ndpyramid.pyramid_regrid

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ndpyramid.pyramid_regrid#

ndpyramid.pyramid_regrid(ds: Dataset, projection: Literal['web-mercator', 'equidistant-cylindrical'] = 'web-mercator', target_pyramid: DataTree | None = None, levels: int | None = None, *, level_list: Sequence[int] | None = None, parallel_weights: bool = True, weights_pyramid: DataTree | None = None, method: str = 'bilinear', regridder_kws: dict | None = None, regridder_apply_kws: dict | None = None, other_chunks: dict | None = None, pixels_per_tile: int = 128) → DataTree[source]#

Make a pyramid using xesmf’s regridders

Parameters:

  • ds (xr.Dataset) – Input dataset

  • projection (str, optional) – Projection to use for the grid, by default ‘web-mercator’

  • target_pyramid (xr.DataTree, optional) – Target grids, if not provided, they will be generated, by default None

  • levels (int, optional) – Number of contiguous levels to build (0..levels-1). Ignored if level_list provided.

  • level_list (Sequence[int], optional) – Explicit list of zoom levels to build (sparse). Mutually exclusive with levels.

  • weights_pyramid (xr.DataTree, optional) – pyramid containing pregenerated weights

  • parallel_weights (Bool) – Use dask to generate parallel weights

  • method (str, optional) – Regridding method. See Regridder for valid options, by default ‘bilinear’

  • regridder_kws (dict) – Keyword arguments to pass to regridder. Default is {‘periodic’: True}

  • regridder_apply_kws (dict) – Keyword arguments such as keep_attrs, skipna, na_thres to pass to __call__(). Default is None

  • other_chunks (dict) – Chunks for non-spatial dims to pass to chunk(). Default is None

  • pixels_per_tile (int, optional) – Number of pixels per tile, by default 128

Returns:

pyramid – Multiscale data pyramid

Return type:

xr.DataTree

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