numpy.ma.prod()

numpy.ma.prod(self, axis=None, dtype=None, out=None) =

Return the product of the array elements over the given axis. Masked elements are set to 1 internally for computation.

Parameters:

Parameters:	axis : {None, int}, optional Axis over which the product is taken. If None is used, then the product is over all the array elements. dtype : {None, dtype}, optional Determines the type of the returned array and of the accumulator where the elements are multiplied. If `dtype` has the value `None` and the type of a is an integer type of precision less than the default platform integer, then the default platform integer precision is used. Otherwise, the dtype is the same as that of a. out : {None, array}, optional Alternative output array in which to place the result. It must have the same shape as the expected output but the type will be cast if necessary.
Returns:	product_along_axis : {array, scalar}, see dtype parameter above. Returns an array whose shape is the same as a with the specified axis removed. Returns a 0d array when a is 1d or axis=None. Returns a reference to the specified output array if specified.

axis : {None, int}, optional

Axis over which the product is taken. If None is used, then the product is over all the array elements.

dtype : {None, dtype}, optional

Determines the type of the returned array and of the accumulator where the elements are multiplied. If dtype has the value None and the type of a is an integer type of precision less than the default platform integer, then the default platform integer precision is used. Otherwise, the dtype is the same as that of a.

out : {None, array}, optional

Alternative output array in which to place the result. It must have the same shape as the expected output but the type will be cast if necessary.

Returns:

product_along_axis : {array, scalar}, see dtype parameter above.

Returns an array whose shape is the same as a with the specified axis removed. Returns a 0d array when a is 1d or axis=None. Returns a reference to the specified output array if specified.

Notes

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

Examples

>>> np.prod([1.,2.])
2.0
>>> np.prod([1.,2.], dtype=np.int32)
2
>>> np.prod([[1.,2.],[3.,4.]])
24.0
>>> np.prod([[1.,2.],[3.,4.]], axis=1)
array([  2.,  12.])

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.ma.prod.html

doc_NumPy

2017-01-10 18:15:45

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