numpy.ma.inner — NumPy v1.13 Manual (original) (raw)
numpy.ma. inner(a, b)[source]¶
Inner product of two arrays.
Ordinary inner product of vectors for 1-D arrays (without complex conjugation), in higher dimensions a sum product over the last axes.
| Parameters: | a, b : array_like If a and b are nonscalar, their last dimensions must match. |
|---|---|
| Returns: | out : ndarray out.shape = a.shape[:-1] + b.shape[:-1] |
| Raises: | ValueError If the last dimension of a and b has different size. |
See also
tensordot
Sum products over arbitrary axes.
Generalised matrix product, using second last dimension of b.
einsum
Einstein summation convention.
Notes
Masked values are replaced by 0.
Examples
Ordinary inner product for vectors:
a = np.array([1,2,3]) b = np.array([0,1,0]) np.inner(a, b) 2
A multidimensional example:
a = np.arange(24).reshape((2,3,4)) b = np.arange(4) np.inner(a, b) array([[ 14, 38, 62], [ 86, 110, 134]])
An example where b is a scalar:
np.inner(np.eye(2), 7) array([[ 7., 0.], [ 0., 7.]])