from typing import Union, Optional, Tuple, Collection, Sequence, Iterable
from anndata import AnnData
import numpy as np
from scipy.sparse import issparse, isspmatrix_csr, csr_matrix, spmatrix
from scipy import sparse
from stlearn import logging as logg
import scanpy
[docs]def log1p(
adata: Union[AnnData, np.ndarray, spmatrix],
copy: bool = False,
chunked: bool = False,
chunk_size: Optional[int] = None,
base: Optional[float] = None,
) -> Optional[AnnData]:
"""\
Wrap function of scanpy.pp.log1p
Copyright (c) 2017 F. Alexander Wolf, P. Angerer, Theis Lab
Logarithmize the data matrix.
Computes :math:`X = \\log(X + 1)`,
where :math:`log` denotes the natural logarithm unless a different base is given.
Parameters
----------
data
The (annotated) data matrix of shape `n_obs` × `n_vars`.
Rows correspond to cells and columns to genes.
copy
If an :class:`~anndata.AnnData` is passed, determines whether a copy
is returned.
chunked
Process the data matrix in chunks, which will save memory.
Applies only to :class:`~anndata.AnnData`.
chunk_size
`n_obs` of the chunks to process the data in.
base
Base of the logarithm. Natural logarithm is used by default.
Returns
-------
Returns or updates `data`, depending on `copy`.
"""
scanpy.pp.log1p(adata, copy=copy, chunked=chunked, chunk_size=chunk_size, base=base)
print("Log transformation step is finished in adata.X")
[docs]def scale(
adata: Union[AnnData, np.ndarray, spmatrix],
zero_center: bool = True,
max_value: Optional[float] = None,
copy: bool = False,
) -> Optional[AnnData]:
"""\
Wrap function of scanpy.pp.scale
Scale data to unit variance and zero mean.
.. note::
Variables (genes) that do not display any variation (are constant across
all observations) are retained and set to 0 during this operation. In
the future, they might be set to NaNs.
Parameters
----------
data
The (annotated) data matrix of shape `n_obs` × `n_vars`.
Rows correspond to cells and columns to genes.
zero_center
If `False`, omit zero-centering variables, which allows to handle sparse
input efficiently.
max_value
Clip (truncate) to this value after scaling. If `None`, do not clip.
copy
If an :class:`~anndata.AnnData` is passed,
determines whether a copy is returned.
Returns
-------
Depending on `copy` returns or updates `adata` with a scaled `adata.X`.
"""
scanpy.pp.scale(adata, zero_center=zero_center, max_value=max_value, copy=copy)
print("Scale step is finished in adata.X")