On 8/29/06, Mathew Yeates <[EMAIL PROTECTED]> wrote:
> I have an M by N array of floats. Associated with the columns are
> character labels
> ['a','b','b','c','d','e','e','e'] note: already sorted so duplicates
> are contiguous
>
> I want to replace the 2 'b' columns with the sum of the 2 columns.
> Similarly, replace the 3 'e' columns with the sum of the 3 'e' columns.
Make a cumsum of the array. Find the index of the last 'a', last 'b',
etc and make the reduced array from that. Then take the diff of the
columns.
I know that's vague, but so is my understanding of python/numpy.
Or even more vague: make a function that does what you want.
Or you could use searchsorted on the labels to get a sequence of ranges. What you have is a sort of binning applied to columns instead of values in a vector. Or, if the overhead isn't to much, use a dictionary of with (keys: array) entries. Index thru the columns adding keys, when the key is new insert a column copy, when it is already present add the new column to the old one.
Chuck
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