def main(): #inputs = ['ip1.txt','ip2.txt'] #inputs = ['ip3.txt','ip4.txt'] #inputs = ['sachin1.txt'] #inputs = ['mal1.txt'] inputs = ['ip5.txt','ip6.txt','ip7.txt'] no_of_clusters = int(sys.argv[1]) doc = Document(inputs,no_of_clusters) count = 0 print "Number of Sentences :" print len(doc.sentences) #print doc.sent_no_swords #print len(doc.sent_no_swords) ''' print "Initial cluster sentences:" for i in range(len(doc.clusters)): print doc.clusters[i][0], ''' print "Selecting sentence from each cluster..." doc.cluster_vector() doc.find_clust_similar_sent() #print "" #print "Cluster sentences:\n" #print doc.clust_sentences #print "Assigning weights to cluster sentences:" #doc.select_cluster_sentences() #doc.printclust_sentences() #doc.print_rogue_clust_sentences() print "Ordering...." for input_file in inputs: count = count +1 if count == 1: doc.print_sent_ordered() #ordering first = ordering.precedence_ordering(doc,doc.clust_sentences) tempv = doc.clust_sentences[0] doc.clust_sentences[0] = doc.clust_sentences[first] doc.clust_sentences[first] = tempv ordered_sentences=ordering.similarity_ordering(doc,doc.clust_sentences) #print doc.clust_sentences,ordered_sentences #****exchange 1st sentence in the cluster with first for i in ordered_sentences: print doc.sentences[i].lstrip().capitalize(),". ",
def main():
#inputs = ['ip1.txt','ip2.txt']
#inputs = ['ip3.txt','ip4.txt']
#inputs = ['sachin1.txt']
#inputs = ['mal1.txt']
inputs = ['ip5.txt', 'ip6.txt', 'ip7.txt']
no_of_clusters = int(sys.argv[1])
doc = Document(inputs, no_of_clusters)
count = 0
print "Number of Sentences :"
print len(doc.sentences)
#print doc.sent_no_swords
#print len(doc.sent_no_swords)
'''
print "Initial cluster sentences:"
for i in range(len(doc.clusters)):
print doc.clusters[i][0],
'''
print "Selecting sentence from each cluster..."
doc.cluster_vector()
doc.find_clust_similar_sent()
#print ""
#print "Cluster sentences:\n"
#print doc.clust_sentences
#print "Assigning weights to cluster sentences:"
#doc.select_cluster_sentences()
print "Initial Summary"
doc.printclust_sentences()
#doc.print_rogue_clust_sentences()
print "Ordering...."
for input_file in inputs:
count = count + 1
if count == 1:
doc.print_sent_ordered()
#ordering
print "Summary after ordering"
first = ordering.precedence_ordering(doc, doc.clust_sentences)
tempv = doc.clust_sentences[0]
doc.clust_sentences[0] = doc.clust_sentences[first]
doc.clust_sentences[first] = tempv
ordered_sentences = ordering.similarity_ordering(doc, doc.clust_sentences)
#print doc.clust_sentences,ordered_sentences
#****exchange 1st sentence in the cluster with first
for i in ordered_sentences:
print doc.sentences[i].lstrip().capitalize(), ". ",
def summarize(inpdir,no_of_clusters,task):
doc = Document(ques_root_directory+inpdir,no_of_clusters)
print "Number of Sentences :"
print len(doc.sentences)
#print doc.sent_no_swords
#print len(doc.sent_no_swords)
print "Initial cluster sentences:"
for i in range(len(doc.clusters)):
print doc.clusters[i][0],
#doc.printinit_clust()
doc.cluster_vector()
doc.find_clust_similar_sent()
print ""
print "Simi based cluster sentences:"
print doc.clust_sentences
doc.printclust_sentences()
print "###"
'''
print "weight cluster sentences:"
doc.select_cluster_sentences()
print doc.clust_sentences
doc.printclust_sentences()
'''
'''
print "document cluster sentences:"
doc.clust_doc_sent()
print doc.clust_sentences
doc.printclust_sentences()
'''
#doc.printclust_sentences()
#doc.print_rogue_clust_sentences()
print "Ordering...."
'''
for input_file in inputs:
count = count +1
if count == 1:
doc.print_sent_ordered()
'''
#ordering
first = ordering.precedence_ordering(doc,doc.clust_sentences)
tempv = doc.clust_sentences[0]
doc.clust_sentences[0] = doc.clust_sentences[first]
doc.clust_sentences[first] = tempv
ordered_sentences=ordering.similarity_ordering(doc,doc.clust_sentences)
#print doc.clust_sentences,ordered_sentences
#****exchange 1st sentence in the cluster with first
print ""
print "SUMMARY of",no_of_clusters," :"
for i in ordered_sentences:
print doc.sentences[i],". "
#doc.print_rogue_clust_sentences()
print("writing op of task "+str(task))
doc.write_rogue_clust_sentences(sys_dir,task)