Previous topic

numpy.negative

Next topic

numpy.divide

numpy.multiply

numpy.multiply(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'multiply'>

Multiply arguments element-wise.

Parameters:
x1, x2 : array_like

Input arrays to be multiplied.

out : ndarray, None, or tuple of ndarray and None, optional

A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

where : array_like, optional

Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.

**kwargs

For other keyword-only arguments, see the ufunc docs.

Returns:
y : ndarray

The product of x1 and x2, element-wise. Returns a scalar if both x1 and x2 are scalars. This is a scalar if both x1 and x2 are scalars.

Notes

Equivalent to x1 * x2 in terms of array broadcasting.

Examples

>>> np.multiply(2.0, 4.0)
8.0
>>> x1 = np.arange(9.0).reshape((3, 3))
>>> x2 = np.arange(3.0)
>>> np.multiply(x1, x2)
array([[  0.,   1.,   4.],
       [  0.,   4.,  10.],
       [  0.,   7.,  16.]])