def get_npapers():
print >> sys.stderr, 'Reading data...'
papers, authors = get_author_papers()
print >> sys.stderr, 'Calculating scores for train set...'
confirmed, deleted = get_train()
outf = open('npapers.train.dat', 'w')
for aid in confirmed:
allPapers = confirmed[aid] + deleted[aid]
for p1 in allPapers:
if p1 in confirmed[aid]:
tf = 'T'
else:
tf = 'F'
print >> outf, aid, p1, len(papers[aid]), tf
outf.close()
print >> sys.stderr, 'Calculating scores for validation set...'
validation = get_valid()
outf = open('npapers.valid.dat', 'w')
for aid in validation:
allPapers = validation[aid]
for p1 in allPapers:
print >> outf, aid, p1, len(papers[aid])
outf.close()
def get_sum_coauthors():
print >> sys.stderr, 'Reading data...'
papers, authors = get_author_papers()
#Create the number of collaborations between 2 authors
num_collaborations = {}
for author in authors.values():
for i in range(0,len(author)):
for j in range(i+1,len(author)):
#Always use the lowest author id as the first key
if author[i]<author[j]:
try:
num_collaborations[(author[i], author[j])] += 1
except KeyError:
num_collaborations[(author[i], author[j])] = 1
else:
try:
num_collaborations[(author[j], author[i])] += 1
except KeyError:
num_collaborations[(author[j], author[i])] = 1
print >> sys.stderr, 'Calculating scores for train set...'
confirmed, deleted = get_train()
print confirmed
outf = open('sumcoauthors.train.dat', 'w')
for aid in confirmed:
allPapers = confirmed[aid] + deleted[aid]
for p1 in allPapers:
sum_coauthors = 0
for author in authors[p1]:
if author<aid:
sum_coauthors += num_collaborations[(author,aid)]
elif aid<author:
sum_coauthors += num_collaborations[(aid,author)]
if p1 in confirmed[aid]:
tf = 'T'
else:
tf = 'F'
print >> outf, aid, p1, sum_coauthors, tf
outf.close()
print >> sys.stderr, 'Calculating scores for validation set...'
validation = get_valid()
outf = open('sumcoauthors.valid.dat', 'w')
for aid in validation:
allPapers = validation[aid]
for p1 in allPapers:
sum_coauthors = 0
for author in authors[p1]:
if author<aid:
sum_coauthors += num_collaborations[(author,aid)]
elif aid<author:
sum_coauthors += num_collaborations[(aid,author)]
print >> outf, aid, p1, sum_coauthors
outf.close()
def get_nvenue():
print >> sys.stderr, 'Reading venue info...'
journal, conference = get_venue()
print >> sys.stderr, 'Reading author-paper info...'
papers, authors = get_author_papers()
print >> sys.stderr, 'Counting papers in journals...'
aid2journal = build_author_venue_count(papers, journal)
print >> sys.stderr, 'Counting papers in conferences...'
aid2conference = build_author_venue_count(papers, conference)
print >> sys.stderr, 'Training set...'
confirmed, deleted = get_train()
outf = open('nvenue.train.dat', 'w')
for aid in confirmed:
for p1 in [p for p in confirmed[aid] + deleted[aid]]:
if p1 in confirmed[aid]:
tf = 'T'
elif p1 in deleted[aid]:
tf = 'F'
else:
raise WhatTheFuck
try:
sj = aid2journal[aid][journal[p1]]
except KeyError:
sj = aid2journal[aid][-1]
try:
sc = aid2conference[aid][conference[p1]]
except KeyError:
sc = aid2conference[aid][-1]
print >> outf, aid, p1, sj, sc, tf
outf.close()
print >> sys.stderr, 'Validation set...'
validation = get_valid()
outf = open('nvenue.valid.dat', 'w')
for aid in validation:
for p1 in validation[aid]:
try:
sj = aid2journal[aid][journal[p1]]
except KeyError:
sj = aid2journal[aid][-1]
try:
sc = aid2conference[aid][conference[p1]]
except KeyError:
sc = aid2conference[aid][-1]
print >> outf, aid, p1, sj, sc
outf.close()
import sys
import gc
from copy import deepcopy
from random import choice
from numpy import log, mean, std
from scipy.misc import factorial
from scipy.sparse import coo_matrix
import scipy.sparse.linalg as sp
from common import get_author_papers, get_train, get_valid
if __name__ == '__main__':
print >> sys.stderr, 'Reading data...'
papers, authors = get_author_papers()
confirmed, deleted = get_train()
print >> sys.stderr, 'Calculating scores for train set...'
confirmed, deleted = get_train()
outf = open('nauthors.train.dat', 'w')
for aid in confirmed:
allPapers = confirmed[aid] + deleted[aid]
for p1 in allPapers:
if p1 in confirmed[aid]:
tf = 'T'
else:
tf = 'F'
print >> outf, aid, p1, len(authors[p1]), tf
outf.close()
print >> sys.stderr, 'Calculating scores for validation set...'
validation = get_valid()
