Hi Nicole, Le 27/03/2012 11:12, Nicole Stoffels a écrit : > *if __name__ == '__main__': > > data_records = random.random((459375, 24)) > correlation = corrcoef(data_records)*
May I assume that your data_record is made of 24 different variables of which you have 459375 observations ? If this is so and if you expect corrcoeff to return a 24*24 matrix, you need to either transpose data_records : >>> correlation = corrcoef(data_records.T) or use the rowvar=0 argument (see np.corrcoef or np.cov docstring) >>> correlation = corrcoef(data_records, rowvar = 0) Both work on my computer, while your example indeed leads to a MemoryError (because shape 459375*459375 would be a decently big matrix...) I don't know if it's your case, but for those used to the Matlab (and textbooks) convention of having variables stored in columns, the default behaviour of numpy's covariance function is a bit surprising. I guess historical reasons are involved in this choice. Just a matter of getting used to it ! Best, Pierre
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