mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-18 18:38:11 +08:00
fb61bd6e9c
This splits the backend into two parts: the local backend for desktop cellxgene and the AWS backend for hosted cellxgene. The local backend is in local_server while the hosted remains in server. The general idea is to copy everything from server to local_server, pull unneeded stuff out of local_server, and keep server as-is for this PR. Not touching server means all the infra and deployment code will continue working just as it did before so we can make those changes incrementally.
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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