U md @shddlZddlmZddlZddddZejedddZej d d d d Z ej d d d dZ dS)N)sparseaxiscCsvt|rt||d\}}n6tj||tjd}t||j|tjd}||d}||j||j|d9}||fS)Nr)rdtype)rissparsesparse_mean_variance_axisnpmeanfloat64multiplyshape)Xrr varZmean_sqrT/home/sam/Atlas/atlas_env/lib/python3.8/site-packages/scanpy/preprocessing/_utils.py _get_mean_vars  r)mtxrcCs|dks tt|tjr$d}|j}n*t|tjrFd}|jddd}ntd||krtt|j|j |j f|t j fSt |j|j f|t j fSdS)a^ This code and internal functions are based on sklearns `sparsefuncs.mean_variance_axis`. Modifications: * allow deciding on the output type, which can increase accuracy when calculating the mean and variance of 32bit floats. * This doesn't currently implement support for null values, but could. * Uses numba not cython )rrrrNz7This function only works on sparse csr and csc matrices)AssertionError isinstancerZ csr_matrixrZ csc_matrix ValueErrorsparse_mean_var_major_axisdataindicesindptrr r sparse_mean_var_minor_axis)rrZax_minorrrrrr s$   r T)cachec Cs|jd}tj||d}tj||d}tj|tjd}t|D] } || } || || 7<q>t|D]} || |<qht|D]@} || } || || } || | | 7<|| d7<qt|D]8} || ||| || d7<|| |<q||fS)z Computes mean and variance for a sparse matrix for the minor axis. Given arrays for a csr matrix, returns the means and variances for each column back. rrrr)rr zeros zeros_likeZint64range) rr major_len minor_lenrZnon_zeromeans variancescountsiZcol_inddiffrrrr-s$     $rcCstj||d}tj||d}t|D]}||} ||d} | | } t| | D]} |||| 7<qN|||<t| | D](} || ||} ||| | 7<q|||| ||d7<|||<q$||fS)z Computes mean and variance for a sparse array for the major axis. Given arrays for a csr matrix, returns the means and variances for each row back. rrr)r r r!r")rrrr#r$rr%r&r(ZstartptrZendptrr'jr)rrrrPs   r) numpyr ZscipyrZnumbarZspmatrixintr Znjitrrrrrrs    "