pyresample.gradient package
Module contents
Implementation of the gradient search algorithm as described by Trishchenko.
- pyresample.gradient.GradientSearchResampler(source_geo_def, target_geo_def)
Create a gradient search resampler.
- class pyresample.gradient.ResampleBlocksGradientSearchResampler(source_geo_def, target_geo_def)
Bases:
BaseResampler
Resample using gradient search based bilinear interpolation, using resample_blocks for lazy processing.
- compute(data, method='bilinear', cache_id=None, **kwargs)
Perform the resampling.
- precompute(**kwargs)
Precompute resampling parameters.
- class pyresample.gradient.StackingGradientSearchResampler(source_geo_def, target_geo_def)
Bases:
BaseResampler
Resample using gradient search based bilinear interpolation, using stacking for dask processing.
- compute(data, fill_value=None, **kwargs)
Resample the given data using gradient search algorithm.
- get_chunk_mappings()
Map source and target chunks together if they overlap.
- pyresample.gradient.block_bilinear_interpolator(data, indices_xy, fill_value=nan, block_info=None, **kwargs)
Bilinear interpolation implementation for resample_blocks.
- pyresample.gradient.block_nn_interpolator(data, indices_xy, fill_value=nan, block_info=None, **kwargs)
Nearest neighbour ‘interpolator’ for resample_blocks.
- pyresample.gradient.check_overlap(src_poly, dst_poly)
Check if the two polygons overlap.
- pyresample.gradient.create_gradient_search_resampler(source_geo_def, target_geo_def)
Create a gradient search resampler.
- pyresample.gradient.ensure_3d_data(func)
Ensure the data is in three dimensions.
- pyresample.gradient.ensure_data_array(func)
Ensure the data is an instance of an xarray.DataArray with correct dimensions.
- pyresample.gradient.get_border_lonlats(geo_def: AreaDefinition)
Get the border x- and y-coordinates.
- pyresample.gradient.get_polygon(prj, geo_def)
Get border polygon from area definition in projection prj.
- pyresample.gradient.gradient_resampler(data, source_area, target_area, method='bilinear')
Do the gradient search resampling.
The input data can be 2d, or 3d with the two last axes being respectively y and x.
- pyresample.gradient.gradient_resampler_indices(source_area, target_area, block_info=None, **kwargs)
Do the gradient search resampling, returning the resulting indices.
- pyresample.gradient.gradient_resampler_indices_block(block_info=None, **kwargs)
Do the gradient search resampling using block_info for areas, returning the resulting indices.
- pyresample.gradient.parallel_gradient_search(data, src_x, src_y, dst_x, dst_y, src_gradient_xl, src_gradient_xp, src_gradient_yl, src_gradient_yp, dst_mosaic_locations, dst_slices, **kwargs)
Run gradient search in parallel in input area coordinates.