"""
Function to load raster tile maps from XYZ tile providers, and load as
:class:`xarray.DataArray`.
"""
from __future__ import annotations
from packaging.version import Version
try:
import contextily
_HAS_CONTEXTILY = True
except ImportError:
_HAS_CONTEXTILY = False
import numpy as np
import xarray as xr
__doctest_requires__ = {("load_tile_map"): ["contextily"]}
[docs]
def load_tile_map(
region,
zoom="auto",
source=None,
lonlat=True,
wait=0,
max_retries=2,
zoom_adjust: int | None = None,
):
"""
Load a georeferenced raster tile map from XYZ tile providers.
The tiles that compose the map are merged and georeferenced into an
:class:`xarray.DataArray` image with 3 bands (RGB). Note that the returned
image is in a Spherical Mercator (EPSG:3857) coordinate reference system.
Parameters
----------
region : list
The bounding box of the map in the form of a list [*xmin*, *xmax*,
*ymin*, *ymax*]. These coordinates should be in longitude/latitude if
``lonlat=True`` or Spherical Mercator (EPSG:3857) if ``lonlat=False``.
zoom : int or str
Optional. Level of detail. Higher levels (e.g. ``22``) mean a zoom
level closer to the Earth's surface, with more tiles covering a smaller
geographical area and thus more detail. Lower levels (e.g. ``0``) mean
a zoom level further from the Earth's surface, with less tiles covering
a larger geographical area and thus less detail [Default is
``"auto"`` to automatically determine the zoom level based on the
bounding box region extent].
.. note::
The maximum possible zoom level may be smaller than ``22``, and depends on
what is supported by the chosen web tile provider source.
source : xyzservices.TileProvider or str
Optional. The tile source: web tile provider or path to a local file.
Provide either:
- A web tile provider in the form of a
:class:`xyzservices.TileProvider` object. See
:doc:`Contextily providers <contextily:providers_deepdive>` for a
list of tile providers [Default is
``xyzservices.providers.OpenStreetMap.HOT``, i.e. OpenStreetMap
Humanitarian web tiles].
- A web tile provider in the form of a URL. The placeholders for the
XYZ in the URL need to be {x}, {y}, {z}, respectively. E.g.
``https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png``.
- A local file path. The file is read with
:doc:`rasterio <rasterio:index>` and all bands are loaded into the
basemap. See
:doc:`contextily:working_with_local_files`.
.. important::
Tiles are assumed to be in the Spherical Mercator projection (EPSG:3857).
lonlat : bool
Optional. If ``False``, coordinates in ``region`` are assumed to be
Spherical Mercator as opposed to longitude/latitude [Default is
``True``].
wait : int
Optional. If the tile API is rate-limited, the number of seconds to
wait between a failed request and the next try [Default is ``0``].
max_retries : int
Optional. Total number of rejected requests allowed before contextily
will stop trying to fetch more tiles from a rate-limited API [Default
is ``2``].
zoom_adjust
The amount to adjust a chosen zoom level if it is chosen automatically. Values
outside of -1 to 1 are not recommended as they can lead to slow execution.
.. note::
The ``zoom_adjust`` parameter requires ``contextily>=1.5.0``.
Returns
-------
raster : xarray.DataArray
Georeferenced 3-D data array of RGB values.
Raises
------
ImportError
If ``contextily`` is not installed or can't be imported. Follow
:doc:`install instructions for contextily <contextily:index>`, (e.g.
via ``python -m pip install contextily``) before using this function.
Examples
--------
>>> import contextily
>>> from pygmt.datasets import load_tile_map
>>> raster = load_tile_map(
... region=[-180.0, 180.0, -90.0, 0.0], # West, East, South, North
... zoom=1, # less detailed zoom level
... source=contextily.providers.OpenTopoMap,
... lonlat=True, # bounding box coordinates are longitude/latitude
... )
>>> raster.sizes
Frozen({'band': 3, 'y': 256, 'x': 512})
>>> raster.coords
Coordinates:
* band (band) uint8 0 1 2
* y (y) float64 -7.081e-10 -7.858e+04 ... -1.996e+07 ...
* x (x) float64 -2.004e+07 -1.996e+07 ... 1.996e+07 2.004e+07
"""
if not _HAS_CONTEXTILY:
raise ImportError(
"Package `contextily` is required to be installed to use this function. "
"Please use `python -m pip install contextily` or "
"`mamba install -c conda-forge contextily` "
"to install the package."
)
contextily_kwargs = {}
if zoom_adjust is not None:
contextily_kwargs["zoom_adjust"] = zoom_adjust
if Version(contextily.__version__) < Version("1.5.0"):
raise TypeError(
"The `zoom_adjust` parameter requires `contextily>=1.5.0` to work. "
"Please upgrade contextily, or manually set the `zoom` level instead."
)
west, east, south, north = region
image, extent = contextily.bounds2img(
w=west,
s=south,
e=east,
n=north,
zoom=zoom,
source=source,
ll=lonlat,
wait=wait,
max_retries=max_retries,
**contextily_kwargs,
)
# Turn RGBA img from channel-last to channel-first and get 3-band RGB only
_image = image.transpose(2, 0, 1) # Change image from (H, W, C) to (C, H, W)
rgb_image = _image[0:3, :, :] # Get just RGB by dropping RGBA's alpha channel
# Georeference RGB image into an xarray.DataArray
left, right, bottom, top = extent
dataarray = xr.DataArray(
data=rgb_image,
coords={
"band": np.array(object=[0, 1, 2], dtype=np.uint8), # Red, Green, Blue
"y": np.linspace(start=top, stop=bottom, num=rgb_image.shape[1]),
"x": np.linspace(start=left, stop=right, num=rgb_image.shape[2]),
},
dims=("band", "y", "x"),
)
# If rioxarray is installed, set the coordinate reference system
if hasattr(dataarray, "rio"):
dataarray = dataarray.rio.set_crs(input_crs="EPSG:3857")
return dataarray