scikit-learn/sklearn/utils/_logistic_sigmoid.pyx

30 lines
745 B
Cython

from libc.math cimport log, exp
import numpy as np
cimport numpy as np
np.import_array()
ctypedef np.float64_t DTYPE_t
cdef inline DTYPE_t _inner_log_logistic_sigmoid(const DTYPE_t x):
"""Log of the logistic sigmoid function log(1 / (1 + e ** -x))"""
if x > 0:
return -log(1. + exp(-x))
else:
return x - log(1. + exp(x))
def _log_logistic_sigmoid(unsigned int n_samples,
unsigned int n_features,
DTYPE_t[:, :] X,
DTYPE_t[:, :] out):
cdef:
unsigned int i
unsigned int j
for i in range(n_samples):
for j in range(n_features):
out[i, j] = _inner_log_logistic_sigmoid(X[i, j])
return out