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Module « numpy.matlib »

Fonction kron - module numpy.matlib

Signature de la fonction kron

def kron(a, b) 

Description

help(numpy.matlib.kron)

Kronecker product of two arrays.

Computes the Kronecker product, a composite array made of blocks of the
second array scaled by the first.

Parameters
----------
a, b : array_like

Returns
-------
out : ndarray

See Also
--------
outer : The outer product

Notes
-----
The function assumes that the number of dimensions of `a` and `b`
are the same, if necessary prepending the smallest with ones.
If ``a.shape = (r0,r1,..,rN)`` and ``b.shape = (s0,s1,...,sN)``,
the Kronecker product has shape ``(r0*s0, r1*s1, ..., rN*SN)``.
The elements are products of elements from `a` and `b`, organized
explicitly by::

    kron(a,b)[k0,k1,...,kN] = a[i0,i1,...,iN] * b[j0,j1,...,jN]

where::

    kt = it * st + jt,  t = 0,...,N

In the common 2-D case (N=1), the block structure can be visualized::

    [[ a[0,0]*b,   a[0,1]*b,  ... , a[0,-1]*b  ],
     [  ...                              ...   ],
     [ a[-1,0]*b,  a[-1,1]*b, ... , a[-1,-1]*b ]]


Examples
--------
>>> import numpy as np
>>> np.kron([1,10,100], [5,6,7])
array([  5,   6,   7, ..., 500, 600, 700])
>>> np.kron([5,6,7], [1,10,100])
array([  5,  50, 500, ...,   7,  70, 700])

>>> np.kron(np.eye(2), np.ones((2,2)))
array([[1.,  1.,  0.,  0.],
       [1.,  1.,  0.,  0.],
       [0.,  0.,  1.,  1.],
       [0.,  0.,  1.,  1.]])

>>> a = np.arange(100).reshape((2,5,2,5))
>>> b = np.arange(24).reshape((2,3,4))
>>> c = np.kron(a,b)
>>> c.shape
(2, 10, 6, 20)
>>> I = (1,3,0,2)
>>> J = (0,2,1)
>>> J1 = (0,) + J             # extend to ndim=4
>>> S1 = (1,) + b.shape
>>> K = tuple(np.array(I) * np.array(S1) + np.array(J1))
>>> c[K] == a[I]*b[J]
True

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