Python concurrent.ThreadExecutor类代码示例

    def test_methodinvoke(self):
        executor = ThreadExecutor()
        state = [None, None]

        class StateSetter(QObject):
            @pyqtSlot(object)
            def set_state(self, value):
                state[0] = value
                state[1] = QThread.currentThread()

        def func(callback):
            callback(QThread.currentThread())

        obj = StateSetter()
        f1 = executor.submit(func, methodinvoke(obj, "set_state", (object,)))
        f1.result()
        # So invoked method can be called from the event loop
        self.app.processEvents()

        self.assertIs(state[1], QThread.currentThread(),
                      "set_state was called from the wrong thread")

        self.assertIsNot(state[0], QThread.currentThread(),
                         "set_state was invoked in the main thread")

        executor.shutdown(wait=True)

    def test_executor(self):
        executor = ThreadExecutor()
        f1 = executor.submit(pow, 100, 100)

        f2 = executor.submit(lambda: 1 / 0)

        f3 = executor.submit(QThread.currentThread)

        self.assertTrue(f1.result(), pow(100, 100))

        with self.assertRaises(ZeroDivisionError):
            f2.result()

        self.assertIsInstance(f2.exception(), ZeroDivisionError)

        self.assertIsNot(f3.result(), QThread.currentThread())

    def setup_layout(self):
        super().setup_layout()

        self._task = None  # type: Optional[Task]
        self._executor = ThreadExecutor()

        # just a test cancel button
        gui.button(self.apply_button, self, "Cancel", callback=self.cancel)

    def __init__(self, parent=None):
        super().__init__(parent)

        self.taxids = taxonomy.common_taxids()
        self.current_taxid_index = self.taxids.index(self.taxid)

        self.data = None
        self.geneinfo = None
        self.nettask = None
        self._invalidated = False

        box = gui.widgetBox(self.controlArea, "Info")
        self.info = gui.widgetLabel(box, "No data on input\n")

        box = gui.widgetBox(self.controlArea, "Organism")
        self.organism_cb = gui.comboBox(
            box, self, "current_taxid_index",
            items=map(taxonomy.name, self.taxids),
            callback=self._update_organism
        )
        box = gui.widgetBox(self.controlArea, "Genes")
        self.genes_cb = gui.comboBox(
            box, self, "gene_var_index", callback=self._update_query_genes
        )
        self.varmodel = itemmodels.VariableListModel()
        self.genes_cb.setModel(self.varmodel)

        gui.checkBox(
            box, self, "use_attr_names",
            "Use attribute names",
            callback=self._update_query_genes
        )

        box = gui.widgetBox(self.controlArea, "Network")
        gui.comboBox(
            box, self, "network_source",
            items=[s.name for s in SOURCES],
            callback=self._on_source_db_changed
        )
        gui.checkBox(
            box, self, "include_neighborhood",
            "Include immediate gene neighbors",
            callback=self.invalidate
        )
        self.score_spin = gui.doubleSpin(
            box, self, "min_score", 0.0, 1.0, step=0.001,
            label="Minimal edge score",
            callback=self.invalidate
        )
        self.score_spin.setEnabled(SOURCES[self.network_source].score_filter)

        box = gui.widgetBox(self.controlArea, "Commit")
        gui.button(box, self, "Retrieve", callback=self.commit, default=True)

        self.setSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
        self.layout().setSizeConstraint(QtGui.QLayout.SetFixedSize)

        self.executor = ThreadExecutor()

#.........这里部分代码省略.........
        )
        self.progress_widget = QProgressBar(
            minimum=0, maximum=0
        )
        self.cancel_button = QPushButton(
            "Cancel", icon=icons.cancel_icon,
        )
        self.cancel_button.clicked.connect(self.cancel)

        w = QWidget()
        vlayout = QVBoxLayout()
        vlayout.setContentsMargins(0, 0, 0, 0)
        hlayout = QHBoxLayout()
        hlayout.setContentsMargins(0, 0, 0, 0)

        hlayout.addWidget(self.progress_widget)
        hlayout.addWidget(self.cancel_button)
        vlayout.addLayout(hlayout)

        self.pathlabel = TextLabel()
        self.pathlabel.setTextElideMode(Qt.ElideMiddle)
        self.pathlabel.setAttribute(Qt.WA_MacSmallSize)

        vlayout.addWidget(self.pathlabel)
        w.setLayout(vlayout)

        self.infostack.addWidget(self.info_area)
        self.infostack.addWidget(w)

        box.layout().addWidget(self.infostack)

        self.__initRecentItemsModel()
        self.__invalidated = True
        self.__executor = ThreadExecutor(self)

        QApplication.postEvent(self, QEvent(RuntimeEvent.Init))

    def __initRecentItemsModel(self):
        if self.currentPath is not None and \
                not os.path.isdir(self.currentPath):
            self.currentPath = None

        recent_paths = []
        for item in self.recent_paths:
            if os.path.isdir(item.abspath):
                recent_paths.append(item)
        recent_paths = recent_paths[:OWImportImages.MaxRecentItems]
        recent_model = self.recent_cb.model()
        for pathitem in recent_paths:
            item = RecentPath_asqstandarditem(pathitem)
            recent_model.appendRow(item)

        self.recent_paths = recent_paths

        if self.currentPath is not None and \
                os.path.isdir(self.currentPath) and self.recent_paths and \
                os.path.samefile(self.currentPath, self.recent_paths[0].abspath):
            self.recent_cb.setCurrentIndex(0)
        else:
            self.currentPath = None
            self.recent_cb.setCurrentIndex(-1)
        self.__actions.reload.setEnabled(self.currentPath is not None)

    def customEvent(self, event):
        """Reimplemented."""
        if event.type() == RuntimeEvent.Init:

    def __init__(self):
        super().__init__()
        #: widget's runtime state
        self.__state = State.NoState
        self._imageMeta = []
        self._imageCategories = {}

        self.__invalidated = False
        self.__pendingTask = None

        vbox = gui.vBox(self.controlArea)
        hbox = gui.hBox(vbox)
        self.recent_cb = QComboBox(
            sizeAdjustPolicy=QComboBox.AdjustToMinimumContentsLengthWithIcon,
            minimumContentsLength=16,
        )
        self.recent_cb.activated[int].connect(self.__onRecentActivated)
        icons = standard_icons(self)

        browseaction = QAction(
            "Open/Load Images", self,
            iconText="\N{HORIZONTAL ELLIPSIS}",
            icon=icons.dir_open_icon,
            toolTip="Select a directory from which to load the images"
        )
        browseaction.triggered.connect(self.__runOpenDialog)
        reloadaction = QAction(
            "Reload", self,
            icon=icons.reload_icon,
            toolTip="Reload current image set"
        )
        reloadaction.triggered.connect(self.reload)
        self.__actions = namespace(
            browse=browseaction,
            reload=reloadaction,
        )

        browsebutton = QPushButton(
            browseaction.iconText(),
            icon=browseaction.icon(),
            toolTip=browseaction.toolTip(),
            clicked=browseaction.trigger
        )
        reloadbutton = QPushButton(
            reloadaction.iconText(),
            icon=reloadaction.icon(),
            clicked=reloadaction.trigger,
            default=True,
        )

        hbox.layout().addWidget(self.recent_cb)
        hbox.layout().addWidget(browsebutton)
        hbox.layout().addWidget(reloadbutton)

        self.addActions([browseaction, reloadaction])

        reloadaction.changed.connect(
            lambda: reloadbutton.setEnabled(reloadaction.isEnabled())
        )
        box = gui.vBox(vbox, "Info")
        self.infostack = QStackedWidget()

        self.info_area = QLabel(
            text="No image set selected",
            wordWrap=True
        )
        self.progress_widget = QProgressBar(
            minimum=0, maximum=0
        )
        self.cancel_button = QPushButton(
            "Cancel", icon=icons.cancel_icon,
        )
        self.cancel_button.clicked.connect(self.cancel)

        w = QWidget()
        vlayout = QVBoxLayout()
        vlayout.setContentsMargins(0, 0, 0, 0)
        hlayout = QHBoxLayout()
        hlayout.setContentsMargins(0, 0, 0, 0)

        hlayout.addWidget(self.progress_widget)
        hlayout.addWidget(self.cancel_button)
        vlayout.addLayout(hlayout)

        self.pathlabel = TextLabel()
        self.pathlabel.setTextElideMode(Qt.ElideMiddle)
        self.pathlabel.setAttribute(Qt.WA_MacSmallSize)

        vlayout.addWidget(self.pathlabel)
        w.setLayout(vlayout)

        self.infostack.addWidget(self.info_area)
        self.infostack.addWidget(w)

        box.layout().addWidget(self.infostack)

        self.__initRecentItemsModel()
        self.__invalidated = True
        self.__executor = ThreadExecutor(self)

#.........这里部分代码省略.........

class OWGeneNetwork(widget.OWWidget):
    name = "Gene Network"
    description = "Extract a gene network for a set of genes."
    icon = "../widgets/icons/GeneNetwork.svg"

    inputs = [("Data", Orange.data.Table, "set_data")]
    outputs = [("Network", network.Graph)]

    settingsHandler = settings.DomainContextHandler()

    taxid = settings.Setting("9606")
    gene_var_index = settings.ContextSetting(-1)
    use_attr_names = settings.ContextSetting(False)

    network_source = settings.Setting(1)
    include_neighborhood = settings.Setting(True)
    min_score = settings.Setting(0.9)

    want_main_area = False

    def __init__(self, parent=None):
        super().__init__(parent)

        self.taxids = taxonomy.common_taxids()
        self.current_taxid_index = self.taxids.index(self.taxid)

        self.data = None
        self.geneinfo = None
        self.nettask = None
        self._invalidated = False

        box = gui.widgetBox(self.controlArea, "Info")
        self.info = gui.widgetLabel(box, "No data on input\n")

        box = gui.widgetBox(self.controlArea, "Organism")
        self.organism_cb = gui.comboBox(
            box, self, "current_taxid_index",
            items=map(taxonomy.name, self.taxids),
            callback=self._update_organism
        )
        box = gui.widgetBox(self.controlArea, "Genes")
        self.genes_cb = gui.comboBox(
            box, self, "gene_var_index", callback=self._update_query_genes
        )
        self.varmodel = itemmodels.VariableListModel()
        self.genes_cb.setModel(self.varmodel)

        gui.checkBox(
            box, self, "use_attr_names",
            "Use attribute names",
            callback=self._update_query_genes
        )

        box = gui.widgetBox(self.controlArea, "Network")
        gui.comboBox(
            box, self, "network_source",
            items=[s.name for s in SOURCES],
            callback=self._on_source_db_changed
        )
        gui.checkBox(
            box, self, "include_neighborhood",
            "Include immediate gene neighbors",
            callback=self.invalidate
        )
        self.score_spin = gui.doubleSpin(
            box, self, "min_score", 0.0, 1.0, step=0.001,
            label="Minimal edge score",
            callback=self.invalidate
        )
        self.score_spin.setEnabled(SOURCES[self.network_source].score_filter)

        box = gui.widgetBox(self.controlArea, "Commit")
        gui.button(box, self, "Retrieve", callback=self.commit, default=True)

        self.setSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
        self.layout().setSizeConstraint(QtGui.QLayout.SetFixedSize)

        self.executor = ThreadExecutor()

    def set_data(self, data):
        self.closeContext()
        self.data = data
        if data is not None:
            self.varmodel[:] = string_variables(data.domain)
            taxid = data_hints.get_hint(data, "taxid", default=self.taxid)

            if taxid in self.taxids:
                self.set_organism(self.taxids.index(taxid))

            self.use_attr_names = data_hints.get_hint(
                data, "genesinrows", default=self.use_attr_names
            )

            if not (0 <= self.gene_var_index < len(self.varmodel)):
                self.gene_var_index = len(self.varmodel) - 1

            self.openContext(data)
            self.invalidate()
            self.commit()
        else:
#.........这里部分代码省略.........

    def __init__(self):
        super().__init__()
        self.data = None
        self.model = None
        self.to_explain = None
        self.explanations = None
        self.stop = True
        self.e = None

        self._task = None
        self._executor = ThreadExecutor()

        info_box = gui.vBox(self.controlArea, "Info")
        self.data_info = gui.widgetLabel(info_box, "Data: N/A")
        self.model_info = gui.widgetLabel(info_box, "Model: N/A")
        self.sample_info = gui.widgetLabel(info_box, "Sample: N/A")

        criteria_box = gui.vBox(self.controlArea, "Stopping criteria")
        self.error_spin = gui.spin(criteria_box,
                                   self,
                                   "gui_error",
                                   0.01,
                                   1,
                                   step=0.01,
                                   label="Error < ",
                                   spinType=float,
                                   callback=self._update_error_spin,
                                   controlWidth=80,
                                   keyboardTracking=False)

        self.p_val_spin = gui.spin(criteria_box,
                                   self,
                                   "gui_p_val",
                                   0.01,
                                   1,
                                   step=0.01,
                                   label="Error p-value < ",
                                   spinType=float,
                                   callback=self._update_p_val_spin,
                                   controlWidth=80, keyboardTracking=False)

        plot_properties_box = gui.vBox(self.controlArea, "Display features")
        self.num_atr_spin = gui.spin(plot_properties_box,
                                     self,
                                     "gui_num_atr",
                                     1,
                                     100,
                                     step=1,
                                     label="Show attributes",
                                     callback=self._update_num_atr_spin,
                                     controlWidth=80,
                                     keyboardTracking=False)

        self.sort_combo = gui.comboBox(plot_properties_box,
                                       self,
                                       "sort_index",
                                       label="Rank by",
                                       items=SortBy.items(),
                                       orientation=Qt.Horizontal,
                                       callback=self._update_combo)

        gui.rubber(self.controlArea)

        self.cancel_button = gui.button(self.controlArea,
                                        self,
                                        "Stop Computation",
                                        callback=self.toggle_button,
                                        autoDefault=True,
                                        tooltip="Stops and restarts computation")
        self.cancel_button.setDisabled(True)

        predictions_box = gui.vBox(self.mainArea, "Model prediction")
        self.predict_info = gui.widgetLabel(predictions_box, "")

        self.mainArea.setMinimumWidth(700)
        self.resize(700, 400)

        class _GraphicsView(QGraphicsView):
            def __init__(self, scene, parent, **kwargs):
                for k, v in dict(verticalScrollBarPolicy=Qt.ScrollBarAlwaysOff,
                                 horizontalScrollBarPolicy=Qt.ScrollBarAlwaysOff,
                                 viewportUpdateMode=QGraphicsView.BoundingRectViewportUpdate,
                                 renderHints=(QPainter.Antialiasing |
                                              QPainter.TextAntialiasing |
                                              QPainter.SmoothPixmapTransform),
                                 alignment=(Qt.AlignTop |
                                            Qt.AlignLeft),
                                 sizePolicy=QSizePolicy(QSizePolicy.MinimumExpanding,
                                                        QSizePolicy.MinimumExpanding)).items():
                    kwargs.setdefault(k, v)
                super().__init__(scene, parent, **kwargs)

        class GraphicsView(_GraphicsView):
            def __init__(self, scene, parent):
                super().__init__(scene, parent,
                                 verticalScrollBarPolicy=Qt.ScrollBarAlwaysOn,
                                 styleSheet='QGraphicsView {background: white}')
                self.viewport().setMinimumWidth(500)
                self._is_resizing = False

#.........这里部分代码省略.........

class OWLearningCurveC(widget.OWWidget):
    name = "Learning Curve (C)"
    description = ("Takes a dataset and a set of learners and shows a "
                   "learning curve in a table")
    icon = "icons/LearningCurve.svg"
    priority = 1010

    inputs = [("Data", Orange.data.Table, "set_dataset", widget.Default),
              ("Test Data", Orange.data.Table, "set_testdataset"),
              ("Learner", Orange.classification.Learner, "set_learner",
               widget.Multiple + widget.Default)]

    #: cross validation folds
    folds = settings.Setting(5)
    #: points in the learning curve
    steps = settings.Setting(10)
    #: index of the selected scoring function
    scoringF = settings.Setting(0)
    #: compute curve on any change of parameters
    commitOnChange = settings.Setting(True)

    def __init__(self):
        super().__init__()

        # sets self.curvePoints, self.steps equidistant points from
        # 1/self.steps to 1
        self.updateCurvePoints()

        self.scoring = [
            ("Classification Accuracy", Orange.evaluation.scoring.CA),
            ("AUC", Orange.evaluation.scoring.AUC),
            ("Precision", Orange.evaluation.scoring.Precision),
            ("Recall", Orange.evaluation.scoring.Recall)
        ]
        #: input data on which to construct the learning curve
        self.data = None
        #: optional test data
        self.testdata = None
        #: A {input_id: Learner} mapping of current learners from input channel
        self.learners = OrderedDict()
        #: A {input_id: List[Results]} mapping of input id to evaluation
        #: results list, one for each curve point
        self.results = OrderedDict()
        #: A {input_id: List[float]} mapping of input id to learning curve
        #: point scores
        self.curves = OrderedDict()

        # [start-snippet-3]
        #: The current evaluating task (if any)
        self._task = None   # type: Optional[Task]
        #: An executor we use to submit learner evaluations into a thread pool
        self._executor = ThreadExecutor()
        # [end-snippet-3]

        # GUI
        box = gui.widgetBox(self.controlArea, "Info")
        self.infoa = gui.widgetLabel(box, 'No data on input.')
        self.infob = gui.widgetLabel(box, 'No learners.')

        gui.separator(self.controlArea)

        box = gui.widgetBox(self.controlArea, "Evaluation Scores")
        gui.comboBox(box, self, "scoringF",
                     items=[x[0] for x in self.scoring],
                     callback=self._invalidate_curves)

        gui.separator(self.controlArea)

        box = gui.widgetBox(self.controlArea, "Options")
        gui.spin(box, self, 'folds', 2, 100, step=1,
                 label='Cross validation folds:  ', keyboardTracking=False,
                 callback=lambda:
                    self._invalidate_results() if self.commitOnChange else None
        )
        gui.spin(box, self, 'steps', 2, 100, step=1,
                 label='Learning curve points:  ', keyboardTracking=False,
                 callback=[self.updateCurvePoints,
                           lambda: self._invalidate_results() if self.commitOnChange else None])
        gui.checkBox(box, self, 'commitOnChange', 'Apply setting on any change')
        self.commitBtn = gui.button(box, self, "Apply Setting",
                                    callback=self._invalidate_results,
                                    disabled=True)

        gui.rubber(self.controlArea)

        # table widget
        self.table = gui.table(self.mainArea,
                               selectionMode=QTableWidget.NoSelection)

    ##########################################################################
    # slots: handle input signals

    def set_dataset(self, data):
        """Set the input train dataset."""
        # Clear all results/scores
        for id in list(self.results):
            self.results[id] = None
        for id in list(self.curves):
            self.curves[id] = None

#.........这里部分代码省略.........

    def __init__(self):
        super().__init__()

        self.data = None
        self.test_data = None
        self.preprocessor = None
        self.train_data_missing_vals = False
        self.test_data_missing_vals = False
        self.scorers = []

        #: An Ordered dictionary with current inputs and their testing results.
        self.learners = OrderedDict()  # type: Dict[Any, Input]

        self.__state = State.Waiting
        # Do we need to [re]test any learners, set by _invalidate and
        # cleared by __update
        self.__needupdate = False
        self.__task = None  # type: Optional[Task]
        self.__executor = ThreadExecutor()

        sbox = gui.vBox(self.controlArea, "Sampling")
        rbox = gui.radioButtons(
            sbox, self, "resampling", callback=self._param_changed)

        gui.appendRadioButton(rbox, "Cross validation")
        ibox = gui.indentedBox(rbox)
        gui.comboBox(
            ibox, self, "n_folds", label="Number of folds: ",
            items=[str(x) for x in self.NFolds], maximumContentsLength=3,
            orientation=Qt.Horizontal, callback=self.kfold_changed)
        gui.checkBox(
            ibox, self, "cv_stratified", "Stratified",
            callback=self.kfold_changed)
        gui.appendRadioButton(rbox, "Cross validation by feature")
        ibox = gui.indentedBox(rbox)
        self.feature_model = DomainModel(
            order=DomainModel.METAS, valid_types=DiscreteVariable)
        self.features_combo = gui.comboBox(
            ibox, self, "fold_feature", model=self.feature_model,
            orientation=Qt.Horizontal, callback=self.fold_feature_changed)

        gui.appendRadioButton(rbox, "Random sampling")
        ibox = gui.indentedBox(rbox)
        gui.comboBox(
            ibox, self, "n_repeats", label="Repeat train/test: ",
            items=[str(x) for x in self.NRepeats], maximumContentsLength=3,
            orientation=Qt.Horizontal, callback=self.shuffle_split_changed)
        gui.comboBox(
            ibox, self, "sample_size", label="Training set size: ",
            items=["{} %".format(x) for x in self.SampleSizes],
            maximumContentsLength=5, orientation=Qt.Horizontal,
            callback=self.shuffle_split_changed)
        gui.checkBox(
            ibox, self, "shuffle_stratified", "Stratified",
            callback=self.shuffle_split_changed)

        gui.appendRadioButton(rbox, "Leave one out")

        gui.appendRadioButton(rbox, "Test on train data")
        gui.appendRadioButton(rbox, "Test on test data")

        self.cbox = gui.vBox(self.controlArea, "Target Class")
        self.class_selection_combo = gui.comboBox(
            self.cbox, self, "class_selection", items=[],
            sendSelectedValue=True, valueType=str,
            callback=self._on_target_class_changed,
            contentsLength=8)

        gui.rubber(self.controlArea)

        self.view = gui.TableView(
            wordWrap=True,
        )
        header = self.view.horizontalHeader()
        header.setSectionResizeMode(QHeaderView.ResizeToContents)
        header.setDefaultAlignment(Qt.AlignCenter)
        header.setStretchLastSection(False)
        header.setContextMenuPolicy(Qt.CustomContextMenu)
        header.customContextMenuRequested.connect(self.show_column_chooser)

        self.result_model = QStandardItemModel(self)
        self.result_model.setHorizontalHeaderLabels(["Method"])
        self.view.setModel(self.result_model)
        self.view.setItemDelegate(ItemDelegate())

        box = gui.vBox(self.mainArea, "Evaluation Results")
        box.layout().addWidget(self.view)

class OWKMeans(widget.OWWidget):
    name = "k-Means"
    description = "k-Means clustering algorithm with silhouette-based " \
                  "quality estimation."
    icon = "icons/KMeans.svg"
    priority = 2100
    keywords = ["kmeans", "clustering"]

    class Inputs:
        data = Input("Data", Table)

    class Outputs:
        annotated_data = Output(
            ANNOTATED_DATA_SIGNAL_NAME, Table, default=True,
            replaces=["Annotated Data"]
        )
        centroids = Output("Centroids", Table)

    class Error(widget.OWWidget.Error):
        failed = widget.Msg("Clustering failed\nError: {}")
        not_enough_data = widget.Msg(
            "Too few ({}) unique data instances for {} clusters"
        )
        no_attributes = widget.Msg("Data is missing features.")

    class Warning(widget.OWWidget.Warning):
        no_silhouettes = widget.Msg(
            "Silhouette scores are not computed for >{} samples".format(
                SILHOUETTE_MAX_SAMPLES)
        )
        not_enough_data = widget.Msg(
            "Too few ({}) unique data instances for {} clusters"
        )

    INIT_METHODS = (("Initialize with KMeans++", "k-means++"),
                    ("Random initialization", "random"))

    resizing_enabled = False
    buttons_area_orientation = Qt.Vertical

    k = Setting(3)
    k_from = Setting(2)
    k_to = Setting(8)
    optimize_k = Setting(False)
    max_iterations = Setting(300)
    n_init = Setting(10)
    smart_init = Setting(0)  # KMeans++
    auto_commit = Setting(True)

    settings_version = 2

    @classmethod
    def migrate_settings(cls, settings, version):
        # type: (Dict, int) -> None
        if version < 2:
            if 'auto_apply' in settings:
                settings['auto_commit'] = settings.get('auto_apply', True)
                settings.pop('auto_apply', None)

    def __init__(self):
        super().__init__()

        self.data = None  # type: Optional[Table]
        self.clusterings = {}

        self.__executor = ThreadExecutor(parent=self)
        self.__task = None  # type: Optional[Task]

        layout = QGridLayout()
        bg = gui.radioButtonsInBox(
            self.controlArea, self, "optimize_k", orientation=layout,
            box="Number of Clusters", callback=self.update_method,
        )

        layout.addWidget(
            gui.appendRadioButton(bg, "Fixed:", addToLayout=False), 1, 1)
        sb = gui.hBox(None, margin=0)
        gui.spin(
            sb, self, "k", minv=2, maxv=30,
            controlWidth=60, alignment=Qt.AlignRight, callback=self.update_k)
        gui.rubber(sb)
        layout.addWidget(sb, 1, 2)

        layout.addWidget(
            gui.appendRadioButton(bg, "From", addToLayout=False), 2, 1)
        ftobox = gui.hBox(None)
        ftobox.layout().setContentsMargins(0, 0, 0, 0)
        layout.addWidget(ftobox, 2, 2)
        gui.spin(
            ftobox, self, "k_from", minv=2, maxv=29,
            controlWidth=60, alignment=Qt.AlignRight,
            callback=self.update_from)
        gui.widgetLabel(ftobox, "to")
        gui.spin(
            ftobox, self, "k_to", minv=3, maxv=30,
            controlWidth=60, alignment=Qt.AlignRight,
            callback=self.update_to)
        gui.rubber(ftobox)

        box = gui.vBox(self.controlArea, "Initialization")
#.........这里部分代码省略.........

#.........这里部分代码省略.........
        memory_error = Msg("Not enough memory.")
        only_one_class_var_value = Msg("Target variable has only one value.")

    class Warning(OWWidget.Warning):
        missing_data = \
            Msg("Instances with unknown target values were removed from{}data.")
        test_data_missing = Msg("Missing separate test data input.")
        scores_not_computed = Msg("Some scores could not be computed.")
        test_data_unused = Msg("Test data is present but unused. "
                               "Select 'Test on test data' to use it.")

    class Information(OWWidget.Information):
        data_sampled = Msg("Train data has been sampled")
        test_data_sampled = Msg("Test data has been sampled")

    def __init__(self):
        super().__init__()

        self.data = None
        self.test_data = None
        self.preprocessor = None
        self.train_data_missing_vals = False
        self.test_data_missing_vals = False
        self.scorers = []

        #: An Ordered dictionary with current inputs and their testing results.
        self.learners = OrderedDict()  # type: Dict[Any, Input]

        self.__state = State.Waiting
        # Do we need to [re]test any learners, set by _invalidate and
        # cleared by __update
        self.__needupdate = False
        self.__task = None  # type: Optional[Task]
        self.__executor = ThreadExecutor()

        sbox = gui.vBox(self.controlArea, "Sampling")
        rbox = gui.radioButtons(
            sbox, self, "resampling", callback=self._param_changed)

        gui.appendRadioButton(rbox, "Cross validation")
        ibox = gui.indentedBox(rbox)
        gui.comboBox(
            ibox, self, "n_folds", label="Number of folds: ",
            items=[str(x) for x in self.NFolds], maximumContentsLength=3,
            orientation=Qt.Horizontal, callback=self.kfold_changed)
        gui.checkBox(
            ibox, self, "cv_stratified", "Stratified",
            callback=self.kfold_changed)
        gui.appendRadioButton(rbox, "Cross validation by feature")
        ibox = gui.indentedBox(rbox)
        self.feature_model = DomainModel(
            order=DomainModel.METAS, valid_types=DiscreteVariable)
        self.features_combo = gui.comboBox(
            ibox, self, "fold_feature", model=self.feature_model,
            orientation=Qt.Horizontal, callback=self.fold_feature_changed)

        gui.appendRadioButton(rbox, "Random sampling")
        ibox = gui.indentedBox(rbox)
        gui.comboBox(
            ibox, self, "n_repeats", label="Repeat train/test: ",
            items=[str(x) for x in self.NRepeats], maximumContentsLength=3,
            orientation=Qt.Horizontal, callback=self.shuffle_split_changed)
        gui.comboBox(
            ibox, self, "sample_size", label="Training set size: ",
            items=["{} %".format(x) for x in self.SampleSizes],
            maximumContentsLength=5, orientation=Qt.Horizontal,

    def __init__(self):
        super().__init__()

        self.data = None  # type: Optional[Table]
        self.clusterings = {}

        self.__executor = ThreadExecutor(parent=self)
        self.__task = None  # type: Optional[Task]

        layout = QGridLayout()
        bg = gui.radioButtonsInBox(
            self.controlArea, self, "optimize_k", orientation=layout,
            box="Number of Clusters", callback=self.update_method,
        )

        layout.addWidget(
            gui.appendRadioButton(bg, "Fixed:", addToLayout=False), 1, 1)
        sb = gui.hBox(None, margin=0)
        gui.spin(
            sb, self, "k", minv=2, maxv=30,
            controlWidth=60, alignment=Qt.AlignRight, callback=self.update_k)
        gui.rubber(sb)
        layout.addWidget(sb, 1, 2)

        layout.addWidget(
            gui.appendRadioButton(bg, "From", addToLayout=False), 2, 1)
        ftobox = gui.hBox(None)
        ftobox.layout().setContentsMargins(0, 0, 0, 0)
        layout.addWidget(ftobox, 2, 2)
        gui.spin(
            ftobox, self, "k_from", minv=2, maxv=29,
            controlWidth=60, alignment=Qt.AlignRight,
            callback=self.update_from)
        gui.widgetLabel(ftobox, "to")
        gui.spin(
            ftobox, self, "k_to", minv=3, maxv=30,
            controlWidth=60, alignment=Qt.AlignRight,
            callback=self.update_to)
        gui.rubber(ftobox)

        box = gui.vBox(self.controlArea, "Initialization")
        gui.comboBox(
            box, self, "smart_init", items=[m[0] for m in self.INIT_METHODS],
            callback=self.invalidate)

        layout = QGridLayout()
        gui.widgetBox(box, orientation=layout)
        layout.addWidget(gui.widgetLabel(None, "Re-runs: "), 0, 0, Qt.AlignLeft)
        sb = gui.hBox(None, margin=0)
        layout.addWidget(sb, 0, 1)
        gui.lineEdit(
            sb, self, "n_init", controlWidth=60,
            valueType=int, validator=QIntValidator(), callback=self.invalidate)
        layout.addWidget(
            gui.widgetLabel(None, "Maximum iterations: "), 1, 0, Qt.AlignLeft)
        sb = gui.hBox(None, margin=0)
        layout.addWidget(sb, 1, 1)
        gui.lineEdit(
            sb, self, "max_iterations", controlWidth=60, valueType=int,
            validator=QIntValidator(), callback=self.invalidate)

        self.apply_button = gui.auto_commit(
            self.buttonsArea, self, "auto_commit", "Apply", box=None,
            commit=self.commit)
        gui.rubber(self.controlArea)

        box = gui.vBox(self.mainArea, box="Silhouette Scores")
        self.mainArea.setVisible(self.optimize_k)
        self.table_model = ClusterTableModel(self)
        table = self.table_view = QTableView(self.mainArea)
        table.setModel(self.table_model)
        table.setSelectionMode(QTableView.SingleSelection)
        table.setSelectionBehavior(QTableView.SelectRows)
        table.setItemDelegate(gui.ColoredBarItemDelegate(self, color=Qt.cyan))
        table.selectionModel().selectionChanged.connect(self.select_row)
        table.setMaximumWidth(200)
        table.horizontalHeader().setStretchLastSection(True)
        table.horizontalHeader().hide()
        table.setShowGrid(False)
        box.layout().addWidget(table)

#.........这里部分代码省略.........
        )
        self.progress_widget = QProgressBar(
            minimum=0, maximum=0
        )
        self.cancel_button = QPushButton(
            "Cancel", icon=icons.cancel_icon,
        )
        self.cancel_button.clicked.connect(self.cancel)

        w = QWidget()
        vlayout = QVBoxLayout()
        vlayout.setContentsMargins(0, 0, 0, 0)
        hlayout = QHBoxLayout()
        hlayout.setContentsMargins(0, 0, 0, 0)

        hlayout.addWidget(self.progress_widget)
        hlayout.addWidget(self.cancel_button)
        vlayout.addLayout(hlayout)

        self.pathlabel = TextLabel()
        self.pathlabel.setTextElideMode(Qt.ElideMiddle)
        self.pathlabel.setAttribute(Qt.WA_MacSmallSize)

        vlayout.addWidget(self.pathlabel)
        w.setLayout(vlayout)

        self.infostack.addWidget(self.info_area)
        self.infostack.addWidget(w)

        box.layout().addWidget(self.infostack)

        self.__initRecentItemsModel()
        self.__invalidated = True
        self.__executor = ThreadExecutor(self)

        QApplication.postEvent(self, QEvent(RuntimeEvent.Init))

    def __initRecentItemsModel(self):
        self._relocate_recent_files()
        recent_paths = []
        for item in self.recent_paths:
            recent_paths.append(item)
        recent_paths = recent_paths[:OWImportImages.MaxRecentItems]
        recent_model = self.recent_cb.model()
        recent_model.clear()

        for pathitem in recent_paths:
            item = RecentPath_asqstandarditem(pathitem)
            recent_model.appendRow(item)

        self.recent_paths = recent_paths

        if self.recent_paths and os.path.isdir(self.recent_paths[0].abspath):
            self.recent_cb.setCurrentIndex(0)
            self.__actions.reload.setEnabled(True)
        else:
            self.recent_cb.setCurrentIndex(-1)
            self.__actions.reload.setEnabled(False)

    def customEvent(self, event):
        """Reimplemented."""
        if event.type() == RuntimeEvent.Init:
            if self.__invalidated:
                try:
                    self.start()
                finally:

class OWNNLearner(OWBaseLearner):
    name = "Neural Network"
    description = "A multi-layer perceptron (MLP) algorithm with " \
                  "backpropagation."
    icon = "icons/NN.svg"
    priority = 90
    keywords = ["mlp"]

    LEARNER = NNLearner

    activation = ["identity", "logistic", "tanh", "relu"]
    act_lbl = ["Identity", "Logistic", "tanh", "ReLu"]
    solver = ["lbfgs", "sgd", "adam"]
    solv_lbl = ["L-BFGS-B", "SGD", "Adam"]

    learner_name = Setting("Neural Network")
    hidden_layers_input = Setting("100,")
    activation_index = Setting(3)
    solver_index = Setting(2)
    max_iterations = Setting(200)
    alpha_index = Setting(0)
    settings_version = 1

    alphas = list(chain([x / 10000 for x in range(1, 10)],
                        [x / 1000 for x in range(1, 10)],
                        [x / 100 for x in range(1, 10)],
                        [x / 10 for x in range(1, 10)],
                        range(1, 10),
                        range(10, 100, 5),
                        range(100, 200, 10),
                        range(100, 1001, 50)))

    def add_main_layout(self):
        form = QFormLayout()
        form.setFieldGrowthPolicy(form.AllNonFixedFieldsGrow)
        form.setVerticalSpacing(25)
        gui.widgetBox(self.controlArea, True, orientation=form)
        form.addRow(
            "Neurons in hidden layers:",
            gui.lineEdit(
                None, self, "hidden_layers_input",
                orientation=Qt.Horizontal, callback=self.settings_changed,
                tooltip="A list of integers defining neurons. Length of list "
                        "defines the number of layers. E.g. 4, 2, 2, 3.",
                placeholderText="e.g. 100,"))
        form.addRow(
            "Activation:",
            gui.comboBox(
                None, self, "activation_index", orientation=Qt.Horizontal,
                label="Activation:", items=[i for i in self.act_lbl],
                callback=self.settings_changed))

        form.addRow(" ", gui.separator(None, 16))
        form.addRow(
            "Solver:",
            gui.comboBox(
                None, self, "solver_index", orientation=Qt.Horizontal,
                label="Solver:", items=[i for i in self.solv_lbl],
                callback=self.settings_changed))
        self.reg_label = QLabel()
        slider = gui.hSlider(
            None, self, "alpha_index",
            minValue=0, maxValue=len(self.alphas) - 1,
            callback=lambda: (self.set_alpha(), self.settings_changed()),
            createLabel=False)
        form.addRow(self.reg_label, slider)
        self.set_alpha()

        form.addRow(
            "Maximal number of iterations:",
            gui.spin(
                None, self, "max_iterations", 10, 10000, step=10,
                label="Max iterations:", orientation=Qt.Horizontal,
                alignment=Qt.AlignRight, callback=self.settings_changed))

    def set_alpha(self):
        self.strength_C = self.alphas[self.alpha_index]
        self.reg_label.setText("Regularization, α={}:".format(self.strength_C))

    @property
    def alpha(self):
        return self.alphas[self.alpha_index]

    def setup_layout(self):
        super().setup_layout()

        self._task = None  # type: Optional[Task]
        self._executor = ThreadExecutor()

        # just a test cancel button
        gui.button(self.apply_button, self, "Cancel", callback=self.cancel)

    def create_learner(self):
        return self.LEARNER(
            hidden_layer_sizes=self.get_hidden_layers(),
            activation=self.activation[self.activation_index],
            solver=self.solver[self.solver_index],
            alpha=self.alpha,
            max_iter=self.max_iterations,
            preprocessors=self.preprocessors)
#.........这里部分代码省略.........