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"""
.. _recipes.rasterio:
=================================
Parsing rasterio's geocoordinates
=================================
Converting a projection's cartesian coordinates into 2D longitudes and
latitudes.
These new coordinates might be handy for plotting and indexing, but it should
be kept in mind that a grid which is regular in projection coordinates will
likely be irregular in lon/lat. It is often recommended to work in the data's
original map projection (see :ref:`recipes.rasterio_rgb`).
"""
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import numpy as np
from rasterio.warp import transform
import xarray as xr
# Read the data
url = "https://github.com/mapbox/rasterio/raw/master/tests/data/RGB.byte.tif"
da = xr.open_rasterio(url)
# Compute the lon/lat coordinates with rasterio.warp.transform
ny, nx = len(da["y"]), len(da["x"])
x, y = np.meshgrid(da["x"], da["y"])
# Rasterio works with 1D arrays
lon, lat = transform(da.crs, {"init": "EPSG:4326"}, x.flatten(), y.flatten())
lon = np.asarray(lon).reshape((ny, nx))
lat = np.asarray(lat).reshape((ny, nx))
da.coords["lon"] = (("y", "x"), lon)
da.coords["lat"] = (("y", "x"), lat)
# Compute a greyscale out of the rgb image
greyscale = da.mean(dim="band")
# Plot on a map
ax = plt.subplot(projection=ccrs.PlateCarree())
greyscale.plot(
ax=ax,
x="lon",
y="lat",
transform=ccrs.PlateCarree(),
cmap="Greys_r",
add_colorbar=False,
)
ax.coastlines("10m", color="r")
plt.show()
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