while answer != "y" and answer != "n":
print "Not Y or N! See similar abstracts? (Y/N)"
answer = raw_input().lower()
# if not, exit
if answer == "n":
if version.lower() == 'p':
for i in range(1,size):
comm.send(0, dest = i)
sys.exit("Thanks for visiting!")
# Calculate similarity values for given article
sim_matrix = []
if version.lower() == 'p':
if rank == 0:
for i in range(1,size):
comm.send(1, dest = i)
sim_matrix = sorted(enumerate(Process.main_parallel_sim(comm, ind, abstracts, type, mattype)), key=lambda ind:ind[1])
else:
tosend = comm.recv(source = 0)
if tosend == 1:
Process.main_parallel_sim(comm, ind, abstracts, type, mattype)
elif tosend == 0:
sys.exit()
else:
if rank == 0:
sim_matrix = sorted(enumerate(Process.main_serial_sim(comm, ind, abstracts, type, mattype)), key=lambda ind:ind[1])
else:
sys.exit()
# print 5 most similar articles
if rank == 0:
print "Similar articles:\n"
setabs = 0
print "Timing tfidf time ..."
# Find tfidf
ptfidfstart = MPI.Wtime()
Process.master_tfidf(comm, abstracts, bigramdictlen)
ptfidfend = MPI.Wtime()
print "Timing topic modelling time ..."
# topic modeling
ptopicstart = MPI.Wtime()
Process.master_topics(comm, abstracts)
ptopicend = MPI.Wtime()
print "Timing similarity measurements time ..."
# test similarity
psimbowstart = MPI.Wtime()
Process.main_parallel_sim(comm, 0, abstracts, 'bow', 'cossim')
psimbowend = MPI.Wtime()
psimbigramstart = MPI.Wtime()
Process.main_parallel_sim(comm, 0, abstracts, 'bigram', 'cossim')
psimbigramend = MPI.Wtime()
psimjacstart = MPI.Wtime()
Process.main_parallel_sim(comm, 0, abstracts, 'bow', 'jaccard')
psimjacend = MPI.Wtime()
# print times
print "Parallel times"
print "Load time: %f secs" % (ploadend - ploadstart)
print "Create and send dictionary time: %f secs" % (pdictend - pdictstart)
print "Clean text time: %f secs" % (pcleanend - pcleanstart)
print "Send abstract time: %f secs" % (pabsend - pabsstart)
print "Frequency time: %f secs" % (pfreqend - pfreqstart)
