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Simple histogram classes, designed for data manipulation

Project description

Description:A very simple ndarray-based histogram class.
Author: Nicholas Devenish


Matplotlib histograms are geared around drawing, not data manipulation. Numpy direct support for histograms is extremely limited, and not very different from matpotlib. This is intended to turn into a set of very lightweight classes for shuffling data around. This is very much a work-in-progress.

The only required depenency is numpy, and the package is designed to work for python >= 2.6


A summary of usage, taken from the docstring follows:

>>> from simplehist import Hist
Initialise with bin indices:
>>> a = Hist([0, 1, 2, 3])
>>> a.bincount
>>> a.bins
(0, 1, 2, 3)
array([ 0.,  0.,  0.])
Optionally include data:
>>> a = Hist([0, 1, 2, 3], data=[1, 0.2, 3])
array([ 1. ,  0.2,  3. ])
Or just specify the blank data type:
>>> a = Hist([0, 1, 2, 3], dtype=int)
array([0, 0, 0])
You can do arithmetic operations in place or seperately:
>>> a = Hist([0, 1, 2, 3], data=[1, 0.2, 3])
>>> b = a + a
>>> b -= a
>>> ==
array([ True,  True,  True], dtype=bool)
And you can fill bins from values:
>>> a = Hist([0,1,2,3])
>>> a.fill(1.4, weight=3)
array([ 0.,  3.,  0.])
Even out of range:
>>> a = Hist([0,1])
>>> a.fill(-10)
>>> a.underflow
If you use pyROOT, you can convert from 1D histograms:
>>> type(source)
<class 'ROOT.TH1D'>
>>> convert = fromTH1(source)
>>> type(convert)
<class 'simplehist.hists.Hist'>

And you can draw histograms, using any of the options that can be passed to matplotlib.pyplot.hist:

>>> hist_object.draw_hist(lw=2)

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