Re: [Numpy-discussion] repmat equivalent?

[Travis O. <oli...@ie...>]

Albert Strasheim wrote:

>Hello all
>
>I recently started using NumPy and one function that I am really
>missing from MATLAB/Octave is repmat. This function is very useful for
>implementing algorithms as matrix multiplications instead of for
>loops.
>  
>
There is a function in scipy.linalg called kron that could be brought 
over which can do a repmat.


In file: /usr/lib/python2.4/site-packages/scipy/linalg/basic.py

def kron(a,b):
    """kronecker product of a and b

    Kronecker product of two matrices is block matrix
    [[ a[ 0 ,0]*b, a[ 0 ,1]*b, ... , a[ 0 ,n-1]*b  ],
     [ ...                                   ...   ],
     [ a[m-1,0]*b, a[m-1,1]*b, ... , a[m-1,n-1]*b  ]]
    """
    if not a.flags['CONTIGUOUS']:
        a = reshape(a, a.shape)
    if not b.flags['CONTIGUOUS']:
        b = reshape(b, b.shape)
    o = outerproduct(a,b)
    o=o.reshape(a.shape + b.shape)
    return concatenate(concatenate(o, axis=1), axis=1)


Thus,

kron(ones((2,3)), arr)

 >>> sl.kron(ones((2,3)),arr)
array([[1, 2, 1, 2, 1, 2],
       [3, 4, 3, 4, 3, 4],
       [1, 2, 1, 2, 1, 2],
       [3, 4, 3, 4, 3, 4]])

gives you the equivalent of

repmat(arr, 2,3)

We could bring this over from scipy into numpy as it is simple enough.

It has a multidimensional extension (i.e. you can pass in a and b as 
higher dimensional arrays),  But, don't ask me to explain it to you 
because I can't without further study....

-Travis