On Saturday, February 4, 2012, Naresh Pai <n...@uark.edu> wrote: > I am somewhat new to Python (been coding with Matlab mostly). I am trying to > simplify (and expedite) a piece of code that is currently a bottleneck in a larger > code. > I have a large array (7000 rows x 4500 columns) titled say, abc, and I am trying > to find a fast method to count the number of instances of each unique value within > it. All unique values are stored in a variable, say, unique_elem. My current code > is as follows: > import numpy as np > #allocate space for storing element count > elem_count = zeros((len(unique_elem),1)) > #loop through and count number of unique_elem > for i in range(len(unique_elem)): > elem_count[i]= np.sum(reduce(np.logical_or,(abc== x for x in [unique_elem[i]]))) > This loop is bottleneck because I have about 850 unique elements and it takes > about 9-10 minutes. Can you suggest a faster way to do this? > Thank you, > Naresh >
no.unique() can return indices and reverse indices. It would be trivial to histogram the reverse indices using np.histogram(). Does that help? Ben Root
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