cls[sr] = {}
cl = result0[i][sr]
cls[sr][userlist[i]['username']] = cl
pairings = [(sr1, u, sr2) for sr1 in args.subreddits for u in userlist
for sr2 in args.subreddits]
pool = multiprocessing.Pool(multiprocessing.cpu_count())
print('Testing classifiers')
result1 = pool.map(test_classifiers, pairings)
pool.close()
pool.join()
boxplot_data = {}
for i in range(0, len(pairings)):
pairing = pairings[i]
res = result1[i]
sr1, u, sr2 = pairing
username = u['username']
if username not in boxplot_data:
boxplot_data[username] = {}
rr = '%s %s' % (sr1, sr2)
boxplot_data[username][rr] = res
for u in boxplot_data:
boxplot = boxplot_data[u]
graph.boxplot_single('data/boxplot_%s' % u, boxplot, None,
(0, len(userlist)),
'trained reddit-tested reddit', 'mean rank'
'Box plot for mean rank for %s' % u)
# for sr2 in args.subreddits ]
pairings = [ (train_user['username'], test_user) for train_user in userlist for test_user in corpora_users]
pool = multiprocessing.Pool(multiprocessing.cpu_count())
print('Testing classifiers')
result1 = pool.map(test_classifiers, pairings)
pool.close()
pool.join()
boxplot_data = {}
for i in range(0, len(pairings)):
pairing = pairings[i]
res = result1[i]
if res is None:
continue
u1, u2 = pairing
if u1 not in boxplot_data:
boxplot_data[u1] = {}
boxplot_data[u1][u2] = res
for u in boxplot_data:
boxplot = boxplot_data[u]
graph.boxplot_single('data/boxplot_%s' % u,
boxplot,
None,
(0, len(userlist)),
'tested user',
'mean rank'
'Box plot for mean rank for %s from worldnews to gaming' % u)
for sr1 in args.subreddits
for u in userlist
for sr2 in args.subreddits ]
pool = multiprocessing.Pool(multiprocessing.cpu_count())
print('Testing classifiers')
result1 = pool.map(test_classifiers, pairings)
pool.close()
pool.join()
boxplot_data = {}
for i in range(0, len(pairings)):
pairing = pairings[i]
res = result1[i]
sr1, u, sr2 = pairing
username = u['username']
if username not in boxplot_data:
boxplot_data[username] = {}
rr = '%s %s' % (sr1, sr2)
boxplot_data[username][rr] = res
for u in boxplot_data:
boxplot = boxplot_data[u]
graph.boxplot_single('data/boxplot_%s' % u,
boxplot,
None,
(0, len(userlist)),
'trained reddit-tested reddit',
'mean rank'
'Box plot for mean rank for %s' % u)
# for sr1 in args.subreddits
# for u in corpora_users
# for sr2 in args.subreddits ]
pairings = [(train_user['username'], test_user) for train_user in userlist
for test_user in corpora_users]
pool = multiprocessing.Pool(multiprocessing.cpu_count())
print('Testing classifiers')
result1 = pool.map(test_classifiers, pairings)
pool.close()
pool.join()
boxplot_data = {}
for i in range(0, len(pairings)):
pairing = pairings[i]
res = result1[i]
if res is None:
continue
u1, u2 = pairing
if u1 not in boxplot_data:
boxplot_data[u1] = {}
boxplot_data[u1][u2] = res
for u in boxplot_data:
boxplot = boxplot_data[u]
graph.boxplot_single(
'data/boxplot_%s' % u, boxplot, None, (0, len(userlist)),
'tested user', 'mean rank'
'Box plot for mean rank for %s from worldnews to gaming' % u)
pairings = [(sr1, u, sr2) for sr1 in args.subreddits for u in userlist for sr2 in args.subreddits]
pool = multiprocessing.Pool(multiprocessing.cpu_count())
print("Testing classifiers")
result1 = pool.map(test_classifiers, pairings)
pool.close()
pool.join()
boxplot_data = {}
for i in range(0, len(pairings)):
pairing = pairings[i]
res = result1[i]
sr1, u, sr2 = pairing
username = u["username"]
if username not in boxplot_data:
boxplot_data[username] = {}
rr = "%s %s" % (sr1, sr2)
boxplot_data[username][rr] = res
for u in boxplot_data:
boxplot = boxplot_data[u]
graph.boxplot_single(
"data/boxplot_%s" % u,
boxplot,
None,
(0, len(userlist)),
"trained reddit-tested reddit",
"mean rank" "Box plot for mean rank for %s" % u,
)
