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Module « numpy.matlib »

Fonction unpackbits - module numpy.matlib

Signature de la fonction unpackbits

Description

help(numpy.matlib.unpackbits)

unpackbits(a, /, axis=None, count=None, bitorder='big')

Unpacks elements of a uint8 array into a binary-valued output array.

Each element of `a` represents a bit-field that should be unpacked
into a binary-valued output array. The shape of the output array is
either 1-D (if `axis` is ``None``) or the same shape as the input
array with unpacking done along the axis specified.

Parameters
----------
a : ndarray, uint8 type
   Input array.
axis : int, optional
    The dimension over which bit-unpacking is done.
    ``None`` implies unpacking the flattened array.
count : int or None, optional
    The number of elements to unpack along `axis`, provided as a way
    of undoing the effect of packing a size that is not a multiple
    of eight. A non-negative number means to only unpack `count`
    bits. A negative number means to trim off that many bits from
    the end. ``None`` means to unpack the entire array (the
    default). Counts larger than the available number of bits will
    add zero padding to the output. Negative counts must not
    exceed the available number of bits.
bitorder : {'big', 'little'}, optional
    The order of the returned bits. 'big' will mimic bin(val),
    ``3 = 0b00000011 => [0, 0, 0, 0, 0, 0, 1, 1]``, 'little' will reverse
    the order to ``[1, 1, 0, 0, 0, 0, 0, 0]``.
    Defaults to 'big'.

Returns
-------
unpacked : ndarray, uint8 type
   The elements are binary-valued (0 or 1).

See Also
--------
packbits : Packs the elements of a binary-valued array into bits in
           a uint8 array.

Examples
--------
>>> import numpy as np
>>> a = np.array([[2], [7], [23]], dtype=np.uint8)
>>> a
array([[ 2],
       [ 7],
       [23]], dtype=uint8)
>>> b = np.unpackbits(a, axis=1)
>>> b
array([[0, 0, 0, 0, 0, 0, 1, 0],
       [0, 0, 0, 0, 0, 1, 1, 1],
       [0, 0, 0, 1, 0, 1, 1, 1]], dtype=uint8)
>>> c = np.unpackbits(a, axis=1, count=-3)
>>> c
array([[0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0],
       [0, 0, 0, 1, 0]], dtype=uint8)

>>> p = np.packbits(b, axis=0)
>>> np.unpackbits(p, axis=0)
array([[0, 0, 0, 0, 0, 0, 1, 0],
       [0, 0, 0, 0, 0, 1, 1, 1],
       [0, 0, 0, 1, 0, 1, 1, 1],
       [0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)
>>> np.array_equal(b, np.unpackbits(p, axis=0, count=b.shape[0]))
True

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