scdrs.pp._get_mean_var_implicit_cov_corr#
- scdrs.pp._get_mean_var_implicit_cov_corr(adata, axis=0, weights=None, transform_func=None, n_chunk=20)[source]#
Compute mean and variance of sparse matrix of the form
adata.X + COV_MAT * COV_BETA + COV_GENE_MEAN.
Computed iteratively over chunks of sparse matrix by converting to dense matrix and computing mean and variance of dense matrix.
- Parameters:
- adataanndata.AnnData
Annotated data matrix (n_obs, n_vars)
- axis{0, 1}, default=0
Axis along which to compute mean and variance
- weightsarray_like, default=None
Weights of length adata.shape[axis].
- transform_funcfunction, default=None
Function to transform the data before computing mean and variance
- n_chunkint, default=20
Number of chunks to split the data into when computing mean and variance this will determine the memory usage
- Returns:
- v_meannp.ndarray
Mean vector.
- v_varnp.ndarray
Variance vector.