8000 [MRG+1] MNT Use std math lib log1p instead of np.log1p in cython inner loops by amueller · Pull Request #11848 · scikit-learn/scikit-learn · GitHub
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[MRG+1] MNT Use std math lib log1p instead of np.log1p in cython inner loops #11848

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Merged
merged 1 commit into from
Aug 18, 2018
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[MRG+1] MNT Use std math lib log1p instead of np.log1p in cython inner loops #11848

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4 changes: 2 additions & 2 deletions sklearn/neighbors/binary_tree.pxi
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Original file line number Diff line number Diff line change
Expand Up @@ -143,7 +143,7 @@

cimport cython
cimport numpy as np
from libc.math cimport fabs, sqrt, exp, cos, pow, log
from libc.math cimport fabs, sqrt, exp, cos, pow, log, log1p
from libc.stdlib cimport calloc, malloc, free
from libc.string cimport memcpy
from sklearn.utils.lgamma cimport lgamma
Expand Down Expand Up @@ -486,7 +486,7 @@ cdef DTYPE_t _log_kernel_norm(DTYPE_t h, ITYPE_t d,
elif kernel == EXPONENTIAL_KERNEL:
factor = logSn(d - 1) + lgamma(d)
elif kernel == LINEAR_KERNEL:
factor = logVn(d) - np.log1p(d)
factor = logVn(d) - log1p(d)
elif kernel == COSINE_KERNEL:
# this is derived from a chain rule integration
factor = 0
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6 changes: 3 additions & 3 deletions sklearn/utils/_logistic_sigmoid.pyx
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Expand Up @@ -2,7 +2,7 @@
#cython: cdivision=True
#cython: wraparound=False

from libc.math cimport log, exp
from libc.math cimport log1p, exp

import numpy as np
cimport numpy as np
Expand All @@ -13,9 +13,9 @@ ctypedef np.float64_t DTYPE_t
cdef DTYPE_t _inner_log_logistic_sigmoid(DTYPE_t x):
"""Log of the logistic sigmoid function log(1 / (1 + e ** -x))"""
if x > 0:
return -np.log1p(exp(-x))
return -log1p(exp(-x))
else:
return x - np.log1p(exp(x))
return x - log1p(exp(x))


def _log_logistic_sigmoid(int n_samples, int n_features,
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