Facetgrid (multiplots)

docs/notebooks/figanos_multiplots.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Figanos multiple plots"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create subplots and facetgrids with Figanos."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# import necessary libraries\n",
+    "import xarray as xr\n",
+    "import cartopy.crs as ccrs\n",
+    "import figanos.matplotlib as fg\n",
+    "import numpy as np\n",
+    "\n",
+    "# use ouranos style\n",
+    "fg.utils.set_mpl_style('ouranos')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# create xarray object from a NetCDF\n",
+    "url = 'https://pavics.ouranos.ca//twitcher/ows/proxy/thredds/dodsC/birdhouse/disk2/cccs_portal/indices/Final/BCCAQv2_CMIP6/tx_max/YS/ssp585/ensemble_percentiles/tx_max_ann_BCCAQ2v2+ANUSPLIN300_historical+ssp585_1950-2100_30ymean_percentiles.nc'\n",
+    "opened = xr.open_dataset(url, decode_timedelta=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Timeseries\n",
+    "Create multiple timeseries plot with matplotlib subplots and figanos as shown below."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Maps\n",
+    "Create multiple maps plot with figanos wrapped around xr.plot.facetgrid.FacetGrid by passing the arguement row and/or col in plot_kw."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Selecting a time and slicing our starting Dataset\n",
+    "ds_space = opened[['tx_max_p50']].isel(time=[0, 1, 2]).sel(lat=slice(40,65), lon=slice(-90,-55))\n",
+    "\n",
+    "# defining our projection.\n",
+    "projection = ccrs.LambertConformal()\n",
+    "\n",
+    "im = fg.gridmap(ds_space, projection = projection, plot_kw = {\"x\": \"lon\", \"y\": \"lat\", \"col\": \"time\"}, features = ['coastline','ocean'], frame = False, use_attrs={\"suptitle\": \"description\"})\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "names = ['station_' + str(i) for i in np.arange(5)]\n",
+    "lat = 45 + np.random.rand(5)*3\n",
+    "lon = np.linspace(-76,-70, 5)\n",
+    "tas = np.array([[20, 25, 30, 15, 5], [5, 0, 10, 2, 3]])\n",
+    "yrs = np.array([[35, 65, 45, 25, 95],\n",
+    "                [15, 75, 10, 15, 50]])\n",
+    "\n",
+    "attrs = {'units': 'degC', 'standard_name': 'air_temperature', 'long_name': 'Near-Surface Daily Maximum Air Temperature'}\n",
+    "\n",
+    "tas = xr.DataArray(data=tas,\n",
+    "                        coords={'season': ['DFJ', 'MAM'],\n",
+    "                                'station': names,\n",
+    "                                'lat':('station', lat),\n",
+    "                                'lon': ('station', lon),\n",
+    "                                'years': (('season', 'station'), yrs),\n",
+    "                                },\n",
+    "                        dims=['season', 'station'],\n",
+    "                        attrs=attrs)\n",
+    "obs = xr.Dataset({'tas': tas})\n",
+    "\n",
+    "# plot\n",
+    "fg.scattermap(obs,\n",
+    "                  transform=ccrs.PlateCarree(),\n",
+    "                  sizes='years',\n",
+    "                  size_range=(25, 100),\n",
+    "                  plot_kw={\n",
+    "                      \"xlim\": (-77,-69),\n",
+    "                      \"ylim\":(43,50),\n",
+    "                      \"col\": \"season\",\n",
+    "                  },\n",
+    "                  features={\n",
+    "                      \"land\": {\"color\": \"#f0f0f0\"},\n",
+    "                      \"rivers\": {\"edgecolor\": \"#cfd3d4\"},\n",
+    "                      \"lakes\": {\"facecolor\": \"#cfd3d4\"},\n",
+    "                      \"coastline\": {\"edgecolor\": \"black\"},\n",
+    "                  }\n",
+    "                 )\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plot over each other"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "names = ['station_' + str(i) for i in np.arange(5)]\n",
+    "lat = 45 + np.random.rand(5)*3\n",
+    "lon = np.linspace(-76,-70, 5)\n",
+    "tas = np.array([[290, 300, 295, 305, 301], [275, 285, 277, 301, 345], [302, 293, 295, 292, 280]])\n",
+    "\n",
+    "attrs = {'units': 'degK', 'standard_name': 'air_temperature', 'long_name': ds_space.tx_max_p50.attrs['description']}\n",
+    "\n",
+    "tas = xr.DataArray(data=tas,\n",
+    "                        coords={'time': ds_space.time.values,\n",
+    "                                'station': names,\n",
+    "                                'lat':('station', lat),\n",
+    "                                'lon': ('station', lon),\n",
+    "                                },\n",
+    "                        dims=['time', 'station'],\n",
+    "                        attrs=attrs)\n",
+    "obs2 = xr.Dataset({'tas': tas})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "vmin=280\n",
+    "vmax=310\n",
+    "\n",
+    "im = fg.gridmap(ds_space,\n",
+    "                projection = projection,\n",
+    "                plot_kw = {\"col\": \"time\",\n",
+    "                           \"xlim\": (-77,-69), \"ylim\": (43,50),\n",
+    "                           \"vmin\": vmin, \"vmax\": vmax,\n",
+    "                           },\n",
+    "                features = ['coastline','ocean'],\n",
+    "                frame = False,\n",
+    "                use_attrs={\"suptitle\": \"description\"}\n",
+    "                )\n",
+    "for i, fax in enumerate(im.axs.flat):\n",
+    "    fg.scattermap(obs2.isel(time=i),\n",
+    "                  ax=fax,\n",
+    "                  transform=ccrs.PlateCarree(),\n",
+    "                  plot_kw={'vmin': vmin, 'vmax': vmax, 'edgecolors':'grey', 'add_colorbar': False}\n",
+    "                 )\n",
+    "im.fig.suptitle('Scattermaps over gridmaps', x=0.45, y=0.95)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}