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-rwxr-xr-xgi/pyp-topics/scripts/contexts2documents.py37
-rwxr-xr-xgi/pyp-topics/scripts/extract_contexts.py144
-rwxr-xr-xgi/pyp-topics/scripts/extract_contexts_test.py72
-rwxr-xr-xgi/pyp-topics/scripts/extract_leaves.py49
-rwxr-xr-xgi/pyp-topics/scripts/map-documents.py20
-rwxr-xr-xgi/pyp-topics/scripts/map-terms.py20
-rw-r--r--gi/pyp-topics/scripts/run.sh13
-rwxr-xr-xgi/pyp-topics/scripts/score-mkcls.py61
-rwxr-xr-xgi/pyp-topics/scripts/score-topics.py64
-rwxr-xr-xgi/pyp-topics/scripts/spans2labels.py137
-rwxr-xr-xgi/pyp-topics/scripts/tokens2classes.py27
-rwxr-xr-xgi/pyp-topics/scripts/topics.py20
12 files changed, 0 insertions, 664 deletions
diff --git a/gi/pyp-topics/scripts/contexts2documents.py b/gi/pyp-topics/scripts/contexts2documents.py
deleted file mode 100755
index 9be4ebbb..00000000
--- a/gi/pyp-topics/scripts/contexts2documents.py
+++ /dev/null
@@ -1,37 +0,0 @@
-#!/usr/bin/python
-
-import sys
-from operator import itemgetter
-
-if len(sys.argv) > 3:
- print "Usage: contexts2documents.py [contexts_index_out] [phrases_index_out]"
- exit(1)
-
-context_index = {}
-phrase_index = {}
-for line in sys.stdin:
- phrase, line_tail = line.split('\t')
-
- raw_contexts = line_tail.split('|||')
- contexts = [c.strip() for x,c in enumerate(raw_contexts) if x%2 == 0]
- counts = [int(c.split('=')[1].strip()) for x,c in enumerate(raw_contexts) if x%2 != 0]
- phrase_index.setdefault(phrase, len(phrase_index))
- print len(contexts),
- for context,count in zip(contexts,counts):
- c = context_index.setdefault(context, len(context_index))
- print "%d:%d" % (c,count),
- print
-if 1 < len(sys.argv) < 4:
- contexts_out = open(sys.argv[1],'w')
- contexts = context_index.items()
- contexts.sort(key = itemgetter(1))
- for context in contexts:
- print >>contexts_out, context[0]
- contexts_out.close()
-if len(sys.argv) == 3:
- phrases_out = open(sys.argv[2],'w')
- phrases = phrase_index.items()
- phrases.sort(key = itemgetter(1))
- for phrase in phrases:
- print >>phrases_out, phrase[0]
- phrases_out.close()
diff --git a/gi/pyp-topics/scripts/extract_contexts.py b/gi/pyp-topics/scripts/extract_contexts.py
deleted file mode 100755
index b2723f2a..00000000
--- a/gi/pyp-topics/scripts/extract_contexts.py
+++ /dev/null
@@ -1,144 +0,0 @@
-#!/usr/bin/python
-
-import sys,collections
-
-def extract_backoff(context_list, order):
- assert len(context_list) == (2*order)
- backoffs = []
- for i in range(1,order+1):
- if i == order:
- backoffs.append(([context_list[i-1]+"|"], ["|"+context_list[i]]))
- else:
- right_limit = 2*order-i
- core = context_list[i:right_limit]
- left = [context_list[i-1]+"|"*(order-i+1)]
- right = ["|"*(order-i+1)+context_list[right_limit]]
- backoffs.append((core, left, right))
-# print context_list, backoffs
- return backoffs
-
-def tuple_to_str(t):
- s=""
- for i,x in enumerate(t):
- if i > 0: s += "|"
- s += str(x)
- return s
-
-if len(sys.argv) < 3:
- print "Usage: extract-contexts.py output_filename order cutoff lowercase"
- exit(1)
-
-output_filename = sys.argv[1]
-order = int(sys.argv[2])
-cutoff = 0
-if len(sys.argv) > 3:
- cutoff = int(sys.argv[3])
-lowercase = False
-if len(sys.argv) > 4:
- lowercase = bool(sys.argv[4])
-
-contexts_dict={}
-contexts_list=[]
-contexts_freq=collections.defaultdict(int)
-contexts_backoff={}
-
-token_dict={}
-token_list=[]
-documents_dict=collections.defaultdict(dict)
-
-contexts_at_order = [i for i in range(order+1)]
-
-prefix = ["<s%d>|<s>"%i for i in range(order)]
-suffix = ["</s%d>|</s>"%i for i in range(order)]
-
-for line in sys.stdin:
- tokens = list(prefix)
- tokens.extend(line.split())
- tokens.extend(suffix)
- if lowercase:
- tokens = map(lambda x: x.lower(), tokens)
-
- for i in range(order, len(tokens)-order):
- context_list = []
- term=""
- for j in range(i-order, i+order+1):
- token,tag = tokens[j].rsplit('|',2)
- if j != i:
- context_list.append(token)
- else:
- if token not in token_dict:
- token_dict[token] = len(token_dict)
- token_list.append(token)
- term = token_dict[token]
-
- context = tuple_to_str(tuple(context_list))
-
- if context not in contexts_dict:
- context_index = len(contexts_dict)
- contexts_dict[context] = context_index
- contexts_list.append(context)
- contexts_at_order[0] += 1
-
- # handle backoff
- backoff_contexts = extract_backoff(context_list, order)
- bo_indexes=[(context_index,)]
-# bo_indexes=[(context,)]
- for i,bo in enumerate(backoff_contexts):
- factor_indexes=[]
- for factor in bo:
- bo_tuple = tuple_to_str(tuple(factor))
- if bo_tuple not in contexts_dict:
- contexts_dict[bo_tuple] = len(contexts_dict)
- contexts_list.append(bo_tuple)
- contexts_at_order[i+1] += 1
-# factor_indexes.append(bo_tuple)
- factor_indexes.append(contexts_dict[bo_tuple])
- bo_indexes.append(tuple(factor_indexes))
-
- for i in range(len(bo_indexes)-1):
- contexts_backoff[bo_indexes[i][0]] = bo_indexes[i+1]
-
- context_index = contexts_dict[context]
- contexts_freq[context_index] += 1
-
- if context_index not in documents_dict[term]:
- documents_dict[term][context_index] = 1
- else:
- documents_dict[term][context_index] += 1
-
-term_file = open(output_filename+".terms",'w')
-for t in token_list: print >>term_file, t
-term_file.close()
-
-contexts_file = open(output_filename+".contexts",'w')
-for c in contexts_list:
- print >>contexts_file, c
-contexts_file.close()
-
-data_file = open(output_filename+".data",'w')
-for t in range(len(token_list)):
- line=""
- num_active=0
- for c in documents_dict[t]:
- count = documents_dict[t][c]
- if contexts_freq[c] >= cutoff:
- line += (' ' + str(c) + ':' + str(count))
- num_active += 1
- if num_active > 0:
- print >>data_file, "%d%s" % (num_active,line)
-data_file.close()
-
-contexts_backoff_file = open(output_filename+".contexts_backoff",'w')
-print >>contexts_backoff_file, len(contexts_list), order,
-#for x in contexts_at_order:
-# print >>contexts_backoff_file, x,
-#print >>contexts_backoff_file
-for x in range(order-1):
- print >>contexts_backoff_file, 3,
-print >>contexts_backoff_file, 2
-
-for x in contexts_backoff:
- print >>contexts_backoff_file, x,
- for y in contexts_backoff[x]: print >>contexts_backoff_file, y,
- print >>contexts_backoff_file
-contexts_backoff_file.close()
diff --git a/gi/pyp-topics/scripts/extract_contexts_test.py b/gi/pyp-topics/scripts/extract_contexts_test.py
deleted file mode 100755
index 693b6e0b..00000000
--- a/gi/pyp-topics/scripts/extract_contexts_test.py
+++ /dev/null
@@ -1,72 +0,0 @@
-#!/usr/bin/python
-
-import sys,collections
-
-def tuple_to_str(t):
- s=""
- for i,x in enumerate(t):
- if i > 0: s += "|"
- s += str(x)
- return s
-
-if len(sys.argv) < 5:
- print "Usage: extract-contexts_test.py output_filename vocab contexts order lowercase"
- exit(1)
-
-output_filename = sys.argv[1]
-output = open(output_filename+".test_data",'w')
-
-unk_term="-UNK-"
-vocab_dict={}
-for i,x in enumerate(file(sys.argv[2], 'r').readlines()):
- vocab_dict[x.strip()]=i
-
-contexts_dict={}
-contexts_list=[]
-for i,x in enumerate(file(sys.argv[3], 'r').readlines()):
- contexts_dict[x.strip()]=i
- contexts_list.append(x.strip())
-
-order = int(sys.argv[4])
-
-lowercase = False
-if len(sys.argv) > 5:
- lowercase = bool(sys.argv[5])
-if lowercase: unk_term = unk_term.lower()
-
-prefix = ["<s%d>|<s>"%i for i in range(order)]
-suffix = ["</s%d>|</s>"%i for i in range(order)]
-
-assert unk_term in vocab_dict
-for line in sys.stdin:
- tokens = list(prefix)
- tokens.extend(line.split())
- tokens.extend(suffix)
- if lowercase:
- tokens = map(lambda x: x.lower(), tokens)
-
- for i in range(order, len(tokens)-order):
- context_list=[]
- term=""
- for j in range(i-order, i+order+1):
- token,tag = tokens[j].rsplit('|',2)
- if j != i:
- context_list.append(token)
- else:
- if token not in vocab_dict:
- term = vocab_dict[unk_term]
- else:
- term = vocab_dict[token]
- context = tuple_to_str(context_list)
- if context not in contexts_dict:
- contexts_dict[context] = len(contexts_dict)
- contexts_list.append(context)
- context_index = contexts_dict[context]
- print >>output, "%d:%d" % (term,context_index),
- print >>output
-output.close()
-
-contexts_file = open(output_filename+".test_contexts",'w')
-for c in contexts_list:
- print >>contexts_file, c
-contexts_file.close()
diff --git a/gi/pyp-topics/scripts/extract_leaves.py b/gi/pyp-topics/scripts/extract_leaves.py
deleted file mode 100755
index 14783b36..00000000
--- a/gi/pyp-topics/scripts/extract_leaves.py
+++ /dev/null
@@ -1,49 +0,0 @@
-#!/usr/bin/python
-
-import nltk
-import nltk.probability
-import sys
-import getopt
-
-lexicalise=False
-rm_traces=False
-cutoff=100
-length_cutoff=10000
-try:
- opts, args = getopt.getopt(sys.argv[1:], "hs:c:l", ["help", "lexicalise", "cutoff","sentence-length","remove-traces"])
-except getopt.GetoptError:
- print "Usage: extract_leaves.py [-lsc]"
- sys.exit(2)
-for opt, arg in opts:
- if opt in ("-h", "--help"):
- print "Usage: extract_leaves.py [-lsc]"
- sys.exit()
- elif opt in ("-l", "--lexicalise"):
- lexicalise = True
- elif opt in ("-c", "--cutoff"):
- cutoff = int(arg)
- elif opt in ("-s", "--sentence-length"):
- length_cutoff = int(arg)
- elif opt in ("--remove-traces"):
- rm_traces = True
-
-token_freq = nltk.probability.FreqDist()
-lines = []
-for line in sys.stdin:
- t = nltk.Tree.parse(line)
- pos = t.pos()
- if len(pos) <= length_cutoff:
- lines.append(pos)
- for token, tag in pos:
- token_freq.inc(token)
-
-for line in lines:
- for token,tag in line:
- if not (rm_traces and tag == "-NONE-"):
- if lexicalise:
- if token_freq[token] < cutoff:
- token = '-UNK-'
- print '%s|%s' % (token,tag),
- else:
- print '%s' % tag,
- print
diff --git a/gi/pyp-topics/scripts/map-documents.py b/gi/pyp-topics/scripts/map-documents.py
deleted file mode 100755
index 703de312..00000000
--- a/gi/pyp-topics/scripts/map-documents.py
+++ /dev/null
@@ -1,20 +0,0 @@
-#!/usr/bin/python
-
-import sys
-
-if len(sys.argv) != 2:
- print "Usage: map-documents.py vocab-file"
- exit(1)
-
-vocab = file(sys.argv[1], 'r').readlines()
-term_dict = map(lambda x: x.strip(), vocab)
-
-for line in sys.stdin:
- tokens = line.split()
- for token in tokens:
- elements = token.split(':')
- if len(elements) == 1:
- print "%s" % (term_dict[int(elements[0])]),
- else:
- print "%s:%s" % (term_dict[int(elements[0])], elements[1]),
- print
diff --git a/gi/pyp-topics/scripts/map-terms.py b/gi/pyp-topics/scripts/map-terms.py
deleted file mode 100755
index eb0298d7..00000000
--- a/gi/pyp-topics/scripts/map-terms.py
+++ /dev/null
@@ -1,20 +0,0 @@
-#!/usr/bin/python
-
-import sys
-
-if len(sys.argv) != 2:
- print "Usage: map-terms.py vocab-file"
- exit(1)
-
-vocab = file(sys.argv[1], 'r').readlines()
-term_dict = map(lambda x: x.strip().replace(' ','_'), vocab)
-
-for line in sys.stdin:
- tokens = line.split()
- for token in tokens:
- elements = token.split(':')
- if len(elements) == 1:
- print "%s" % (term_dict[int(elements[0])]),
- else:
- print "%s:%s" % (term_dict[int(elements[0])], elements[1]),
- print
diff --git a/gi/pyp-topics/scripts/run.sh b/gi/pyp-topics/scripts/run.sh
deleted file mode 100644
index 19e625b1..00000000
--- a/gi/pyp-topics/scripts/run.sh
+++ /dev/null
@@ -1,13 +0,0 @@
-#!/bin/sh
-
-
-./simple-extract-context.sh ~/workspace/clsp2010/jhuws2010/data/btec/split.zh-en.al 1 | ~/workspace/pyp-topics/scripts/contexts2documents.py > split.zh-en.data
-
-~/workspace/pyp-topics/bin/pyp-topics-train -d split.zh-en.data -t 50 -s 100 -o split.zh-en.documents.gz -w split.zh-en.topics.gz
-gunzip split.zh-en.documents.gz
-
-~/workspace/cdec/extools/extractor -i ../jhuws2010/data/btec/split.zh-en.al -S 1 -c 500000 -L 12 --base_phrase_spans | ~/workspace/pyp-topics/scripts/spans2labels.py split.zh-en.phrases split.zh-en.contexts split.zh-en.documents > corpus.zh-en.labelled_spans
-
-paste -d " " ~/workspace/clsp2010/jhuws2010/data/btec/split.zh-en.al corpus.labelled_spans > split.zh-en.labelled_spans
-
-./simple-extract.sh ~/workspace/clsp2010/scratch/split.zh-en.labelled_spans
diff --git a/gi/pyp-topics/scripts/score-mkcls.py b/gi/pyp-topics/scripts/score-mkcls.py
deleted file mode 100755
index 6bd33fc5..00000000
--- a/gi/pyp-topics/scripts/score-mkcls.py
+++ /dev/null
@@ -1,61 +0,0 @@
-#!/usr/bin/python
-
-import sys
-from collections import defaultdict
-
-def dict_max(d):
- max_val=-1
- max_key=None
- for k in d:
- if d[k] > max_val:
- max_val = d[k]
- max_key = k
- assert max_key
- return max_key
-
-if len(sys.argv) != 3:
- print "Usage: score-mkcls.py gold classes"
- exit(1)
-
-gold_file=open(sys.argv[1],'r')
-
-term_to_topics = {}
-for line in open(sys.argv[2],'r'):
- term,cls = line.split()
- term_to_topics[term] = cls
-
-gold_to_topics = defaultdict(dict)
-topics_to_gold = defaultdict(dict)
-
-for gold_line in gold_file:
- gold_tokens = gold_line.split()
- for gold_token in gold_tokens:
- gold_term,gold_tag = gold_token.rsplit('|',1)
- pred_token = term_to_topics[gold_term]
- gold_to_topics[gold_tag][pred_token] \
- = gold_to_topics[gold_tag].get(pred_token, 0) + 1
- topics_to_gold[pred_token][gold_tag] \
- = topics_to_gold[pred_token].get(gold_tag, 0) + 1
-
-pred=0
-correct=0
-gold_file=open(sys.argv[1],'r')
-for gold_line in gold_file:
- gold_tokens = gold_line.split()
-
- for gold_token in gold_tokens:
- gold_term,gold_tag = gold_token.rsplit('|',1)
- pred_token = term_to_topics[gold_term]
- print "%s|%s|%s" % (gold_token, pred_token, dict_max(topics_to_gold[pred_token])),
- pred += 1
- if gold_tag == dict_max(topics_to_gold[pred_token]):
- correct += 1
- print
-print >>sys.stderr, "Many-to-One Accuracy = %f" % (float(correct) / pred)
-#for x in gold_to_topics:
-# print x,dict_max(gold_to_topics[x])
-#print "###################################################"
-#for x in range(len(topics_to_gold)):
-# print x,dict_max(topics_to_gold[str(x)])
-# print x,topics_to_gold[str(x)]
-#print term_to_topics
diff --git a/gi/pyp-topics/scripts/score-topics.py b/gi/pyp-topics/scripts/score-topics.py
deleted file mode 100755
index 1d8a1fcd..00000000
--- a/gi/pyp-topics/scripts/score-topics.py
+++ /dev/null
@@ -1,64 +0,0 @@
-#!/usr/bin/python
-
-import sys
-from collections import defaultdict
-
-def dict_max(d):
- max_val=-1
- max_key=None
- for k in d:
- if d[k] > max_val:
- max_val = d[k]
- max_key = k
- assert max_key
- return max_key
-
-if len(sys.argv) != 3:
- print "Usage: score-topics.py gold pred"
- exit(1)
-
-gold_file=open(sys.argv[1],'r')
-pred_file=open(sys.argv[2],'r')
-
-gold_to_topics = defaultdict(dict)
-topics_to_gold = defaultdict(dict)
-term_to_topics = defaultdict(dict)
-
-for gold_line,pred_line in zip(gold_file,pred_file):
- gold_tokens = gold_line.split()
- pred_tokens = pred_line.split()
- assert len(gold_tokens) == len(pred_tokens)
-
- for gold_token,pred_token in zip(gold_tokens,pred_tokens):
- gold_term,gold_tag = gold_token.rsplit('|',1)
- gold_to_topics[gold_tag][pred_token] \
- = gold_to_topics[gold_tag].get(pred_token, 0) + 1
- term_to_topics[gold_term][pred_token] \
- = term_to_topics[gold_term].get(pred_token, 0) + 1
- topics_to_gold[pred_token][gold_tag] \
- = topics_to_gold[pred_token].get(gold_tag, 0) + 1
-
-pred=0
-correct=0
-gold_file=open(sys.argv[1],'r')
-pred_file=open(sys.argv[2],'r')
-for gold_line,pred_line in zip(gold_file,pred_file):
- gold_tokens = gold_line.split()
- pred_tokens = pred_line.split()
-
- for gold_token,pred_token in zip(gold_tokens,pred_tokens):
- gold_term,gold_tag = gold_token.rsplit('|',1)
-# print "%s|%s" % (gold_token, dict_max(gold_to_topics[gold_tag])),
- print "%s|%s|%s" % (gold_token, pred_token, dict_max(topics_to_gold[pred_token])),
- pred += 1
- if gold_tag == dict_max(topics_to_gold[pred_token]):
- correct += 1
- print
-print >>sys.stderr, "Many-to-One Accuracy = %f" % (float(correct) / pred)
-#for x in gold_to_topics:
-# print x,dict_max(gold_to_topics[x])
-#print "###################################################"
-#for x in range(len(topics_to_gold)):
-# print x,dict_max(topics_to_gold[str(x)])
-# print x,topics_to_gold[str(x)]
-#print term_to_topics
diff --git a/gi/pyp-topics/scripts/spans2labels.py b/gi/pyp-topics/scripts/spans2labels.py
deleted file mode 100755
index 50fa8106..00000000
--- a/gi/pyp-topics/scripts/spans2labels.py
+++ /dev/null
@@ -1,137 +0,0 @@
-#!/usr/bin/python
-
-import sys
-from operator import itemgetter
-
-if len(sys.argv) <= 2:
- print "Usage: spans2labels.py phrase_context_index [order] [threshold] [languages={s,t,b}{s,t,b}] [type={tag,tok,both},{tag,tok,both}]"
- exit(1)
-
-order=1
-threshold = 0
-cutoff_cat = "<UNK>"
-if len(sys.argv) > 2:
- order = int(sys.argv[2])
-if len(sys.argv) > 3:
- threshold = float(sys.argv[3])
-phr=ctx='t'
-if len(sys.argv) > 4:
- phr, ctx = sys.argv[4]
- assert phr in 'stb'
- assert ctx in 'stb'
-phr_typ = ctx_typ = 'both'
-if len(sys.argv) > 5:
- phr_typ, ctx_typ = sys.argv[5].split(',')
- assert phr_typ in ('tag', 'tok', 'both')
- assert ctx_typ in ('tag', 'tok', 'both')
-
-#print >>sys.stderr, "Loading phrase index"
-phrase_context_index = {}
-for line in file(sys.argv[1], 'r'):
- phrase,tail= line.split('\t')
- contexts = tail.split(" ||| ")
- try: # remove Phil's bizarre integer pair
- x,y = contexts[0].split()
- x=int(x); y=int(y)
- contexts = contexts[1:]
- except:
- pass
- if len(contexts) == 1: continue
- assert len(contexts) % 2 == 0
- for i in range(0, len(contexts), 2):
- #parse contexts[i+1] = " C=1 P=0.8 ... "
- features=dict([ keyval.split('=') for keyval in contexts[i+1].split()])
- category = features['C']
- if features.has_key('P') and float(features['P']) < threshold:
- category = cutoff_cat
-
- phrase_context_index[(phrase,contexts[i])] = category
- #print (phrase,contexts[i]), category
-
-#print >>sys.stderr, "Labelling spans"
-for line in sys.stdin:
- #print >>sys.stderr, "line", line.strip()
- line_segments = line.split(' ||| ')
- assert len(line_segments) >= 3
- source = ['<s>' for x in range(order)] + line_segments[0].split() + ['</s>' for x in range(order)]
- target = ['<s>' for x in range(order)] + line_segments[1].split() + ['</s>' for x in range(order)]
- phrases = [ [int(i) for i in x.split('-')] for x in line_segments[2].split()]
-
- if phr_typ != 'both' or ctx_typ != 'both':
- if phr in 'tb' or ctx in 'tb':
- target_toks = ['<s>' for x in range(order)] + map(lambda x: x.rsplit('_', 1)[0], line_segments[1].split()) + ['</s>' for x in range(order)]
- target_tags = ['<s>' for x in range(order)] + map(lambda x: x.rsplit('_', 1)[-1], line_segments[1].split()) + ['</s>' for x in range(order)]
-
- if phr in 'tb':
- if phr_typ == 'tok':
- targetP = target_toks
- elif phr_typ == 'tag':
- targetP = target_tags
- if ctx in 'tb':
- if ctx_typ == 'tok':
- targetC = target_toks
- elif ctx_typ == 'tag':
- targetC = target_tags
-
- if phr in 'sb' or ctx in 'sb':
- source_toks = ['<s>' for x in range(order)] + map(lambda x: x.rsplit('_', 1)[0], line_segments[0].split()) + ['</s>' for x in range(order)]
- source_tags = ['<s>' for x in range(order)] + map(lambda x: x.rsplit('_', 1)[-1], line_segments[0].split()) + ['</s>' for x in range(order)]
-
- if phr in 'sb':
- if phr_typ == 'tok':
- sourceP = source_toks
- elif phr_typ == 'tag':
- sourceP = source_tags
- if ctx in 'sb':
- if ctx_typ == 'tok':
- sourceC = source_toks
- elif ctx_typ == 'tag':
- sourceC = source_tags
- else:
- sourceP = sourceC = source
- targetP = targetC = target
-
- #print >>sys.stderr, "line", source, '---', target, 'phrases', phrases
-
- print "|||",
-
- for s1,s2,t1,t2 in phrases:
- s1 += order
- s2 += order
- t1 += order
- t2 += order
-
- phraset = phrases = contextt = contexts = ''
- if phr in 'tb':
- phraset = reduce(lambda x, y: x+y+" ", targetP[t1:t2], "").strip()
- if phr in 'sb':
- phrases = reduce(lambda x, y: x+y+" ", sourceP[s1:s2], "").strip()
-
- if ctx in 'tb':
- left_context = reduce(lambda x, y: x+y+" ", targetC[t1-order:t1], "")
- right_context = reduce(lambda x, y: x+y+" ", targetC[t2:t2+order], "").strip()
- contextt = "%s<PHRASE> %s" % (left_context, right_context)
- if ctx in 'sb':
- left_context = reduce(lambda x, y: x+y+" ", sourceC[s1-order:s1], "")
- right_context = reduce(lambda x, y: x+y+" ", sourceC[s2:s2+order], "").strip()
- contexts = "%s<PHRASE> %s" % (left_context, right_context)
-
- if phr == 'b':
- phrase = phraset + ' <SPLIT> ' + phrases
- elif phr == 's':
- phrase = phrases
- else:
- phrase = phraset
-
- if ctx == 'b':
- context = contextt + ' <SPLIT> ' + contexts
- elif ctx == 's':
- context = contexts
- else:
- context = contextt
-
- #print "%d-%d-%d-%d looking up" % (s1-order,s2-order,t1-order,t2-order), (phrase, context)
- label = phrase_context_index.get((phrase,context), cutoff_cat)
- if label != cutoff_cat: #cutoff'd spans are left unlabelled
- print "%d-%d-%d-%d:X%s" % (s1-order,s2-order,t1-order,t2-order,label),
- print
diff --git a/gi/pyp-topics/scripts/tokens2classes.py b/gi/pyp-topics/scripts/tokens2classes.py
deleted file mode 100755
index 33df255f..00000000
--- a/gi/pyp-topics/scripts/tokens2classes.py
+++ /dev/null
@@ -1,27 +0,0 @@
-#!/usr/bin/python
-
-import sys
-
-if len(sys.argv) != 3:
- print "Usage: tokens2classes.py source_classes target_classes"
- exit(1)
-
-source_to_topics = {}
-for line in open(sys.argv[1],'r'):
- term,cls = line.split()
- source_to_topics[term] = cls
-
-target_to_topics = {}
-for line in open(sys.argv[2],'r'):
- term,cls = line.split()
- target_to_topics[term] = cls
-
-for line in sys.stdin:
- source, target, tail = line.split(" ||| ")
-
- for token in source.split():
- print source_to_topics[token],
- print "|||",
- for token in target.split():
- print target_to_topics[token],
- print "|||", tail,
diff --git a/gi/pyp-topics/scripts/topics.py b/gi/pyp-topics/scripts/topics.py
deleted file mode 100755
index 0db1af71..00000000
--- a/gi/pyp-topics/scripts/topics.py
+++ /dev/null
@@ -1,20 +0,0 @@
-#!/usr/bin/python
-
-import sys
-
-if len(sys.argv) != 2:
- print "Usage: topics.py words-per-topic"
- exit(1)
-
-for t,line in enumerate(sys.stdin):
- tokens = line.split()
- terms = []
- for token in tokens:
- elements = token.rsplit(':',1)
- terms.append((int(elements[1]),elements[0]))
- terms.sort()
- terms.reverse()
-
- print "Topic %d:" % t
- map(lambda (x,y) : sys.stdout.write(" %s:%s\n" % (y,x)), terms[:int(sys.argv[1])])
- print