SimpleHist Simple histogram classes, designed for data manipulation
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data classes data manipulation histogram histogram classes

SimpleHist Description

Simple histogram classes, designed for data manipulation Matplotlib histograms are geared around drawing, not data manuipulation. Numpy direct support for histograms is extremely limited, and not very different from matpotlib. SimpleHist 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 > 2.6Type "make test" to run the core unit tests. Some tests, such as the pyROOT-based tests, must be run explicitly (or through python2.7> unittest discovery). At the moment, the ROOT test requires pyROOT, which is why it doesn't run by default as not many people have (or need) this dependency.Usage:A summary of usage, taken from the hists.py docstring follows:Importing: >>> from simplehist import HistInitialise with bin indices: >>> a = Hist() >>> a.bincount 3 >>> a.bins (0, 1, 2, 3) >>> a.data array()Optionally include data: >>> a = Hist(, data=) >>> a.data array()Or just specify the blank data type: >>> a = Hist(, dtype=int) >>> a.data array()You can do arithmetic operations in place or seperately: >>> a = Hist(, data=) >>> b = a + a >>> b -= a >>> a.data == b.data array(, dtype=bool)And you can fill bins from values: >>> a = Hist() >>> a.fill(1.4, weight=3) >>> a.data array()Even out of range: >>> a = Hist() >>> a.fill(-10) >>> a.underflow 1.0If 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) Requirements: · Python

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