On Thu, Nov 26, 2009 at 2:44 PM, Wayne Watson <sierra_mtnv...@sbcglobal.net> wrote: > I decided to try some example code from Subject. > > import numpy > import pylab > # Build a vector of 10000 normal deviates with variance 0.5^2 and mean 2 > mu, sigma = 2, 0.5 > v = numpy.random.normal(mu,sigma,10000) > # Plot a normalized histogram with 50 bins > pylab.hist(v, bins=50, normed=1) # matplotlib version (plot) > pylab.show() > # Compute the histogram with numpy and then plot it > (n, bins) = numpy.histogram(v, bins=50, normed=1) # NumPy version (no plot) > pylab.plot(.5*(bins[1:]+bins[:-1]), n) > pylab.show() > > After the histogram is displayed how do I get to the plot? > Where is histogram described in some detail? Normalized? > The histogram x-axis goes from 0 to 4.5. How does that happen? > Is v is two dimensional? What if it's one dimensional?
some quick answers: matlplotlib's histogram uses numpy histogram for the calculations, options are pretty well explained in the numpy docs, matplotlib has docs and examples for the display. If I use numpy.histogram, then, I think, I used bar plot for the display (scipy.stats.tutorial might also have an example where I had taken the pattern from somewhere else) numpy also has 2d and multidimensional histogram, but I don't know if the new 3d features of matplotlib can display them. Josef > > > > -- > Wayne Watson (Watson Adventures, Prop., Nevada City, CA) > > (121.015 Deg. W, 39.262 Deg. N) GMT-8 hr std. time) > Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet > > 350 350 350 350 350 350 350 350 350 350 > Make the number famous. See 350.org > The major event has passed, but keep the number alive. > > Web Page: <www.speckledwithstars.net/> > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
