SciPy

numpy.ma.masked_array.product

masked_array.product(axis=None, dtype=None, out=None)[source]

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

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.

See also

prod
equivalent function

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.])