vdot(a, b, /)

Some inconsistencies with the Dask version may exist.

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.

This docstring was copied from numpy.vdot.

See Also

dot

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

Examples

This example is valid syntax, but we were not able to check execution

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

This example is valid syntax, but we were not able to check execution

>>> np.vdot(b, a)  # doctest: +SKIP
(70+8j)

Note that higher-dimensional arrays are flattened!

This example is valid syntax, but we were not able to check execution

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

This example is valid syntax, but we were not able to check execution

>>> np.vdot(b, a)  # doctest: +SKIP
30

This example is valid syntax, but we were not able to check execution

>>> 1*4 + 4*1 + 5*2 + 6*2  # doctest: +SKIP
30

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.routines.dot dask.array.routines.vdot

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