def preprocess(inputPath, inputPtnPath, outputPath):
# Checking output path
projizz.checkPath(outputPath)
model, table = projizz.readPrefixTreeModelWithTable(
"../yago/yagoPatternTree.model",
"../patty/yagoPatternTreeWithConfidence.table")
start_time = datetime.now()
# Processes pool
proceessorNumber = multiprocessing.cpu_count()
if proceessorNumber > 20:
proceessorNumber = 20
pool = multiprocessing.Pool(processes=proceessorNumber)
t = 0
result = []
for filename in os.listdir(inputPtnPath):
if ".json" in filename:
result.append(
pool.apply_async(
mapper,
(t, filename, inputPath, inputPtnPath, model, table)))
t += 1
pool.close()
pool.join()
patternInstances = {}
# Reducer
for r in result:
sibf = r.get()
for key in sibf:
for ptnId in sibf[key]:
if not ptnId in patternInstances:
patternInstances[ptnId] = {}
for rela in sibf[key][ptnId]:
for inst in sibf[key][ptnId][rela]:
if not rela in patternInstances[ptnId]:
patternInstances[ptnId][rela] = {}
if not key in patternInstances[ptnId][rela]:
patternInstances[ptnId][rela][key] = []
patternInstances[ptnId][rela][key].append(inst)
# Write to files
# NOTE
# Output Format:
# ptnId.json (json)
# rela: keys
# key: line text
for ptnId in patternInstances:
projizz.jsonWrite(patternInstances[ptnId],
os.path.join(outputPath, "%s.json" % (ptnId)))
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds, diff.microseconds)
def main(inputPath, inputPtnPath, vsmPath, confidence, psfile, outputPath,
outputFilename):
model, table = projizz.readPrefixTreeModelWithTable(
"../yago/yagoPatternTree.model",
"../patty/yagoPatternTreeWithConfidence.table")
properties = projizz.buildYagoProperties({"tp": [], "fp": [], "fn": []})
domainRange = projizz.getYagoRelationDomainRange()
idf, docs, lens = projizz.getVSMmodels(vsmPath)
st = projizz.getSortedPatternStatistic(projizz.jsonRead(psfile))
vsmData = (idf, docs, lens)
projizz.checkPath(outputPath)
start_time = datetime.now()
pool = multiprocessing.Pool(processes=multiprocessing.cpu_count())
t = 0
result = []
for filename in os.listdir(inputPtnPath):
if ".json" in filename:
partAns = copy.deepcopy(properties)
result.append(
pool.apply_async(
mapper, (t, filename, inputPath, inputPtnPath, table, st,
partAns, domainRange, confidence, vsmData)))
#result.append( mapper( t, filename, inputPath, inputPtnPath, table, partAns, domainRange, confidence, vsmData ))
t += 1
pool.close()
pool.join()
expResult = {}
for res in result:
r = res.get()
for keyname in r:
if not keyname in expResult:
expResult[keyname] = copy.deepcopy(properties)
for m in r[keyname]:
if m == "produced":
continue
expResult[keyname][m]["tp"] += r[keyname][m]["tp"]
expResult[keyname][m]["fp"] += r[keyname][m]["fp"]
expResult[keyname][m]["fn"] += r[keyname][m]["fn"]
for keyname in expResult:
p = expResult[keyname]
keydirName = "vsm-%d" % (keyname)
projizz.checkPath(os.path.join(outputPath, keydirName))
projizz.jsonWrite(p,
os.path.join(outputPath, keydirName, outputFilename))
print "start write out to %s" % (os.path.join(outputPath, keydirName))
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds, diff.microseconds)
def preprocess(inputPath,inputPtnPath,outputPath):
# Checking output path
projizz.checkPath(outputPath)
model, table = projizz.readPrefixTreeModelWithTable("../yago/yagoPatternTree.model", "../patty/yagoPatternTreeWithConfidence.table")
start_time = datetime.now()
# Processes pool
proceessorNumber = multiprocessing.cpu_count()
if proceessorNumber > 20:
proceessorNumber = 20
pool = multiprocessing.Pool(processes=proceessorNumber)
t = 0
result = []
for filename in os.listdir(inputPtnPath):
if ".json" in filename:
result.append( pool.apply_async( mapper, (t,filename,inputPath,inputPtnPath, model, table)) )
t += 1
pool.close()
pool.join()
patternInstances = {}
# Reducer
for r in result:
sibf = r.get()
for key in sibf:
for ptnId in sibf[key]:
if not ptnId in patternInstances:
patternInstances[ptnId] = {}
for rela in sibf[key][ptnId]:
for inst in sibf[key][ptnId][rela]:
if not rela in patternInstances[ptnId]:
patternInstances[ptnId][rela] = {}
if not key in patternInstances[ptnId][rela]:
patternInstances[ptnId][rela][key] = []
patternInstances[ptnId][rela][key].append(inst)
# Write to files
# NOTE
# Output Format:
# ptnId.json (json)
# rela: keys
# key: line text
for ptnId in patternInstances:
projizz.jsonWrite(patternInstances[ptnId],os.path.join(outputPath,"%s.json" % (ptnId)))
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds, diff.microseconds)
def main(inputPath, inputPtnPath, vsmPath, confidence, psfile, outputPath, outputFilename):
model, table = projizz.readPrefixTreeModelWithTable("../yago/yagoPatternTree.model","../patty/yagoPatternTreeWithConfidence.table")
properties = projizz.buildYagoProperties({"tp":[],"fp":[],"fn":[]})
domainRange = projizz.getYagoRelationDomainRange()
idf,docs,lens = projizz.getVSMmodels(vsmPath)
st = projizz.getSortedPatternStatistic( projizz.jsonRead(psfile) )
vsmData = (idf, docs, lens)
projizz.checkPath(outputPath)
start_time = datetime.now()
pool = multiprocessing.Pool(processes=multiprocessing.cpu_count())
t = 0
result = []
for filename in os.listdir(inputPtnPath):
if ".json" in filename:
partAns = copy.deepcopy(properties)
result.append(pool.apply_async(mapper, ( t, filename, inputPath, inputPtnPath, table, st, partAns, domainRange, confidence, vsmData )))
#result.append( mapper( t, filename, inputPath, inputPtnPath, table, partAns, domainRange, confidence, vsmData ))
t += 1
pool.close()
pool.join()
expResult = {}
for res in result:
r = res.get()
for keyname in r:
if not keyname in expResult:
expResult[keyname] = copy.deepcopy(properties)
for m in r[keyname]:
if m == "produced":
continue
expResult[keyname][m]["tp"] += r[keyname][m]["tp"]
expResult[keyname][m]["fp"] += r[keyname][m]["fp"]
expResult[keyname][m]["fn"] += r[keyname][m]["fn"]
for keyname in expResult:
p = expResult[keyname]
keydirName = "vsm-%d" % (keyname)
projizz.checkPath( os.path.join(outputPath,keydirName))
projizz.jsonWrite(p,os.path.join(outputPath,keydirName,outputFilename))
print "start write out to %s" % (os.path.join(outputPath,keydirName))
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds, diff.microseconds)
def buildModels(inputpath, outputPath):
projizz.checkPath(outputPath)
cpuCount = multiprocessing.cpu_count()
if cpuCount > 8:
cpuCount = 8
pool = multiprocessing.Pool(processes=cpuCount)
t = 0
relations = projizz.getYagoRelation()
for relation in relations:
if relation == "produced":
continue
pool.apply_async(trainModel, (t, relation, inputpath, outputPath))
t += 1
pool.close()
pool.join()
print "Done training all classifiers"
def buildModels(inputpath,outputPath):
projizz.checkPath(outputPath)
cpuCount = multiprocessing.cpu_count()
if cpuCount > 8:
cpuCount = 8
pool = multiprocessing.Pool(processes=cpuCount)
t = 0
relations = projizz.getYagoRelation()
for relation in relations:
if relation == "produced":
continue
pool.apply_async(trainModel, (t,relation,inputpath,outputPath))
t += 1
pool.close()
pool.join()
print "Done training all classifiers"
def preprocess(inputPath, topN, outputPath):
# Checking output path
projizz.checkPath(outputPath)
model, table = projizz.readPrefixTreeModelWithTable(
"../yago/yagoPatternTree.model",
"../patty/yagoPatternTreeWithConfidence.table")
start_time = datetime.now()
# Processes pool
proceessorNumber = multiprocessing.cpu_count()
if proceessorNumber > 20:
proceessorNumber = 20
pool = multiprocessing.Pool(processes=proceessorNumber)
t = 0
result = []
for filename in os.listdir(inputPath):
if ".json" in filename:
result.append(
pool.apply_async(
mapper,
(t, filename, inputPath, topN, outputPath, model, table)))
t += 1
pool.close()
pool.join()
words = {}
idf = {}
tfs = {}
# Reducer - DF
types = 0
for r in result:
fn, tks = r.get()
tfs[fn] = tks
types += 1
for t in tks:
if t not in words:
words[t] = 0
words[t] += 1
print "Doc#", types, "words#", len(words)
projizz.jsonWrite(words, os.path.join(outputPath, "documentFreq.df"))
# Calculate idf
for w in words:
if words[w] == 0:
continue
idf[w] = math.log(float(types) / float(words[w]), 10)
projizz.jsonWrite(idf, os.path.join(outputPath, "idf.idf"))
print "Write out idf file"
# Calculate td-idf weight
for fn in tfs:
tks = tfs[fn]
weight = {}
for t in tks:
tf = tks[t]
if t not in idf:
continue
weight[t] = tf * idf[t]
projizz.jsonWrite(weight, os.path.join(outputPath, fn))
print "build", fn, "tf-idf weight"
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds, diff.microseconds)
def preprocess(inputPath, inputPtnPath, outputPath, confidence):
# Checking output path
projizz.checkPath(outputPath)
model, table = projizz.readPrefixTreeModelWithTable(
"../yago/yagoPatternTree.model",
"../patty/yagoPatternTreeWithConfidence.table")
start_time = datetime.now()
# Processes pool
proceessorNumber = multiprocessing.cpu_count()
if proceessorNumber > 20:
proceessorNumber = 20
pool = multiprocessing.Pool(processes=proceessorNumber)
t = 0
result = []
for filename in os.listdir(inputPtnPath):
if ".json" in filename:
result.append(
pool.apply_async(mapper, (t, filename, inputPath, inputPtnPath,
model, table, confidence)))
#result.append( mapper(t,filename,inputPath,inputPtnPath, model, table, confidence))
t += 1
pool.close()
pool.join()
modelArticles = {}
negAritcles = {}
POSArticles = {}
NEGArticles = {}
# Reducer
for r in result:
sibr, osibr, p, n = r.get()
for rela in sibr:
if not rela in modelArticles:
modelArticles[rela] = []
modelArticles[rela] += sibr[rela]
for rela in osibr:
if not rela in negAritcles:
negAritcles[rela] = []
negAritcles[rela] += osibr[rela]
for rela in p:
if not rela in POSArticles:
POSArticles[rela] = []
POSArticles[rela] += p[rela]
for rela in n:
if not rela in NEGArticles:
NEGArticles[rela] = []
NEGArticles[rela] += n[rela]
#
# relation.json: [line, line, line, ....]
#
for rela in modelArticles:
print rela
projizz.jsonWrite(modelArticles[rela],
os.path.join(outputPath, "%s.json" % (rela)))
for rela in negAritcles:
print rela
projizz.jsonWrite(negAritcles[rela],
os.path.join(outputPath, "%s.other" % (rela)))
for rela in POSArticles:
print rela
projizz.jsonWrite(POSArticles[rela],
os.path.join(outputPath, "%s.pos" % (rela)))
for rela in NEGArticles:
print rela
projizz.jsonWrite(NEGArticles[rela],
os.path.join(outputPath, "%s.neg" % (rela)))
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds, diff.microseconds)
def generate(inputSPIpath, inputTestPath, outputVSMpath, confidence):
# Checking output path
projizz.checkPath(outputVSMpath)
model, table = projizz.readPrefixTreeModelWithTable(
"../yago/yagoPatternTree.model",
"../patty/yagoPatternTreeWithConfidence.table")
# Processes pool
proceessorNumber = multiprocessing.cpu_count()
if proceessorNumber > 20:
proceessorNumber = 20
pool = multiprocessing.Pool(processes=proceessorNumber)
# Collect not used keys
# because using 5-fold CV
t = 0
result = []
for filename in os.listdir(inputTestPath):
if ".json" in filename:
result.append(
pool.apply_async(mapper, (t, filename, inputTestPath)))
t += 1
pool.close()
pool.join()
notUsedKeys = []
for r in result:
ks = r.get()
notUsedKeys += ks
### Build Model
# Paatern Selection
modelArticles = projizz.buildYagoProperties([])
words = []
count = 0
for filename in os.listdir(inputSPIpath):
if ".json" in filename:
ptnId = filename[:-5]
# ignore invalidate pattern
if not projizz.isPatternValidate(
ptnId, table, confidence=confidence):
continue
count += 1
print count, ptnId
ptnInstance = projizz.jsonRead(os.path.join(
inputSPIpath, filename))
for rela in ptnInstance:
for key in ptnInstance[rela]:
# ignore in testing data's key
if key in notUsedKeys:
continue
for line in ptnInstance[rela][key]:
modelArticles[rela].append(line)
if count % 100 == 0:
print "Read", count, "files"
for relation in modelArticles:
print relation
projizz.jsonWrite(modelArticles[relation],
os.path.join(outputVSMpath, "%s.txt" % (relation)))
def generate(inputSPIpath,inputTestPath,outputVSMpath,confidence):
# Checking output path
projizz.checkPath(outputVSMpath)
model, table = projizz.readPrefixTreeModelWithTable("../yago/yagoPatternTree.model", "../patty/yagoPatternTreeWithConfidence.table")
# Processes pool
proceessorNumber = multiprocessing.cpu_count()
if proceessorNumber > 20:
proceessorNumber = 20
pool = multiprocessing.Pool(processes=proceessorNumber)
# Collect not used keys
# because using 5-fold CV
t = 0
result = []
for filename in os.listdir(inputTestPath):
if ".json" in filename:
result.append( pool.apply_async( mapper, (t,filename,inputTestPath) ) )
t += 1
pool.close()
pool.join()
notUsedKeys = []
for r in result:
ks = r.get()
notUsedKeys += ks
### Build Model
# Paatern Selection
modelArticles = projizz.buildYagoProperties([])
words = []
count = 0
for filename in os.listdir(inputSPIpath):
if ".json" in filename:
ptnId = filename[:-5]
# ignore invalidate pattern
if not projizz.isPatternValidate(ptnId, table, confidence=confidence):
continue
count += 1
print count,ptnId
ptnInstance = projizz.jsonRead( os.path.join(inputSPIpath,filename) )
for rela in ptnInstance:
for key in ptnInstance[rela]:
# ignore in testing data's key
if key in notUsedKeys:
continue
for line in ptnInstance[rela][key]:
modelArticles[rela].append(line)
if count%100 == 0:
print "Read",count,"files"
for relation in modelArticles:
print relation
projizz.jsonWrite(modelArticles[relation],os.path.join(outputVSMpath,"%s.txt" % (relation)))
def preprocess(inputPath,outputPath):
# Checking output path
projizz.checkPath(outputPath)
model, table = projizz.readPrefixTreeModelWithTable("../yago/yagoPatternTree.model", "../patty/yagoPatternTreeWithConfidence.table")
start_time = datetime.now()
# Processes pool
proceessorNumber = multiprocessing.cpu_count()
if proceessorNumber > 20:
proceessorNumber = 20
pool = multiprocessing.Pool(processes=proceessorNumber)
t = 0
result = []
for filename in os.listdir(inputPath):
if ".json" in filename:
result.append( pool.apply_async( mapper, (t,filename,inputPath,outputPath, model, table)) )
t += 1
pool.close()
pool.join()
words = {}
idf = {}
tfs = {}
# Reducer - DF
types = 0
for r in result:
fn,tks = r.get()
tfs[fn] = tks
types += 1
for t in tks:
if t not in words:
words[t] = 0
words[t] += 1
print "Doc#",types,"words#",len(words)
projizz.jsonWrite(words,os.path.join(outputPath,"documentFreq.df"))
# Calculate idf
for w in words:
if words[w] == 0:
continue
idf[w] = math.log(float(types)/float(words[w]),10)
projizz.jsonWrite(idf,os.path.join(outputPath,"idf.idf"))
print "Write out idf file"
# Calculate td-idf weight
for fn in tfs:
tks = tfs[fn]
weight = {}
for t in tks:
tf = tks[t]
if t not in idf:
continue
weight[t] = tf * idf[t]
projizz.jsonWrite(weight,os.path.join(outputPath,fn))
print "build",fn,"tf-idf weight"
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds, diff.microseconds)
def preprocess(inputPath,inputPtnPath,outputPath,confidence):
# Checking output path
projizz.checkPath(outputPath)
model, table = projizz.readPrefixTreeModelWithTable("../yago/yagoPatternTree.model", "../patty/yagoPatternTreeWithConfidence.table")
start_time = datetime.now()
# Processes pool
proceessorNumber = multiprocessing.cpu_count()
if proceessorNumber > 20:
proceessorNumber = 20
pool = multiprocessing.Pool(processes=proceessorNumber)
t = 0
result = []
for filename in os.listdir(inputPtnPath):
if ".json" in filename:
result.append( pool.apply_async( mapper, (t,filename,inputPath,inputPtnPath, model, table, confidence)) )
#result.append( mapper(t,filename,inputPath,inputPtnPath, model, table, confidence))
t += 1
pool.close()
pool.join()
modelArticles = {}
negAritcles = {}
POSArticles = {}
NEGArticles = {}
# Reducer
for r in result:
sibr, osibr, p, n = r.get()
for rela in sibr:
if not rela in modelArticles:
modelArticles[rela] = []
modelArticles[rela] += sibr[rela]
for rela in osibr:
if not rela in negAritcles:
negAritcles[rela] = []
negAritcles[rela] += osibr[rela]
for rela in p:
if not rela in POSArticles:
POSArticles[rela] = []
POSArticles[rela] += p[rela]
for rela in n:
if not rela in NEGArticles:
NEGArticles[rela] = []
NEGArticles[rela] += n[rela]
#
# relation.json: [line, line, line, ....]
#
for rela in modelArticles:
print rela
projizz.jsonWrite(modelArticles[rela],os.path.join(outputPath,"%s.json" % (rela)))
for rela in negAritcles:
print rela
projizz.jsonWrite(negAritcles[rela],os.path.join(outputPath,"%s.other" % (rela)))
for rela in POSArticles:
print rela
projizz.jsonWrite(POSArticles[rela],os.path.join(outputPath,"%s.pos" % (rela)))
for rela in NEGArticles:
print rela
projizz.jsonWrite(NEGArticles[rela],os.path.join(outputPath,"%s.neg" % (rela)))
diff = datetime.now() - start_time
print "Spend %d.%d seconds" % (diff.seconds, diff.microseconds)
