Vectorizing a Numpy slice operation

Question

Say I have a Numpy vector,

A = zeros(100)

and I divide it into subvectors by a list of breakpoints which index into A, for ins

Answer 1

There really isn't a single answer to your question, but several techniques that you can use as building blocks. Another one you may find helpful:

All numpy ufuncs have a .reduceat method, which you can use to your advantage for some of your calculations:

>>> a = np.arange(100)
>>> breaks = np.linspace(0, 100, 11, dtype=np.intp)
>>> counts = np.diff(breaks)
>>> counts
array([10, 10, 10, 10, 10, 10, 10, 10, 10, 10])
>>> sums = np.add.reduceat(a, breaks[:-1], dtype=np.float)
>>> sums
array([  45.,  145.,  245.,  345.,  445.,  545.,  645.,  745.,  845.,  945.])
>>> sums / counts  # i.e. the mean
array([  4.5,  14.5,  24.5,  34.5,  44.5,  54.5,  64.5,  74.5,  84.5,  94.5])