138 lines
3.3 KiB
Cython
138 lines
3.3 KiB
Cython
|
"""
|
||
|
|
The :mod:`sklearn.utils.arrayfuncs` module includes a small collection of auxiliary
|
||
|
|
functions that operate on arrays.
|
||
|
|
"""
|
||
|
|
|
||
|
|
from cython cimport floating
|
||
|
|
from cython.parallel cimport prange
|
||
|
|
from libc.math cimport fabs
|
||
|
|
from libc.float cimport DBL_MAX, FLT_MAX
|
||
|
|
|
||
|
|
from ._cython_blas cimport _copy, _rotg, _rot
|
||
|
|
from ._typedefs cimport float64_t
|
||
|
|
|
||
|
|
|
||
|
|
ctypedef fused real_numeric:
|
||
|
|
short
|
||
|
|
int
|
||
|
|
long
|
||
|
|
long long
|
||
|
|
float
|
||
|
|
double
|
||
|
|
|
||
|
|
|
||
|
|
def min_pos(const floating[:] X):
|
||
|
|
"""Find the minimum value of an array over positive values.
|
||
|
|
|
||
|
|
Returns the maximum representable value of the input dtype if none of the
|
||
|
|
values are positive.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
X : ndarray of shape (n,)
|
||
|
|
Input array.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
min_val : float
|
||
|
|
The smallest positive value in the array, or the maximum representable value
|
||
|
|
of the input dtype if no positive values are found.
|
||
|
|
|
||
|
|
Examples
|
||
|
|
--------
|
||
|
|
>>> import numpy as np
|
||
|
|
>>> from sklearn.utils.arrayfuncs import min_pos
|
||
|
|
>>> X = np.array([0, -1, 2, 3, -4, 5])
|
||
|
|
>>> min_pos(X)
|
||
|
|
2.0
|
||
|
|
"""
|
||
|
|
cdef Py_ssize_t i
|
||
|
|
cdef floating min_val = FLT_MAX if floating is float else DBL_MAX
|
||
|
|
for i in range(X.size):
|
||
|
|
if 0. < X[i] < min_val:
|
||
|
|
min_val = X[i]
|
||
|
|
return min_val
|
||
|
|
|
||
|
|
|
||
|
|
def _all_with_any_reduction_axis_1(real_numeric[:, :] array, real_numeric value):
|
||
|
|
"""Check whether any row contains all values equal to `value`.
|
||
|
|
|
||
|
|
It is equivalent to `np.any(np.all(X == value, axis=1))`, but it avoids to
|
||
|
|
materialize the temporary boolean matrices in memory.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
array: array-like
|
||
|
|
The array to be checked.
|
||
|
|
value: short, int, long, float, or double
|
||
|
|
The value to use for the comparison.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
any_all_equal: bool
|
||
|
|
Whether or not any rows contains all values equal to `value`.
|
||
|
|
"""
|
||
|
|
cdef Py_ssize_t i, j
|
||
|
|
|
||
|
|
for i in range(array.shape[0]):
|
||
|
|
for j in range(array.shape[1]):
|
||
|
|
if array[i, j] != value:
|
||
|
|
break
|
||
|
|
else: # no break
|
||
|
|
return True
|
||
|
|
return False
|
||
|
|
|
||
|
|
|
||
|
|
# General Cholesky Delete.
|
||
|
|
# Remove an element from the cholesky factorization
|
||
|
|
# m = columns
|
||
|
|
# n = rows
|
||
|
|
#
|
||
|
|
# TODO: put transpose as an option
|
||
|
|
def cholesky_delete(floating[:, :] L, int go_out):
|
||
|
|
cdef:
|
||
|
|
int n = L.shape[0]
|
||
|
|
int m = L.strides[0]
|
||
|
|
floating c, s
|
||
|
|
floating *L1
|
||
|
|
int i
|
||
|
|
|
||
|
|
if floating is float:
|
||
|
|
m /= sizeof(float)
|
||
|
|
else:
|
||
|
|
m /= sizeof(double)
|
||
|
|
|
||
|
|
# delete row go_out
|
||
|
|
L1 = &L[0, 0] + (go_out * m)
|
||
|
|
for i in range(go_out, n-1):
|
||
|
|
_copy(i + 2, L1 + m, 1, L1, 1)
|
||
|
|
L1 += m
|
||
|
|
|
||
|
|
L1 = &L[0, 0] + (go_out * m)
|
||
|
|
for i in range(go_out, n-1):
|
||
|
|
_rotg(L1 + i, L1 + i + 1, &c, &s)
|
||
|
|
if L1[i] < 0:
|
||
|
|
# Diagonals cannot be negative
|
||
|
|
L1[i] = fabs(L1[i])
|
||
|
|
c = -c
|
||
|
|
s = -s
|
||
|
|
|
||
|
|
L1[i + 1] = 0. # just for cleanup
|
||
|
|
L1 += m
|
||
|
|
|
||
|
|
_rot(n - i - 2, L1 + i, m, L1 + i + 1, m, c, s)
|
||
|
|
|
||
|
|
|
||
|
|
def sum_parallel(const floating [:] array, int n_threads):
|
||
|
|
"""Parallel sum, always using float64 internally."""
|
||
|
|
cdef:
|
||
|
|
float64_t out = 0.
|
||
|
|
int i = 0
|
||
|
|
|
||
|
|
for i in prange(
|
||
|
|
array.shape[0], schedule='static', nogil=True, num_threads=n_threads
|
||
|
|
):
|
||
|
|
out += array[i]
|
||
|
|
|
||
|
|
return out
|