def load_vectorspace(filename):
f = open(filename, 'r')
vectors = dict()
for line in f:
data = line.split('|')
if len(data) == 4 and '' not in data:
a1 = VectorUtil.string_to_vector(data[1].replace(' ', ''))
p = VectorUtil.string_to_vector(data[2].replace(' ', ''))
a2 = VectorUtil.string_to_vector(data[3].replace(' ', ''))
vectors.update({data[0]: (a1, p, a2)})
return vectors
def load_vectorspace(filename):
f = open(filename,'r')
vectors = dict()
for line in f:
data = line.split('|')
if len(data) == 4 and '' not in data:
a1 = VectorUtil.string_to_vector(data[1].replace(' ',''))
p = VectorUtil.string_to_vector(data[2].replace(' ',''))
a2 = VectorUtil.string_to_vector(data[3].replace(' ',''))
vectors.update({data[0]: (a1,p,a2)})
return vectors
def reduce_vectors_of_file_column(self,
vectors_file,
rel_list_filename,
col,
n_dim=100,
n_samples=100,
step=1):
self.labels = []
self.data = []
self.preds = []
incomplete_vector_set_relation_list = []
fin = open(vectors_file, 'r+')
#fout= open(filename+'_reduced','a+')
rel_list_file = open(rel_list_filename, 'r')
sys.stderr.write('Loading most frequent relations list.\n')
most_frequent_relations_list = []
sample_count = 0
for line in rel_list_file:
most_frequent_relations_list.append(line.split('\t')[0])
sample_count = sample_count + 1
if sample_count == n_samples:
break
#print(str(most_frequent_relations_list))
sys.stderr.write('Done.' + str(len(most_frequent_relations_list)) +
'\n')
sample_count = 0
for line in fin:
line = line.split('|')
vec = line[col].replace(' ', '')
rel = line[0].replace(' ', '')
if rel in most_frequent_relations_list:
#print('Loading data of relation ' + rel + '\n')
vec = VectorUtil.string_to_vector(vec)
predvec = line[pred_root_col].replace(' ', '')
if step == 1 and predvec is not '':
# print('pred col = ' + str(line[pred_root_col]))
predvec = VectorUtil.string_to_vector(predvec)
self.preds.append(predvec)
if predvec is not '':
self.labels.append(rel)
self.data.append(vec)
sample_count = sample_count + 1
else:
sys.stderr.write(
'WARNING: relation "' + rel +
'" skipped due to the absence of predicate root vector.\n'
)
incomplete_vector_set_relation_list.append(rel)
sys.stderr.write(str(len(self.data)) + ' relations loaded.\n')
if step == 1:
sys.stderr.write('Creating new file..\n')
fout = self.create_empty_output_file(
vectors_file + '_reduced_step1.csv', n_samples, self.labels)
fin.seek(0)
elif step >= 2:
fin.close()
fin = open(vectors_file + '_reduced_step' + str(step - 1) + '.csv',
'r')
fout = open(vectors_file + '_reduced_step' + str(step) + '.csv',
'w')
sys.stderr.write('Reducing, please wait...\n')
dimred = TruncatedSVD(n_components=n_dim)
dimred.fit(self.data)
sys.stderr.write('Reduction finished.\n')
sample_count = 0
for line in fin:
if line == '\n':
continue
sline = line.split('|')
rel = sline[0].replace(' ', '')
if rel in most_frequent_relations_list:
if rel in incomplete_vector_set_relation_list:
continue
if len(sline) - 1 < col:
sys.stderr.write('WARNING: not enough columns in line\n')
# sys.stderr.write(str(len(sline)) + '\n')
rel_pos = self.labels.index(rel)
if step == 1:
sline[pred_root_col] = VectorUtil.vector_to_string(
self.preds[rel_pos])
vecred = dimred.transform(self.data[rel_pos])
#sys.stderr.write('Transformed vector size is ' + str(len(vecred))+ ' x ' + str(len(vecred[0])) + '\n')
if len(vecred) == 1:
vec_write = vecred[0]
#self.data[sample_count] = vec
sline[col] = VectorUtil.vector_to_string(
vec_write) #vector reduced is put in the right column
rvstr = '|'.join(sline)
#sline[0] = rel
#print(sline[col])
# sys.stderr.write(rvstr)
fout.write(rvstr + '\n')
fout.flush()
sample_count = sample_count + 1
fout.close()
def reduce_vectors_of_file_column(self,vectors_file,rel_list_filename,col,n_dim=100,n_samples=100,step=1):
self.labels = []
self.data = []
self.preds = []
incomplete_vector_set_relation_list = []
fin= open(vectors_file,'r+')
#fout= open(filename+'_reduced','a+')
rel_list_file = open(rel_list_filename,'r')
sys.stderr.write('Loading most frequent relations list.\n')
most_frequent_relations_list = []
sample_count = 0
for line in rel_list_file:
most_frequent_relations_list.append(line.split('\t')[0])
sample_count = sample_count + 1
if sample_count == n_samples:
break
#print(str(most_frequent_relations_list))
sys.stderr.write('Done.' + str(len(most_frequent_relations_list)) + '\n')
sample_count = 0
for line in fin:
line = line.split('|')
vec = line[col].replace(' ','')
rel = line[0].replace(' ','')
if rel in most_frequent_relations_list:
#print('Loading data of relation ' + rel + '\n')
vec = VectorUtil.string_to_vector(vec)
predvec = line[pred_root_col].replace(' ','')
if step == 1 and predvec is not '':
# print('pred col = ' + str(line[pred_root_col]))
predvec = VectorUtil.string_to_vector(predvec)
self.preds.append(predvec)
if predvec is not '':
self.labels.append(rel)
self.data.append(vec)
sample_count = sample_count + 1
else:
sys.stderr.write('WARNING: relation "' + rel + '" skipped due to the absence of predicate root vector.\n')
incomplete_vector_set_relation_list.append(rel)
sys.stderr.write(str(len(self.data))+' relations loaded.\n')
if step == 1:
sys.stderr.write('Creating new file..\n')
fout = self.create_empty_output_file(vectors_file+'_reduced_step1.csv',n_samples,self.labels)
fin.seek(0)
elif step >= 2:
fin.close()
fin = open(vectors_file+'_reduced_step'+str(step-1)+'.csv','r')
fout = open(vectors_file+'_reduced_step'+str(step)+'.csv','w')
sys.stderr.write('Reducing, please wait...\n')
dimred = TruncatedSVD(n_components=n_dim)
dimred.fit(self.data)
sys.stderr.write('Reduction finished.\n')
sample_count = 0
for line in fin:
if line == '\n':
continue
sline = line.split('|')
rel = sline[0].replace(' ','')
if rel in most_frequent_relations_list:
if rel in incomplete_vector_set_relation_list:
continue
if len(sline)-1 < col:
sys.stderr.write('WARNING: not enough columns in line\n')
# sys.stderr.write(str(len(sline)) + '\n')
rel_pos = self.labels.index(rel)
if step == 1:
sline[pred_root_col] = VectorUtil.vector_to_string(self.preds[rel_pos])
vecred = dimred.transform(self.data[rel_pos])
#sys.stderr.write('Transformed vector size is ' + str(len(vecred))+ ' x ' + str(len(vecred[0])) + '\n')
if len(vecred) == 1:
vec_write = vecred[0]
#self.data[sample_count] = vec
sline[col] = VectorUtil.vector_to_string(vec_write) #vector reduced is put in the right column
rvstr = '|'.join(sline)
#sline[0] = rel
#print(sline[col])
# sys.stderr.write(rvstr)
fout.write(rvstr+'\n')
fout.flush()
sample_count = sample_count + 1
fout.close()
