def test_matchPub(self):
self.extractor = Extractor().getInstance()
pubdao = PublicationDao()
person_id = 13419
person_name = 'jie tang'
# Read sources from files
all_models = {}
for page in range(0, 3):
filename = "".join((person_name, '_page_', str(page), '.html'))
f = file(os.path.join(self.settings.source_dir, filename), 'r')
html = f.read()
models = self.extractor.extract_from_source(html)
if models is not None:
self.extractor._Extractor__merge_into_extractedmap(
all_models, models)
print 'Total found DEBUG %s items.' % len(all_models)
# part 2
pubs = pubdao.getPublicationByPerson(person_id,
self.settings.generation)
printout = False
if printout:
for key, models in all_models.items():
print key, " --> ", models
print '==================='
for pub in pubs:
print pub
(pubs_matched, pubs_not_matched) = self.matchPub(pubs, all_models)
print '- test done -', len(pubs_matched), len(pubs_not_matched)
return pubs_not_matched
def test_matchPub(self):
self.extractor = Extractor().getInstance()
pubdao = PublicationDao()
person_id = 13419
person_name = 'jie tang'
# Read sources from files
all_models = {}
for page in range(0, 3):
filename = "".join((person_name, '_page_', str(page), '.html'))
f = file(os.path.join(self.settings.source_dir, filename), 'r')
html = f.read()
models = self.extractor.extract_from_source(html)
if models is not None:
self.extractor._Extractor__merge_into_extractedmap(all_models, models)
print 'Total found DEBUG %s items.' % len(all_models)
# part 2
pubs = pubdao.getPublicationByPerson(person_id, self.settings.generation)
printout = False
if printout:
for key, models in all_models.items():
print key, " --> ", models
print '==================='
for pub in pubs:
print pub
(pubs_matched, pubs_not_matched) = self.matchPub(pubs, all_models)
print '- test done -', len(pubs_matched), len(pubs_not_matched)
return pubs_not_matched
def test_getpublications(self): '''Test get all publications from database.''' print '-TEST-:', TestCase.test_getpublications.__doc__ pubdao = PublicationDao() pubs = pubdao.getPublicationByPerson(13423, self.settings.generation) # id for jie tang, current generation for pub in pubs: print pub print '-END TEST-'
class DebugSuit():
def __init__(self):
self.extractor = Extractor.getInstance()
self.matcher = PubMatcher.getInstance()
self.pubdao = PublicationDao()
def debug_person(self, person_id, person_name, generation):
'''Test method extract_from_source.'''
print '- DEBUG Person "%s" -:' % person_name
pubs = self.pubdao.getPublicationByPerson(person_id, generation)
all_models = self.extractor.getNodesByPersonName(person_name)
# if True:#print all all_models
# print '-' * 100, 'This is all_models'
# for key, models in all_models.items():
# print key, ':'
# for model in models:
# print '\t', model.readable_title, '(', model, ')'
# print '=' * 100 , 'all_models print done'
(pubs_found, pubs_notfound) = PubMatcher.getInstance().matchPub(pubs, all_models)
for pub in pubs_found:
print 'pubs found' , pub
print '-' * 100
for pub in pubs_notfound:
print 'not found' , pub
print '|||||||||||||||||||||||||||| get by pubs '
# todo here should be a while
query, used_pubs = Extractor.pinMaxQuery(pubs_notfound)
print '%s pub, query: %s' % (len(used_pubs), query)
all_models = self.extractor.getNodesByPubs(used_pubs)
(pubs_found, pubs_notfound) = PubMatcher.getInstance().matchPub(used_pubs, all_models)
for pub in pubs_found:
print 'pubs found' , pub
print '-' * 100
for pub in pubs_notfound:
print 'not found' , pub
print '- END DEBUG -'
def debug_pubs(self):
'''Debug get by pub'''
print '-TEST-:', self.debug_pubs.__doc__.strip()
#----------------------------------------------------
pub_candidates = []
# group 1
# pub_candidates.append(Publication(-1, 2000, 'Some Reflections on Proof Transformations', "pubkey", -1, "Peter B. Andrews", -5))
# pub_candidates.append(Publication(-1, 2000, 'Theorem Proving via General Mappings', "pubkey", -1, "Peter B. Andrews", -5))
# pub_candidates.append(Publication(-1, 2000, 'Connections and Higher-Order Logic', "pubkey", -1, "Peter B. Andrews", -5))
# pub_candidates.append(Publication(-1, 2000, 'The TPS Theorem Proving System', "pubkey", -1, "Peter B. Andrews,Sunil Issar,Dan Nesmith,Frank Pfenning", -5))
# group 2
# pub_candidates.append(Publication(-1, 2000, 'Linearizable concurrent objects', "pubkey", -1, "MP Herlihy, JM Wing", -5))
# pub_candidates.append(Publication(-1, 2000, 'Protein structure prediction using a combination of sequence homology and global energy minimization I. Global energy minimization of surface loops', "pubkey", -1, "MJ Dudek, HA Scheraga", -5))
# group 3
# pub_candidates.append(Publication(-1, 2000, 'Implementation of Prolog databases and database operation builtins in the WAM-Plus model', "pubkey", -1, "Z Chenxi, C Yungui, L Bo", -5))
# group 4
pub_candidates.append(Publication(-1, 2000, 'Procedural Semantics for Fuzzy Disjunctive Programs on Residuated Lattices', "pubkey", -1, "Dusan Guller", -5))
extractor = Extractor.getInstance()
query, used_pubs = Extractor.pinMaxQuery(pub_candidates)
print '%s pub, query: %s' % (len(used_pubs), query)
#
# Get WEB PAGE
#
use_web = True # ***************
if use_web:
all_models = extractor.getNodesByPubs(used_pubs)
else:
f = file('debug_pubs.txt', 'r')
html = f.read()
models = self.extractor.extract_from_source(html)
all_models = self.extractor._Extractor__merge_into_extractedmap(None, models)
print '\n- all_models ----------------------'
if all_models is not None:
for key, models in all_models.items():
print key
for model in models:
print "\t", model
else:
print 'all_models is None'
print '- all_models end ----------------------\n'
(pubs_found, pubs_notfound) = PubMatcher.getInstance().matchPub(used_pubs, all_models)
for pub in pubs_found:
print 'pubs found' , pub
print '-' * 100
for pub in pubs_notfound:
print 'not found' , pub
print '- test done -'
class DebugSuit():
def __init__(self):
self.extractor = Extractor.getInstance()
self.matcher = PubMatcher.getInstance()
self.pubdao = PublicationDao()
def debug_person(self, person_id, person_name, generation):
'''Test method extract_from_source.'''
print '- DEBUG Person "%s" -:' % person_name
pubs = self.pubdao.getPublicationByPerson(person_id, generation)
all_models = self.extractor.getNodesByPersonName(person_name)
# if True:#print all all_models
# print '-' * 100, 'This is all_models'
# for key, models in all_models.items():
# print key, ':'
# for model in models:
# print '\t', model.readable_title, '(', model, ')'
# print '=' * 100 , 'all_models print done'
(pubs_found,
pubs_notfound) = PubMatcher.getInstance().matchPub(pubs, all_models)
for pub in pubs_found:
print 'pubs found', pub
print '-' * 100
for pub in pubs_notfound:
print 'not found', pub
print '|||||||||||||||||||||||||||| get by pubs '
# todo here should be a while
query, used_pubs = Extractor.pinMaxQuery(pubs_notfound)
print '%s pub, query: %s' % (len(used_pubs), query)
all_models = self.extractor.getNodesByPubs(used_pubs)
(pubs_found, pubs_notfound) = PubMatcher.getInstance().matchPub(
used_pubs, all_models)
for pub in pubs_found:
print 'pubs found', pub
print '-' * 100
for pub in pubs_notfound:
print 'not found', pub
print '- END DEBUG -'
def debug_pubs(self):
'''Debug get by pub'''
print '-TEST-:', self.debug_pubs.__doc__.strip()
#----------------------------------------------------
pub_candidates = []
# group 1
# pub_candidates.append(Publication(-1, 2000, 'Some Reflections on Proof Transformations', "pubkey", -1, "Peter B. Andrews", -5))
# pub_candidates.append(Publication(-1, 2000, 'Theorem Proving via General Mappings', "pubkey", -1, "Peter B. Andrews", -5))
# pub_candidates.append(Publication(-1, 2000, 'Connections and Higher-Order Logic', "pubkey", -1, "Peter B. Andrews", -5))
# pub_candidates.append(Publication(-1, 2000, 'The TPS Theorem Proving System', "pubkey", -1, "Peter B. Andrews,Sunil Issar,Dan Nesmith,Frank Pfenning", -5))
# group 2
# pub_candidates.append(Publication(-1, 2000, 'Linearizable concurrent objects', "pubkey", -1, "MP Herlihy, JM Wing", -5))
# pub_candidates.append(Publication(-1, 2000, 'Protein structure prediction using a combination of sequence homology and global energy minimization I. Global energy minimization of surface loops', "pubkey", -1, "MJ Dudek, HA Scheraga", -5))
# group 3
# pub_candidates.append(Publication(-1, 2000, 'Implementation of Prolog databases and database operation builtins in the WAM-Plus model', "pubkey", -1, "Z Chenxi, C Yungui, L Bo", -5))
# group 4
pub_candidates.append(
Publication(
-1, 2000,
'Procedural Semantics for Fuzzy Disjunctive Programs on Residuated Lattices',
"pubkey", -1, "Dusan Guller", -5))
extractor = Extractor.getInstance()
query, used_pubs = Extractor.pinMaxQuery(pub_candidates)
print '%s pub, query: %s' % (len(used_pubs), query)
#
# Get WEB PAGE
#
use_web = True # ***************
if use_web:
all_models = extractor.getNodesByPubs(used_pubs)
else:
f = file('debug_pubs.txt', 'r')
html = f.read()
models = self.extractor.extract_from_source(html)
all_models = self.extractor._Extractor__merge_into_extractedmap(
None, models)
print '\n- all_models ----------------------'
if all_models is not None:
for key, models in all_models.items():
print key
for model in models:
print "\t", model
else:
print 'all_models is None'
print '- all_models end ----------------------\n'
(pubs_found, pubs_notfound) = PubMatcher.getInstance().matchPub(
used_pubs, all_models)
for pub in pubs_found:
print 'pubs found', pub
print '-' * 100
for pub in pubs_notfound:
print 'not found', pub
print '- test done -'
