Comments (3)
Ah, yes... thanks for pointing this out... It should work but there is something non-trivial, as the data matrix is cast to a vector when it has a single column or row (just like numpy arrays) so that flattening is unnecessary. I never looked into this on the level of the file, though... We're giving the whole file backing an overhaul anyways and will fix it during that.
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iām very sure i got rid of that behavior at one point and enforced that the data matrix was always 2D.
we should go back to that behavior, mohammad is struggling with problems regarding this as well.
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Finally fixed via #55.
Btw @mckinsel, looking at your call above: You can also init an AnnData directly from a DataFrame (adata = AnnData(df)
) since a few weeks.
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Related Issues (20)
- TypeError: Can't implicitly convert non-string objects to strings HOT 4
- Error concatenating scRNA with visium dataset
- memory usage of concat HOT 3
- Using `Pint` for units HOT 9
- UMAP of gene subset of adata HOT 2
- Error using sc.pl.stacked_violin HOT 1
- NotImplementedError with concat_on_disk
- Issue when setting anndata.X to numpy array HOT 3
- Does anndata.raw can be automatically modified after define it?
- Make the call to `_check_uniqueness()` optional in `_init_as_actual()` (and `__init__()`) HOT 1
- `concat_on_disk` outer join
- `concat_on_disk` merge strategies are untested/not implemented
- Potentially flaky benchmark HOT 2
- Reading Anndata from only parts of h5ad file: Hack solution HOT 8
- 2D indexing (no ā:ā) in `sparse_dataset` is not lazy HOT 7
- Set of categories changes when slicing AnnData, but not when slicing DataFrame HOT 1
- Gpu failing because of `cp.full` with `np.nan`
- Add path parameter to write_zarr method HOT 8
- GPU writing HOT 1
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