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# -----------------------------------------------------------------------------
# Copyright (c) 2011-2017, The BIOM Format Development Team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
# -----------------------------------------------------------------------------
from __future__ import division
import numpy as np
cimport numpy as cnp
def _transform(arr, ids, metadata, function, axis):
"""Transform non-zero values of a sparse array, in place.
Only non null values can be modified: the density of the sparse
matrix can't increase. However, zeroing values is fine.
Parameters
----------
arr : csr_matrix or csc_matrix
Matrix whose rows or columns (respectively) are to be
transformed.
ids : 1D array_like
ids along the given axis.
metadata : 1D array_like or None
metadata along the given axis.
function : function
A function that takes three values: an array of nonzero values
for each column or row of `arr`, an id string and a metadata
dictionary. It must return an array of transformed values.
axis : int
Transform rows of `arr` if 0, columns if 1.
"""
cdef:
Py_ssize_t n, row_or_col
cnp.ndarray[cnp.int32_t, ndim=1] indptr = arr.indptr
cnp.ndarray[cnp.float64_t, ndim=1] data = arr.data
cdef cnp.int32_t start, end
if metadata is None:
metadata = (None,) * len(ids)
n = arr.shape[axis]
for row_or_col in range(n):
start, end = indptr[row_or_col], indptr[row_or_col+1]
id_ = ids[row_or_col]
md = metadata[row_or_col]
data[start:end] = function(data[start:end], id_, md)
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