#
# * The source code in this file is based on the soure code of NumPy.
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# * Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
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# used to endorse or promote products derived from this software
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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import nlcpy
[ドキュメント]def count_nonzero(a, axis=None, keepdims=False):
"""Counts the number of non-zero values in the array ``a``.
The word "non-zero" is in reference to the Python 2.x built-in method
``__nonzero__()`` (renamed ``__bool__()`` in Python 3.x) of Python objects that
tests an object's "truthfulness". For example, any number is considered truthful
if it is nonzero, whereas any string is considered truthful if it is not the empty
string. Thus, this function (recursively) counts how many elements in a (and in
sub-arrays thereof) have their ``__nonzero__()`` or ``__bool__()`` method evaluated
to ``True``.
Parameters
----------
a : array_like
The array for which to count non-zeros.
axis : int or tuple, optional
Axis or tuple of axes along which to count non-zeros. Default is None, meaning
that non-zeros will be counted along a flattened version of ``a``.
keepdims : bool, optional
If this is set to True, the axes that are counted are left in the result as
dimensions with size one. With this option, the result will broadcast correctly
against the input array.
Returns
-------
count : int or array of int
Number of non-zero values in the array along a given axis.
Otherwise, the total number of non-zero values in the array is returned.
See Also
--------
nonzero : Returns the indices of the elements that are non-zero.
Examples
--------
>>> import nlcpy as vp
>>> vp.count_nonzero(vp.eye(4))
array(4)
>>> a = vp.array([[0, 1, 7, 0], [3, 0, 2, 19]])
>>> vp.count_nonzero(a)
array(5)
>>> vp.count_nonzero(a, axis=0)
array([1, 1, 2, 1])
>>> vp.count_nonzero(a, axis=1)
array([2, 3])
>>> vp.count_nonzero(a, axis=1, keepdims=True)
array([[2],
[3]])
"""
a = nlcpy.asarray(a).astype('?', copy=False)
return a.sum(axis=axis, dtype=nlcpy.intp, keepdims=keepdims)