From 9b765a6f7ddfd70cb11b760e20ce84a4f9d05942 Mon Sep 17 00:00:00 2001 From: Olufunke Awowale Date: Fri, 14 Feb 2025 18:16:22 -0500 Subject: [PATCH 1/4] datatree imerghh_7 notebook --- DataTree/DataTree_Tutorial.ipynb | 323 +++++++++++++++++++++++++++++++ 1 file changed, 323 insertions(+) create mode 100644 DataTree/DataTree_Tutorial.ipynb diff --git a/DataTree/DataTree_Tutorial.ipynb b/DataTree/DataTree_Tutorial.ipynb new file mode 100644 index 00000000..32d14fa4 --- /dev/null +++ b/DataTree/DataTree_Tutorial.ipynb @@ -0,0 +1,323 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# How to use `xarray.DataTree` with hierarchical data\n", + "\n", + "\n", + "## Overview: \n", + "\n", + "This notebook will demonstrate how to use `xarray.DataTree` with [_GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 (GPM_3IMERGHH_07)_](https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGHH_07/summary) and use xarray's plotting capabilities to plot precipitation in the Gulf of Mexico during Hurricane Ida. GPM_3IMERGHH_07 is a L3 gridded product with a group hierarchical structure." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import cartopy.crs as ccrs\n", + "import matplotlib.pyplot as plt\n", + "from xarray import open_datatree\n", + "from metpy.plots import ctables" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Opening the dataset with `open_datatree()`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7 = open_datatree('~/Downloads/3B-HHR.MS.MRG.3IMERG.20210829-S073000-E075959.0450.V07B.HDF5', engine='h5netcdf')\n", + "gpm_imerghh_7" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### List all of the groups with `.groups`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7.groups" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Accessing variables in a nested groups\n", + "Nested variables and groups can be accessed with either dict-like syntax or method based syntax." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7['/Grid']\n", + "\n", + "# Returns only the data contained in the \"/Grid\" group" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7['/Grid/precipitation']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7.Grid.precipitation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get the parent and child nodes from a group" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7['/Grid/Intermediate'].parent" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7.Grid.children" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### `Xarray.DataTree` objects and `xarray.Dataset` objects have the same key properties like:\n", + "\n", + "- `dims`: a dictionary mapping of dimension names to lengths, for the variables in a node, and a node’s ancestors.\n", + "\n", + "- `data_vars`: a dict-like container of DataArrays corresponding to variables in a node.\n", + "\n", + "- `coords`: another dict-like container of DataArrays, corresponding to coordinate variables in a node, and a node’s ancestors.\n", + "\n", + "- `attrs`: dict with metadata relevant to data in a node.\n", + "\n", + "With `DataTree` you can get these properties at any of the nodes (groups) they are defined in." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7.dims\n", + "# Note there are no dimensions, coordinates, or data variables defined at the root node" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7.attrs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7['/Grid'].dims" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7['/Grid/Intermediate'].dims" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "gpm_imerghh_7['/Grid/Intermediate'].data_vars" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting precipitation data with DataTree\n", + "Xarray’s plotting capabilities are centered around DataArray objects. To plot DataTree objects we access their relevant DataArrays in this case, `gpm_imerghh_7['/Grid/precipitation']`. \n", + "\n", + "We use the `.where()` method to get a subset of precipitation data over the Gulf of Mexico." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "precipitation_subset = gpm_imerghh_7['/Grid/precipitation'].where(\n", + " (gpm_imerghh_7['/Grid/precipitation'].lat >= 20) & (gpm_imerghh_7['/Grid/precipitation'].lat <= 35) & \n", + " (gpm_imerghh_7['/Grid/precipitation'].lon >= -110) & (gpm_imerghh_7['/Grid/precipitation'].lon <= -78), drop=True\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Data masking\n", + "We add a data mask to the precipitation values that are zero." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "precipitation_subset_mask = precipitation_subset.where(precipitation_subset > 0.0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Add a custom precipitation color map from [metpy](https://unidata.github.io/MetPy/latest/api/generated/metpy.plots.ctables.html)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "clevs = [0, 1, 2.5, 5, 7.5, 10, 15, 20, 30, 40,\n", + " 50, 70, 100, 150, 200, 250, 300, 400, 500, 600, 750]\n", + "norm, cmap = ctables.registry.get_with_boundaries('precipitation', clevs)\n", + "cmap" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot the data with `.plot()`\n", + "Note since this data is two-dimensional it calls `xarray.plot.pcolormesh()` by default with just the `.plot()` method." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Half-hourly precipitation rate in the Gulf of Mexico on August 29, 2021 at 07:30')" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Set the figure size, projection, extent and grid lines to the plot\n", + "fig = plt.figure(figsize=(8, 8))\n", + "ax = plt.axes(projection=ccrs.PlateCarree())\n", + "ax.set_extent([-100, -80, 20, 35])\n", + "ax.coastlines()\n", + "gl = ax.gridlines(draw_labels=True, linewidth=1, color='black', linestyle='--')\n", + "gl.right_labels = False\n", + "gl.top_labels = False\n", + "\n", + "# Get the minimum and maximum values in the array\n", + "min = precipitation_subset_mask.min()\n", + "max = precipitation_subset_mask.max()\n", + "\n", + "# Plot the precipitation data\n", + "precipitation_subset_mask[0].plot(x=\"lon\", y=\"lat\",\n", + " ax=ax, cmap=cmap,\n", + " cbar_kwargs={\"orientation\":\"horizontal\", \"pad\": 0.05},\n", + " vmin=min, vmax=max)\n", + "\n", + "plt.title('Half-hourly precipitation rate in the Gulf of Mexico on August 29, 2021 at 07:30')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "utf-upgrade-datatree", + "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": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 16cb11379392e76d0d35e1f68641847404c7fa9a Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 18 Feb 2025 15:01:09 +0000 Subject: [PATCH 2/4] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- DataTree/DataTree_Tutorial.ipynb | 62 ++++++++++++-------------------- 1 file changed, 22 insertions(+), 40 deletions(-) diff --git a/DataTree/DataTree_Tutorial.ipynb b/DataTree/DataTree_Tutorial.ipynb index 32d14fa4..255e772d 100644 --- a/DataTree/DataTree_Tutorial.ipynb +++ b/DataTree/DataTree_Tutorial.ipynb @@ -38,7 +38,9 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7 = open_datatree('~/Downloads/3B-HHR.MS.MRG.3IMERG.20210829-S073000-E075959.0450.V07B.HDF5', engine='h5netcdf')\n", + "gpm_imerghh_7 = open_datatree(\n", + " '~/Downloads/3B-HHR.MS.MRG.3IMERG.20210829-S073000-E075959.0450.V07B.HDF5', engine='h5netcdf'\n", + ")\n", "gpm_imerghh_7" ] }, @@ -200,8 +202,11 @@ "outputs": [], "source": [ "precipitation_subset = gpm_imerghh_7['/Grid/precipitation'].where(\n", - " (gpm_imerghh_7['/Grid/precipitation'].lat >= 20) & (gpm_imerghh_7['/Grid/precipitation'].lat <= 35) & \n", - " (gpm_imerghh_7['/Grid/precipitation'].lon >= -110) & (gpm_imerghh_7['/Grid/precipitation'].lon <= -78), drop=True\n", + " (gpm_imerghh_7['/Grid/precipitation'].lat >= 20)\n", + " & (gpm_imerghh_7['/Grid/precipitation'].lat <= 35)\n", + " & (gpm_imerghh_7['/Grid/precipitation'].lon >= -110)\n", + " & (gpm_imerghh_7['/Grid/precipitation'].lon <= -78),\n", + " drop=True,\n", ")" ] }, @@ -235,8 +240,7 @@ "metadata": {}, "outputs": [], "source": [ - "clevs = [0, 1, 2.5, 5, 7.5, 10, 15, 20, 30, 40,\n", - " 50, 70, 100, 150, 200, 250, 300, 400, 500, 600, 750]\n", + "clevs = [0, 1, 2.5, 5, 7.5, 10, 15, 20, 30, 40, 50, 70, 100, 150, 200, 250, 300, 400, 500, 600, 750]\n", "norm, cmap = ctables.registry.get_with_boundaries('precipitation', clevs)\n", "cmap" ] @@ -251,30 +255,9 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Half-hourly precipitation rate in the Gulf of Mexico on August 29, 2021 at 07:30')" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Set the figure size, projection, extent and grid lines to the plot\n", "fig = plt.figure(figsize=(8, 8))\n", @@ -286,25 +269,25 @@ "gl.top_labels = False\n", "\n", "# Get the minimum and maximum values in the array\n", - "min = precipitation_subset_mask.min()\n", + "min = precipitation_subset_mask.min()\n", "max = precipitation_subset_mask.max()\n", "\n", "# Plot the precipitation data\n", - "precipitation_subset_mask[0].plot(x=\"lon\", y=\"lat\",\n", - " ax=ax, cmap=cmap,\n", - " cbar_kwargs={\"orientation\":\"horizontal\", \"pad\": 0.05},\n", - " vmin=min, vmax=max)\n", + "precipitation_subset_mask[0].plot(\n", + " x=\"lon\",\n", + " y=\"lat\",\n", + " ax=ax,\n", + " cmap=cmap,\n", + " cbar_kwargs={\"orientation\": \"horizontal\", \"pad\": 0.05},\n", + " vmin=min,\n", + " vmax=max,\n", + ")\n", "\n", "plt.title('Half-hourly precipitation rate in the Gulf of Mexico on August 29, 2021 at 07:30')" ] } ], "metadata": { - "kernelspec": { - "display_name": "utf-upgrade-datatree", - "language": "python", - "name": "python3" - }, "language_info": { "codemirror_mode": { "name": "ipython", @@ -314,8 +297,7 @@ "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.5" + "pygments_lexer": "ipython3" } }, "nbformat": 4, From fe39686167c3e4745ac2f6399e263977177affdc Mon Sep 17 00:00:00 2001 From: Olufunke Awowale Date: Tue, 4 Mar 2025 20:15:47 -0500 Subject: [PATCH 3/4] added more methods and suggestions --- _toc.yml | 1 + .../01_datatree_imerghh.ipynb | 171 ++++++++++++------ 2 files changed, 112 insertions(+), 60 deletions(-) rename DataTree/DataTree_Tutorial.ipynb => fundamentals/01_datatree_imerghh.ipynb (53%) diff --git a/_toc.yml b/_toc.yml index 6c0aeda8..97e03a85 100644 --- a/_toc.yml +++ b/_toc.yml @@ -18,6 +18,7 @@ parts: - file: fundamentals/01_datastructures - file: fundamentals/01.1_creating_data_structures - file: fundamentals/01.1_io + - file: fundamentals/01_datatree_imerghh.ipynb - file: fundamentals/02_labeled_data.md sections: - file: fundamentals/02.1_indexing_Basic.ipynb diff --git a/DataTree/DataTree_Tutorial.ipynb b/fundamentals/01_datatree_imerghh.ipynb similarity index 53% rename from DataTree/DataTree_Tutorial.ipynb rename to fundamentals/01_datatree_imerghh.ipynb index 255e772d..bf8b02c6 100644 --- a/DataTree/DataTree_Tutorial.ipynb +++ b/fundamentals/01_datatree_imerghh.ipynb @@ -15,14 +15,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import cartopy.crs as ccrs\n", "import matplotlib.pyplot as plt\n", - "from xarray import open_datatree\n", - "from metpy.plots import ctables" + "import xarray as xr" ] }, { @@ -38,17 +37,19 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7 = open_datatree(\n", - " '~/Downloads/3B-HHR.MS.MRG.3IMERG.20210829-S073000-E075959.0450.V07B.HDF5', engine='h5netcdf'\n", + "imerghh_730 = xr.open_datatree(\n", + " '~/xarray-data/imerghh_730.hdf5', engine='h5netcdf'\n", ")\n", - "gpm_imerghh_7" + "imerghh_730" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### List all of the groups with `.groups`" + "### Nodes\n", + "Groups in a netcdf4 or hdf5 file in the DataTree model are represented as \"nodes\" in the DataTree model.\n", + "We can list all of the groups with `.groups`" ] }, { @@ -57,7 +58,7 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7.groups" + "imerghh_730.groups" ] }, { @@ -74,7 +75,7 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7['/Grid']\n", + "imerghh_730['/Grid']\n", "\n", "# Returns only the data contained in the \"/Grid\" group" ] @@ -85,7 +86,7 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7['/Grid/precipitation']" + "imerghh_730['/Grid/precipitation']" ] }, { @@ -94,7 +95,9 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7.Grid.precipitation" + "imerghh_730.Grid.precipitation\n", + "\n", + "# Method based syntax" ] }, { @@ -110,7 +113,7 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7['/Grid/Intermediate'].parent" + "imerghh_730['/Grid/Intermediate'].parent" ] }, { @@ -119,7 +122,7 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7.Grid.children" + "imerghh_730.Grid.children" ] }, { @@ -145,7 +148,7 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7.dims\n", + "imerghh_730.dims\n", "# Note there are no dimensions, coordinates, or data variables defined at the root node" ] }, @@ -155,7 +158,7 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7.attrs" + "imerghh_730.attrs" ] }, { @@ -164,7 +167,7 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7['/Grid'].dims" + "imerghh_730['/Grid'].dims" ] }, { @@ -173,7 +176,7 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7['/Grid/Intermediate'].dims" + "imerghh_730['/Grid/Intermediate'].dims" ] }, { @@ -182,17 +185,16 @@ "metadata": {}, "outputs": [], "source": [ - "gpm_imerghh_7['/Grid/Intermediate'].data_vars" + "imerghh_730['/Grid/Intermediate'].data_vars" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Plotting precipitation data with DataTree\n", - "Xarray’s plotting capabilities are centered around DataArray objects. To plot DataTree objects we access their relevant DataArrays in this case, `gpm_imerghh_7['/Grid/precipitation']`. \n", - "\n", - "We use the `.where()` method to get a subset of precipitation data over the Gulf of Mexico." + "### Creating a DataTree from a dictionary with `DataTree.from_dict()`\n", + "You can create a DataTree from a dictionary of `xr.Datasets` objects or `xr.DataTree` objects.\n", + "The key of the dictionary is the node/group of the new DataTree object." ] }, { @@ -201,21 +203,18 @@ "metadata": {}, "outputs": [], "source": [ - "precipitation_subset = gpm_imerghh_7['/Grid/precipitation'].where(\n", - " (gpm_imerghh_7['/Grid/precipitation'].lat >= 20)\n", - " & (gpm_imerghh_7['/Grid/precipitation'].lat <= 35)\n", - " & (gpm_imerghh_7['/Grid/precipitation'].lon >= -110)\n", - " & (gpm_imerghh_7['/Grid/precipitation'].lon <= -78),\n", - " drop=True,\n", - ")" + "imerghh_830 = xr.open_datatree('~/xarray-data/imerghh_830.hdf5', engine='h5netcdf')\n", + "xr.DataTree.from_dict({'time_830': imerghh_830})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Data masking\n", - "We add a data mask to the precipitation values that are zero." + "### Using `DataTree.from_dict()` to make a DataTree object\n", + "Lets combine our two DataTree objects (`imerghh_730` and `imerghh_830`) at each time stamp with `DataTree.from_dict()`.\n", + "All of the groups in the original datasets will remain intact but now we have two additional groups `/time_730` and `/time_830`.\n", + "The groups `/Grid` and `/Grid/Intermediate`are nested in ancestor node's `/time_730` and `/time_830` respectively. They are all children of the root node `'/'`" ] }, { @@ -224,33 +223,84 @@ "metadata": {}, "outputs": [], "source": [ - "precipitation_subset_mask = precipitation_subset.where(precipitation_subset > 0.0)" + "combined_imerghh_tree = xr.DataTree.from_dict({'time_730': imerghh_730,\n", + " 'time_830': imerghh_830})\n", + "combined_imerghh_tree" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "combined_imerghh_tree.children" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Add a custom precipitation color map from [metpy](https://unidata.github.io/MetPy/latest/api/generated/metpy.plots.ctables.html)" + "### Combining data with DataTree\n", + "DataTree objects (like Dataset objects) can contain `DataArray` objects. We can `concat` and `merge` DataArrays in an DataTree along a specified dimension. Lets combine the precipitation data from nodes `/time_730` and `/time_830`. Note these datasets have the same size across their `\"time\"`, `\"lat\"` and `\"lon\"` dimensions.\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "precip_concat = xr.concat([combined_imerghh_tree['time_730/Grid/precipitation'], combined_imerghh_tree['time_830/Grid/precipitation']], dim='time')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting precipitation data with DataTree\n", + "Xarray’s plotting capabilities are centered around DataArray objects. To plot DataTree objects we access their relevant DataArrays in this case, our concatenated `DataArray` `precip_concat`. \n", + "\n", + "We use the `.where()` method to get a subset of precipitation data over the Gulf of Mexico." + ] + }, + { + "cell_type": "code", + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ - "clevs = [0, 1, 2.5, 5, 7.5, 10, 15, 20, 30, 40, 50, 70, 100, 150, 200, 250, 300, 400, 500, 600, 750]\n", - "norm, cmap = ctables.registry.get_with_boundaries('precipitation', clevs)\n", - "cmap" + "precip_concat_sub = precip_concat.where(\n", + " (precip_concat.lat >= 20)\n", + " & (precip_concat.lat <= 35)\n", + " & (precip_concat.lon >= -110)\n", + " & (precip_concat.lon <= -78),\n", + " drop=True,)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Plot the data with `.plot()`\n", - "Note since this data is two-dimensional it calls `xarray.plot.pcolormesh()` by default with just the `.plot()` method." + "### Data masking\n", + "We add a data mask to the precipitation values that are zero. We will use the `.where()` method to get data values greater than 0.0" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "precipitation_subset_mask = precip_concat_sub.where(precip_concat_sub > 0.0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot the data with `.plot()` as a `FacetGrid` object\n", + "We can use `xarray.plot.FacetGrid` objects to make plots with multiple axes. Each axes shows the same relationship conditioned on different levels of some dimension, in our case different time stamps. Note since this data is two-dimensional it calls `xarray.plot.pcolormesh()` by default with just the `.plot()` method." ] }, { @@ -259,35 +309,35 @@ "metadata": {}, "outputs": [], "source": [ - "# Set the figure size, projection, extent and grid lines to the plot\n", - "fig = plt.figure(figsize=(8, 8))\n", - "ax = plt.axes(projection=ccrs.PlateCarree())\n", - "ax.set_extent([-100, -80, 20, 35])\n", - "ax.coastlines()\n", - "gl = ax.gridlines(draw_labels=True, linewidth=1, color='black', linestyle='--')\n", - "gl.right_labels = False\n", - "gl.top_labels = False\n", - "\n", - "# Get the minimum and maximum values in the array\n", - "min = precipitation_subset_mask.min()\n", - "max = precipitation_subset_mask.max()\n", - "\n", "# Plot the precipitation data\n", - "precipitation_subset_mask[0].plot(\n", + "precip_plot = precipitation_subset_mask.plot(figsize=(12, 6), transform=ccrs.PlateCarree(), subplot_kws={'projection':ccrs.PlateCarree()},\n", " x=\"lon\",\n", " y=\"lat\",\n", - " ax=ax,\n", - " cmap=cmap,\n", - " cbar_kwargs={\"orientation\": \"horizontal\", \"pad\": 0.05},\n", - " vmin=min,\n", - " vmax=max,\n", + " col='time', # The dimension (\"time\") we are faceting our plot on\n", + " col_wrap=2, # Number of subplots\n", + " cmap='jet',\n", + " cbar_kwargs={\"orientation\": \"horizontal\", \"pad\": 0.15, \"shrink\": 0.6},\n", + " vmin=precipitation_subset_mask.min(),\n", + " vmax=precipitation_subset_mask.max(),\n", + "\n", ")\n", "\n", - "plt.title('Half-hourly precipitation rate in the Gulf of Mexico on August 29, 2021 at 07:30')" + "\n", + "for ax in precip_plot.axs.flat:\n", + " ax.set_extent([-100, -80, 20, 35])\n", + " ax.coastlines()\n", + " gl = ax.gridlines(linewidth=1, color='black', linestyle='--')\n", + " gl.left_labels = True\n", + " gl.bottom_labels = True\n" ] } ], "metadata": { + "kernelspec": { + "display_name": "utf-upgrade-datatree", + "language": "python", + "name": "python3" + }, "language_info": { "codemirror_mode": { "name": "ipython", @@ -297,7 +347,8 @@ "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython3" + "pygments_lexer": "ipython3", + "version": "3.12.5" } }, "nbformat": 4, From cd7b423265cfb6e8315bbf542b952bceeb4334f9 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 5 Mar 2025 01:16:09 +0000 Subject: [PATCH 4/4] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- fundamentals/01_datatree_imerghh.ipynb | 46 +++++++++++++------------- 1 file changed, 23 insertions(+), 23 deletions(-) diff --git a/fundamentals/01_datatree_imerghh.ipynb b/fundamentals/01_datatree_imerghh.ipynb index bf8b02c6..c66bbd16 100644 --- a/fundamentals/01_datatree_imerghh.ipynb +++ b/fundamentals/01_datatree_imerghh.ipynb @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -37,9 +37,7 @@ "metadata": {}, "outputs": [], "source": [ - "imerghh_730 = xr.open_datatree(\n", - " '~/xarray-data/imerghh_730.hdf5', engine='h5netcdf'\n", - ")\n", + "imerghh_730 = xr.open_datatree('~/xarray-data/imerghh_730.hdf5', engine='h5netcdf')\n", "imerghh_730" ] }, @@ -223,8 +221,7 @@ "metadata": {}, "outputs": [], "source": [ - "combined_imerghh_tree = xr.DataTree.from_dict({'time_730': imerghh_730,\n", - " 'time_830': imerghh_830})\n", + "combined_imerghh_tree = xr.DataTree.from_dict({'time_730': imerghh_730, 'time_830': imerghh_830})\n", "combined_imerghh_tree" ] }, @@ -247,11 +244,17 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "precip_concat = xr.concat([combined_imerghh_tree['time_730/Grid/precipitation'], combined_imerghh_tree['time_830/Grid/precipitation']], dim='time')" + "precip_concat = xr.concat(\n", + " [\n", + " combined_imerghh_tree['time_730/Grid/precipitation'],\n", + " combined_imerghh_tree['time_830/Grid/precipitation'],\n", + " ],\n", + " dim='time',\n", + ")" ] }, { @@ -266,7 +269,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -275,7 +278,8 @@ " & (precip_concat.lat <= 35)\n", " & (precip_concat.lon >= -110)\n", " & (precip_concat.lon <= -78),\n", - " drop=True,)" + " drop=True,\n", + ")" ] }, { @@ -288,7 +292,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -310,16 +314,18 @@ "outputs": [], "source": [ "# Plot the precipitation data\n", - "precip_plot = precipitation_subset_mask.plot(figsize=(12, 6), transform=ccrs.PlateCarree(), subplot_kws={'projection':ccrs.PlateCarree()},\n", + "precip_plot = precipitation_subset_mask.plot(\n", + " figsize=(12, 6),\n", + " transform=ccrs.PlateCarree(),\n", + " subplot_kws={'projection': ccrs.PlateCarree()},\n", " x=\"lon\",\n", " y=\"lat\",\n", - " col='time', # The dimension (\"time\") we are faceting our plot on\n", - " col_wrap=2, # Number of subplots\n", + " col='time', # The dimension (\"time\") we are faceting our plot on\n", + " col_wrap=2, # Number of subplots\n", " cmap='jet',\n", " cbar_kwargs={\"orientation\": \"horizontal\", \"pad\": 0.15, \"shrink\": 0.6},\n", " vmin=precipitation_subset_mask.min(),\n", " vmax=precipitation_subset_mask.max(),\n", - "\n", ")\n", "\n", "\n", @@ -328,16 +334,11 @@ " ax.coastlines()\n", " gl = ax.gridlines(linewidth=1, color='black', linestyle='--')\n", " gl.left_labels = True\n", - " gl.bottom_labels = True\n" + " gl.bottom_labels = True" ] } ], "metadata": { - "kernelspec": { - "display_name": "utf-upgrade-datatree", - "language": "python", - "name": "python3" - }, "language_info": { "codemirror_mode": { "name": "ipython", @@ -347,8 +348,7 @@ "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.5" + "pygments_lexer": "ipython3" } }, "nbformat": 4,