Author thomasahle
Recipients steven.daprano, terry.reedy, thomasahle, tim.peters, vajrasky
Date 2014-05-31.09:15:25
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Message-id <1401527727.26.0.430936232383.issue21592@psf.upfronthosting.co.za>
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I think "minimize expected-case time" is a good goal. If we wanted "minimize worst-case time" we would have to use k-means rather than quickselect.

My trials on random data, where sort arguably has a disadvantage, suggests sorting is about twice as fast for most input sizes. With pypy quick-select is easily 5-10 times faster, which I take as a suggestion that a C-implementation might be worth a try.

For designing a realistic test-suite, I suppose we need to look at what tasks medians are commonly used for. I'm thinking median filters from image processing, medians clustering, robust regressing, anything else?
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2014-05-31 09:15:27thomasahlesetrecipients: + thomasahle, tim.peters, terry.reedy, steven.daprano, vajrasky
2014-05-31 09:15:27thomasahlesetmessageid: <1401527727.26.0.430936232383.issue21592@psf.upfronthosting.co.za>
2014-05-31 09:15:27thomasahlelinkissue21592 messages
2014-05-31 09:15:25thomasahlecreate