Hello! I'd like to know if there is a Sage function to retrieve a distribution of some experimental data. I have a 1D list of measured values and I need to obtain a second list containing the distribution of that data, for example, to fit it with some Gaussian or Poisson curve.
Thanks.
The numpy histogram function will bin values together: http://docs.scipy.org/doc/numpy/refer...
The Sage Timeseries histogram function also bins data: http://www.sagemath.org/doc/reference...
I use matplotlib for that purpose. Have a look at the first example on the page
http://matplotlib.sourceforge.net/exa...
Edit: To get a list use
import numpy as np
import pylab as P
mu, sigma = 200, 25
x = mu + sigma*P.randn(10000)
n, bins, patches = P.hist(x, 50, normed=1, histtype='stepfilled')
P.setp(patches, 'facecolor', 'g', 'alpha', 0.75)
y = P.normpdf( bins, mu, sigma)
l = P.plot(bins, y, 'k--', linewidth=1.5)
print bins
I used the hist() function from Matplotlib also, but does it allow to store the distribution in the list for? The problem is that I need to do some fitting to this distribution, and not only to visualize it.
I have found a way to achieve approximately what I need using the histogram() function from scipy.stats module.
Something like this:
from scipy.stats import histogram
distribution_list = histogram(data_list, numbins=10, defaultlimits=(90,164))
It gives the values for the bins, the first bin start and the bin width. To obtain the distribution list with the actual values for further work (like fitting, plotting, adding to something, etc.) one can do something like this:
from scipy.stats import histogram
distribution_list = histogram(data_list, numbins=10, defaultlimits=(90,164))
actual_distribution = []
i = 0
for bin in distribution_list[0]:
actual_distribution.append((distribution_list[1]+i*distribution_list[2], bin))
i+=1
But maybe there are some other (more simple or built-in or smarter) ways to get a distribution out of a list of numbers?
Thanks.
Asked: 2012-02-03 13:03:20 +0100
Seen: 1,213 times
Last updated: Oct 28 '14
Copyright Sage, 2010. Some rights reserved under creative commons license. Content on this site is licensed under a Creative Commons Attribution Share Alike 3.0 license.