ9SXdMdIs6cTg+lZe0cPdpP2/Hhac4imGmEaJthpouz0VoMThC9Xs+qVasm/aINCrdgsLnWGCvcnPbR2D4tC7YgaWlprFgRmvVWVFSkyQcfUJaNxwq2qKgoNmzYENKnvr6e4WFtfQkbDAY1kSco3IKxfmMTfbR23UiSRHyCDpDp6rKHCLeKik48Hj86yUdCvGn6EwlmFG2qhDAxMuLjwMHjDA9PdMPb7SMcOHAcl8s7ySsFWsZqNZK9KFTQ5qxICpM1swe/3z9hya+zs1PTyznBpJRg0oHZbAZQBYkkSZp8OBwv3IJZtVoVbKB42vr72oAegsKttEzJyvZ4/YCHgNzBwEDfdKcRzDDau3vDyJGjfQwPj1BW3hEi3BwOxRU9bBuh4Yi4QQSjyLLMa/84zJ53mkKOP/no7pDkBK0xVdHh9vZ26urqNCncLBYLSUlJk2aJFhQUEBcXR0JCwoQkBa1gMBjUWodBFi9erEnBFkSWZSRcKMJNcR4oeIAuJAKavJdmM0K0zSArlicTE2PG5wtQVt6BzabcIBWVHXi9AaKiTOTlanNXBJ9v6lIn07XNZ4KCLZh0cPmVSgxXeqYS4/b0r9/TpHDz+/2Ul1cwMK7ocHCp9Hh7B4cPa0+4SZJEXl4eRUXFE7JE9Xo9BQWFrFxZoElPG4DD4aKmpibkWFNTE0NDQ4yMaK+sULB0kCIDxq/wBIAA0dExE/Y91gqz9TtJm3dvmHA6PTidHiIijPh8AUrL2gHwegNYrQZcLi8Oh/YmD5fLy969rTS3DE5oGxp2s3tPM13d9pk3LMwc2NeKy+cnryiNj169ko3nLQLg5s+vY3FOAsUbs/jn/9VqruSHzWZncMiERAqrVhWpRYdTU1NZvjwPSKOr26PJwPK6ul4qq7rx+UKvCb8/QHVNDzW1PQQC2hKzAAcPHuW9vc30DwyfELAFAHh9Pg4cbGL3nmO43dqbez0eEzp9NjBemFnQSQvweJPx+7WVAAbQ1+fknX830tvrmNDWdnyQf7/bqDpdZhoh2maQjk47Pp+M0+lFpwu9EVwuH36/THuH9vYF7Ol14B7xceRIX4hwG7aNUF6ueCGPHx/WnOckKzuO6FgL2UsTSVkQM+bzSxSszcQaYWJpXjI6vbYmVUlnRpKsyFhpaXWpIsTr9XO83QeY0OmikSTD9CeaZ7jdPrp7HGoIxljhVl3TTX+/i74+Jw6ntsSJw+FicMgHGIFUcnJySUhIAEAnJQFRBAIGmpu1tTG6LMu0tA7i98uAHsXbdjzYSkA24Hb76O2bKFzmO4fr2ggElFWwscKtvWOIurpe/H6orw9PJrYQbTPI8mWJpKdHA0z6tJuSEknuCu0tj2ZnxbH4RKD9kSN9tLYpmV1VVZ34fAHiYi2sKkzTXMmPtPQY8nKVbWTajg9z5ES8Y/mJzK6ICCMbz8lGr9fWbRwbY6FoVTo6nURvr5Oa2m4AKio7sds9mEx61qxegNmsLdFmNEpYrUNAQBVuHo9SYHhgwAXImM2DWMzaul6sVjNxsW4UUWKkrn6QwSHFcx+QrYCMXjdAVpb2knv8/rHLfDoU8QYwOtf6NRiekrM0DnACEhWVHfT1KXUPGxr6AAlJsrN0aXj2C9fW3RtmJEkiKzN2gpdNaYOszLhJ2+Y7Sh2ldtLTlGKox471A0rcQEyMGb2+F49He4UvARYsiFHjHINeWI/HR0SEkdUlGZoTJkESEyNYVZiGTiepE6rDoQi21SUZREZqr0xBIBAg4HcDnQSF2573Wk+0ykAXcsCluZ0ilGLLhazMT0KS/MiygYqKnhOtMgsWmNmwoUBzCRqSJJGYIANuYARFsI1dJrWhk9wkJGhvF43U1BQKVqYSFG6HqoNZ6opgW12yMGS7uJlEiLYZxG4foay8nUBAZrzTSJYVV+xk5UDmO83NzXR3d9PT00BMTOgEEfC309/fp8kdEYKV3HU6J4vGlfwoWpVKXV0NAwMDYbIu/CQmRpCXF+qZLi5K16Rgg9GahhFWAzB+94NezCaZ4uJiTe4U4XQ6cTqHKSkO3Rw9MUFPSnIkfX3ay9qXZRmbrRflWhl/vTiR6Ccgd2G3ay9kB8YKt7F4wyrYQIi2GaWtbUhJOrAYGK8/rFYDPl+AltahyV88j1m4cCHx8fH4/HqGh0ODO+0OHUajUZM7InR2dtLR0UFNTQ1tbe1jWgKUlpbT29tLdXU1fr+2EhGCeL1+mpsHQ44da+zXZKA9KF/CR44cQZJ06HQJIW2SFIvJZOHIkSOau158Ph/l5eU0NjVRWdkc0tbX76G8/BD19fX09PRMcYb5i8fjQQJMptCHH70+Ehkj0ok+WsXrG/8AaMDnC6/nUYi2GcRotAEOXG4lvTo5adQdrxTVdWAyaq+Eg16vZ9GiFUhSGsolOVa4xZOWvkKTOyKkpaWRkqIsV/h83ZiMwXHpweNxIEk6CgoKQuqUaYX+gSEOHGxTYtiMyucPxriVlrbicmnPY+12u+nvH8DhjCQQMKOUbVA8sbJswmaPYGBgaMqN0+crBoOBRYsWAYn4/EoMW2JC8KvPgEwKMTHxJCaGJ0YpnBiNRmRi8XgU72t2dhzAieSENGSMmEza81z7fD4OHqyjrq73xJFg9QIlxq2iop5AIDyxfkK0zSCSFAlEABJmk4/ly5XAV4vZhxL4GXGij7YYGnZTUXEMWZbR67wECz3CECDT0tJBU7P2lgFdLh8DgxHIRCEBXq8ScC/hQUYiICfT1eXV3LLxwMAwZWXtOJ0+jEYdRUWKsF2Zn4okwdCwl737juF2a6vkh8lkxhqxELCiCLZuJPXLxg+YsVgWYrFoa3k0EAjQ0uoEolBi+3pxu4NzjJKcMGyLwGZzhs3GcCBJEgZDEhAHQEI8LFqo/F+n86LIgzT0Bm1dLwAHDh5mcEhPMIatuCj7RIsLkOjtk6iqOhIW24Rom0F0OjMgIeFkxHOcurrDALhHOlCUvISkM4fTxLDQ0d5BINCNXt+DyTSAhCJCJIaJirQj0cfxtqNhe7IJF+4RHz5fAKs1leTklJC2hdkrAAt2h0dzy4GSpEfCAPhB7kSWg4VBXUh0owgWI1qb3ny+ACMjfkYF21jR2gME8HgDeDzauo+8Xh8ejwzIxMf7kXDidCoCLSbajST5kGUddru2vLOyLKPTW078NsDAQDNHjihCJBDoQpI8gA5k7SU7+bw6FEeKDavFpa70GA1DKMkJOjze8My72vtrhJFFi+KJiDCi07mpqupVg18loLAgHZkIUpK152lbsCCJ9o5mAn43bj8hFdsdDiWTNDMzWXOV3BPirRQXpWM26zh8ODRQOipKR9GqNOLjrZor+REXF0nJ6gwOHz6My+misrISgJqaGmRZJi7Ww8qVy7FYtJX1JkmBE6LVi8kYwDumyL3ZJOHxdiJhPBGGoJ2xMZtNnLNhMZ2dA8TEGCkfOK62RUVZWb48A4djhAULtFXyQ5IkCgvS6O1z4HYZOXJkmI4OZe9Rk9FAUVEmPp+exERtZdUCFBYu4GBlLTr/CC6Xn/379wPg83kxGgfx65wUrFwVFtu0NdvPAlJSokhISMBgCNXLSUlJpKZEaS7YHqC6sR3k0af/ybLbqo+2aW4ZECAmxsThw9UT9tisqanB57NpTrAFMeoNrMzLJSoqCu8JdRIIBEhOTmZRtvZq14ESG6rTBdDrvFgslpA2g8GA0SCj0/knzD1awGIxERNjVAV+kI6ODrq7O8jI0F48GyhxoCnJURO2qoqLiyMmJkqTgg2gV+rmeGo1SXlK1n5wjjEajUSuMNOeWsOg3B8W27Q3s4WZQCBAbW2tehEEOXTokOaW/4LYHKOxJLIMDsfECtxyQHuxW+M3RQ/usRmcYGtqaujs1FYVdwC7bYSnHt3N7584QFpqRkhbTHQKj/9yN889vR+vV1tZkh6PB6fTSSAQwGazodfr1f1YnU4nPp+PkZERzSUiAPT391NZWUkgECAxMZHNmzerbW1tbTQ0NGhufgni8XgoKysLOdbT00NjY6Nmx6TX3YOMTOnQPhwRoyVPBiP6qR6qxC/7GRgRom3eExRsXV1dSJJEfr6yAbhOp6O3t1ezwu3CDUUE9GacXibUrwvI4A7oOG/9Gs0tj/b09KiCrbi4WN1jc9myZWRkKGLl6NGjmivh4HR4sNtH8Hjt1DfUh7TV1h5Clr0MDrjwjGhrXEwmU4iXOiEhgZSUlGn7aAGfz6fOrYmJiRQWFqpzyfLlywFFuGm15EdZWRkOhwOTycTatWvVtqamJs0Kt/XJG1kapVwbA/E9OKxKQs9gpBKmUpywlvz4wrDYpq1vwTDT0NCgCraCggKSkpQYivz8fFW4HT58OMxWzjwtLS1Ifi9W48SlYRkw66C+vk5zk0daWho5OTkUFxcTGxurHpckiRUrVrBw4UJKSko0V/IjJS2aT92yktXnWNDpYPhEYrHdJmMyS2zYEsFnbismMkpbpQr8fj+SJKmCpKenh3feeUdt1+v1SJKkuR0RJEnCbFYSvNLT00Me/hISEjCZTEiSNGFJeb4jyzLl5eWqYCspKVF3hViyZAmgCLfjx49Pd5p5ycjICDTpibTHgASD8b1qW+xgAp4mX9juIyHaZpCMjAxMJhMFBQUkJ48WM0xISKCwsBCTyURmZmYYLQwPsbFJQAYQw3hZppPMwAKio9M1F+8nyzI+XxR+/8SgcVkGry+GQEBbgg1gaGiItuNH0eklersC7P+38hR84N8OnA4wmqCu7pAy8WoIk8nEUIqP8ogWdVk0yOLFizkW18fxeJvmPG2SJKlipLq6mt7e0S/giooKPB4PJpNJc7F+kiSxaNEizGYzJSUlIbUwMzMzycnJITIycoK3VgscPnyYEfcIae4FIcdjDDHEu5MYHh7m6NGjYbFNW1dpmImOjmbjxo2TekYSExOnbJvvtLX1oOx7FweAzOCJf01IcgpIOrq6bCxbFtDUEmlnp53GpgF0OomiVWlERyviLRCQqavvpqvLTm+Pg40btRV4Hx0dTXx8PDqdjuSERMreO5HZ5YXVq1fTdrye+Ph4zRUFbbN18Z33foUv4MfhdHCOvFxt+0frLp5tfQWAgtRl5CcuDZeZM45Op2PlypVUV1fT09NDVVUVOTk5ALhcLiwWS4iXSUukpKSQmJg46fdOdnY2CxYs0OR3Um5uLocPH8af7lHKhZ5g2DdMzooV+Dtlli4Nzz2knZl+ljDdDaDFmwMgJyeNYOV2RbjFnPh/Mkg6ZNnFkqUxmhJsAKmpUSQlRhAIyFRUdjIwoASQ19X30NVlR5JgxYpkTQk2UL6ECwsLSUleyN//pyqk7X+eqyAvt5CcnBzNeWYzo1O5e/UNAPyt7S3+ZdunLvn9uXU7ALcWXE1ewpKw2RgugsItOTkZWZapr1diIccvC2oR8Z00EYvFgpQVoHpIyTYuTlyttpUO7SNqkTVsnlltzfaCWcnuQ8eQGEZWU6iD8Vs6/AEXktTNgRrtFdfV6SQKC9NU4VZ1SMkU7e52IElQWJBGsgbr+gH09jh56tE92IZHSEmPBiAy2kR72xC/e3wfLqf3JGeYn2w053NlzLkAvGkv5dutv1XbLopaw0XW1VO9dN6j0+lYtmxZyLGsrCxNCzbB5FT0lVLRVwrA6qT15MUXAJATo3iv3+16m6ND9VO+/oNEiDZB2IlJSKbbBc6AC6Xa9Ch6XR/DIzBsTNCcpw1GhVtiYgRj8zC0LNh6uuw8+ci72IZHSMuI5rOf3wDAzV/YQNQJ4fbUY3twOrS10bXL5aK5uZnzolZxy5IrlWM+ZQw+nn0Bl0avo729HZvNNt1p5i0ej4fy8vKQY8eOHQuJcRMIAAyS4kVbnbSegoTRIrprkzewPDYPCQm9LjyeNhHTJgg7axYn4e2LxWV3AxYISUeIIs7q4NL1i8Nk3exApwtd6tPrtbX0NxazxYDVaiQyysTtX9qE2aKI+dTUaG7/8iaeenQ3kVEmjEZtLe1YrVZWrVqF3W6nwxFaiy0yKpLc1FwMBoNaOkZLeDweSktLcTqdmM1mCgoK2LlzJ7IsU1VVRWFhoZrNLxCsTFhFakQ6SZbkkOOSJLEhZRPLYleQaAnP9aI914Vg1tHU1HRCsKUAOhISxi5XxBEIRFJVdUhzJT9ASTqoqe2mpye04HBFZSf9/dra4DpITKyFz39lE7d/aRNR0aF79aalx/DFezdz8+3rMZq0JdpAyUR/x1HFzw8+A0CkUYlp+2PNP/h7z9uazAT0+Xwhgm1sDFtSUpIq3Pr7w1MsVTA7GS/YgkiSFDbBBkK0CWYBMbEpQCqgIzExgvw85WZZujThRI84YmKzw2Ve2AgKtmDSwcr8VAASE0aTE7Qq3CKjzFPWYUtIjNSkYAP4U+0/VcF2W8HHefVjv1HbfnfoJR6veEFzDz96vZ6kpKQJgg2ULMHk5GQiIyOJiooKo5UCwakhRJsg7AQCJ55eEiMoLEhVsyEzF8SybJmyJ6CE9r6Eu7psqmArLEgjKUn5ssnPT1GTEw5Vd+H3aytBIxCQqa7poqa2e4IA8fkClJa1c+yY9rwmbbYuHil7DlAE2x1Fn1QzaL9c8ikAfn/oZWr7j4XNxnAgSRJLly5l3bp1E5IOglmlJSUlmisRI5ibCNEmCDspyVGUlGSECLYg2VlxlBSns2JFkuZKOIyM9IM8jCx3YzaPbsmk00no9AOAHZ+vg0BAW9s1DdtG6Op20NlpDxFuPl+A8op2hobcNDYPMDKircr/mdGp3LjkVtbEXBQi2ACuWX4pF6RcxRULrtNUjbYg1e02fvlWE/7ARC/jrvo+nn1Pe1X/AY4c7+Wrf3wXh2tiIer3alv5zgt7NLdN3mxHJCIIZgXxcVNXaQ+NcdMO1T1ezAygAw4cOEBxcTEAtYcP09vTgwR0O8EbgIl7JsxfjvTZcHvbsRii6eyEgF8RZ1WHOrHZvCD30+tyM+hKJ9WsnSmubcDFH9804Ass48nYRr6wZbQe299K23lrbzoScE3uMPnp2klGsI/4+PKfKxh0eXF6fHz3I3lq2zv1vXzz74fxBWQWJ0VwYZ52Yv58/gBf+UsVHQ6ZO599j1/fdA4mg/LQvL/uOF//xzFcPkh5/RBfurwozNYKgghPm0AwS7lsTQ7ljjiCzoGysjIAerq7Aeh0wqLcVUSYtSTZYIHVR4TRi07qR5ZtdHUrSRrDw26Q+5EkO0lWH5EGbS0bZ8Zb+dIFihftqbeb+M2u0WXQh984AsBNm7LJS4sOi33hIsps4JuXL0cvSfyjopMf/L9a1eP23f+rxReQuWxlKltWaCt71KDX8fVLl2PUQWWPnzuffQ+nWykR85//PIrLB0vjDdy0Ne8kZ5p/9NhG+MoLFXQPT/RAHum289X/qcQRJk++EG0CwSxFr5O45yMlIcItSKcTluSt4pyl2vqiAUhLSyMtLQ0AndQP2E+0DCJJyv+X5eRoMrD8gmw93z8/BglFuH30sT1q232bovnoEr3mwgwALlmZyo8/lq8Kt4/+ShmXoGD7wVV5GDRYB3LrygX89KoVqnC79jfvAaiC7Xe3nkOMVXuxfvf/o5Z3Gvq4/bnSEOF2rMfB7c+VsaOul0ffDM/eo9q7SgWCOURH+3FuPX8pg77QZb5FS5aRqrPhcrmmeOX8RZIk8vLySElRsmmlE1ugSSfEW05ODtnZ2ss2drlc1NfXE+kf5v7zo5GAQZeyM8Q9G6JIlmw0NjYyPDwcXkPDRFC4AdjcipfkwtxkzQq2IEHhBjB0oh51doxes4IN4D8/tIKMOAst/S5uf66UHpsyMF95oZJBp5e89Gju3Bae7eC0e6UKBLOcrq4u6uvrKS8rJcEY6op3dzbQ2NhIWVmZJgOF/X4ZlzsGmdClPpkEbHaz5spagFJcNzc3F4BIv41rciDoU0s64YFcunSpJovrBjGOS3TS6yUktOd5HI9FFxpKYNTJ6NHePRQkI87KUzeUqMLt6icUD+SgSxFsT3y6mBhreMJShGgTCGYpiYmJGI1GVYD0nXCqjdUjaWlpmtvUOZglOjw8EjoYKL+OzyrVCn6/n87OTgLoCMiwPhV+dM5ouw893d3deL3a3Jd1x+Ee7vvbIQD0J5aIX6/uDolx0yLv1bby1b83hBw7OhjgzmffmzSrVCsEhdtYEiONYRVsIESbQDBrOXqsMeQLNtGqfNFI0qhWaWpqxuPR1h6bTqeH/kGXmnQwlmByQnuXHY9HWx5In89HZ/cQOgI4faEixOaRMeCnt9+mSdH21qE2Xn2vSo1he+Or5wKKeKtu7OSpfx3UpHALCrZgDNsrX1ZU/tjkBC0LN+e4OcQfALc3vAlOQrQJBLOUI3YTHj90OUEyRTB2T9bmESsBGY4Mg19jt/Hhrn7kQLsq2JYsUWJLgls06aR+HCMt9DvcYbMxHBxps9N61IXPKxNlDF3yizZJ+HwyXW0e9tdqq/DwkMONva2ey7LhztURfP/KXDWG7buXZnFbnswKyzA7ysMTWB4ufP4A33/1SEjSQbRFiWH7wUeWqcLt6Z11YbY0PBzptnP7c0rGftwJz9qgyzshOWGm0dZsPwuw2+1TLtvY7fZJjwu0yYdKsjluzGRRbiGpCaFxSB/blE+VN40LNq7FatJOLTKAxXFGjHrlCTgnJ4fMzEwAVqxYoWaVxphk4qzaWjZekhHB0hVmDMbJY7QMBomsRSZKlmkrps2s03O8QfEuLrY6aTp2TJ2DDYOtmAwSvd0+kjFPd5p5h0Gv4+fXFrE2wzIh6WBzbjo/vWoF5y+K4I6LV4bRyvAQFGzBpIPnP7cWgPRYs5qcEC7hJkTbDNLV1cW+ffs4NmbSCNLU1MS+fftob28Pk3WC2YYkSdyyZRkJ/n46OztD2qoqK7h1UyY5qdqquQVKrF9ERARRUVGqYANlvJYtW4bRaCQ5ORmLxRJGK2cei8VCSsrkm1wHiY+PIzpaW9eMxWpkzboMRkaUZa3W1lbKyspPtMq4nAFiY83kFaSFzcZwYXL4yev2II9MDCWIdgRY3usjEOblwHDw6JtH8Q251aSDaIviaXv0uiIyYs30d9n5w+7msNgmRNsMEow9am5uDhFuLS0tHDt2LKSP1hgeHiYQmHxyGBoa0lxQOYAsy9TX13P8uLLFzvLlywGIiYnB5/NRXl6uyfINNptS6sRut1NbW6teNz6fj4qKCrxeLwMDA5q7l9xuN/390y99Dg0Nac6j7/P58AVsmM06VbjZ7TYAXM4A1ggdRrMfm01b91IgIPO/Lx6i4/gwv3lkN0ODo+WDyg8e53+eK6PpaD/7dreE0crwcFVyJOf0u/jswriQpIPUGDOfTorknAEXl6WGpw6kEG0zSFZWFsuWLQMU4dbU1ASg/rtkyRIWLVoUHuPCSF9fH6WlpVRXV08Qbu3t7Rw8eJCjR49qTrh1dnaqgi03N1dd+isoKCA2Nhafz0dlZaXmSn7ExsZSUFCAJElqWRSAqqoqhoeHMRgMlJSUYDZra7nLarWSn58/5cbnRqORFStWaM7TFrweLBYLZnPoV541Qvk9Pz+fxMTEcJgXNnQ6iUs+ugBrhERfj4PfPLKb4SElDvTlFyqQZVi41ETJOu1s7RXE7VCWPl//31r+vXN0Z5FX/3GYst0tIIPLEZ6HQiHaZpixwq21tVU9rlXBBopHSZZlenp6QoRbZ2cnhw8fBpjSCzefSU1NJTU1ldzcXDIyMtTjBoOBoqIiEhISyM/P11zJD4Dk5GRVuHWf2NbLZrOpX9BaEyageOmPHj2Kx+PBNy571OeV8Xq9NDY2arIgs9VqZenSpZO2JSQkkpqaOsMWhR9ZlgngYv35VlW4/dcP3zrRBlmLDeSuMuJya+96Sc/2sGSF4mH7v78eYs87TQC893YjACtLzMQni5g2zZCVlTXhaXjhwoVhsib8JCUlUVhYiCRJ9PT0qEIt6EHJzMxk2bJlmtt+R6fTkZ+fHyLYgowVblolOTlZLSYbpLi4WJOCTUFiaHAEv0/GYFDulWBGrcGoZI/abR7N3UcAAwMDVFfXTNrW39/HkSNHNOfJlySJwsJCMhYksv58a0hbUqqe/GLziZ1HtOdp8/v9LMs3qcLt1f8dvXZWlpjJWmzE5xN7j2qGpqamCfE2kyUnaAmny0Vubi6SJNHb26seX7BgAQajUXNLgEGm+4LV4pfvWHw+n7p8HKS1tVWTXlmAwQEnsuxDf0Kw5efnh4hag0FCkgJ0ddjCZWJYUOI/KwgmHYxlbHJCV1d3GKwLL52dndhsNnze0FAChz1AbGwCTU1NuN3aKp0DkJeXh8FgYFl+qHMlMkZH1mIjJpNJXTGbaYRom2GamprUpIOxy6HjkxO0RN3RRo40NFBdf5T4+PiQtiHHCE2Njby7r1STYzMyMjKlCHG73ZocEyAkEcNgUEqeBGPcxiYnaAmLVcJkVgSbXq8P8TgajYrHwGCUiIrR1rTv88pUHRzB5QioMWzBuTeYnNDe4qW7Izyek3AhyzIdHR34fD4sVg/RsToSU5RQi4wsI8PDA6eU3DIfaWpqwu/347DJjH02HnEG8IwooQhtbW1hsU1bd2+YCQozUGLYgptaB2MtmpubaWxsDJt94WLPcR8DbtD5PbR3j04Qbh/YB3vxy/BGi/Y8bS6Xi/3793Po0KEJImR4eJi9e/fS0NCgOeE2XrCtWrUKUJ6OtSzcYmJi1AQMv99PWVmZ+oXr9XoxmUysXLlScwH3ZouBTVvSsEaOJh0E516z2YzZrCM9y8KK/KRwmjnjSJKE7EtksN+P0SSxYYuV4g1KmZzFyxUPU8tRmciI+OlOMy9JTU1FliEqRkfxBgu5RYonsmSjFZMZQEdy8vTldT4ohGibQSIiIpAkaULSwYIFC9SYrYiIiPAZGCZuPC+HY+5IBtxgMYBXVi5LiwH8MrzTLvGVD5dobjmwv78fj8dDb29viHCz2WyUlpbi9/vp6urS3NJxsNyHXq+npKSEqCgl9T4pKYmCggIABgcHwxZzEk4kyUJmVh5RUVF4PB4OHVL22rRYLCxclIdeH54yBeHE7/cTkJWg8fz8fDULG6CoqAiTyYReL2suQSMQkNnzTgv7/+3C6QicWD4fnWOP1I5QU+Gg9lBXGK0MD3ve7uTguy78fpnUDAOZCxVPdWy8Hs+IzLtv2qks7T3JWT4YtFVKPcwkJyezfv16IiMjJ7RlZWWRkJAwadt8p6mxkdWxDlrtyr6asaYAwbyc0m7YkiFztKaCxPXrNSXcoqOj0el0BAIBent7VdFWUVGhetdiYmLQ6bT17GUwGDAYDEiSpC77BTGbzeh0OoxGo+bGxen0UFp2HFmWyM7Oxm4fDZ5OSl5Iff0AAOvWZhITo63Cw0EBP/4BJxAIKKIuENCcx1qSYNO2WFqbR7BGhM6rJpOJzMUyKRlGluVpL7EnMclKb4+f/h4/yWmjMkmWZTrafDhsAeITwnMPaWtWmwVMJ8q0KNhAyZKUJMiOBrMhdPJYl6pMLlr7AgZFkK1evVr97H19fcBo+ZPExEQKCws1NzaSJKHT6RgZGaGsrIyREUXi22w2ysvLCQQCmiyDAj5AKZzb0uJAZtSr1trqACQknIC2ig4HAgE18auuri4keaW8vFwVcsHrSCvIsozDMURMnH5CNQO/34/FoiMmVkdPT0+YLAwfBksfF30kMkSwgTL3ZC8xcsGHI5F14Yn109ZsL5iVLFq0iJycHACs+olPuwkJCaxdu1ZTXrYgQeE2/rMnJCRoUrCBstS3evVqLBYLLpeLiooKQCmu6/P5iI2NpaioSE1Q0AoREREUrMwAgpX9E4mKWnLi/xJgZ/nyBGJitLX3aFDkB6mrq1Nji8cuoWvtXgqWFAIl5hGUFR8Y9UiazWZ1btYSbrd7yj18JUnCYJSw2cKTha2tq1QwK5Flma6+wRP/n9jeO2jT3JZE4xkv2rQoYMcyVrgFSxJoWbCB4ik6cuQIMEBQuNns3hOtDqCPpqYmnE5nmCwMD0ajkQ0bNoRcE+Mz/7RYjywQCJy4XkYZv8fxyMiIJvfDXrJkScjvhYWFE/qsWLFipswJQYg2Qdgpr23ANqBkiXa7Qy/JATfoAl7e2XtQczEnoGSJlpaWTsiE7OvrmzSrVEtYLJYJXoDc3FxNCjZQYv0iIiKIsFrJzgoVIKkpcURHRWGxWKbc5mo+Yzab2bBhw6TL5nl5eaSnp4fBqvAzfk4Nety05nUcz/gqDsGEnrE0NDTMlDkhaPsvI5gVNNjNtNigasBAasS47XcMFjodsKvLOMWr5y/jBVtw94PghDo+q1RrDA8Pq7tnBKmsrNRkMVBQarMVFhaSlbWCltbQTMiubi8pqUspLi7WrKj1+XyTeqi1ev9MV61g7JhYrdZJ+8xnxoeejBe3er1ezVSfaYRoE4Sda9cvJCk1g+JEP8hyyDJFssFNTGwM37pSeyU/bDZbSNJBMP6kqKhInVCGhoY0V/ID4OjRo5SWluLz+dQYLbPZjMvlYt++fXR1aa9MAUBPr5O6+n6UpAMHC7NH75mjRwfp6LSHz7gw4nA4OHjw4KRlYMYnJ2iJk235ptfrsVi0lWkMEBcXx7nnnquWExpLYmIimzdvDlt5LiHaBGGnu7ubSFcHyDKpqalqrEDw3wjfMC3HtLc3YEJCAiaTaUKWaHR0NKtXr0av15OSkqI5z0l7ezvNzc0EAgGsVqv6xBuMZfP5fFRXV4ctUDhcOBwjVFd3ERRsq1ZlqPUgJUkRa/X1fQwOaiumzefzTRBs42OW6urqQrbP0wKSJJGYmDjtUmhUVJQma4eCsuvBZLHULpcrrA/KQrQJwo7RaESSJFJTU8nPz1c9asHfAU3G4VitVtauXTtplmhMTAzr169n+fLlmvNAJicnq/XZXC6XWgoluCUPKF82Wiuho9fLGAw2VbAlJY1W+C9alY0k2dDpbBgM2loODNZiC5KXl0dmZiZAyAOP1orryrKs7hwy2RwiSRJDQ0Nh264pnDgcDsrKyiYVbU6nc8q2mUCINkHYiY+PZ+3atSGCLUhaWhrr1q1j8eLFmhMnoATbT/UkbLVaNTkmRqORc845R61sX1dXByibfgMsXryYtWvXai6Y2mKxsG7tCgoK0kIEG0BsbCzFRdmsLlk86ZLPfGbsEt/4pIO1a9eqwu1kS4XzDUmS1I3RJ1vFkGWZ6OhotQyIlmhoaAgRZeP3xHY4HGHbclJbs5pg1hIVFTWlAImOjtakOBFMjdFoJC8vj4yMjJDjy5YtY/HixZoTbKB8yTY2NtLU1KRmAQbx+/00NTXR1NSkucB7vV5PUVERWVlZE7JETSYTBQUFLFmyhLi4uPAYGCZkWebIkSNTJmiAElc7vgyIFvB4DQRlbHJyMitXrgRGhb0M+HzhKeCtvZktjHj9AR598wiDTu+ENpvbx8NvHGHEp72gcoDANPFq07XNdxwOx5TxEzabTXNxfkFaW1s5fvz4hG2sDAYDDQ0NmotPAqUgaH9/P3a7nbKyshDhdujQIQYHBxkcHNRcnTafz0dlZSWtra2qNzaIw+GgurqaxsZG+vvDU+E+XEiSpG56LssyBoOB1atXh/TR6/Vq1rqWcDqGkQCZCGQ5Sn0I9PujkDEjAYODA2GxTYi2GeSn/6rnmd0tfOG/y0KEm33Ex53Pl/PHPS384B+HpznD/MTm9nLrM6W8Wds9oa190MWnfrufyrahMFgWXux2O/v37+fgwYMThFtfXx8HDhygsrJSc8JtcHCQhoYG6uvraW5uDmmrra2ltbWVqqoqzW1LZLVaKSkpwWg0qsItOAZDQ0Po9XqKi4s1uTwaGxsLKMteY4VbZWUlXq8Xk8mkueXRQCCgLvFJkhRybSxYsABQPLThWgYMJ5mZKchYgSR6egPU1LQA4HAagBRkzCxevCAstgnRNoN8an0WiZEm6rvsfOG/yxhyKcLtqy9Wcej4MLFWAzduzA6zlTPPn/e1UdE2xLdeqg4Rbp1Dbm5/roz6LjsP/atec+Kku7sbnz+A3W4PEW79/f3qpvF9/f2TljGYz1gslpDlnKC3YGyWm8Fg1FxWLcCgy4clIV0Vbnv37gVOCJfULLps2ttZxO/309bRTa9LWRZuaGhQ4yC9Xi/+ADT0uBgcHAyjlTOPTqcjMTERUDxtvb296hw7MDDqRQrGjmqJhQsXEhWpAwYB6Okd+9DcR1yshdTU1HCYJkTbTLIkOZInbyhRhdvtfywFoKbdRqzVwG8+U8KKNG097QHcunkRlxek4gvIfOulanbVKRsUf/mFCtoH3WQnWPnFtas0F9fWJ8XyZDWM+BWvW3l5OTBanbumH/7caCUgaes2rm/pDBHwwQ2txy77eTweugaGJ7x2PtPRZ6O0tIyBjhaMsaFfKFGJaXS0NtFQU8XR9r4wWRgevAGJRxsbeLDj77Q6FM9jsI6fPwA/OrqfX3W/TptLW/MLQEFBAYsXLwagqalJrfLvdDoxmUysWbNmQhC+FqipqcHhcGA2uYGxgs2F0eBhaGhowhZgM4W2ZvtZQFC4WQw62odGl2+0KtgA9DqJH1yZrwq3b/9vLQAdQyNkJ1h56obVpMSYw2zlzJMSY6XTrefJQ4pwczgcaltNPzx7GBJjIzHqtXUbp6Wm8EoTOKdwMPa74dVWHQmx2rqfYiItDHjAoANHT2iZhoGu45j1MOiRSIjRVimUEdmFHHGIrUm5PN77/3AFRufd57pKSYzvYU1iIkcdtWG0Mjy8caCMf9UeIjVDWeoLJh0YjUaa3CP86d+7NBcDCSBFRnPY5aTP6QS6GRVuA7TbHdS6HCSEaa/aeTvb//jHP2bTpk1ERETMuqyg5GgzBn3oU11qjPaqTo8lKNyKs2JDjmtVsAEc7rThGPHTaoe3xpVK+nMD+GWobrfh8WkrG/Bo5yA72+FXleAeJ9x6XfBwBbzXEaBvWFt1t5q7+njqkExFL0gSyDJ4DcqSsU6ChkH4daVMTVNHeA2dYVzDXr6U8nk+HHM5FyaU8FTfqHDzmHq5NeEWro3/BObOmDBbOrMMOZx097lYbslnT2MTvjFZxU0OO1FyIiusK3n6re1htDI87G84xgprHkMBM3afE2gHoNftRDIkkGvN58Xdu8Ni27wVbR6Ph2uuuYY77rgj3KaEYHMrSQf2kdDA8vHJCVqka9hN51DovpFVx7WXgBBkc04ixVmx5MTCRZmhbTfngkmnLC1bjOFJPQ8Xa3PS2Lw0jm4X/GXcCsXvahUP3CfXZZKRoK2A+5z0BNanSvypHlW4GX2Kl+ToEPy+FgoSoWSptjZHT0+Op9+jCPgLo7ex0lLCj7r+G4Ab4j+DRWfG7nFx7uqccJo548RGRtDl6cUv+1lszqHF61eFW4w+jWh9ND3eblYtXBZmS2eeEZ8Hd8DNAlMmQwEzjhNxw5IhniRDEsP+YSJ04dmTdd6Ktu9///vcc889FBYWhtsUlaBgCyYd/P4mJb06IcKoJidoVbi1D7q4/bkyOodHWBA36lkbn5ygJSLNBn54WRa35oNRD4dPxAa7fLA0Fr63ycxHV4UnGDacGHQSt5dEsjkdPha6GxGfWQ6XZ8PHciM0FwMJcE2umc3psHucM21fF6xKhBtWmpDQVkKPz+cjM8pBu10p6XFh9DZuS/gsgCrYzPoe/B7tLQPeeell1DprVOHW51dWfKL0UfR4u4mMlNlSkBdmK2eekqRsWl3HVeHmRvHCJhoSGfYPM+ixUZwenuxR7aVXTcHIyEhIiYDhYSWI2ev1TihUeab8/LXD1HcMkRxp4JfXFrIowUwD8ItrVnLvi9U09dh44J81/Oiq/LPyfnOFziE3X36hgt7hEZYmWvjFJwoo3bOTS/OTeK2ml+/9/RCyP5ctK5LDbeqMMjAwwOHqKvQS1PbDX4/I3J0Hzx+W+XQuWAxu9u/fT3FxMXq9drxtQ0NDdBxv44pFijepwy4TDdhGZDIiIT0C6uvriY+P19T2Z5IkUVRUhCmmjZ72NmQZNWHjmqUyUcnpFC7NxGAwnLU5ba6QlJSEy93OuwMtbIorZKEpE6e3nlZ3C/i85CREER0dralxkWWZ0tJSCiKiqXHUkBeZT7IhCedIP33eHggMEzFioqWlZUIR6/lOVlYcTmcfRxxHWBqZR4I+DifdOPwOhj3HybZGk5ERf9aul9M5jyTP8zoKzzzzDHffffdJ07nvv/9+vv/97084/vzzz2t2w1yBQCAQCAQfLE6nk0996lMMDQ0REzN9bOWc8rRNJazGsn//ftauXXva5/7Wt77Fvffeq/4+PDxMVlYWl1xyyUkH8XSQZVldtvF6vWzfvp2LL74Yo9EY0qYlZFnmxYPtbFuRTHK0KWRcdHoDf9rbyifWZBBhmlOX6/vm3w29PPjPGuxeJenApJP5ar6Dn9dE4g1IxFsgJsLE0zetw6yhuLaatn5qqw/hCyhxWr7A6LjEmiVuzYM+j8Rlm9eRoqEEn5buQeqqKzHrlRi25+pAQhmbppFIChIlfAHIWJpLblZ4Mt/CgcPj45o/P0FCTJcawybLfpyOeiIil/O2Yzdv9FXw43O+ynnLtOVRAnjx7beJ8McTpY8KGZcWTzMfWreWpLjYk59knlFVVUV9RyeSIZ5EQ2LIuHR4u4jVjbAsK4tly85OvF9wZe9UmFPfgnfddRfXXXfdtH0WLVp0Ruc2m82YzROzFI1G44Stcs42M/Ees51Pb1w04VhwXG49f+nMGzQLWJWdgEcy4vIrQbDfvGw5tJWSmx7LgVYbXU44Ly+FqAjtCBOAhUlR3H9EoselJB3cck4GOOtZvyiOt44M8+tDsCBGz42xVowaKrC7MC2RN/brIRDg97WwOlXPzz+9ge2vv8ZfjkgEkIg2SWzNSsOoIZGvlz2kxQxzXcJNagzbxnVZ7Pl3PZKkZ2v0VgLIeI2dGI0Lw23ujPL8WzuICCQSbVCSDlLTosABAWCRZRn/PHCQj23aSGKstjJre/wSkjFRTToYMdqwAiOyjwXmLI572pAjIs/a9/bpnGdOJSIkJSWRm5s77Y/Foq0vMMH8ZffRfoZcimD77kdy+fAqpTL5z64poDgrFhnYUdeD26ut/WprO+w02xTB9tmNmdy+RRH1P/hYIVty4uhzQ22vn16btraxqmvt5reHAjxdowi2R2/ejNGgiLPzM438qR6eqJLZe7j5JGeaX9iHPNyYeL0q2M7buJj4GCXkpW/EBsAF0dtwt2qrtNCQw4nBF6FmiaZlxLI5PxeAWme9mpzwp3d2hNnSmaejb2BUsJkcfPzcjQAc97apyQnv1FSHxbY5JdpOh5aWFsrLy2lpacHv91NeXk55eTl2uz3cpgkEp8Tlhalckp/Cdz+Sy1Ulo8s2ESYDj11fxIbF8Xz/ijzNlfw4Z1kK169N57MbM7nrwmVqSIFRr+Oha4vZtiyeb16+nPR4bRWRXbkojc+simJtWqhgA7j/2vVsyzbykWVmzi9cMs1Z5h/pyfE4dB6GTwi2hNjR6+Lqi1fROzJMn9vOh84vCKOVM09sZAR9vkHaPcdJy4hla+FoAtydl3+Iaudhmkea+fCaDWG0MjxYrCY6vO2MmBxct2WzevyWiy+i1dtKu+c4eVmLwmLbvF07+O53v8uzzz6r/l5SUgLAjh072Lp1a5isEghOHYNOxwNXr5w0zjHSbODxTxdrMgZSkiS+dlmu+v+xGPU6/uuT2hwXgLuvWI/f75+QTazX63nw05s0lWU8lqu2FeLz+Sbdj/aTl5dM2TbfueNDl+J2uyddobrno1dM2TbfuW7LZlwuF1brxFpsX7j8sinbZoJ562l75plnkGV5wo8QbIK5xHTiQ6vCBJTPPtXn1/K4AFMKM60KtiDTiTItCrYg04kyLQq2INOJsnAJNpjHok0gEAgEAoFgPiFEm0AgEAgEAsEcQIg2gUAgEAgEgjmAEG0CgUAgEAgEcwAh2gQCgUAgEAjmAEK0CQQCgUAgEMwBhGgTCAQCgUAgmAMI0SYQCAQCgUAwBxCiTSAQCAQCgWAOIESbQCAQCAQCwRxAiDaBQCAQCASCOYAQbQKBQCAQCARzACHaBAKBQCAQCOYAQrQJBAKBQCAQzAGEaBMIBAKBQCCYAwjRJhAIBAKBQDAHEKJNIBAIBAKBYA4gRJtAIBAIBALBHECINoFAIBAIBII5gBBtAoFAIBAIBHMAIdoEAoFAIBAI5gBCtAkEAoFAIBDMAYRoEwgEAoFAIJgDCNEmEAgEAoFAMAcQok0gEAgEAoFgDiBEm0AgEAgEAsEcQIg2gUAgEAgEgjmAEG0CgUAgEAgEcwAh2gQCgUAgEAjmAEK0CQQCgUAgEMwBhGgTCAQCgUAgmAMI0SYQCAQCgUAwBxCiTSAQCAQCgWAOIESbQCAQCAQCwRzAEG4DZiuyLAMwPDz8gb2H1+vF6XQyPDyM0Wj8wN5nriHGZXLEuEyOGJepEWMzOWJcJkeMy+R80OMS1BlB3TEdQrRNgc1mAyArKyvMlggEAoFAIJjv2Gw2YmNjp+0jyaci7TRIIBCgvb2d6OhoJEn6QN5jeHiYrKwsWltbiYmJ+UDeYy4ixmVyxLhMjhiXqRFjMzliXCZHjMvkfNDjIssyNpuNjIwMdLrpo9aEp20KdDodmZmZM/JeMTEx4gaZBDEukyPGZXLEuEyNGJvJEeMyOWJcJueDHJeTediCiEQEgUAgEAgEgjmAEG0CgUAgEAgEcwAh2sKI2Wzme9/7HmazOdymzCrEuEyOGJfJEeMyNWJsJkeMy+SIcZmc2TQuIhFBIBAIBAKBYA4gPG0CgUAgEAgEcwAh2gQCgUAgEAjmAEK0CQQCgUAgEMwBhGgTCAQCgUAgmAMI0XaWeOCBB1i3bh3R0dGkpKRw1VVXUVdXF9JHkqRJf372s59Ned5nnnlm0te43e4P+iOdFZ544glWrVqlFiXcuHEjr776qtouyzL3338/GRkZWK1Wtm7dSnV19UnP+7e//Y38/HzMZjP5+fm8/PLLH+THOOtMNy5er5f77ruPwsJCIiMjycjI4MYbb6S9vX3ac871awVOfr3cfPPNEz7fOeecc9LzzufrBbQ5t0zGAw88gCRJ3H333eoxrc4xYxk/LlqeY8Yy2fUy2+cYIdrOErt27eLOO+/kvffeY/v27fh8Pi655BIcDofap6OjI+Tn97//PZIk8fGPf3zac8fExEx4rcVi+aA/0lkhMzOTBx98kAMHDnDgwAEuuOACrrzySnXSfOihh/jFL37Br371K/bv309aWhoXX3yxuvfrZOzZs4dPfvKT3HDDDVRUVHDDDTdw7bXXsnfv3pn6WO+b6cbF6XRSWlrKd77zHUpLS3nppZeor6/niiuuOOl55/K1Aie/XgAuu+yykM/3yiuvTHvO+X69gDbnlvHs37+fp556ilWrVoUc1+ocE2SycdHyHBNkqusFZvkcIws+ELq7u2VA3rVr15R9rrzySvmCCy6Y9jx/+MMf5NjY2LNsXXiJj4+Xn376aTkQCMhpaWnygw8+qLa53W45NjZW/s1vfjPl66+99lr5sssuCzl26aWXytddd90HZvNMEByXydi3b58MyM3NzVO+fj5eK7IcOi433XSTfOWVV57W67V4vWhtbrHZbPKyZcvk7du3y1u2bJG/8pWvyLIsa36OmWpcJkNLc8x04zLb5xjhafuAGBoaAiAhIWHS9q6uLv75z39y6623nvRcdrudhQsXkpmZyUc+8hHKysrOqq0zhd/v54UXXsDhcLBx40YaGxvp7OzkkksuUfuYzWa2bNnC7t27pzzPnj17Ql4DcOmll077mtnM+HGZjKGhISRJIi4ubtpzzZdrBaYel507d5KSksLy5cv53Oc+R3d397Tn0dr1osW55c477+TDH/4wF110Uchxrc8xU43LZGhpjjnZuMzmOUZsGP8BIMsy9957L5s3b6agoGDSPs8++yzR0dFcffXV054rNzeXZ555hsLCQoaHh3nkkUc499xzqaioYNmyZR+E+WedqqoqNm7ciNvtJioqipdffpn8/Hz1gk5NTQ3pn5qaSnNz85Tn6+zsnPQ1nZ2dZ9/4D5CpxmU8brebb37zm3zqU5+adrPi+XCtwPTjcvnll3PNNdewcOFCGhsb+c53vsMFF1zAwYMHp6xWrrXrRUtzC8ALL7xAaWkp+/fvn9AW/BtrcY6ZblzGo6U55mTjMuvnmLPuuxPIX/ziF+WFCxfKra2tU/ZZsWKFfNddd532uf1+v1xUVCR/6Utfej8mzigjIyNyQ0ODvH//fvmb3/ymnJSUJFdXV8vvvvuuDMjt7e0h/W+77Tb50ksvnfJ8RqNRfv7550OO/fd//7dsNps/EPs/KKYal7F4PB75yiuvlEtKSuShoaHTOv9cvFZk+dTGJUh7e7tsNBrlv/3tb1OeT0vXiyxra25paWmRU1JS5PLycvXY2OUurc4xJxuXsWhpjjmdcQky2+YY4Wk7y3zpS1/i//7v/3j77bfJzMyctM8777xDXV0df/nLX077/DqdjnXr1tHQ0PB+TZ0xTCYTOTk5AKxdu5b9+/fzyCOPcN999wHKU0p6errav7u7e8JTy1jS0tImPMGc7DWzkanG5cknnwSUDK9rr72WxsZG3nrrrWmfgCdjLl4rcPJxGUt6ejoLFy6c9jNq5XoB7c0tBw8epLu7mzVr1qjH/H4/b7/9Nr/61a/UDH6tzTEnG5eRkRH0er3m5phTHZexzLY5RsS0nSVkWeauu+7ipZde4q233mLx4sVT9v3d737HmjVrKCoqOqP3KS8vD5mA5hqyLDMyMsLixYtJS0tj+/btapvH42HXrl1s2rRpytdv3Lgx5DUAr7/++rSvmQsExwVGBVtDQwNvvPEGiYmJZ3S+uX6tQOi4jKevr4/W1tZpP6MWrpcgWptbLrzwQqqqqigvL1d/1q5dy6c//WnKy8tZsmSJJueYk43LWMGmpTnmVMZlPLNujjnrvjuNcscdd8ixsbHyzp075Y6ODvXH6XSG9BsaGpIjIiLkJ554YtLz3HDDDfI3v/lN9ff7779f/te//iUfPXpULisrkz/72c/KBoNB3rt37wf6ec4W3/rWt+S3335bbmxslCsrK+X/+I//kHU6nfz666/LsizLDz74oBwbGyu/9NJLclVVlXz99dfL6enp8vDwsHqO8WPy7rvvynq9Xn7wwQfl2tpa+cEHH5QNBoP83nvvzfjnO1OmGxev1ytfccUVcmZmplxeXh5yPY2MjKjnmG/XiixPPy42m03+6le/Ku/evVtubGyUd+zYIW/cuFFesGCBpq+XIFqbW6Zi/HKXVueY8YwdFy3PMeMZOy5zYY4Rou0sAUz684c//CGk35NPPilbrVZ5cHBw0vNs2bJFvummm9Tf7777bjk7O1s2mUxycnKyfMkll8i7d+/+AD/J2eWWW26RFy5cqNp/4YUXhnzRBAIB+Xvf+56clpYmm81m+fzzz5erqqpCzjF+TGRZll988UV5xYoVstFolHNzc6eNN5iNTDcujY2NU15PO3bsUM8x364VWZ5+XJxOp3zJJZfIycnJstFolLOzs+WbbrpJbmlpCTmH1q6XIFqbW6ZivGjT6hwznrHjouU5Zjxjx2UuzDGSLMvy2fffCQQCgUAgEAjOJiKmTSAQCAQCgWAOIESbQCAQCAQCwRxAiDaBQCAQCASCOYAQbQKBQCAQCARzACHaBAKBQCAQCOYAQrQJBAKBQCAQzAGEaBMIBAKBQCCYAwjRJhAIBAKBQDAHEKJNIBAIBAKBYA4gRJtAIBAINMfHPvYx4uPj+cQnPhFuUwSCU0aINoFAIBBoji9/+cv88Y9/DLcZAsFpIUSbQDBH2bp1K3ffffesOc9Mc6Z2h+vzztTfazb/Pbdu3YokSUiSRHl5eVht2bZtG9HR0ZO23Xzzzaqdf//732fWMIFgGoRoEwjCzG9+8xuio6Px+XzqMbvdjtFo5Lzzzgvp+8477yBJEvX19bz00kv88Ic/nGlz5wyzWbxomc997nN0dHRQUFAQblOm5JFHHqGjoyPcZggEEzCE2wCBQOts27YNu93OgQMHOOeccwBFnKWlpbF//36cTicREREA7Ny5k4yMDJYvXx5OkzWHx+PBZDKF24x5QUREBGlpaR/4+6xZs4aRkZEJx19//XUyMjKmfW1sbCyxsbEflGkCwRkjPG0CQZhZsWIFGRkZ7Ny5Uz22c+dOrrzySpYuXcru3btDjm/btg2Y6EnaunUrX/7yl/nGN75BQkICaWlp3H///SHv5XA4uPHGG4mKiiI9PZ2f//znJ7Xvr3/9K4WFhVitVhITE7noootwOBzqe951113cddddxMXFkZiYyLe//W1kWVZfL8syDz30EEuWLMFqtVJUVMRf//rXkPc4WZ/Ttfvmm29m165dPPLII+oyV1NTk9oeCASmHafg57r33ntJSkri4osvPqXPMd1Yncr7joyM8OUvf5mUlBQsFgubN29m//79U37OM/l7TkYgEOAnP/kJy5Ytw2KxkJqayg033HBG5zoTmpqakCSJl156ifPPPx+r1cqaNWtoampi586drF+/noiICLZt20Z/f/8p2Xzw4EEOHTo04edkgk0gmM0I0SYQzAK2bt3Kjh071N937NjB1q1b2bJli3rc4/GwZ88eVbRNxrPPPktkZCR79+7loYce4gc/+AHbt29X27/+9a+zY8cOXn75ZV5//XV27tzJwYMHpzxfR0cH119/Pbfccgu1tbXs3LmTq6++OkSUPfvssxgMBvbu3cujjz7KL3/5S55++mm1/dvf/jZ/+MMfeOKJJ6iuruaee+7hM5/5DLt27TrlPqdr9yOPPMLGjRvVpbiOjg6ysrJOeZzGfq53332XJ5988qQ2nupYTfe+3/jGN/jb3/7Gs88+S2lpKTk5OVx66aWqUBnP6Y7LVDzwwAM8//zzPPXUU9TV1fHSSy+xdevW0z7PmRKMb3v88cf5yU9+wp49e+jr6+OGG27gpz/9Kb/+9a/ZuXMnVVVV/O53v5sVNgsEYUEWCARh56mnnpIjIyNlr9crDw8PywaDQe7q6pJfeOEFedOmTbIsy/KuXbtkQD569Kgsy7K8ZcsW+Stf+Yp6ji1btsibN28OOe+6devk++67T5ZlWbbZbLLJZJJfeOEFtb2vr0+2Wq0h5xnLwYMHZUBuamqatH3Lli1yXl6eHAgE1GP33XefnJeXJ8uyLNvtdtlisci7d+8Oed2tt94qX3/99afU50zsDto2WfvJxinYp7i4WP39VD7HqYzVdO9rt9tlo9Eo/+lPf1LbPR6PnJGRIT/00EMTPteZjstknHfeefI3vvGN03rNmTDV3+T++++X4+Pj5Z6eHvXYzTffLGdnZ8t2u109dtlll8n33nvvWbH5kksukZOSkmSr1SovWLBA3rdv34Q+gPzyyy+f8XsIBGcbEdMmEMwCtm3bhsPhYP/+/QwMDLB8+XJSUlLYsmULN9xwAw6Hg507d5Kdnc2SJUumPM+qVatCfk9PT6e7uxuAo0eP4vF42Lhxo9qekJDAihUrpjxfUVERF154IYWFhVx66aVccsklfOITnyA+Pl7tc8455yBJkvr7xo0b+fnPf47f76empga3283FF18ccl6Px0NJSQnASfucid0nY7pxCrJ27Vr1/6fyOU5lrE729/F6vZx77rlqu9FoZP369dTW1k74DGdzXK644gruu+8+ysrKuPrqq7n22mtJSEgA4NixY1RXV/PRj34UgL///e/s2rWLX/7yl6f9PlNRXl7OFVdcQVJSknqspaWF66+/nsjIyJBjH/7wh09q86nw2muvnTX7BYKZQiyPCgSzgJycHDIzM9mxYwc7duxgy5YtAKSlpbF48WLeffddduzYwQUXXDDteYxGY8jvkiQRCAQAQpbpThW9Xs/27dt59dVXyc/P57HHHmPFihU0Njae0uuD7/3Pf/6T8vJy9aempkaNBztZnzOx+2RMN05BxoqFU/kcpzJWp/L3GSuAg8fHHxvb/2zwta99jdraWi666CIee+wxcnJyVLtfffVVDh8+rPatrKykqKjorL03QEVFhZqEE6S8vJwNGzaov7vdburr6ykuLj6pzQLBfEWINoFglrBt2zZ27tzJzp07Q2JztmzZwmuvvcZ77703bTzbycjJycFoNPLee++pxwYGBqivr5/2dZIkce655/L973+fsrIyTCYTL7/8sto+9nzB35ctW4Zeryc/Px+z2UxLSws5OTkhP8EYs5P1OVO7TSYTfr//lMdnOk7lc8DJx2o6cnJyMJlM/Pvf/1aPeb1eDhw4QF5e3qT9z2RcpmL58uV84xvfoLS0FKfTSU1NDbt27eLb3/42v/3tbykpKcHlclFZWUl9fT0bN25k4cKF1NTUnNH7BRkeHqapqUn1WAI0NzfT398fcqy6uhq/3x8iGCezWSCYz4jlUYFglrBt2zbuvPNOvF6v6mkDRbTdcccduN3u9yXaoqKiuPXWW/n6179OYmIiqamp/Od//ic63dTPbnv37uXNN9/kkksuISUlhb1799LT0xMiIlpbW7n33nv5/Oc/T2lpKY899piaxRgdHc3XvvY17rnnHgKBAJs3b2Z4eJjdu3cTFRXFTTfddEp9TtdugEWLFrF3716ampqIiooiISHhpK+ZilOx8VTGajoiIyO54447+PrXv05CQgLZ2dk89NBDOJ1Obr311gn9z+TvORkPPfQQqamprFu3Dr1ez9NPP018fDybNm0iPj6egoICnn/+eVWcVlZW8qEPfYif/OQn/OhHP+If//gH+fn5p/WeY6moqECn04UsHZeXlxMXF8eiRYtC+i1ZsoTo6OhpbRYI5jNCtAkEs4Rt27bhcrnIzc0lNTVVPb5lyxZsNhtLly4N8eqcCT/72c+w2+1cccUVREdH89WvfpWhoaEp+8fExPD222/z8MMPMzw8zMKFC/n5z3/O5Zdfrva58cYbcblcrF+/Hr1ez5e+9CVuv/12tf2HP/whKSkpPPDAAxw7doy4uDhWr17Nf/zHf5xyn9O1G5Tls5tuuon8/HxcLheNjY0hIuB0OZmNpzJWJ+PBBx8kEAhwww03YLPZWLt2La+99lpIXNxYTmVcnnnmGT772c9OuZzqdrv5yU9+QktLC1FRUZx77rm89dZb6nu2tbWp153T6SQQCHDLLbcAijdzbD2zk73XZFRUVJCbm4vValWPlZWVTViCraioUJdGT2azQDBfkeQPImBEIBBogq1bt1JcXMzDDz8cblMEU3D//fery+6nS1tbG9ddd526ZLtv3z5+8Ytf8MILLwCKYL/99tvZvHnzKb3XXLteJEni5Zdf5qqrrgq3KQIBIGLaBAKBYF7z2muv8dBDD53RaxsbG0OK0VZWVlJYWKj+XlVVFbId1am81+OPP05UVBRVVVVnZNNM8IUvfIGoqKhwmyEQTEAsjwoEAsE8Zs+ePWf82oKCAhoaGigsLOTFF1+kqqqKCy+8EACfz4fdbicuLu6U3+tPf/oTLpcLgOzs7DO264PmBz/4AV/72tcApSyLQDBbEMujAoFAIBAIBHMAsTwqEAgEAoFAMAcQok0gEAgEAoFgDiBEm0AgEAgEAsEcQIg2gUAgEAgEgjmAEG0CgUAgEAgEcwAh2gQCgUAgEAjmAEK0CQQCgUAgEMwBhGgTCAQCgUAgmAMI0SYQCAQCgUAwBxCiTSAQCAQCgWAOIESbQCAQCAQCwRxAiDaBQCAQCASCOYAQbQKBQCAQCARzgP8P4e2zQTI10z4AAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# scatter plot normalised residual as a function of threshold\n", - "\n", - "df = data[\"error_norm\"].reset_index([\"threshold\", \"country_iso_a3\"])\n", - "colours = [country_cmap[value] for value in df.country_iso_a3.values]\n", - "\n", - "f, ax = plt.subplots(figsize=(8,6))\n", - "ax.scatter(df.threshold, df.error_norm, c=colours, label=\"Country\", marker=\"x\")\n", - "handles = [Line2D([0], [0], marker='o', color='w', markerfacecolor=v, label=k, markersize=8) for k, v in country_cmap.items() if isinstance(k, str)]\n", - "ax.legend(title='Country', handles=handles, fontsize=9, loc=\"upper right\")\n", - "ax.grid()\n", - "ax.axhline(0, ls=\"--\", c=\"cornflowerblue\")\n", - "ax.set_xlabel(r\"Wind speed threshold, $s_{th}$, $[m s^{-1}]$\")\n", - "ax.set_ylabel(r\"Normalised residual, $\\mathrm{\\frac{p_{d,mod} - p_{d,obs}}{p_{d,obs}}}$\")\n", - "ax.set_title(\"Population disconnected, $p_{d}(s_{th})$, residuals\")\n", - "ax.set_ylim(-1.5, 4)\n", - "\n", - "plt.subplots_adjust(right=0.8)\n", - "\n", - "# N.B. a couple of values are more more than 400% out, therefore out of plot area\n", - "# -1, worst possible score (model 100% underestimated)\n", - "# 0, perfect score\n", - "# + valued, progressively greater model overestimate\n", - "\n", - "# N.B. our residuals, i.e. (mod - obs) / obs are not symmetric about 0 (-1 is the worst possible score)\n", - "# but we plot this measure as a) it's normalised, so can compare across scales\n", - "# and b) something like sign(mod - obs) * mod / obs, would give a perfect 0 for mod = 0 " - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "fa3130db", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# as above, but only plot each storm-country pair once, at the threshold with minimum absolute error\n", - "\n", - "measure = \"error_norm\"\n", - "\n", - "results = []\n", - "for event_iso, df in data.groupby([\"event_id\", \"country_iso_a3\"]):\n", - " min_error_mask = df.error_abs == df.error_abs.min()\n", - " try:\n", - " # only store the threshold, error pair if there's only a single minima\n", - " threshold, = df[min_error_mask].index.get_level_values(\"threshold\")\n", - " statistic, = df.loc[min_error_mask, measure]\n", - " results.append((threshold, *event_iso, statistic))\n", - " except ValueError:\n", - " continue\n", - " \n", - "df = pd.DataFrame(results, columns=[\"threshold\", \"event_id\", \"country_iso_a3\", measure])\n", - "\n", - "f, ax = plt.subplots(figsize=(6,4))\n", - "ax.scatter(\n", - " df.threshold,\n", - " df.error_norm,\n", - " c=[country_cmap[value] for value in df.country_iso_a3]\n", - ")\n", - "ax.set_ylabel(r\"Normalised residual, $\\mathrm{\\frac{p_{d,mod}(s_{th}) - p_{d,obs}}{p_{d,obs}}}$\")\n", - "ax.set_xlabel(r\"Wind speed threshold, $s_{th}$, $[m s^{-1}]$\")\n", - "ax.set_title(\"Population disconnected, $p_{d}$, residuals,\\nfor threshold, $s_{th}$, with $min(abs(p_{d,mod}-p_{d,obs}))$\")\n", - "ax.set_ylim(-1.1, 1)\n", - "ax.set_xticks(thresholds)\n", - "ax.grid()\n", - "handles = [\n", - " Line2D([0], [0], marker='o', color='w', markerfacecolor=v, label=k, markersize=8)\n", - " for k, v in country_cmap.items() if isinstance(k, str)\n", - "]\n", - "ax.legend(handles=handles, ncol=int(len(handles) / 2), fontsize=7, loc=\"lower right\")" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "b0ba11bc", - "metadata": {}, - "outputs": [], - "source": [ - "def plot_residual_distribution_by_threshold(*, measure: str, x_label: str, x_min: float, x_max: float, bin_width: float, target: float = None):\n", - " n = len(thresholds)\n", - " ncols = min([n, 4])\n", - " nrows = (n // ncols) + (n % ncols)\n", - " f, axes = plt.subplots(ncols=ncols, nrows=nrows, figsize=(3 + 2.5 * ncols, 2 + 2.25 * nrows), squeeze=False)\n", - " \n", - " n_bins = int((x_max - x_min) / bin_width + 1)\n", - " bins = np.linspace(x_min, x_max, n_bins)\n", - "\n", - " max_ylim = 0\n", - " for row in range(nrows):\n", - " for col in range(ncols):\n", - "\n", - " i = col + (row * ncols)\n", - " ax = axes[row, col]\n", - " if i < n:\n", - " threshold = thresholds[i]\n", - " residual = data.loc[threshold, :, :][measure]\n", - "\n", - " ax.grid()\n", - "\n", - " # distribution\n", - " ax.hist(\n", - " residual,\n", - " bins=bins,\n", - " alpha=0.5,\n", - " label=\"Dist.\",\n", - " facecolor=wind_cmap[threshold]\n", - " )\n", - "\n", - " # rug plot\n", - " ax.plot(residual, np.zeros(len(residual)), 'b|', ms=15, alpha=0.5, label=\"Data\")\n", - "\n", - " # average measures\n", - " mean = np.nanmean(residual)\n", - " median = np.nanmedian(residual)\n", - " ax.axvline(median, ls=\"--\", c=\"red\", label=r\"$p_{50}$\")\n", - " ax.axvline(mean, ls=\"-\", c=\"green\", label=r\"$\\mu$\")\n", - "\n", - " # target\n", - " if target is not None:\n", - " ax.axvline(0, ls=\"--\", c=\"cornflowerblue\", label=\"Target\")\n", - "\n", - " ax.set_xlim(x_min, x_max)\n", - " _, max_y = ax.get_ylim()\n", - " max_ylim = max([max_ylim, max_y])\n", - "\n", - " ax.set_title(f\"$s_{{th}} = {threshold} \\ m s^{{-1}}$\", size=10)\n", - " props = dict(boxstyle='round', facecolor='wheat', alpha=0.35)\n", - " ax.text(\n", - " 0.95,\n", - " 0.95,\n", - " \"\\n\".join([f\"$p_{{50}}$ = {median:.2f}\", f\"$\\mu$ = {mean:.2f}\"]),\n", - " transform=ax.transAxes,\n", - " fontsize=8,\n", - " verticalalignment='top',\n", - " horizontalalignment='right',\n", - " bbox=props\n", - " )\n", - "\n", - " # disable any axes we don't need\n", - " else:\n", - " ax.set_axis_off()\n", - "\n", - " # set a common y range for all subplots\n", - " for row in range(nrows):\n", - " for col in range(ncols):\n", - " i = col + (row * ncols)\n", - " ax = axes[row, col]\n", - " if i < n:\n", - " ax.set_ylim(0, max_ylim)\n", - "\n", - " handles, labels = plt.gca().get_legend_handles_labels()\n", - " by_label = dict(zip(labels, handles))\n", - " f.legend(by_label.values(), by_label.keys(), ncol=5, bbox_to_anchor=(0.68, 0.93))\n", - "\n", - " f.supxlabel(x_label)\n", - " f.supylabel(\"Frequency\")\n", - " f.suptitle(\"Population disconnected, $p_{d}(s_{th})$, residuals\")\n", - "\n", - " plt.subplots_adjust(bottom=0.1, top=0.82, left=0.08, right=0.87, hspace=0.3, wspace=0.25)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "84279603", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# plot residual distributions by threshold\n", - "plot_residual_distribution_by_threshold(\n", - " measure=\"error_norm\",\n", - " x_label=r\"Normalised residual, $\\mathrm{\\frac{p_{d,mod} - p_{d,obs}}{p_{d,obs}}}$\",\n", - " x_min=-1,\n", - " x_max=4,\n", - " bin_width=2/5,\n", - " target=0\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.8" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/validation/undesa_pd_2022_hh-size-composition.xlsx b/validation/undesa_pd_2022_hh-size-composition.xlsx deleted file mode 100644 index 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zB{-*9wUXJTrYosM)yw_v$E$tg3ij{h(x=zmUwcqrw`VoI@cg*B+q?e!2vVW{sbHN2 zc|3bT6-fgk8WBjr{b@FjoEnQ%u* z*mu{&YL95yXmn;}0}UuMY3{GF3*^&}RD5ZpbT z$HIt;>Byli2%u&?YTGUl*t9ODKi@(xFA(8mjws4mIHE#GeJzDEW}HV*k<1#$tLfHA ze&C{O=lpB~yfG+yYezzS4>fm}A$9S>i5TQ|D|&*(JW7nZysAN?)9d{?xn-C$js~h- z-@Q4r>??e$)zy&SD*W$Qpp!~X*7tv5!Ov}w|6#!&&Ht|iV!uFZ-HV zDq>a|cZ*XDz5`EOQpRXZL&{>^x1LUKIZWow~XHnu~mu%k#A<+l}Sm7gT{%WuACfd%aOhlCRk8s0o z_)s$|?G!Je<{00H>Zez~qk-2C@WTHa4gRvu_#b8PClCIjfx%B2IR8O|F&YpJpxf}o z9X=b5X&h+$NdtjDXmAy_-cm+PPe6mamx+ZzC9W*72C}rhZ3od{)>vK2d?OGcY|~=a zZ^N>f@f?k{yo`dgCVZ=7;Rq`_6@N7Sz_N@N2CRKF|L<2yS=*0zT<&p;0&N(Z%_ajkW8ciH7O$aUeFss8#L|w!-e8MllEIXTW1qnXFU}UdlM(!KL#QS z(*FcNf7fXO4gy#Qja@(*=Wpo&^cwo})$&u9{F+gJRZ6`Jbc-bD$$#vm|CJa)4p{$X zGh}FIXZ5?M+Hr-w76v^v5efjn`zt5tFFa5oK$-u1u$!Hu)&GY0Z6WgP5l6K_7(zsU z`h5KhDjV_Ng>W)AF>(Hv$W78!O5^yqu`wPkf_HR*scF!u0d|w^j0M%=y2n#s2i ze?|D!lkZ;$6kmTL{M#Vw@1|IPqWst1MgKxsSpSLgtFO^ti}9-+++P4Th_8NWia+`K zlN^8P-CqHJH7)xK&t2@E@jIzZU18Hd24(1pru3 zUj5Eu>Q{h&+8+HK01x$7fWIt}ent7G!Oh=Mtk8Z%`EAGhr)9|B0U$7b1^8Kv-=h4} zhT-oh?=gQx`EAer=d$qM0b)pg1^8Kv-=h3;rSR`4-DIx-|FLfPYi0g(8RqZV3n>4V z{a=eRzvlkuME38wb7}sT`_HMz@AS?;Cn~WNT*`6fK)T!e*v9RDg*!k From 6474489529c0b846a48286174796ab4b80acdc6d Mon Sep 17 00:00:00 2001 From: Fred Thomas Date: Mon, 22 Jan 2024 16:54:55 +0000 Subject: [PATCH 3/5] Collate outage sizes at given RPs across countries --- .../exposure/electricity_grid/disruption.smk | 67 ++++++++++++++++++- 1 file changed, 66 insertions(+), 1 deletion(-) diff --git a/workflow/rules/exposure/electricity_grid/disruption.smk b/workflow/rules/exposure/electricity_grid/disruption.smk index 92a0cf53..196dfe2a 100644 --- a/workflow/rules/exposure/electricity_grid/disruption.smk +++ b/workflow/rules/exposure/electricity_grid/disruption.smk @@ -259,7 +259,7 @@ rule plot_pop_affected_return_periods: ax.set_xscale("log") ax.set_xlabel("Return period [years]", labelpad=10) - ax.set_ylabel(f"Population affected", labelpad=10) + ax.set_ylabel(f"Population at risk of disconnection", labelpad=10) ax.grid(alpha=0.4, which="both") plt.subplots_adjust(right=0.8) @@ -312,6 +312,71 @@ snakemake -c1 -- results/power/by_storm_set/STORM-constant/pop_affected_RP_plots """ +def pop_affected_return_period_paths(wildcards) -> list[str]: + """ + Return a list of paths, one for each country. + """ + import json + + country_set_path = f"{wildcards.OUTPUT_DIR}/power/by_storm_set/{wildcards.STORM_SET}/countries_impacted.json" + with open(country_set_path, "r") as fp: + countries = json.load(fp) + + return expand( + rules.disruption_pop_affected_return_periods.output.return_periods_interpolated, + OUTPUT_DIR=wildcards.OUTPUT_DIR, + COUNTRY_ISO_A3=countries, + STORM_SET=wildcards.STORM_SET, + ) + + +rule disruption_pop_affected_return_period_map: + """ + Number of people at risk of disconnection by country, by return period. + """ + input: + return_period_data = pop_affected_return_period_paths, + admin_boundaries = "{OUTPUT_DIR}/input/admin-boundaries/admin-level-0.geoparquet", + params: + return_periods = config["return_period_years"] + output: + return_period_maps = directory("{OUTPUT_DIR}/power/by_storm_set/{STORM_SET}/disruption/pop_affected_RP/"), + run: + import geopandas as gpd + import pandas as pd + + countries = gpd.read_parquet(input.admin_boundaries) + countries = countries.rename(columns={"GID_0": "ISO_A3"}).set_index("ISO_A3") + + data_by_country = [] + for path in input.return_period_data: + iso_a3: str = path.split("/")[-4] + df = pd.read_parquet(path) + df["ISO_A3"] = iso_a3 + df = df.reset_index().set_index(["return_period_years", "threshold", "ISO_A3"]) + # threshold indicies are transformed into columns, long -> wide + df = df.unstack("threshold") + df.columns = df.columns.droplevel(0) + data_by_country.append(df) + + data = pd.concat(data_by_country) + + os.makedirs(output.return_period_maps) + for return_period in params.return_periods: + # select one return period -- table now has country rows and threshold columns + df = data.xs(return_period, level="return_period_years") + + # merge in geometry column, and name + gdf = gpd.GeoDataFrame(df.join(countries)) + + gdf.to_parquet(os.path.join(output.return_period_maps, f"{return_period}.gpq")) + +""" +Test with: +snakemake -c1 -- results/power/by_storm_set/STORM-constant/disruption/pop_affected_RP +""" + + def disruption_per_target_sample_files(wildcards) -> list[str]: """ Return a list of paths, one for each sample. From 7c645ac4cd4ef9a24bcd8be039ca21dfdad1c4e4 Mon Sep 17 00:00:00 2001 From: Fred Thomas Date: Mon, 22 Jan 2024 16:55:28 +0000 Subject: [PATCH 4/5] Retain per-sample winds N.B. The all sample (concatenated) wind file is not always required, so not always created. --- workflow/rules/exposure/wind_fields.smk | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/workflow/rules/exposure/wind_fields.smk b/workflow/rules/exposure/wind_fields.smk index dc3f9db7..f153fce3 100644 --- a/workflow/rules/exposure/wind_fields.smk +++ b/workflow/rules/exposure/wind_fields.smk @@ -218,7 +218,7 @@ rule estimate_wind_fields: output: # enable or disable plotting in the config file plot_dir=directory("{OUTPUT_DIR}/power/by_country/{COUNTRY_ISO_A3}/storms/{STORM_SET}/{SAMPLE}/plots/"), - wind_speeds=temp("{OUTPUT_DIR}/power/by_country/{COUNTRY_ISO_A3}/storms/{STORM_SET}/{SAMPLE}/max_wind_field.nc"), + wind_speeds="{OUTPUT_DIR}/power/by_country/{COUNTRY_ISO_A3}/storms/{STORM_SET}/{SAMPLE}/max_wind_field.nc", script: "../../scripts/intersect/estimate_wind_fields.py" From cf5dce1c056ab426bf241472a2125c642cb0f864 Mon Sep 17 00:00:00 2001 From: Fred Thomas Date: Mon, 22 Jan 2024 17:07:00 +0000 Subject: [PATCH 5/5] Update test config --- tests/config/config.yaml | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/tests/config/config.yaml b/tests/config/config.yaml index b5b6b4ab..ab1e53e6 100644 --- a/tests/config/config.yaml +++ b/tests/config/config.yaml @@ -96,6 +96,11 @@ wind_grid_resolution_deg: 0.1 # approx 11km latitude # Failure thresholds m/s. These values are the thresholds at which the network assets # are expected to fail based on available literature. transmission_windspeed_failure: [20., 35] +# when plotting, mark this threshold as the central value +best_estimate_windspeed_failure_threshold: 35 + +# return periods at which to report +return_period_years: [2, 5, 10, 20, 50, 100, 200, 500, 1000] # whether to plot maximum wind fields and storm track animations for each storm plot_wind: