def main():
"""
Just runs some example code.
"""
# setup the flow
flow = Flow(name="list files")
listfiles = ListFiles()
listfiles.config["dir"] = str(helper.get_data_dir())
listfiles.config["list_files"] = True
listfiles.config["list_dirs"] = False
listfiles.config["recursive"] = False
listfiles.config["regexp"] = ".*.arff"
flow.actors.append(listfiles)
tee = Tee()
flow.actors.append(tee)
convert = Convert()
convert.config["setup"] = conversion.PassThrough()
tee.actors.append(convert)
console = Console()
console.config["prefix"] = "Match: "
tee.actors.append(console)
load = LoadDataset()
load.config["use_custom_loader"] = True
flow.actors.append(load)
cross = CrossValidate()
cross.config["setup"] = Classifier(classname="weka.classifiers.trees.J48",
options=["-C", "0.3"])
flow.actors.append(cross)
summary = EvaluationSummary()
summary.config["matrix"] = True
flow.actors.append(summary)
# print flow
flow.setup()
print("\n" + flow.tree + "\n")
# save the flow
fname = tempfile.gettempdir() + os.sep + "simpleflow.json"
Flow.save(flow, fname)
# load flow
fl2 = Flow.load(fname)
# output flow
fl2.setup()
print("\n" + fl2.tree + "\n")
def main():
"""
Just runs some example code.
"""
# setup the flow
flow = Flow(name="stopping the flow")
outer = ForLoop()
outer.config["max"] = 10
flow.actors.append(outer)
ssv = SetStorageValue()
ssv.config["storage_name"] = "current"
flow.actors.append(ssv)
tee = Tee()
tee.config["condition"] = "@{current} == 7"
flow.actors.append(tee)
stop = Stop()
tee.actors.append(stop)
console = Console()
flow.actors.append(console)
# run the flow
msg = flow.setup()
if msg is None:
print("\n" + flow.tree + "\n")
msg = flow.execute()
if msg is not None:
print("Error executing flow:\n" + msg)
else:
print("Error setting up flow:\n" + msg)
flow.wrapup()
flow.cleanup()
def main():
"""
Just runs some example code.
"""
# setup the flow
flow = Flow(name="stopping the flow")
outer = ForLoop()
outer.config["max"] = 10
flow.actors.append(outer)
ssv = SetStorageValue()
ssv.config["storage_name"] = "current"
flow.actors.append(ssv)
tee = Tee()
tee.config["condition"] = "@{current} == 7"
flow.actors.append(tee)
stop = Stop()
tee.actors.append(stop)
console = Console()
flow.actors.append(console)
# run the flow
msg = flow.setup()
if msg is None:
print("\n" + flow.tree + "\n")
msg = flow.execute()
if msg is not None:
print("Error executing flow:\n" + msg)
else:
print("Error setting up flow:\n" + msg)
flow.wrapup()
flow.cleanup()
def main():
"""
Just runs some example code.
"""
# setup the flow
helper.print_title("Attribute selection")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="attribute selection")
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
flow.actors.append(filesupplier)
loaddataset = LoadDataset()
loaddataset.config["incremental"] = False
flow.actors.append(loaddataset)
attsel = AttributeSelection()
attsel.config["search"] = ASSearch(classname="weka.attributeSelection.BestFirst")
attsel.config["eval"] = ASEvaluation(classname="weka.attributeSelection.CfsSubsetEval")
flow.actors.append(attsel)
results = Tee()
results.name = "output results"
flow.actors.append(results)
picker = ContainerValuePicker()
picker.config["value"] = "Results"
picker.config["switch"] = True
results.actors.append(picker)
console = Console()
console.config["prefix"] = "Attribute selection results:"
results.actors.append(console)
reduced = Tee()
reduced.name = "reduced dataset"
flow.actors.append(reduced)
picker = ContainerValuePicker()
picker.config["value"] = "Reduced"
picker.config["switch"] = True
reduced.actors.append(picker)
console = Console()
console.config["prefix"] = "Reduced dataset:\n\n"
reduced.actors.append(console)
# run the flow
msg = flow.setup()
if msg is None:
print("\n" + flow.tree + "\n")
msg = flow.execute()
if msg is not None:
print("Error executing flow:\n" + msg)
else:
print("Error setting up flow:\n" + msg)
flow.wrapup()
flow.cleanup()
def main():
"""
Just runs some example code.
"""
# setup the flow
count = 50
helper.print_title("build clusterer incrementally")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="build clusterer incrementally")
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
flow.actors.append(filesupplier)
initcounter = InitStorageValue()
initcounter.config["storage_name"] = "counter"
initcounter.config["value"] = 0
flow.actors.append(initcounter)
loaddataset = LoadDataset()
loaddataset.config["incremental"] = True
flow.actors.append(loaddataset)
remove = Filter(name="remove class attribute")
remove.config["setup"] = filters.Filter(
classname="weka.filters.unsupervised.attribute.Remove",
options=["-R", "last"])
flow.actors.append(remove)
inccounter = UpdateStorageValue()
inccounter.config["storage_name"] = "counter"
inccounter.config["expression"] = "{X} + 1"
flow.actors.append(inccounter)
train = Train()
train.config["setup"] = Clusterer(classname="weka.clusterers.Cobweb")
flow.actors.append(train)
pick = ContainerValuePicker()
pick.config["value"] = "Model"
pick.config["switch"] = True
flow.actors.append(pick)
tee = Tee(name="output model every " + str(count) + " instances")
tee.config["condition"] = "@{counter} % " + str(count) + " == 0"
flow.actors.append(tee)
trigger = Trigger(name="output # of instances")
tee.actors.append(trigger)
getcounter = GetStorageValue()
getcounter.config["storage_name"] = "counter"
trigger.actors.append(getcounter)
console = Console()
console.config["prefix"] = "# of instances: "
trigger.actors.append(console)
console = Console(name="output model")
tee.actors.append(console)
# run the flow
msg = flow.setup()
if msg is None:
print("\n" + flow.tree + "\n")
msg = flow.execute()
if msg is not None:
print("Error executing flow:\n" + msg)
else:
print("Error setting up flow:\n" + msg)
flow.wrapup()
flow.cleanup()
def main():
"""
Just runs some example code.
"""
# setup the flow
count = 50
helper.print_title("build classifier incrementally")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="build classifier incrementally")
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
flow.actors.append(filesupplier)
initcounter = InitStorageValue()
initcounter.config["storage_name"] = "counter"
initcounter.config["value"] = 0
flow.actors.append(initcounter)
loaddataset = LoadDataset()
loaddataset.config["incremental"] = True
flow.actors.append(loaddataset)
select = ClassSelector()
select.config["index"] = "last"
flow.actors.append(select)
inccounter = UpdateStorageValue()
inccounter.config["storage_name"] = "counter"
inccounter.config["expression"] = "{X} + 1"
flow.actors.append(inccounter)
train = Train()
train.config["setup"] = Classifier(classname="weka.classifiers.bayes.NaiveBayesUpdateable")
flow.actors.append(train)
pick = ContainerValuePicker()
pick.config["value"] = "Model"
pick.config["switch"] = True
flow.actors.append(pick)
tee = Tee(name="output model every " + str(count) + " instances")
tee.config["condition"] = "@{counter} % " + str(count) + " == 0"
flow.actors.append(tee)
trigger = Trigger(name="output # of instances")
tee.actors.append(trigger)
getcounter = GetStorageValue()
getcounter.config["storage_name"] = "counter"
trigger.actors.append(getcounter)
console = Console()
console.config["prefix"] = "# of instances: "
trigger.actors.append(console)
console = Console(name="output model")
tee.actors.append(console)
# run the flow
msg = flow.setup()
if msg is None:
print("\n" + flow.tree + "\n")
msg = flow.execute()
if msg is not None:
print("Error executing flow:\n" + msg)
else:
print("Error setting up flow:\n" + msg)
flow.wrapup()
flow.cleanup()
def main():
"""
Just runs some example code.
"""
# setup the flow
helper.print_title("Attribute selection")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="attribute selection")
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
flow.actors.append(filesupplier)
loaddataset = LoadDataset()
loaddataset.config["incremental"] = False
flow.actors.append(loaddataset)
attsel = AttributeSelection()
attsel.config["search"] = ASSearch(
classname="weka.attributeSelection.BestFirst")
attsel.config["eval"] = ASEvaluation(
classname="weka.attributeSelection.CfsSubsetEval")
flow.actors.append(attsel)
results = Tee()
results.name = "output results"
flow.actors.append(results)
picker = ContainerValuePicker()
picker.config["value"] = "Results"
picker.config["switch"] = True
results.actors.append(picker)
console = Console()
console.config["prefix"] = "Attribute selection results:"
results.actors.append(console)
reduced = Tee()
reduced.name = "reduced dataset"
flow.actors.append(reduced)
picker = ContainerValuePicker()
picker.config["value"] = "Reduced"
picker.config["switch"] = True
reduced.actors.append(picker)
console = Console()
console.config["prefix"] = "Reduced dataset:\n\n"
reduced.actors.append(console)
# run the flow
msg = flow.setup()
if msg is None:
print("\n" + flow.tree + "\n")
msg = flow.execute()
if msg is not None:
print("Error executing flow:\n" + msg)
else:
print("Error setting up flow:\n" + msg)
flow.wrapup()
flow.cleanup()
