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#cython: embedsignature=True
#cython: language_level=3
import numpy
cimport numpy as np
import cython
cdef extern from "numpy/npy_math.h":
bint npy_isnan(double x)
from numpy cimport NPY_FLOAT64 as NPY_float64
@cython.boundscheck(False)
@cython.wraparound(False)
def valuecount(np.ndarray[np.float64_t, ndim=2] a not None):
"""Count the occurrences of each value.
It does so in-place, on a 2-d array of shape (2, N); the first row
contains values and the second contains weights (1's, if unweighted).
The array should be sorted by the elements in the first row (e.g.
a.sort(axis=0)). The function 'compresses' the array by merging
consecutive columns with the same value in the first row, and adding
the corresponding weights in the second row.
Examples
--------
>>> a = np.array([[1, 1, 2, 3, 3], [0.1, 0.2, 0.3, 0.4, 0.5]])
>>> _orange.valuecount(a)
[[ 1. 2. 3. ]
[ 0.3 0.3 0.9]]
"""
cdef np.npy_intp *dim
dim = np.PyArray_DIMS(a)
if dim[0] != 2:
raise ValueError("valuecount expects an array with shape (2, N)")
cdef Py_ssize_t N = dim[1]
cdef Py_ssize_t src
if N == 0 or npy_isnan(a[0, 0]):
return a[:, :0]
for src in range(1, N):
if a[0, src] == a[0, src - 1] or npy_isnan(a[0, src]):
break
else:
return a
cdef int dst = src - 1
for src in range(src, N):
if a[0, src] != a[0, src]:
break
if a[0, src] == a[0, dst]:
a[1, dst] += a[1, src]
else:
dst += 1
a[0, dst] = a[0, src]
a[1, dst] = a[1, src]
return a[:, :dst + 1]
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