def prod(a, axis=None, out=None):
"""
Product of array elements over a given axis.
Parameters
----------
a : array_like
Elements to multiply.
axis : None or int or tuple of ints, optional
Axis or axes along which a multiply is performed.
The default (`axis` = `None`) is perform a multiply over all
the dimensions of the input array. `axis` may be negative, in
which case it counts from the last to the first axis.
.. versionadded:: 1.7.0
If this is a tuple of ints, a multiply is performed on multiple
axes, instead of a single axis or all the axes as before.
out : ndarray, optional
Array into which the output is placed. By default, a new array is
created. If `out` is given, it must be of the appropriate shape
(the shape of `a` with `axis` removed, i.e.,
``numpy.delete(a.shape, axis)``). Its type is preserved. See
`doc.ufuncs` (Section "Output arguments") for more details.
Returns
-------
protuct_along_axis : ndarray
An array with the same shape as `a`, with the specified
axis removed. If `a` is a 0-d array, or if `axis` is None, a scalar
is returned. If an output array is specified, a reference to
`out` is returned.
Examples
--------
>>> np.prod([0.5, 1.5])
2.0
>>> np.prod([0.5, 0.7, 0.2, 1.5], dtype=np.int32)
1
>>> np.prod([[0, 1], [0, 5]])
6
>>> np.prod([[0, 1], [0, 5]], axis=0)
array([0, 6])
>>> np.prod([[0, 1], [0, 5]], axis=1)
array([1, 5])
If the accumulator is too small, overflow occurs:
>>> np.ones(128, dtype=np.int8).prod(dtype=np.int8)
-128
"""
if not bhary.check(a) and not bhary.check(out):
return numpy.prod(a, axis=axis,
out=out) #NumPy 1.6 doesn't support axis=None
else:
return ufunc.multiply.reduce(a, axis=axis, out=out)
def prod(a, axis=None, out=None):
"""
Product of array elements over a given axis.
Parameters
----------
a : array_like
Elements to multiply.
axis : None or int or tuple of ints, optional
Axis or axes along which a multiply is performed.
The default (`axis` = `None`) is perform a multiply over all
the dimensions of the input array. `axis` may be negative, in
which case it counts from the last to the first axis.
.. versionadded:: 1.7.0
If this is a tuple of ints, a multiply is performed on multiple
axes, instead of a single axis or all the axes as before.
out : ndarray, optional
Array into which the output is placed. By default, a new array is
created. If `out` is given, it must be of the appropriate shape
(the shape of `a` with `axis` removed, i.e.,
``numpy.delete(a.shape, axis)``). Its type is preserved. See
`doc.ufuncs` (Section "Output arguments") for more details.
Returns
-------
protuct_along_axis : ndarray
An array with the same shape as `a`, with the specified
axis removed. If `a` is a 0-d array, or if `axis` is None, a scalar
is returned. If an output array is specified, a reference to
`out` is returned.
Examples
--------
>>> np.prod([0.5, 1.5])
2.0
>>> np.prod([0.5, 0.7, 0.2, 1.5], dtype=np.int32)
1
>>> np.prod([[0, 1], [0, 5]])
6
>>> np.prod([[0, 1], [0, 5]], axis=0)
array([0, 6])
>>> np.prod([[0, 1], [0, 5]], axis=1)
array([1, 5])
If the accumulator is too small, overflow occurs:
>>> np.ones(128, dtype=np.int8).prod(dtype=np.int8)
-128
"""
if not ndarray.check(a) and not ndarray.check(out):
return numpy.prod(a, axis=axis, out=out)#NumPy 1.6 doesn't support axis=None
else:
return ufunc.multiply.reduce(a, axis=axis, out=out)