Module « numpy.matlib »

Fonction prod - module numpy.matlib

Signature de la fonction prod

def prod(a, axis=None, dtype=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>) 

Description

prod.__doc__

    Return the product of array elements over a given axis.

    Parameters
    ----------
    a : array_like
        Input data.
    axis : None or int or tuple of ints, optional
        Axis or axes along which a product is performed.  The default,
        axis=None, will calculate the product of all the elements in the
        input array. If axis is negative it counts from the last to the
        first axis.

        .. versionadded:: 1.7.0

        If axis is a tuple of ints, a product is performed on all of the
        axes specified in the tuple instead of a single axis or all the
        axes as before.
    dtype : dtype, optional
        The type of the returned array, as well as of the accumulator in
        which the elements are multiplied.  The dtype of `a` is used by
        default unless `a` has an integer dtype of less precision than the
        default platform integer.  In that case, if `a` is signed then the
        platform integer is used while if `a` is unsigned then an unsigned
        integer of the same precision as the platform integer is used.
    out : ndarray, optional
        Alternative output array in which to place the result. It must have
        the same shape as the expected output, but the type of the output
        values will be cast if necessary.
    keepdims : bool, optional
        If this is set to True, the axes which are reduced are left in the
        result as dimensions with size one. With this option, the result
        will broadcast correctly against the input array.

        If the default value is passed, then `keepdims` will not be
        passed through to the `prod` method of sub-classes of
        `ndarray`, however any non-default value will be.  If the
        sub-class' method does not implement `keepdims` any
        exceptions will be raised.
    initial : scalar, optional
        The starting value for this product. See `~numpy.ufunc.reduce` for details.

        .. versionadded:: 1.15.0

    where : array_like of bool, optional
        Elements to include in the product. See `~numpy.ufunc.reduce` for details.

        .. versionadded:: 1.17.0

    Returns
    -------
    product_along_axis : ndarray, see `dtype` parameter above.
        An array shaped as `a` but with the specified axis removed.
        Returns a reference to `out` if specified.

    See Also
    --------
    ndarray.prod : equivalent method
    :ref:`ufuncs-output-type`

    Notes
    -----
    Arithmetic is modular when using integer types, and no error is
    raised on overflow.  That means that, on a 32-bit platform:

    >>> x = np.array([536870910, 536870910, 536870910, 536870910])
    >>> np.prod(x)
    16 # may vary

    The product of an empty array is the neutral element 1:

    >>> np.prod([])
    1.0

    Examples
    --------
    By default, calculate the product of all elements:

    >>> np.prod([1.,2.])
    2.0

    Even when the input array is two-dimensional:

    >>> np.prod([[1.,2.],[3.,4.]])
    24.0

    But we can also specify the axis over which to multiply:

    >>> np.prod([[1.,2.],[3.,4.]], axis=1)
    array([  2.,  12.])

    Or select specific elements to include:

    >>> np.prod([1., np.nan, 3.], where=[True, False, True])
    3.0

    If the type of `x` is unsigned, then the output type is
    the unsigned platform integer:

    >>> x = np.array([1, 2, 3], dtype=np.uint8)
    >>> np.prod(x).dtype == np.uint
    True

    If `x` is of a signed integer type, then the output type
    is the default platform integer:

    >>> x = np.array([1, 2, 3], dtype=np.int8)
    >>> np.prod(x).dtype == int
    True

    You can also start the product with a value other than one:

    >>> np.prod([1, 2], initial=5)
    10