[Numpy-discussion] NumPy Histogram for Tentative NumPy Tutorial Questions

[josef.pktd at gmail.com]

On Thu, Nov 26, 2009 at 2:44 PM, Wayne Watson
<sierra_mtnview at 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

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