Support dask array conditional in compress#2555
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jcrist merged 2 commits intodask:masterfrom Jul 25, 2017
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Compress now works with dask arrays as conditionals without calling compute on them. If the conditional is concrete we take an optimized path and return an array of known shape. If it's lazy we return an array of unknown shape along the specified axis.
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cc @jakirkham. |
jakirkham
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Jul 25, 2017
| for i in range(a.ndim))] | ||
| inds = tuple(range(a.ndim)) | ||
| out = atop(np.compress, inds, condition, (inds[axis],), a, inds, | ||
| axis=axis, dtype=a.dtype) |
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Neat! Was wondering if this was doable with atop, but was not totally figuring out how.
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Implements `da.extract` using `da.compress`.
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I also added |
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jakirkham
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Jul 28, 2017
| out = atop(np.compress, inds, condition, (inds[axis],), a, inds, | ||
| axis=axis, dtype=a.dtype) | ||
| out._chunks = tuple((np.NaN,) * len(c) if i == axis else c | ||
| for i, c in enumerate(out.chunks)) |
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As a follow-up, it would be great if there was a formal API for declaring a dimension to be of unknown size.
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Compress now works with dask arrays as conditionals without calling compute on them. If the conditional is concrete we take an optimized path and return an array of known shape. If it's lazy we return an array of unknown shape along the specified axis.
Supersedes #2548, fixes #2540.