From: <hu...@ya...> - 2006-05-26 18:27:11
|
Here a sample: the data are in the file data.dat join. In [1]: import pylab In [2]: import scipy In [3]: import scipy.stats In [4]: data1,data2=pylab.load('data.dat',unpack=True) In [5]: pylab.hist(data1,20) (Out[5]: array([ 4, 6, 23, 52, 90, 128, 184, 244, 283, 293, 297, 330, 321, 231, 188, 140, 94, 48, 29, 15]), array([ 0.00998046, 0.01054459, 0.01110872, 0.01167285, 0.01223698, 0.01280111, 0.01336524, 0.01392937, 0.0144935 , 0.01505763, 0.01562176, 0.01618589, 0.01675002, 0.01731415, 0.01787828, 0.01844241, 0.01900654, 0.01957067, 0.0201348 , 0.02069894]), <a list of 20 Patch objects>) In [6]: scipy.stats.histogram(data1,20) Out[6]: (array([ 1, 7, 17, 43, 75, 126, 185, 248, 303, 302, 314, 353, 315, 241, 178, 145, 70, 51, 20, 6]), 0.0096835454084847374, 0.00059382155039052636, 0) > humufr> Hi, just a small question about histogram. I saw that the > humufr> result of the hist function from pylab and histogram from > humufr> numpy+scipy can be slightly different when the array is > humufr> big and with real data (not integer). I'll probably told > humufr> something stupid but perhaps that will be good to have > humufr> consistancies between both function, won't it? > > Complete example, please... > > JDH > > > ------------------------------------------------------- > All the advantages of Linux Managed Hosting--Without the Cost and Risk! > Fully trained technicians. The highest number of Red Hat certifications in > the hosting industry. Fanatical Support. Click to learn more > http://sel.as-us.falkag.net/sel?cmd=lnk&kid=107521&bid=248729&dat=121642 > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users |