From 3f2cc751d1f2655aa0ff14ca735da648899edc40 Mon Sep 17 00:00:00 2001
From: Victor Chahuneau <vchahune@cs.cmu.edu>
Date: Fri, 10 Aug 2012 19:03:38 -0400
Subject: [python] Examples directory including Rampion

---
 python/test.py | 70 ----------------------------------------------------------
 1 file changed, 70 deletions(-)
 delete mode 100644 python/test.py

(limited to 'python/test.py')

diff --git a/python/test.py b/python/test.py
deleted file mode 100644
index eb9e6a95..00000000
--- a/python/test.py
+++ /dev/null
@@ -1,70 +0,0 @@
-#coding: utf8
-import cdec
-import gzip
-
-weights = '../tests/system_tests/australia/weights'
-grammar_file = '../tests/system_tests/australia/australia.scfg.gz'
-
-# Load decoder width configuration
-decoder = cdec.Decoder(formalism='scfg')
-# Read weights
-decoder.read_weights(weights)
-
-print dict(decoder.weights)
-
-# Read grammar
-with gzip.open(grammar_file) as f:
-    grammar = f.read()
-
-# Input sentence
-sentence = u'澳洲 是 与 北韩 有 邦交 的 少数 国家 之一 。'
-print '    Input:', sentence.encode('utf8')
-
-# Decode
-forest = decoder.translate(sentence, grammar=grammar)
-
-# Get viterbi translation
-print 'Output[0]:', forest.viterbi().encode('utf8')
-f_tree, e_tree = forest.viterbi_trees()
-print ' FTree[0]:', f_tree.encode('utf8')
-print ' ETree[0]:', e_tree.encode('utf8')
-print 'LgProb[0]:', forest.viterbi_features().dot(decoder.weights)
-
-# Get k-best translations
-kbest = zip(forest.kbest(5), forest.kbest_trees(5), forest.kbest_features(5))
-for i, (sentence, (f_tree, e_tree), features) in enumerate(kbest, 1):
-    print 'Output[%d]:' % i, sentence.encode('utf8')
-    print ' FTree[%d]:' % i, f_tree.encode('utf8')
-    print ' ETree[%d]:' % i, e_tree.encode('utf8')
-    print ' FVect[%d]:' % i, dict(features)
-
-# Sample translations from the forest
-for sentence in forest.sample(5):
-    print 'Sample:', sentence.encode('utf8')
-
-# Get feature vector for 1best
-fsrc = forest.viterbi_features()
-
-# Feature expectations
-print 'Feature expectations:', dict(forest.inside_outside())
-
-# Reference lattice
-lattice = ((('australia',0,1),),(('is',0,1),),(('one',0,1),),(('of',0,1),),(('the',0,4),('a',0,4),('a',0,1),('the',0,1),),(('small',0,1),('tiny',0,1),('miniscule',0,1),('handful',0,2),),(('number',0,1),('group',0,1),),(('of',0,2),),(('few',0,1),),(('countries',0,1),),(('that',0,1),),(('has',0,1),('have',0,1),),(('diplomatic',0,1),),(('relations',0,1),),(('with',0,1),),(('north',0,1),),(('korea',0,1),),(('.',0,1),),)
-
-lat = cdec.Lattice(lattice)
-assert (lattice == tuple(lat))
-
-# Intersect forest and lattice
-assert forest.intersect(lat)
-
-# Get best synchronous parse
-f_tree, e_tree = forest.viterbi_trees()
-print 'FTree:', f_tree.encode('utf8')
-print 'ETree:', e_tree.encode('utf8')
-
-# Compare 1best and reference feature vectors
-fref = forest.viterbi_features()
-print dict(fsrc - fref)
-
-# Prune hypergraph
-forest.prune(density=100)
-- 
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