[Numpy-discussion] general version of repmat?

[Bill Baxter]

Here's a new version of 'reparray'.

I tested the previous version against 'repmat' for the 2d case and
found it to be as much as 3x slower in some instances.  Ick.  So I
redid it using the approach repmat uses -- reshape() and repeat()
rather than concatenate().  Now it's very nearly as fast as repmat for
the 2-d case.

def reparray(A, tup):
    if numpy.isscalar(tup):
        tup = (tup,)
    d = len(tup)
    c = numpy.array(A,copy=False,subok=True,ndmin=d)
    shape = list(c.shape)
    n = c.size
    for i, nrep in enumerate(tup):
        if nrep!=1:
            c = c.reshape(-1,n).repeat(nrep,0)
        dim_in = shape[i]
        dim_out = dim_in*nrep
        shape[i] = dim_out
        n /= dim_in
    return c.reshape(shape)

The full file with tests and timing code is attached.

One thing I noticed while doing this was that repmat doesn't preserve
subclasses.  Which is funny considering 'mat' is part of the name and
it only works on 2-d arrays.  Using asanyarray() instead of asarray()
in the first line should fix that.

--Bill
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