Mohamed Amgad Tageldin kheffah
ShinNoNoir
/ kappa.py
Created
February 10, 2013 13:13
Simple implementation of the Fleiss' kappa measure in Python
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| def fleiss_kappa(ratings, n, k): | |
| ''' | |
| Computes the Fleiss' kappa measure for assessing the reliability of | |
| agreement between a fixed number n of raters when assigning categorical | |
| ratings to a number of items. | |
| Args: | |
| ratings: a list of (item, category)-ratings | |
| n: number of raters | |
| k: number of categories |
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| # the following two lines give a two-line status, with the current window highlighted | |
| hardstatus alwayslastline | |
| hardstatus string '%{= kG}[%{G}%H%? %1`%?%{g}][%= %{= kw}%-w%{+b yk} %n*%t%?(%u)%? %{-}%+w %=%{g}][%{B}%m/%d %{W}%C%A%{g}]' | |
| # huge scrollback buffer | |
| defscrollback 5000 | |
| # no welcome message | |
| startup_message off |
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| import matplotlib,numpy | |
| import pylab | |
| # A random colormap for matplotlib | |
| cmap = matplotlib.colors.ListedColormap ( numpy.random.rand ( 256,3)) | |
| pylab.imshow ( Z, cmap = cmap) | |
| pylab.show() |