"""Function to load raster tile maps from XYZ tile providers, and load as:class:`xarray.DataArray`."""from__future__importannotationsfrompackaging.versionimportVersiontry:importcontextily_HAS_CONTEXTILY=TrueexceptImportError:_HAS_CONTEXTILY=Falseimportnumpyasnpimportxarrayasxr__doctest_requires__={("load_tile_map"):["contextily"]}
[docs]defload_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 """ifnot_HAS_CONTEXTILY:raiseImportError("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={}ifzoom_adjustisnotNone:contextily_kwargs["zoom_adjust"]=zoom_adjustifVersion(contextily.__version__)<Version("1.5.0"):raiseTypeError("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=regionimage,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.DataArrayleft,right,bottom,top=extentdataarray=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 systemifhasattr(dataarray,"rio"):dataarray=dataarray.rio.set_crs(input_crs="EPSG:3857")returndataarray