mae_plot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "import matplotlib.ticker as mticker\n",
    "\n",
    "# Read the mae details CSV file\n",
    "mae_details = pd.read_csv('/work2/07174/soelem/validation/mae_swot_with_flag.csv')\n",
    "\n",
    "# Drop rows with NaN values in any of the relevant columns\n",
    "mae_details = mae_details.dropna(subset=['Latitude', 'Longitude', 'MAE_without', 'MAE_with'])\n",
    "\n",
    "# Extract the latitude, longitude, and mae values\n",
    "lats = mae_details['Latitude']\n",
    "lons = mae_details['Longitude']\n",
    "mae_values = mae_details['MAE_with'].round(3)\n",
    "mae_without_values = mae_details['MAE_without'].round(3)\n",
    "\n",
    "# Calculate the difference\n",
    "mae_difference = mae_without_values - mae_values\n",
    "\n",
    "# Masks for improved, worsened, and unchanged\n",
    "improved_mask = mae_difference > 0\n",
    "worsened_mask = mae_difference < 0\n",
    "unchanged_mask = mae_difference == 0\n",
    "\n",
    "# Calculate the counts for each category\n",
    "improved_count = improved_mask.sum()\n",
    "worsened_count = worsened_mask.sum()\n",
    "unchanged_count = unchanged_mask.sum()\n",
    "\n",
    "# Set up the plot with Cartopy\n",
    "fig = plt.figure(figsize=(10, 5), dpi=600)\n",
    "ax = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree())\n",
    "\n",
    "# Set the extent of the plot to the bounding box\n",
    "ax.set_extent([-100, -60, 20, 50], crs=ccrs.PlateCarree())\n",
    "\n",
    "# Add map features\n",
    "ax.add_feature(cfeature.COASTLINE)  # Add coastline\n",
    "# ax.add_feature(cfeature.BORDERS, linestyle=':')  # Add country borders\n",
    "ax.add_feature(cfeature.LAND, facecolor='darkgrey')  # Add land\n",
    "ax.add_feature(cfeature.OCEAN)  # Add ocean\n",
    "ax.add_feature(cfeature.LAKES, alpha=0.5)  # Add lakes\n",
    "# ax.add_feature(cfeature.RIVERS)  # Add rivers\n",
    "\n",
    "# Plot the scatter points with updated labels\n",
    "ax.scatter(lons[improved_mask], lats[improved_mask], color='blue', edgecolor='black', linewidth=0.5, s=100, transform=ccrs.PlateCarree(), label=f'Improved - {improved_count} stations', zorder=3)\n",
    "ax.scatter(lons[worsened_mask], lats[worsened_mask], color='red', edgecolor='black', linewidth=0.5, s=100, transform=ccrs.PlateCarree(), label=f'Worsened - {worsened_count} stations', zorder=3)\n",
    "ax.scatter(lons[unchanged_mask], lats[unchanged_mask], color='white', edgecolor='black', linewidth=0.5, s=100, transform=ccrs.PlateCarree(), label=f'Unchanged - {unchanged_count} stations', zorder=3)\n",
    "\n",
    "# Add a legend\n",
    "plt.legend(loc='lower right', fontsize='medium')\n",
    "\n",
    "# Add gridlines and labels\n",
    "gl = ax.gridlines(draw_labels=True)\n",
    "gl.xlocator = mticker.MultipleLocator(5)  # Set longitude gridline interval\n",
    "gl.ylocator = mticker.MultipleLocator(5)  # Set latitude gridline interval\n",
    "gl.ylabel_style = {'rotation': 90}\n",
    "\n",
    "# Display the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import size\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "# Read the mae details CSV file\n",
    "mae_details = pd.read_csv('/work2/07174/soelem/validation/mae_swot_with_flag.csv')\n",
    "\n",
    "# Drop rows with NaN values in any of the relevant columns\n",
    "mae_details = mae_details.dropna(subset=['Latitude', 'Longitude', 'MAE_with', 'MAE_without'])\n",
    "\n",
    "# Extract the latitude, longitude, and mae values\n",
    "lats = mae_details['Latitude']\n",
    "lons = mae_details['Longitude']\n",
    "mae_values = mae_details['MAE_with'].round(3)\n",
    "mae_without_values = mae_details['MAE_without'].round(3)\n",
    "\n",
    "# Calculate the percentage difference\n",
    "mae_difference = (mae_without_values - mae_values) / mae_values * 100\n",
    "\n",
    "# Masks for improved, worsened, and unchanged\n",
    "improved_mask = mae_difference > 0\n",
    "worsened_mask = mae_difference < 0\n",
    "unchanged_mask = mae_difference == 0\n",
    "\n",
    "# Additional masks for more than 20% improvement or deterioration\n",
    "more_than_20_improved_mask = mae_difference > 5\n",
    "less_than_20_improved_mask = (mae_difference > 0) & (mae_difference <= 5)\n",
    "more_than_20_worsened_mask = mae_difference < -5\n",
    "less_than_20_worsened_mask = (mae_difference < 0) & (mae_difference >= -5)\n",
    "\n",
    "# Calculate the counts for each category\n",
    "improved_count = improved_mask.sum()\n",
    "worsened_count = worsened_mask.sum()\n",
    "unchanged_count = unchanged_mask.sum()\n",
    "more_than_20_improved_count = more_than_20_improved_mask.sum()\n",
    "less_than_20_improved_count = less_than_20_improved_mask.sum()\n",
    "more_than_20_worsened_count = more_than_20_worsened_mask.sum()\n",
    "less_than_20_worsened_count = less_than_20_worsened_mask.sum()\n",
    "\n",
    "# Set up the plot with Cartopy\n",
    "fig = plt.figure(figsize=(10, 8), dpi=600)\n",
    "ax = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree())\n",
    "\n",
    "# Set the extent of the plot to the bounding box\n",
    "ax.set_extent([-100, -60, 20, 50], crs=ccrs.PlateCarree())\n",
    "\n",
    "# Add map features\n",
    "ax.add_feature(cfeature.COASTLINE)  # Add coastline\n",
    "ax.add_feature(cfeature.LAND, facecolor='darkgrey')  # Add land\n",
    "ax.add_feature(cfeature.OCEAN)  # Add ocean\n",
    "ax.add_feature(cfeature.LAKES, alpha=0.5)  # Add lakes\n",
    "\n",
    "# Plot the scatter points with zorder set to a higher value and the new categories\n",
    "ax.scatter(lons[more_than_20_improved_mask], lats[more_than_20_improved_mask], color='blue', edgecolor='black', linewidth=0.5, s=150, transform=ccrs.PlateCarree(), label=f'More than 5% Improvement - {more_than_20_improved_count} stations', zorder=3)\n",
    "ax.scatter(lons[less_than_20_improved_mask], lats[less_than_20_improved_mask], color='lightblue', edgecolor='black', linewidth=0.5, s=150, transform=ccrs.PlateCarree(), label=f'Less than 5% Improvement - {less_than_20_improved_count} stations', zorder=3)\n",
    "ax.scatter(lons[more_than_20_worsened_mask], lats[more_than_20_worsened_mask], color='red', edgecolor='black', linewidth=0.5, s=150, transform=ccrs.PlateCarree(), label=f'More than 5% Deterioration - {more_than_20_worsened_count} stations', zorder=3)\n",
    "ax.scatter(lons[less_than_20_worsened_mask], lats[less_than_20_worsened_mask], color='lightcoral', edgecolor='black', linewidth=0.5, s=150, transform=ccrs.PlateCarree(), label=f'Less than 5% Deterioration - {less_than_20_worsened_count} stations', zorder=3)\n",
    "ax.scatter(lons[unchanged_mask], lats[unchanged_mask], color='white', edgecolor='black', linewidth=0.5, s=150, transform=ccrs.PlateCarree(), label=f'Unchanged - {unchanged_count} stations', zorder=3)\n",
    "\n",
    "# Add a legend\n",
    "plt.legend(loc='lower right', fontsize='medium')\n",
    "\n",
    "# Add gridlines and labels\n",
    "gl = ax.gridlines(draw_labels=True)\n",
    "gl.ylabel_style = {'rotation': 90}\n",
    "\n",
    "# Display the plot\n",
    "plt.show()"
   ]
  }
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