Python Flow.setup方法代码示例

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
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")

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """
    """
    Plots a dataset.
    """

    # setup the flow
    helper.print_title("Plot dataset")
    iris = helper.get_data_dir() + os.sep + "iris.arff"

    flow = Flow(name="plot dataset")

    filesupplier = FileSupplier()
    filesupplier.config["files"] = [iris]
    flow.actors.append(filesupplier)

    loaddataset = LoadDataset()
    flow.actors.append(loaddataset)

    branch = Branch()
    flow.actors.append(branch)

    seq = Sequence(name="matrix plot")
    branch.actors.append(seq)

    mplot = MatrixPlot()
    mplot.config["percent"] = 50.0
    mplot.config["wait"] = False
    seq.actors.append(mplot)

    seq = Sequence(name="line plot")
    branch.actors.append(seq)

    copy = Copy()
    seq.actors.append(copy)

    flter = Filter()
    flter.config["setup"] = filters.Filter(
        classname="weka.filters.unsupervised.attribute.Remove", options=["-R", "last"])
    flter.config["keep_relationname"] = True
    seq.actors.append(flter)

    lplot = LinePlot()
    lplot.config["percent"] = 50.0
    lplot.config["wait"] = True
    seq.actors.append(lplot)

    # 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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """

    # setup the flow
    flow = Flow(name="math expression")

    outer = ForLoop()
    outer.config["max"] = 100
    flow.actors.append(outer)

    expr = MathExpression()
    expr.config["expression"] = "math.sqrt({X})"
    flow.actors.append(expr)

    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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def load_incremental():
    """
    Loads a dataset incrementally.
    """

    # setup the flow
    helper.print_title("Load dataset (incremental)")
    iris = helper.get_data_dir() + os.sep + "iris.arff"

    flow = Flow(name="load dataset")

    filesupplier = FileSupplier()
    filesupplier.config["files"] = [iris]
    flow.actors.append(filesupplier)

    loaddataset = LoadDataset()
    loaddataset.config["incremental"] = True
    flow.actors.append(loaddataset)

    console = Console()
    flow.actors.append(console)

    # run the flow
    msg = flow.setup()
    if msg is None:
        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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """

    # setup the flow
    flow = Flow(name="list files")
    # flow.print_help()

    listfiles = ListFiles()
    listfiles.config["dir"] = str(tempfile.gettempdir())
    listfiles.config["list_files"] = True
    listfiles.config["list_dirs"] = False
    listfiles.config["recursive"] = False
    listfiles.config["regexp"] = ".*r.*"
    # listfiles.print_help()
    flow.actors.append(listfiles)

    console = Console()
    console.config["prefix"] = "Match: "
    # console.print_help()
    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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def load_custom_loader():
    """
    Loads a dataset using a custom loader.
    """

    # setup the flow
    helper.print_title("Load dataset (custom loader)")
    iris = helper.get_data_dir() + os.sep + "iris.csv"

    flow = Flow(name="load dataset")

    filesupplier = FileSupplier()
    filesupplier.config["files"] = [iris]
    flow.actors.append(filesupplier)

    loaddataset = LoadDataset()
    loaddataset.config["incremental"] = False
    loaddataset.config["use_custom_loader"] = True
    loaddataset.config["custom_loader"] = Loader(classname="weka.core.converters.CSVLoader")
    flow.actors.append(loaddataset)

    console = Console()
    flow.actors.append(console)

    # run the flow
    msg = flow.setup()
    if msg is None:
        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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """
    """
    Loads data from a database.
    """

    # setup the flow
    helper.print_title("Load from database")

    flow = Flow(name="load from database")

    loaddatabase = LoadDatabase()
    loaddatabase.config["db_url"] = "jdbc:mysql://HOSTNAME:3306/DBNAME"
    loaddatabase.config["user"] = "DBUSER"
    loaddatabase.config["password"] = "DBPW"
    loaddatabase.config["query"] = "select * from TABLE"
    flow.actors.append(loaddatabase)

    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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """
    # setup the flow
    helper.print_title("Generate dataset")

    flow = Flow(name="generate dataset")

    generator = DataGenerator()
    generator.config["setup"] = datagen.DataGenerator(classname="weka.datagenerators.classifiers.classification.Agrawal")
    flow.actors.append(generator)

    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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """

    # setup the flow
    flow = Flow(name="update storage value")

    start = Start()
    flow.actors.append(start)

    init = InitStorageValue()
    init.config["storage_name"] = "max"
    init.config["value"] = "int(1)"
    flow.actors.append(init)

    trigger = Trigger()
    flow.actors.append(trigger)

    outer = ForLoop()
    outer.name = "outer"
    outer.config["max"] = 3
    trigger.actors.append(outer)

    trigger2 = Trigger()
    trigger.actors.append(trigger2)

    inner = ForLoop()
    inner.name = "inner"
    inner.config["max"] = "@{max}"
    trigger2.actors.append(inner)

    console = Console()
    trigger2.actors.append(console)

    update = UpdateStorageValue()
    update.config["storage_name"] = "max"
    update.config["expression"] = "{X} + 2"
    trigger.actors.append(update)

    # 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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """

    # setup the flow
    flow = Flow(name="combine storage")

    outer = ForLoop()
    outer.name = "outer"
    outer.config["max"] = 3
    flow.actors.append(outer)

    ssv = SetStorageValue()
    ssv.config["storage_name"] = "max"
    flow.actors.append(ssv)

    trigger = Trigger()
    flow.actors.append(trigger)

    inner = ForLoop()
    inner.name = "inner"
    inner.config["max"] = "@{max}"
    trigger.actors.append(inner)

    ssv2 = SetStorageValue()
    ssv2.config["storage_name"] = "inner"
    trigger.actors.append(ssv2)

    trigger2 = Trigger()
    trigger.actors.append(trigger2)

    combine = CombineStorage()
    combine.config["format"] = "@{max} / @{inner}"
    trigger2.actors.append(combine)

    console = Console()
    trigger2.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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """
    """
    Loads/filters a dataset incrementally and saves it to a new file.
    """

    # setup the flow
    helper.print_title("Load/filter/save dataset (incrementally)")
    iris = helper.get_data_dir() + os.sep + "iris.arff"

    flow = Flow(name="Load/filter/save dataset (incrementally)")

    filesupplier = FileSupplier()
    filesupplier.config["files"] = [iris]
    flow.actors.append(filesupplier)

    loaddataset = LoadDataset()
    loaddataset.config["incremental"] = True
    flow.actors.append(loaddataset)

    flter = Filter()
    flter.config["setup"] = filters.Filter(
        classname="weka.filters.unsupervised.attribute.Remove", options=["-R", "last"])
    flow.actors.append(flter)

    rename = RenameRelation()
    rename.config["name"] = "iris-reduced"
    flow.actors.append(rename)

    dumper = InstanceDumper()
    dumper.config["output"] = tempfile.gettempdir() + os.sep + "out.arff"
    flow.actors.append(dumper)

    # 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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """

    # setup the flow
    helper.print_title("build and save clusterer")
    iris = helper.get_data_dir() + os.sep + "iris_no_class.arff"

    flow = Flow(name="build and save clusterer")

    filesupplier = FileSupplier()
    filesupplier.config["files"] = [iris]
    flow.actors.append(filesupplier)

    loaddataset = LoadDataset()
    flow.actors.append(loaddataset)

    train = Train()
    train.config["setup"] = Clusterer(classname="weka.clusterers.SimpleKMeans")
    flow.actors.append(train)

    pick = ContainerValuePicker()
    pick.config["value"] = "Model"
    flow.actors.append(pick)

    console = Console()
    pick.actors.append(console)

    writer = ModelWriter()
    writer.config["output"] = str(tempfile.gettempdir()) + os.sep + "simplekmeans.model"
    flow.actors.append(writer)

    # 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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def incremental():
    """
    Just runs some example code.
    """
    """
    Loads/filters a dataset incrementally.
    """

    # setup the flow
    helper.print_title("Filter datasets (incrementally)")
    iris = helper.get_data_dir() + os.sep + "iris.arff"
    anneal = helper.get_data_dir() + os.sep + "anneal.arff"

    flow = Flow(name="filter datasets (incrementally)")

    filesupplier = FileSupplier()
    filesupplier.config["files"] = [iris, anneal]
    flow.actors.append(filesupplier)

    loaddataset = LoadDataset()
    loaddataset.config["incremental"] = True
    flow.actors.append(loaddataset)

    flter = Filter()
    flter.config["setup"] = filters.Filter(
        classname="weka.filters.unsupervised.attribute.Remove", options=["-R", "1"])
    flter.config["keep_relationname"] = True
    flow.actors.append(flter)

    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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """

    # setup the flow
    helper.print_title("Cross-validate clusterer")
    iris = helper.get_data_dir() + os.sep + "iris.arff"

    flow = Flow(name="cross-validate clusterer")

    filesupplier = FileSupplier()
    filesupplier.config["files"] = [iris]
    flow.actors.append(filesupplier)

    loaddataset = LoadDataset()
    flow.actors.append(loaddataset)

    flter = Filter()
    flter.name = "Remove class"
    flter.config["filter"] = filters.Filter(
        classname="weka.filters.unsupervised.attribute.Remove", options=["-R", "last"])
    flow.actors.append(flter)

    cv = CrossValidate()
    cv.config["setup"] = Clusterer(classname="weka.clusterers.EM")
    flow.actors.append(cv)

    console = Console()
    console.config["prefix"] = "Loglikelihood: "
    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()

# 需要导入模块: from weka.flow.control import Flow [as 别名]
# 或者: from weka.flow.control.Flow import setup [as 别名]
def main():
    """
    Just runs some example code.
    """
    """
    Tests some conversions.
    """

    # setup the flow
    helper.print_title("conversions")

    flow = Flow(name="conversions")

    strings = StringConstants()
    strings.config["strings"] = ["weka.classifiers.trees.J48", "weka.classifiers.functions.SMO"]
    flow.actors.append(strings)

    c2a = CommandlineToAny()
    c2a.config["wrapper"] = "weka.classifiers.Classifier"
    convert1 = Convert()
    convert1.config["setup"] = c2a
    flow.actors.append(convert1)

    convert2 = Convert()
    convert2.config["setup"] = AnyToCommandline()
    flow.actors.append(convert2)

    console = Console()
    console.config["prefix"] = "setup: "
    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()