mirror of
https://github.com/chanzuckerberg/cellxgene.git
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ab1b9368a0
This had the wrong dim passed into n_comps, and so failed when the number of genes was less than 50.
54 lines
1.7 KiB
Python
54 lines
1.7 KiB
Python
import importlib
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import numpy as np
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"""
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Wrapper for various scanpy modules. Will raise NotImplementedError if the scanpy
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module is not installed/available
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"""
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def get_scanpy_module():
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try:
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sc = importlib.import_module("scanpy")
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# Future: we could enforce versions here, eg, lookat sc.__version__
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return sc
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except ModuleNotFoundError as e:
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raise NotImplementedError("Please install scanpy to enable UMAP re-embedding") from e
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except Exception as e:
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# will capture other ImportError corner cases
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raise NotImplementedError() from e
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def scanpy_umap(adata, obs_mask=None, pca_options={}, neighbors_options={}, umap_options={}):
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"""
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Given adata and an obs mask, return a new embedding for adata[obs_mask, :]
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as an ndarray of shape (len(obs_mask), N), where N>=2.
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Do NOT mutate adata.
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"""
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# backed mode is incompatible with the current implementation
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if adata.isbacked:
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raise NotImplementedError("Backed mode is incompatible with re-embedding")
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# safely get scanpy module, which may not be present.
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sc = get_scanpy_module()
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# https://github.com/theislab/anndata/issues/311
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obs_mask = slice(None) if obs_mask is None else obs_mask
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adata = adata[obs_mask, :].copy()
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for k in list(adata.obsm.keys()):
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del adata.obsm[k]
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for k in list(adata.uns.keys()):
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del adata.uns[k]
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sc.pp.pca(adata, zero_center=None, n_comps=min(adata.n_vars - 1, 50), **pca_options)
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sc.pp.neighbors(adata, **neighbors_options)
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sc.tl.umap(adata, **umap_options)
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umap = adata.obsm["X_umap"]
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result = np.full((obs_mask.shape[0], umap.shape[1]), np.NaN)
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result[obs_mask] = umap
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return result
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