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Module « numpy »

Fonction bitwise_count - module numpy

Signature de la fonction bitwise_count

def bitwise_count(*args, **kwargs) 

Description

help(numpy.bitwise_count)

bitwise_count(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature])

Computes the number of 1-bits in the absolute value of ``x``.
Analogous to the builtin `int.bit_count` or ``popcount`` in C++.

Parameters
----------
x : array_like, unsigned int
    Input array.
out : ndarray, None, or tuple of ndarray and None, optional
    A location into which the result is stored. If provided, it must have
    a shape that the inputs broadcast to. If not provided or None,
    a freshly-allocated array is returned. A tuple (possible only as a
    keyword argument) must have length equal to the number of outputs.
where : array_like, optional
    This condition is broadcast over the input. At locations where the
    condition is True, the `out` array will be set to the ufunc result.
    Elsewhere, the `out` array will retain its original value.
    Note that if an uninitialized `out` array is created via the default
    ``out=None``, locations within it where the condition is False will
    remain uninitialized.
**kwargs
    For other keyword-only arguments, see the
    :ref:`ufunc docs <ufuncs.kwargs>`.

Returns
-------
y : ndarray
    The corresponding number of 1-bits in the input.
    Returns uint8 for all integer types
    This is a scalar if `x` is a scalar.

References
----------
.. [1] https://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetParallel

.. [2] Wikipedia, "Hamming weight",
       https://en.wikipedia.org/wiki/Hamming_weight

.. [3] http://aggregate.ee.engr.uky.edu/MAGIC/#Population%20Count%20(Ones%20Count)

Examples
--------
>>> import numpy as np
>>> np.bitwise_count(1023)
np.uint8(10)
>>> a = np.array([2**i - 1 for i in range(16)])
>>> np.bitwise_count(a)
array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15],
      dtype=uint8)

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