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I have, I suspect, an elementary problem that I am too inexperienced to resolve. I have two numpy arrays, each representing the values of a specific property of a set of cells. Now, I want to associate the two values for each cell, that is for each index of the numpy array. But I want to associate them ROUGHLY, that means, APPROXIMATELY, so that there is a weak, linear correlation between the values representing one property and the values representing the second property of each individual cell. Up to now I have used the following procedure. I have divided each population of values into four segments based on the value of the standard deviation thus. 1. values > mean + 1 std (sigma) 2. values > mean but < mean + 1 std (sigma) 3. values < mean but > mean + 1 std (sigma) 4. values < mean + 1 std (sigma). Then I randomly select a value from group 1 for the first property and I associate it with a randomly selected sample of the second property from its group 1. And so on through the total population. This gave me a very rough linear association between the two properties, but I am wondering whether I can do it in a simpler and better way. -- Sydney _________ Professor Sydney Shall Department of Haematology/Oncology Phone: +(0)2078489200 E-Mail: sydney.shall [Correspondents outside the College should add @kcl.ac.uk] _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor