This is documentation for an old release of NumPy (version 1.6.0). Read this page Search for this page in the documentation of the latest stable release (version > 1.17).

numpy.vdot

numpy.vdot(a, b)

Return the dot product of two vectors.

The vdot(a, b) function handles complex numbers differently than dot(a, b). If the first argument is complex the complex conjugate of the first argument is used for the calculation of the dot product.

Note that vdot handles multidimensional arrays differently than dot: it does not perform a matrix product, but flattens input arguments to 1-D vectors first. Consequently, it should only be used for vectors.

Parameters :

a : array_like

If a is complex the complex conjugate is taken before calculation of the dot product.

b : array_like

Second argument to the dot product.

Returns :

output : ndarray

Dot product of a and b. Can be an int, float, or complex depending on the types of a and b.

See also

dot

Return the dot product without using the complex conjugate of the first argument.

Examples

>>> a = np.array([1+2j,3+4j])
>>> b = np.array([5+6j,7+8j])
>>> np.vdot(a, b)
(70-8j)
>>> np.vdot(b, a)
(70+8j)

Note that higher-dimensional arrays are flattened!

>>> a = np.array([[1, 4], [5, 6]])
>>> b = np.array([[4, 1], [2, 2]])
>>> np.vdot(a, b)
30
>>> np.vdot(b, a)
30
>>> 1*4 + 4*1 + 5*2 + 6*2
30