# Copyright (c) 2022, TU Wien, Department of Geodesy and Geoinformation
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import warnings
try:
import matplotlib.pyplot as plt
import matplotlib as mp
except ImportError:
warnings.warn("Matplotlib is necessary for plotting grids. "
"Call `conda install matplotlib`")
try:
import cartopy
import cartopy.crs as ccrs
except ImportError:
warnings.warn("Cartopy is necessary for plotting grids."
"Call `conda install cartopy`")
import numpy as np
import pygeogrids.grids as grids
[docs]def plot_cell_grid_partitioning(
output, cellsize_lon=5.0, cellsize_lat=5.0, figsize=(12, 6), fontsize=2,
):
"""
Plot an overview of a global cell partitioning.
Parameters
----------
output: str
output file path, must end with .png
cellsize_lon: float, optional (default: 5.0)
Cell sampling in longitude dimension
cellsize_lat: float, optional (default: 5.0)
Cell sampling in latitude dimension
figsize: tuple, optional (default: (12, 6))
Figure size (inch)
fontsize: float, optional (default: 2)
Font size for labels on the map
"""
fig, ax = plt.subplots(figsize=figsize,
subplot_kw={"projection": ccrs.PlateCarree()})
ax.add_feature(cartopy.feature.LAND, color='coral')
ax.add_feature(cartopy.feature.LAKES, color='aqua')
ax.add_feature(cartopy.feature.OCEAN, color='aqua')
for y in np.arange(-90, 90, cellsize_lat):
ax.plot([-180, 180], [y, y], '--', transform=ccrs.PlateCarree(), lw=0.5,
color='black')
for x in np.arange(-180, 180, cellsize_lat):
ax.plot([x, x], [-90, 90], '--', transform=ccrs.PlateCarree(), lw=0.5,
color='black')
label_lats = np.arange(-90 + cellsize_lat / 2.0, 90, cellsize_lat)
label_lons = np.arange(-180 + cellsize_lon / 2.0, 180, cellsize_lon)
lons, lats = np.meshgrid(label_lons, label_lats)
cells = grids.lonlat2cell(
lons.flatten(),
lats.flatten(),
cellsize_lon=cellsize_lon,
cellsize_lat=cellsize_lat,
)
for lon, lat, cell in zip(lons.flatten(), lats.flatten(), cells):
ax.text(
lon,
lat,
"{:}".format(cell),
fontsize=fontsize,
va="center",
ha="center",
weight="bold",
)
fig.savefig(output, format="png", dpi=300)
plt.close(fig)