def make_kw_approach(filename):
#Load abstracts
print "Reading data file..."
read_abstracts_from_xml("pubmed_result.xml")
global abstracts
bacteria_list = []
bacteria_list = read_txt_file(filename)
i=0
for abstract in abstracts :
kwe.make_keyword_candidates(abstract.AbstractText)
kwe.make_cooccurrence_matrix()
abstract.key_words = kwe.make_keywords_list()
#print i
#print abstract.key_words
#Tie bacteria & abstracts
#Tie keywords to bacteria: key_word<abstract_id, abstract_id, ...>
for bacteria in bacteria_list :
if abstract.AbstractText.rfind( bacteria.name ) != -1 :
#print bacteria.name
#print abstract.AbstractText
bacteria.Freq += 1
for keyword in abstract.key_words :
try :
bacteria.key_words[keyword].append(abstract.id)
except :
bacteria.key_words[keyword] = []
bacteria.key_words[keyword].append(abstract.id)
#i+=1
#if i == 2 : break
print "Done with extraction keywords"
#for bacteria in bacteria_list :
# print bacteria.name
# print bacteria.key_words
#Adjacency matric, strong connections
adj_matrix = []
for i in xrange(len(bacteria_list)):
adj_matrix.append([])
for j in xrange(len(bacteria_list)):
adj_matrix[i].append(0)
for i in xrange( len(bacteria_list) ) :
for j in xrange( (i+1), len(bacteria_list) ) :
for kw in bacteria_list[i].key_words :
for kww in bacteria_list[j].key_words :
if kw == kww :
skw = set()
skw = set(list(kw))
skww = set()
skww = set(list(skww))
if len(skw.symmetric_difference(skww)) > 0 :
adj_matrix[i][j] += 1
print_adj_matrix_to_csv1(bacteria_list, adj_matrix, 'adj_matrix_strong.csv')
for bacteria in bacteria_list :
with open(str(bacteria.name)+".csv", 'wb') as csvfile :
spamwriter = csv.writer(csvfile)
#print bacteria.name
for item in bacteria.key_words :
spamwriter.writerow( str(item) )
def calculate_index_words(text):
#print text
kwe.make_keyword_candidates(text)
kwe.make_cooccurrence_matrix()
return kwe.make_keywords_list()
def make_kw_approach(filename):
#Load abstracts
print "Reading data file..."
read_abstracts_from_xml("pubmed_result.xml")
global abstracts
bacteria_list = []
bacteria_list = read_txt_file(filename)
i = 0
for abstract in abstracts:
kwe.make_keyword_candidates(abstract.AbstractText)
kwe.make_cooccurrence_matrix()
abstract.key_words = kwe.make_keywords_list()
#print i
#print abstract.key_words
#Tie bacteria & abstracts
#Tie keywords to bacteria: key_word<abstract_id, abstract_id, ...>
for bacteria in bacteria_list:
if abstract.AbstractText.rfind(bacteria.name) != -1:
#print bacteria.name
#print abstract.AbstractText
bacteria.Freq += 1
for keyword in abstract.key_words:
try:
bacteria.key_words[keyword].append(abstract.id)
except:
bacteria.key_words[keyword] = []
bacteria.key_words[keyword].append(abstract.id)
#i+=1
#if i == 2 : break
print "Done with extraction keywords"
#for bacteria in bacteria_list :
# print bacteria.name
# print bacteria.key_words
#Adjacency matric, strong connections
adj_matrix = []
for i in xrange(len(bacteria_list)):
adj_matrix.append([])
for j in xrange(len(bacteria_list)):
adj_matrix[i].append(0)
for i in xrange(len(bacteria_list)):
for j in xrange((i + 1), len(bacteria_list)):
for kw in bacteria_list[i].key_words:
for kww in bacteria_list[j].key_words:
if kw == kww:
skw = set()
skw = set(list(kw))
skww = set()
skww = set(list(skww))
if len(skw.symmetric_difference(skww)) > 0:
adj_matrix[i][j] += 1
print_adj_matrix_to_csv1(bacteria_list, adj_matrix,
'adj_matrix_strong.csv')
for bacteria in bacteria_list:
with open(str(bacteria.name) + ".csv", 'wb') as csvfile:
spamwriter = csv.writer(csvfile)
#print bacteria.name
for item in bacteria.key_words:
spamwriter.writerow(str(item))
def calculate_index_words(text):
#print text
kwe.make_keyword_candidates(text)
kwe.make_cooccurrence_matrix()
return kwe.make_keywords_list()