Vous êtes un professionnel et vous avez besoin d'une formation ? Programmation Python
Les compléments Voir le programme détaillé

Module « numpy »

Fonction vdot - module numpy

Signature de la fonction vdot

Description

help(numpy.vdot)

vdot(a, b, /)

Return the dot product of two vectors.

The `vdot` function handles complex numbers differently than `dot`:
if the first argument is complex, it is replaced by its complex conjugate
in the dot product calculation. `vdot` also handles multidimensional
arrays differently than `dot`: it does not perform a matrix product, but
flattens the arguments to 1-D arrays before taking a vector dot product.

Consequently, when the arguments are 2-D arrays of the same shape, this
function effectively returns their
`Frobenius inner product <https://en.wikipedia.org/wiki/Frobenius_inner_product>`_
(also known as the *trace inner product* or the *standard inner product*
on a vector space of matrices).

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
--------
>>> import numpy as np
>>> 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

Vous êtes un professionnel et vous avez besoin d'une formation ? Sensibilisation à
l'Intelligence Artificielle Voir le programme détaillé