def runExperiment(args):
""" Build a model and test it."""
model, dataSet = setupExperiment(args)
allRanks, avgRanks, avgStats = testModel(
model, [d for d in dataSet if d[2] % 100 == 0], categorySize=6, verbosity=args.verbosity
)
printRankResults("JUnit5", avgRanks, avgStats)
return model
def runExperiment(args):
""" Build a model and test it."""
model, dataSet = setupExperiment(args)
if args.testB:
allRanks, avgRanks, avgStats = testModel(model,
[d for d in dataSet if d[2]%100==0],
categorySize=CATEGORY_SIZE,
verbosity=args.verbosity)
printRankResults("JUnit3B", avgRanks, avgStats)
else:
allRanks, avgRanks, avgStats = testModel(model,
dataSet,
categorySize=CATEGORY_SIZE,
verbosity=args.verbosity)
printRankResults("JUnit3", avgRanks, avgStats)
return allRanks, avgRanks, avgStats
def runExperiment(args):
""" Build a model, test it, print and return results metrics."""
model, dataSet = setupExperiment(args)
allRanks, avgRanks, avgStats = testModel(model,
dataSet,
categorySize=CATEGORY_SIZE,
verbosity=args.verbosity)
printRankResults("JUnit1", avgRanks, avgStats)
return allRanks, avgRanks, avgStats
def runExperiment(args):
""" Build a model and test it."""
model, dataSet = setupExperiment(args)
allRanks, avgRanks, avgStats = testModel(
model, [d for d in dataSet if d[2] % 100 == 0],
categorySize=6,
verbosity=args.verbosity)
printRankResults("JUnit5", avgRanks, avgStats)
return model
def runExperiment(args):
""" Build a model, test it, print and return results metrics."""
model, dataSet = setupExperiment(args)
allRanks, avgRanks, avgStats = testModel(model,
dataSet,
categorySize=CATEGORY_SIZE,
verbosity=args.verbosity)
printRankResults("JUnit1", avgRanks, avgStats)
return allRanks, avgRanks, avgStats
def runExperiment(args, testIndex=0):
""" Build a model and test it.
@param testIndex (int) Specifies the doc of each group we use for inference.
"""
model, dataSet = setupExperiment(args)
allRanks, avgRanks, avgStats = testModel(
model, [d for d in dataSet if d[2] % 100 == testIndex], categorySize=CATEGORY_SIZE, verbosity=args.verbosity
)
printRankResults("JUnit2", avgRanks, avgStats)
return allRanks, avgRanks, avgStats
def runExperiment(args):
""" Build a model and test it."""
# TODO: args.verbosity deprecated b/c PrettyTable formatting can't handle
# large text items.
args.verbosity = 0
model, dataSet = setupExperiment(args)
allRanks, avgRanks, avgStats = testModel(model,
[d for d in dataSet if d[2]%100==0],
categorySize=CATEGORY_SIZE,
verbosity=args.verbosity)
printRankResults("JUnit4", avgRanks, avgStats)
return allRanks, avgRanks, avgStats
def runExperiment(args, testIndex=0):
""" Build a model and test it.
@param testIndex (int) Specifies the doc of each group we use for inference.
"""
model, dataSet = setupExperiment(args)
allRanks, avgRanks, avgStats = testModel(
model,
[d for d in dataSet if d[2]%100==testIndex],
categorySize=CATEGORY_SIZE,
verbosity=args.verbosity
)
printRankResults("JUnit2", avgRanks, avgStats)
return allRanks, avgRanks, avgStats
def runExperiment(args):
""" Build a model and test it."""
# Filtering text helps word level and union pooler models for test 4.
# It does not help keywords or document fingerprint models.
if args.modelName == "htm":
args.filterText = True
model, dataSet = setupExperiment(args)
allRanks, avgRanks, avgStats = testModel(
model, [d for d in dataSet if d[2] % 100 == 0],
categorySize=CATEGORY_SIZE,
verbosity=args.verbosity)
printRankResults("JUnit4", avgRanks, avgStats)
return allRanks, avgRanks, avgStats
def runExperiment(args):
""" Build a model and test it."""
# Filtering text helps word level and union pooler models for test 4.
# It does not help keywords or document fingerprint models.
if args.modelName == "htm":
args.filterText = True
model, dataSet = setupExperiment(args)
allRanks, avgRanks, avgStats = testModel(
model,
[d for d in dataSet if d[2]%100==0],
categorySize=CATEGORY_SIZE,
verbosity=args.verbosity
)
printRankResults("JUnit4", avgRanks, avgStats)
return allRanks, avgRanks, avgStats