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 theinput array. If axis is negative it counts from the last to thefirst axis. If axis is a tuple of ints, a product is performed on all of theaxes specified in the tuple instead of a single axis or all theaxes as before. - dtype:dtype, optional
The type of the returned array, as well as of the accumulator inwhich the elements are multiplied. The dtype ofa is used bydefault unlessa has an integer dtype of less precision than thedefault platform integer. In that case, ifa is signed then theplatform integer is used while ifa is unsigned then an unsignedinteger of the same precision as the platform integer is used. - out:ndarray, optional
Alternative output array in which to place the result. It must havethe same shape as the expected output, but the type of the outputvalues will be cast if necessary. - keepdims:bool, optional
If this is set to True, the axes which are reduced are left in theresult as dimensions with size one. With this option, the resultwill broadcast correctly against the input array. If the default value is passed, thenkeepdims will not bepassed through to theprod method of sub-classes ofndarray, however any non-default value will be. If thesub-class’ method does not implementkeepdims anyexceptions will be raised. - initial:scalar, optional
The starting value for this product. Seereduce for details.
|
|---|
| Returns: | - product_along_axis:ndarray, see
dtype parameter above. An array shaped asa but with the specified axis removed.Returns a reference toout if specified.
|
|---|
See also
ndarray.prod- equivalent method
numpy.doc.ufuncs- Section “Output arguments”
Notes
Arithmetic is modular when using integer types, and no error israised on overflow. That means that, on a 32-bit platform:
>>>x=np.array([536870910,536870910,536870910,536870910])>>>np.prod(x)# random16
The product of an empty array is the neutral element 1:
Examples
By default, calculate the product of all elements:
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.])
If the type ofx is unsigned, then the output type isthe unsigned platform integer:
>>>x=np.array([1,2,3],dtype=np.uint8)>>>np.prod(x).dtype==np.uintTrue
Ifx is of a signed integer type, then the output typeis the default platform integer:
>>>x=np.array([1,2,3],dtype=np.int8)>>>np.prod(x).dtype==intTrue
You can also start the product with a value other than one:
>>>np.prod([1,2],initial=5)10
