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Module « numpy.matlib »

Fonction cumulative_prod - module numpy.matlib

Signature de la fonction cumulative_prod

def cumulative_prod(x, /, *, axis=None, dtype=None, out=None, include_initial=False) 

Description

help(numpy.matlib.cumulative_prod)

Return the cumulative product of elements along a given axis.

This function is an Array API compatible alternative to `numpy.cumprod`.

Parameters
----------
x : array_like
    Input array.
axis : int, optional
    Axis along which the cumulative product is computed. The default
    (None) is only allowed for one-dimensional arrays. For arrays
    with more than one dimension ``axis`` is required.
dtype : dtype, optional
    Type of the returned array, as well as of the accumulator in which
    the elements are multiplied.  If ``dtype`` is not specified, it
    defaults to the dtype of ``x``, unless ``x`` has an integer dtype
    with a precision less than that of the default platform integer.
    In that case, the default platform integer is used instead.
out : ndarray, optional
    Alternative output array in which to place the result. It must
    have the same shape and buffer length as the expected output
    but the type of the resulting values will be cast if necessary.
    See :ref:`ufuncs-output-type` for more details.
include_initial : bool, optional
    Boolean indicating whether to include the initial value (ones) as
    the first value in the output. With ``include_initial=True``
    the shape of the output is different than the shape of the input.
    Default: ``False``.

Returns
-------
cumulative_prod_along_axis : ndarray
    A new array holding the result is returned unless ``out`` is
    specified, in which case a reference to ``out`` is returned. The
    result has the same shape as ``x`` if ``include_initial=False``.

Notes
-----
Arithmetic is modular when using integer types, and no error is
raised on overflow.

Examples
--------
>>> a = np.array([1, 2, 3])
>>> np.cumulative_prod(a)  # intermediate results 1, 1*2
...                        # total product 1*2*3 = 6
array([1, 2, 6])
>>> a = np.array([1, 2, 3, 4, 5, 6])
>>> np.cumulative_prod(a, dtype=float) # specify type of output
array([   1.,    2.,    6.,   24.,  120.,  720.])

The cumulative product for each column (i.e., over the rows) of ``b``:

>>> b = np.array([[1, 2, 3], [4, 5, 6]])
>>> np.cumulative_prod(b, axis=0)
array([[ 1,  2,  3],
       [ 4, 10, 18]])

The cumulative product for each row (i.e. over the columns) of ``b``:

>>> np.cumulative_prod(b, axis=1)
array([[  1,   2,   6],
       [  4,  20, 120]])

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