def process_sentences(usr, rcts_impo, no_cache):
no_cache = True
purps = get_aliases_p(rcts_impo)
print 'Purps:', purps
print 'NO_cache:', no_cache
if no_cache:
for pur_p in purps:
print 'Collect ractionlines for(1):', pur_p, '-----'
ractionlines = mdOntology.mdAbstractBaseOntology()
ractionlines.nodesER = rcts_impo
print 'Found:', len(
ractionlines.nodesER), '-> Ready to start inference-engine:'
#===============
process_termo(rcts_impo, usr, pur_p, ractionlines)
def process_sentences(usr,rcts_impo):
#
purps=get_aliases_p( rcts_impo )
print 'Purps:',purps
for pur_p in purps:
aliases=get_aliases_ob ()
layers=[]
layers2=[]
layers=get_ontology(aliases,pur_p,usr)
nms=[]
for dks in layers:
for dk1 in dks:
for dk in dk1:
nms.append(dk.name)
print 'GetLayers:(',aliases,',',pur_p,')->',(layers),'{',nms,'}'
#===============
#======== load ractionlines baseado no cenario escolhido => parametro de linha de comando purpose
print 'Collect ractionlines for(1):',pur_p,'-----'
ractionlines=mdOntology.mdAbstractBaseOntology ()
ractionlines.nodesER=rcts_impo
print 'Found:',len(ractionlines.nodesER),'-> Ready to start inference-engine:'
#===============
print 'OBJS:',aliases,' Result:',layers
if len(layers)>0:
print 'Start process of rct:-------------------------'
# doc
print 'Process layers:',len(layers)
for doc in layers:
#sente
print 'Process doc:',len(doc)
for sentece in doc:
#lines
print 'Process Sentence:',len(sentece)
ids=0
try:
for s in sentece:
ids+=1
#print s.name,'---',ids
print 'AK-sentence:[',sentece,']'
process_termo(sentece,usr,pur_p,ractionlines)
except Exception,ess1:
print 'Error process termo:',ess1
log.exception( '===========================' )
else:
process_termo([],usr,pur_p,ractionlines)
#===============
'''
def process_sentences(usr, rcts_impo):
purps = ret_usr_inter(usr)
for pur_p in purps:
aliases = get_aliases_ob()
layers = []
layers = get_ontology(aliases, pur_p, usr)
print 'GetLayers:(', aliases, ',', pur_p, ')->', len(layers)
layers2 = get_ontology2(aliases, pur_p, usr)
print 'GetLayers2:(', aliases, ',', pur_p, ')->', len(layers2)
#===============
#======== load ractionlines baseado no cenario escolhido => parametro de linha de comando purpose
print 'Collect ractionlines for(1):', pur_p, '-----'
ractionlines = mdOntology.mdAbstractBaseOntology()
ractionlines.nodesER = rcts_impo
print 'Found:', len(
ractionlines.nodesER), '-> Ready to start inference-engine:'
#===============
print 'OBJS:', aliases, ' Result:', layers
if len(layers) > 0:
print 'Start process of rct:-------------------------'
# doc
print 'Process layers:', len(layers)
for doc in layers:
#sente
print 'Process doc:', len(doc)
for sentece in doc:
#lines
print 'Process Sentence:', len(sentece)
ids = 0
try:
for s in sentece:
ids += 1
#print s.name,'---',ids
process_termo(sentece, usr, pur_p, ractionlines)
except Exception, ess1:
print 'Error process termo:', ess1
#===============
print 'OBJS Rels:', aliases, ' Result:', layers2
if len(layers2) > 0:
print 'Start process of rct:-------------------------'
# doc
for doc in layers2:
#sente
for sentece in doc:
#lines
process_termo(sentece, usr, pur_p, ractionlines, True)
def process_sentences2(usr,rcts_impo,layers_param):
#purps=ret_usr_inter(usr)
purps=get_aliases_p( rcts_impo )
print 'Purps:',purps
for pur_p in purps:
aliases=get_aliases_ob ()
layers=[]
layers2=[]
#======== load ractionlines baseado no cenario escolhido => parametro de linha de comando purpose
print 'Collect ractionlines for(1):',pur_p,'-----'
ractionlines=mdOntology.mdAbstractBaseOntology ()
ractionlines.nodesER=rcts_impo
print 'Found:',len(ractionlines.nodesER),'-> Ready to start inference-engine:'
#===============
print 'OBJS:',aliases,' Result:',layers
if True :
try:
process_termo(layers_param,usr,pur_p,ractionlines)
except Exception,ess1:
log.exception( '===========================' )
print 'Error process termo:',ess1