python - Plotting histogram of brownian motion? -

my task plot histogram of simulation of brownian motion. thankfully, i've made program simulates brownian motion, , plots on scatter plot function of time , distance. output looks like:

however, need convert histogram, 5 different locations (e.g: histogram @ t=0,1,2,3,4).

currently packages have numpy, mattplotlib, , scipy. have seen examples of how plot normal distribution, how plot distribution data have gathered?

here code have far: http://pastebin.com/aepqdqd2

(since couldn't post 2 links, had paste both files together, first 1 one computation brownian motion , second 1 outputs graph on imgur link)

this not homework, given credit problem, , instructor explicitly said allowed use whatever information can.

thanks.

use pylab.hist this, after calculating index of time point you're interested in, it:

# -*- coding: utf-8 -*- import numpy pylab import plot, xlabel, ylabel, title, grid, show, hist, legend brownian import brownian  #this code performs main iteration of euler marayuma process, t=0 t=10.  def main():  # wiener process parameter.     delta = 2     # total time.     t = 10.0     # number of steps.     n = 500     # time step size     dt = t/n     # number of realizations generate.     m = 1000     # create empty array store realizations.     x = numpy.empty((m,n+1))     # initial values of x.     x[:, 0] = 0      brownian(x[:,0], n, dt, delta, out=x[:,1:])     t = numpy.linspace(0.0, n*dt, n+1)      # time points of interest     ts = [4., 3., 2., 1.]     t in ts:         = int(t/t * n)         hist(x[:, it], alpha=0.7, label='%.1f s' % t, normed=true)     legend()     show()  if __name__ == "__main__":     main() 

(you may care plot histograms on separate figures and/or make bin size constant across time points.)