From e26434979adc33bd949566ba7bf02dff64e80a3e Mon Sep 17 00:00:00 2001
From: Chris Dyer <cdyer@cab.ark.cs.cmu.edu>
Date: Tue, 2 Oct 2012 00:19:43 -0400
Subject: cdec cleanup, remove bayesian stuff, parsing stuff

---
 gi/evaluation/conditional_entropy.py | 61 ------------------------------------
 1 file changed, 61 deletions(-)
 delete mode 100644 gi/evaluation/conditional_entropy.py

(limited to 'gi/evaluation/conditional_entropy.py')

diff --git a/gi/evaluation/conditional_entropy.py b/gi/evaluation/conditional_entropy.py
deleted file mode 100644
index 356d3b1d..00000000
--- a/gi/evaluation/conditional_entropy.py
+++ /dev/null
@@ -1,61 +0,0 @@
-#!/usr/bin/env python
-
-import sys, math, itertools, getopt
-
-def usage():
-    print >>sys.stderr, 'Usage:', sys.argv[0], '[-s slash_threshold] input-1 input-2'
-    sys.exit(0)
-
-optlist, args = getopt.getopt(sys.argv[1:], 'hs:')
-slash_threshold = None
-for opt, arg in optlist:
-    if opt == '-s':
-        slash_threshold = int(arg)
-    else:
-        usage()
-if len(args) != 2:
-    usage()
-
-ginfile = open(args[0])
-pinfile = open(args[1])
-
-# evaluating: H(G | P) = sum_{g,p} p(g,p) log { p(p) / p(g,p) }
-#                      = sum_{g,p} c(g,p)/N { log c(p) - log N - log c(g,p) + log N }
-#                      = 1/N sum_{g,p} c(g,p) { log c(p) - log c(g,p) }
-# where G = gold, P = predicted, N = number of events
-
-N = 0
-gold_frequencies = {}
-predict_frequencies = {}
-joint_frequencies = {}
-
-for gline, pline in itertools.izip(ginfile, pinfile):
-    gparts = gline.split('||| ')[1].split()
-    pparts = pline.split('||| ')[1].split()
-    assert len(gparts) == len(pparts)
-
-    for gpart, ppart in zip(gparts, pparts):
-        gtag = gpart.split(':',1)[1]
-        ptag = ppart.split(':',1)[1]
-
-        if slash_threshold == None or gtag.count('/') + gtag.count('\\') <= slash_threshold:
-            joint_frequencies.setdefault((gtag, ptag), 0)
-            joint_frequencies[gtag,ptag] += 1
-
-            predict_frequencies.setdefault(ptag, 0)
-            predict_frequencies[ptag] += 1
-
-            gold_frequencies.setdefault(gtag, 0)
-            gold_frequencies[gtag] += 1
-
-            N += 1
-
-hg2p = 0
-hp2g = 0
-for (gtag, ptag), cgp in joint_frequencies.items():
-    hp2g += cgp * (math.log(predict_frequencies[ptag], 2) - math.log(cgp, 2))
-    hg2p += cgp * (math.log(gold_frequencies[gtag], 2) - math.log(cgp, 2))
-hg2p /= N
-hp2g /= N
-
-print 'H(P|G)', hg2p, 'H(G|P)', hp2g, 'VI', hg2p + hp2g
-- 
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