Feature/pyramid reproject map blocks #12
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updates: - [github.com/pre-commit/pre-commit-hooks: v3.4.0 → v4.1.0](pre-commit/pre-commit-hooks@v3.4.0...v4.1.0) - https://github.com/ambv/black → https://github.com/psf/black - [github.com/psf/black: 20.8b1 → 21.12b0](psf/black@20.8b1...21.12b0) - https://gitlab.com/pycqa/flake8 → https://github.com/PyCQA/flake8 - [github.com/PyCQA/flake8: 3.9.0 → 4.0.1](PyCQA/flake8@3.9.0...4.0.1) - https://github.com/pre-commit/mirrors-isort → https://github.com/PyCQA/isort - [github.com/PyCQA/isort: v5.8.0 → 5.10.1](PyCQA/isort@v5.8.0...5.10.1)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
andersy005
reviewed
Mar 25, 2022
| pyramid[lkey] = xr.Dataset(attrs=ds.attrs) | ||
| shape = (dim, dim) | ||
| for k, da in ds.items(): | ||
| template_shape = (chunked_dim_sizes) + shape # TODO: pick up here. |
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where is chunked_dim_sizes supposed to come from?
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Good question. Clearly I didn't finish this part.
If I recall correctly, this is mean to support cases where non-spatial dims are chunked. The most common examples would be chunks along the band or time dimensions.
To do this, we need to construct a template that includes the correct shape for each block.
Co-authored-by: Anderson Banihirwe <[email protected]>
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Thanks for starting work on this Joe and Anderson! I'm planning to pick this feature up, but since the code base has changed a bunch it'll be easier to work in a fresh PR so I'll close this one now. |
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This PR adds a new feature to the
pyramid_reprojectfunction. Rather than iterating over extra dimensions in each DataArray, we now allow the DataArray to be chunked as a dask.array. Under the hood we usexarray.map_blocksto execute rioxarray's reproject function.