Hi,
I noticed that numpy.random.choice was very slow, with the
replace=False option, and then I noticed it can (for most cases) be
made many hundreds of times faster in Python code:
In [18]: sample = np.random.uniform(size=1000000)
In [19]: timeit np.random.choice(sample, 500, replace=False)
42.1 ms ± 214 µs per loop (mean ± std. dev. of 7 runs, 10
loops each)
IIn [22]: def rc(x, size):
...: n = np.prod(size)
...: n_plus = n * 2
...: inds = np.unique(np.random.randint(0, n_plus+1, size=n_plus))[:n]
...: return x[inds].reshape(size)
In [23]: timeit rc(sample, 500)
86.5 µs ± 421 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)each)
Is there a reason why it's so slow in C? Could something more
intelligent than the above be used to speed it up?
Cheers,
Matthew
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