{
    "file_diffs": [
        {
            "old_file_content": "\"\"\"\nLinear Projection widget\n------------------------\n\"\"\"\n\nfrom itertools import islice, permutations, chain\nfrom math import factorial\n\nimport numpy as np\n\nfrom sklearn.neighbors import NearestNeighbors\nfrom sklearn.metrics import r2_score\n\nfrom AnyQt.QtGui import QStandardItem, QPalette\nfrom AnyQt.QtCore import Qt, QRectF, QLineF, pyqtSignal as Signal\n\nimport pyqtgraph as pg\n\nfrom Orange.data import Table, Domain\nfrom Orange.preprocess import Normalize\nfrom Orange.preprocess.score import ReliefF, RReliefF\nfrom Orange.projection import PCA, LDA, LinearProjector\nfrom Orange.util import Enum\nfrom Orange.widgets import gui, report\nfrom Orange.widgets.gui import OWComponent\nfrom Orange.widgets.settings import Setting, ContextSetting, SettingProvider\nfrom Orange.widgets.utils.localization import pl\nfrom Orange.widgets.utils.plot import variables_selection\nfrom Orange.widgets.utils.plot.owplotgui import VariableSelectionModel\nfrom Orange.widgets.utils.widgetpreview import WidgetPreview\nfrom Orange.widgets.visualize.utils import VizRankDialog\nfrom Orange.widgets.visualize.utils.component import OWGraphWithAnchors\nfrom Orange.widgets.visualize.utils.plotutils import AnchorItem\nfrom Orange.widgets.visualize.utils.widget import OWAnchorProjectionWidget\nfrom Orange.widgets.widget import Msg\n\n\nMAX_LABEL_LEN = 20\n\n\nclass LinearProjectionVizRank(VizRankDialog, OWComponent):\n    captionTitle = \"Score Plots\"\n    n_attrs = Setting(3)\n    minK = 10\n\n    attrsSelected = Signal([])\n    _AttrRole = next(gui.OrangeUserRole)\n\n    def __init__(self, master):\n        # Add the spin box for a number of attributes to take into account.\n        VizRankDialog.__init__(self, master)\n        OWComponent.__init__(self, master)\n\n        box = gui.hBox(self)\n        max_n_attrs = len(master.model_selected)\n        self.n_attrs_spin = gui.spin(\n            box, self, \"n_attrs\", 3, max_n_attrs, label=\"Number of variables: \",\n            controlWidth=50, alignment=Qt.AlignRight, callback=self._n_attrs_changed)\n        gui.rubber(box)\n        self.last_run_n_attrs = None\n        self.attr_color = master.attr_color\n        self.attrs = []\n\n    def initialize(self):\n        super().initialize()\n        self.n_attrs_spin.setDisabled(False)\n        self.attr_color = self.master.attr_color\n\n    def before_running(self):\n        \"\"\"\n        Disable the spin for number of attributes before running and\n        enable afterwards. Also, if the number of attributes is different than\n        in the last run, reset the saved state (if it was paused).\n        \"\"\"\n        if self.n_attrs != self.last_run_n_attrs:\n            self.saved_state = None\n            self.saved_progress = 0\n        if self.saved_state is None:\n            self.scores = []\n            self.rank_model.clear()\n        self.last_run_n_attrs = self.n_attrs\n        self.n_attrs_spin.setDisabled(True)\n\n    def stopped(self):\n        self.n_attrs_spin.setDisabled(False)\n\n    def check_preconditions(self):\n        master = self.master\n        if not super().check_preconditions():\n            return False\n        elif not master.btn_vizrank.isEnabled():\n            return False\n        n_cont_var = len([v for v in master.continuous_variables\n                          if v is not master.attr_color])\n        self.n_attrs_spin.setMaximum(n_cont_var)\n        return True\n\n    def state_count(self):\n        n_all_attrs = len(self.attrs)\n        if not n_all_attrs:\n            return 0\n        n_attrs = self.n_attrs\n        return factorial(n_all_attrs) // (2 * factorial(n_all_attrs - n_attrs) * n_attrs)\n\n    def iterate_states(self, state):\n        if state is None:  # on the first call, compute order\n            self.attrs = self._score_heuristic()\n            state = list(range(self.n_attrs))\n        else:\n            state = list(state)\n\n        def combinations(n, s):\n            while True:\n                yield s\n                for up, _ in enumerate(s):\n                    s[up] += 1\n                    if up + 1 == len(s) or s[up] < s[up + 1]:\n                        break\n                    s[up] = up\n                if s[-1] == n:\n                    break\n\n        for c in combinations(len(self.attrs), state):\n            for p in islice(permutations(c[1:]), factorial(len(c) - 1) // 2):\n                yield (c[0], ) + p\n\n    def compute_score(self, state):\n        master = self.master\n        data = master.data\n        domain = Domain([self.attrs[i] for i in state], data.domain.class_vars)\n        projection = master.projector(data.transform(domain))\n        ec = projection(data).X\n        y = column_data(data, self.attr_color, dtype=float)\n        if ec.shape[0] < self.minK:\n            return None\n        n_neighbors = min(self.minK, len(ec) - 1)\n        knn = NearestNeighbors(n_neighbors=n_neighbors).fit(ec)\n        ind = knn.kneighbors(return_distance=False)\n        # pylint: disable=invalid-unary-operand-type\n        if self.attr_color.is_discrete:\n            return -np.sum(y[ind] == y.reshape(-1, 1)) / n_neighbors / len(y)\n        return -r2_score(y, np.mean(y[ind], axis=1)) * (len(y) / len(data))\n\n    def bar_length(self, score):\n        return max(0, -score)\n\n    def _score_heuristic(self):\n        def normalized(a):\n            span = np.max(a, axis=0) - np.min(a, axis=0)\n            span[span == 0] = 1\n            return (a - np.mean(a, axis=0)) / span\n\n        domain = self.master.data.domain\n        attr_color = self.master.attr_color\n        domain = Domain(\n            attributes=[v for v in chain(domain.variables, domain.metas)\n                        if v.is_continuous and v is not attr_color],\n            class_vars=attr_color\n        )\n        data = self.master.data.transform(domain).copy()\n        with data.unlocked():\n            data.X = normalized(data.X)\n        relief = ReliefF if attr_color.is_discrete else RReliefF\n        weights = relief(n_iterations=100, k_nearest=self.minK)(data)\n        results = sorted(zip(weights, domain.attributes), key=lambda x: (-x[0], x[1].name))\n        return [attr for _, attr in results]\n\n    def row_for_state(self, score, state):\n        attrs = [self.attrs[i] for i in state]\n        item = QStandardItem(\", \".join(a.name for a in attrs))\n        item.setData(attrs, self._AttrRole)\n        return [item]\n\n    def on_selection_changed(self, selected, deselected):\n        if not selected.indexes():\n            return\n        attrs = selected.indexes()[0].data(self._AttrRole)\n        self.selectionChanged.emit([attrs])\n\n    def _n_attrs_changed(self):\n        if self.n_attrs != self.last_run_n_attrs or self.saved_state is None:\n            self.button.setText(\"Start\")\n        else:\n            self.button.setText(\"Continue\")\n        self.button.setEnabled(self.check_preconditions())\n\n\nclass OWLinProjGraph(OWGraphWithAnchors):\n    hide_radius = Setting(0)\n\n    @property\n    def always_show_axes(self):\n        return self.master.placement == Placement.Circular\n\n    @property\n    def scaled_radius(self):\n        return self.hide_radius / 100 + 1e-5\n\n    def update_radius(self):\n        self.update_circle()\n        self.update_anchors()\n\n    def set_view_box_range(self):\n        def min_max(a, b):\n            return (min(np.amin(a), np.amin(b), -1.05),\n                    max(np.amax(a), np.amax(b), 1.05))\n\n        points, _ = self.master.get_anchors()\n        coords = self.master.get_coordinates_data()\n        if points is None or coords is None:\n            return\n\n        min_x, max_x = min_max(points[:, 0], coords[0])\n        min_y, max_y = min_max(points[:, 1], coords[1])\n        rect = QRectF(min_x, min_y, max_x - min_x, max_y - min_y)\n        self.view_box.setRange(rect, padding=0.025)\n\n    def update_anchors(self):\n        points, labels = self.master.get_anchors()\n        if points is None:\n            return\n        r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))\n        if self.anchor_items is None:\n            self.anchor_items = []\n            for point, label in zip(points, labels):\n                anchor = AnchorItem(line=QLineF(0, 0, *point))\n                anchor._label.setToolTip(f\"<b>{label}</b>\")\n                label = label[:MAX_LABEL_LEN - 3] + \"...\" if len(label) > MAX_LABEL_LEN else label\n                anchor.setText(label)\n                anchor.setFont(self.parameter_setter.anchor_font)\n\n                visible = self.always_show_axes or np.linalg.norm(point) > r\n                anchor.setVisible(bool(visible))\n                anchor.setPen(pg.mkPen((100, 100, 100)))\n                self.plot_widget.addItem(anchor)\n                self.anchor_items.append(anchor)\n        else:\n            for anchor, point, label in zip(self.anchor_items, points, labels):\n                anchor.setLine(QLineF(0, 0, *point))\n                visible = self.always_show_axes or np.linalg.norm(point) > r\n                anchor.setVisible(bool(visible))\n                anchor.setFont(self.parameter_setter.anchor_font)\n\n    def update_circle(self):\n        super().update_circle()\n\n        if self.always_show_axes:\n            self.plot_widget.removeItem(self.circle_item)\n            self.circle_item = None\n\n        if self.circle_item is not None:\n            points, _ = self.master.get_anchors()\n            if points is None:\n                return\n\n            r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))\n            self.circle_item.setRect(QRectF(-r, -r, 2 * r, 2 * r))\n            color = self.plot_widget.palette().color(QPalette.Disabled, QPalette.Text)\n            pen = pg.mkPen(color, width=1, cosmetic=True)\n            self.circle_item.setPen(pen)\n\n\nPlacement = Enum(\"Placement\", dict(Circular=0, LDA=1, PCA=2), type=int,\n                 qualname=\"Placement\")\n\n\nclass OWLinearProjection(OWAnchorProjectionWidget):\n    name = \"Linear Projection\"\n    description = \"A multi-axis projection of data onto \" \\\n                  \"a two-dimensional plane.\"\n    icon = \"icons/LinearProjection.svg\"\n    priority = 240\n    keywords = \"linear projection\"\n\n    Projection_name = {Placement.Circular: \"Circular Placement\",\n                       Placement.LDA: \"Linear Discriminant Analysis\",\n                       Placement.PCA: \"Principal Component Analysis\"}\n\n    settings_version = 6\n\n    placement = Setting(Placement.Circular)\n    selected_vars = ContextSetting([])\n    vizrank = SettingProvider(LinearProjectionVizRank)\n    GRAPH_CLASS = OWLinProjGraph\n    graph = SettingProvider(OWLinProjGraph)\n\n    class Error(OWAnchorProjectionWidget.Error):\n        no_cont_features = Msg(\"Plotting requires numeric features\")\n\n    class Information(OWAnchorProjectionWidget.Information):\n        no_lda = Msg(\"LDA placement is disabled due to unsuitable target.\\n{}\")\n\n    def _add_controls(self):\n        box = gui.vBox(self.controlArea, box=\"Features\")\n        self._add_controls_variables(box)\n        self._add_controls_placement(box)\n        super()._add_controls()\n        self.gui.add_control(\n            self._effects_box, gui.hSlider, \"Hide radius:\", master=self.graph,\n            value=\"hide_radius\", minValue=0, maxValue=100, step=10,\n            createLabel=False, callback=self.__radius_slider_changed\n        )\n\n    def _add_controls_variables(self, box):\n        self.model_selected = VariableSelectionModel(self.selected_vars)\n        variables_selection(box, self, self.model_selected)\n        self.model_selected.selection_changed.connect(\n            self.__model_selected_changed)\n        self.vizrank, self.btn_vizrank = LinearProjectionVizRank.add_vizrank(\n            None, self, \"Suggest Features\", self.__vizrank_set_attrs)\n        box.layout().addWidget(self.btn_vizrank)\n\n    def _add_controls_placement(self, box):\n        self.radio_placement = gui.radioButtonsInBox(\n            box, self, \"placement\",\n            btnLabels=[self.Projection_name[x] for x in Placement],\n            callback=self.__placement_radio_changed\n        )\n\n    def _add_buttons(self):\n        self.gui.box_zoom_select(self.buttonsArea)\n        gui.auto_send(self.buttonsArea, self, \"auto_commit\")\n\n    @property\n    def continuous_variables(self):\n        if self.data is None or self.data.domain is None:\n            return []\n        dom = self.data.domain\n        return [v for v in chain(dom.variables, dom.metas) if v.is_continuous]\n\n    @property\n    def effective_variables(self):\n        return self.selected_vars\n\n    @property\n    def effective_data(self):\n        cvs = None\n        if self.placement == Placement.LDA:\n            cvs = self.data.domain.class_vars\n        return self.data.transform(Domain(self.effective_variables, cvs))\n\n    def __vizrank_set_attrs(self, attrs):\n        if not attrs:\n            return\n        self.selected_vars[:] = attrs\n        # Ugly, but the alternative is to have yet another signal to which\n        # the view will have to connect\n        self.model_selected.selection_changed.emit()\n\n    def __model_selected_changed(self):\n        self.projection = None\n        self._check_options()\n        self.init_projection()\n        self.setup_plot()\n        self.commit.deferred()\n\n    def __placement_radio_changed(self):\n        self.controls.graph.hide_radius.setEnabled(\n            self.placement != Placement.Circular)\n        self.projection = self.projector = None\n        self._init_vizrank()\n        self.init_projection()\n        self.setup_plot()\n        self.commit.deferred()\n\n    def __radius_slider_changed(self):\n        self.graph.update_radius()\n\n    def colors_changed(self):\n        super().colors_changed()\n        self._init_vizrank()\n\n    @OWAnchorProjectionWidget.Inputs.data\n    def set_data(self, data):\n        super().set_data(data)\n        self._check_options()\n        self._init_vizrank()\n        self.init_projection()\n\n    def _check_options(self):\n        buttons = self.radio_placement.buttons\n        for btn in buttons:\n            btn.setEnabled(True)\n\n        problem = None\n        if self.data is not None:\n            if (class_var := self.data.domain.class_var) is None:\n                problem = \"Current data has no target variable\"\n            elif not class_var.is_discrete:\n                problem = f\"{class_var.name} is not categorical\"\n            elif (nclasses := len(distinct := np.unique(self.data.Y))) == 0:\n                problem = f\"Data has no defined values for {class_var.name}\"\n            elif nclasses < 3:\n                vals = \" and \".join(f\"'{class_var.values[int(i)]}'\" for i in distinct)\n                problem = \\\n                    f\"Data contains just {['one', 'two'][nclasses - 1]} distinct \" \\\n                    f\"{pl(nclasses, 'value')} ({vals}) for '{class_var.name}'; \" \\\n                    \"at least three are required.\"\n        if problem is None:\n            self.Information.no_lda.clear()\n        else:\n            self.Information.no_lda(problem)\n            buttons[Placement.LDA].setEnabled(False)\n            if self.placement == Placement.LDA:\n                self.placement = Placement.Circular\n\n        self.controls.graph.hide_radius.setEnabled(\n            self.placement != Placement.Circular)\n\n    def _init_vizrank(self):\n        is_enabled, msg = False, \"\"\n        if self.data is None:\n            msg = \"There is no data.\"\n        elif self.attr_color is None:\n            msg = \"Color variable has to be selected\"\n        elif self.attr_color.is_continuous and \\\n                self.placement == Placement.LDA:\n            msg = \"Suggest Features does not work for Linear \" \\\n                  \"Discriminant Analysis Projection when \" \\\n                  \"continuous color variable is selected.\"\n        elif len([v for v in self.continuous_variables\n                  if v is not self.attr_color]) < 3:\n            msg = \"Not enough available continuous variables\"\n        elif np.sum(np.all(np.isfinite(self.data.X), axis=1)) < 2:\n            msg = \"Not enough valid data instances\"\n        else:\n            is_enabled = \\\n                not np.isnan(self.data.get_column(self.attr_color)).all()\n        self.btn_vizrank.setToolTip(msg)\n        self.btn_vizrank.setEnabled(is_enabled)\n        if is_enabled:\n            self.vizrank.initialize()\n\n    def check_data(self):\n        def error(err):\n            err()\n            self.data = None\n\n        super().check_data()\n        if self.data is not None:\n            if not len(self.continuous_variables):\n                error(self.Error.no_cont_features)\n\n    def init_attr_values(self):\n        super().init_attr_values()\n        self.selected_vars[:] = self.continuous_variables[:3]\n        self.model_selected[:] = self.continuous_variables\n\n    def init_projection(self):\n        if self.placement == Placement.Circular:\n            self.projector = CircularPlacement()\n        elif self.placement == Placement.LDA:\n            self.projector = LDA(solver=\"eigen\", n_components=2)\n        elif self.placement == Placement.PCA:\n            self.projector = PCA(n_components=2)\n            self.projector.component = 2\n            self.projector.preprocessors = PCA.preprocessors + [Normalize()]\n\n        super().init_projection()\n\n    def get_coordinates_data(self):\n        def normalized(a):\n            span = np.max(a, axis=0) - np.min(a, axis=0)\n            span[span == 0] = 1\n            return (a - np.mean(a, axis=0)) / span\n\n        embedding = self.get_embedding()\n        if embedding is None:\n            return None, None\n        norm_emb = normalized(embedding[self.valid_data])\n        return (norm_emb.ravel(), np.zeros(len(norm_emb), dtype=float)) \\\n            if embedding.shape[1] == 1 else norm_emb.T\n\n    def _get_send_report_caption(self):\n        def projection_name():\n            return self.Projection_name[self.placement]\n\n        return report.render_items_vert((\n            (\"Projection\", projection_name()),\n            (\"Color\", self._get_caption_var_name(self.attr_color)),\n            (\"Label\", self._get_caption_var_name(self.attr_label)),\n            (\"Shape\", self._get_caption_var_name(self.attr_shape)),\n            (\"Size\", self._get_caption_var_name(self.attr_size)),\n            (\"Jittering\", self.graph.jitter_size != 0 and\n             \"{} %\".format(self.graph.jitter_size))))\n\n    @classmethod\n    def migrate_settings(cls, settings_, version):\n        if version < 2:\n            settings_[\"point_width\"] = settings_[\"point_size\"]\n        if version < 3:\n            settings_graph = {}\n            settings_graph[\"jitter_size\"] = settings_[\"jitter_value\"]\n            settings_graph[\"point_width\"] = settings_[\"point_width\"]\n            settings_graph[\"alpha_value\"] = settings_[\"alpha_value\"]\n            settings_graph[\"class_density\"] = settings_[\"class_density\"]\n            settings_[\"graph\"] = settings_graph\n        if version < 4:\n            if \"radius\" in settings_:\n                settings_[\"graph\"][\"hide_radius\"] = settings_[\"radius\"]\n            if \"selection_indices\" in settings_ and \\\n                    settings_[\"selection_indices\"] is not None:\n                selection = settings_[\"selection_indices\"]\n                settings_[\"selection\"] = [(i, 1) for i, selected in\n                                          enumerate(selection) if selected]\n        if version < 5:\n            if \"placement\" in settings_ and \\\n                    settings_[\"placement\"] not in Placement:\n                settings_[\"placement\"] = Placement.Circular\n\n    @classmethod\n    def migrate_context(cls, context, version):\n        values = context.values\n        if version < 2:\n            domain = context.ordered_domain\n            c_domain = [t for t in context.ordered_domain if t[1] == 2]\n            d_domain = [t for t in context.ordered_domain if t[1] == 1]\n            for d, old_val, new_val in ((domain, \"color_index\", \"attr_color\"),\n                                        (d_domain, \"shape_index\", \"attr_shape\"),\n                                        (c_domain, \"size_index\", \"attr_size\")):\n                index = context.values[old_val][0] - 1\n                values[new_val] = (d[index][0], d[index][1] + 100) \\\n                    if 0 <= index < len(d) else None\n        if version < 3:\n            values[\"graph\"] = {\n                \"attr_color\": values[\"attr_color\"],\n                \"attr_shape\": values[\"attr_shape\"],\n                \"attr_size\": values[\"attr_size\"]\n            }\n        if version == 3:\n            values[\"attr_color\"] = values[\"graph\"][\"attr_color\"]\n            values[\"attr_size\"] = values[\"graph\"][\"attr_size\"]\n            values[\"attr_shape\"] = values[\"graph\"][\"attr_shape\"]\n            values[\"attr_label\"] = values[\"graph\"][\"attr_label\"]\n        if version < 6 and \"selected_vars\" in values:\n            values[\"selected_vars\"] = (values[\"selected_vars\"], -3)\n\n    # for backward compatibility with settings < 6, pull the enum from global\n    # namespace into class\n    Placement = Placement\n\n\ndef column_data(table, var, dtype):\n    dtype = np.dtype(dtype)\n    col = table.get_column(var)\n    if dtype != col.dtype:\n        col = col.astype(dtype)\n    if col.base is not None:\n        col = col.copy()\n    return col\n\n\nclass CircularPlacement(LinearProjector):\n    def get_components(self, X, Y):\n        # Return circular axes for linear projection\n        n_axes = X.shape[1]\n        if n_axes == 1:\n            axes_angle = [0]\n        elif n_axes == 2:\n            axes_angle = [0, np.pi / 2]\n        else:\n            axes_angle = np.linspace(0, 2 * np.pi, n_axes,\n                                     endpoint=False)\n        return np.vstack((np.cos(axes_angle), np.sin(axes_angle)))\n\n\nif __name__ == \"__main__\":  # pragma: no cover\n    iris = Table(\"iris\")\n    WidgetPreview(OWLinearProjection).run(set_data=iris,\n                                          set_subset_data=iris[::10])\n",
            "new_file_content": "\"\"\"\nLinear Projection widget\n------------------------\n\"\"\"\n\nfrom itertools import islice, permutations, chain\nfrom math import factorial\n\nimport numpy as np\n\nfrom sklearn.neighbors import NearestNeighbors\nfrom sklearn.metrics import r2_score\n\nfrom AnyQt.QtGui import QStandardItem, QPalette\nfrom AnyQt.QtCore import Qt, QRectF, QLineF, pyqtSignal as Signal\n\nimport pyqtgraph as pg\n\nfrom Orange.data import Table, Domain\nfrom Orange.preprocess import Normalize\nfrom Orange.preprocess.score import ReliefF, RReliefF\nfrom Orange.projection import PCA, LDA, LinearProjector\nfrom Orange.util import Enum\nfrom Orange.widgets import gui, report\nfrom Orange.widgets.gui import OWComponent\nfrom Orange.widgets.settings import Setting, ContextSetting, SettingProvider\nfrom Orange.widgets.utils.localization import pl\nfrom Orange.widgets.utils.plot import variables_selection\nfrom Orange.widgets.utils.plot.owplotgui import VariableSelectionModel\nfrom Orange.widgets.utils.widgetpreview import WidgetPreview\nfrom Orange.widgets.visualize.utils import VizRankDialog\nfrom Orange.widgets.visualize.utils.component import OWGraphWithAnchors\nfrom Orange.widgets.visualize.utils.plotutils import AnchorItem\nfrom Orange.widgets.visualize.utils.widget import OWAnchorProjectionWidget\nfrom Orange.widgets.widget import Msg\n\n\nMAX_LABEL_LEN = 20\n\n\nclass LinearProjectionVizRank(VizRankDialog, OWComponent):\n    captionTitle = \"Score Plots\"\n    n_attrs = Setting(3)\n    minK = 10\n\n    attrsSelected = Signal([])\n    _AttrRole = next(gui.OrangeUserRole)\n\n    def __init__(self, master):\n        # Add the spin box for a number of attributes to take into account.\n        VizRankDialog.__init__(self, master)\n        OWComponent.__init__(self, master)\n\n        box = gui.hBox(self)\n        max_n_attrs = len(master.model_selected)\n        self.n_attrs_spin = gui.spin(\n            box, self, \"n_attrs\", 3, max_n_attrs, label=\"Number of variables: \",\n            controlWidth=50, alignment=Qt.AlignRight, callback=self._n_attrs_changed)\n        gui.rubber(box)\n        self.last_run_n_attrs = None\n        self.attr_color = master.attr_color\n        self.attrs = []\n\n    def initialize(self):\n        super().initialize()\n        self.n_attrs_spin.setDisabled(False)\n        self.attr_color = self.master.attr_color\n\n    def before_running(self):\n        \"\"\"\n        Disable the spin for number of attributes before running and\n        enable afterwards. Also, if the number of attributes is different than\n        in the last run, reset the saved state (if it was paused).\n        \"\"\"\n        if self.n_attrs != self.last_run_n_attrs:\n            self.saved_state = None\n            self.saved_progress = 0\n        if self.saved_state is None:\n            self.scores = []\n            self.rank_model.clear()\n        self.last_run_n_attrs = self.n_attrs\n        self.n_attrs_spin.setDisabled(True)\n\n    def stopped(self):\n        self.n_attrs_spin.setDisabled(False)\n\n    def check_preconditions(self):\n        master = self.master\n        if not super().check_preconditions():\n            return False\n        elif not master.btn_vizrank.isEnabled():\n            return False\n        n_cont_var = len([v for v in master.continuous_variables\n                          if v is not master.attr_color])\n        self.n_attrs_spin.setMaximum(n_cont_var)\n        self.n_attrs_spin.setValue(self.n_attrs)\n        return True\n\n    def state_count(self):\n        n_all_attrs = len(self.attrs)\n        if not n_all_attrs:\n            return 0\n        n_attrs = self.n_attrs\n        return factorial(n_all_attrs) // (2 * factorial(n_all_attrs - n_attrs) * n_attrs)\n\n    def iterate_states(self, state):\n        if state is None:  # on the first call, compute order\n            self.attrs = self._score_heuristic()\n            state = list(range(self.n_attrs))\n        else:\n            state = list(state)\n\n        def combinations(n, s):\n            while True:\n                yield s\n                for up, _ in enumerate(s):\n                    s[up] += 1\n                    if up + 1 == len(s) or s[up] < s[up + 1]:\n                        break\n                    s[up] = up\n                if s[-1] == n:\n                    break\n\n        for c in combinations(len(self.attrs), state):\n            for p in islice(permutations(c[1:]), factorial(len(c) - 1) // 2):\n                yield (c[0], ) + p\n\n    def compute_score(self, state):\n        master = self.master\n        data = master.data\n        domain = Domain([self.attrs[i] for i in state], data.domain.class_vars)\n        projection = master.projector(data.transform(domain))\n        ec = projection(data).X\n        y = column_data(data, self.attr_color, dtype=float)\n        if ec.shape[0] < self.minK:\n            return None\n        n_neighbors = min(self.minK, len(ec) - 1)\n        knn = NearestNeighbors(n_neighbors=n_neighbors).fit(ec)\n        ind = knn.kneighbors(return_distance=False)\n        # pylint: disable=invalid-unary-operand-type\n        if self.attr_color.is_discrete:\n            return -np.sum(y[ind] == y.reshape(-1, 1)) / n_neighbors / len(y)\n        return -r2_score(y, np.mean(y[ind], axis=1)) * (len(y) / len(data))\n\n    def bar_length(self, score):\n        return max(0, -score)\n\n    def _score_heuristic(self):\n        def normalized(a):\n            span = np.max(a, axis=0) - np.min(a, axis=0)\n            span[span == 0] = 1\n            return (a - np.mean(a, axis=0)) / span\n\n        domain = self.master.data.domain\n        attr_color = self.master.attr_color\n        domain = Domain(\n            attributes=[v for v in chain(domain.variables, domain.metas)\n                        if v.is_continuous and v is not attr_color],\n            class_vars=attr_color\n        )\n        data = self.master.data.transform(domain).copy()\n        with data.unlocked():\n            data.X = normalized(data.X)\n        relief = ReliefF if attr_color.is_discrete else RReliefF\n        weights = relief(n_iterations=100, k_nearest=self.minK)(data)\n        results = sorted(zip(weights, domain.attributes), key=lambda x: (-x[0], x[1].name))\n        return [attr for _, attr in results]\n\n    def row_for_state(self, score, state):\n        attrs = [self.attrs[i] for i in state]\n        item = QStandardItem(\", \".join(a.name for a in attrs))\n        item.setData(attrs, self._AttrRole)\n        return [item]\n\n    def on_selection_changed(self, selected, deselected):\n        if not selected.indexes():\n            return\n        attrs = selected.indexes()[0].data(self._AttrRole)\n        self.selectionChanged.emit([attrs])\n\n    def _n_attrs_changed(self):\n        if self.n_attrs != self.last_run_n_attrs or self.saved_state is None:\n            self.button.setText(\"Start\")\n        else:\n            self.button.setText(\"Continue\")\n        self.button.setEnabled(self.check_preconditions())\n\n\nclass OWLinProjGraph(OWGraphWithAnchors):\n    hide_radius = Setting(0)\n\n    @property\n    def always_show_axes(self):\n        return self.master.placement == Placement.Circular\n\n    @property\n    def scaled_radius(self):\n        return self.hide_radius / 100 + 1e-5\n\n    def update_radius(self):\n        self.update_circle()\n        self.update_anchors()\n\n    def set_view_box_range(self):\n        def min_max(a, b):\n            return (min(np.amin(a), np.amin(b), -1.05),\n                    max(np.amax(a), np.amax(b), 1.05))\n\n        points, _ = self.master.get_anchors()\n        coords = self.master.get_coordinates_data()\n        if points is None or coords is None:\n            return\n\n        min_x, max_x = min_max(points[:, 0], coords[0])\n        min_y, max_y = min_max(points[:, 1], coords[1])\n        rect = QRectF(min_x, min_y, max_x - min_x, max_y - min_y)\n        self.view_box.setRange(rect, padding=0.025)\n\n    def update_anchors(self):\n        points, labels = self.master.get_anchors()\n        if points is None:\n            return\n        r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))\n        if self.anchor_items is None:\n            self.anchor_items = []\n            for point, label in zip(points, labels):\n                anchor = AnchorItem(line=QLineF(0, 0, *point))\n                anchor._label.setToolTip(f\"<b>{label}</b>\")\n                label = label[:MAX_LABEL_LEN - 3] + \"...\" if len(label) > MAX_LABEL_LEN else label\n                anchor.setText(label)\n                anchor.setFont(self.parameter_setter.anchor_font)\n\n                visible = self.always_show_axes or np.linalg.norm(point) > r\n                anchor.setVisible(bool(visible))\n                anchor.setPen(pg.mkPen((100, 100, 100)))\n                self.plot_widget.addItem(anchor)\n                self.anchor_items.append(anchor)\n        else:\n            for anchor, point, label in zip(self.anchor_items, points, labels):\n                anchor.setLine(QLineF(0, 0, *point))\n                visible = self.always_show_axes or np.linalg.norm(point) > r\n                anchor.setVisible(bool(visible))\n                anchor.setFont(self.parameter_setter.anchor_font)\n\n    def update_circle(self):\n        super().update_circle()\n\n        if self.always_show_axes:\n            self.plot_widget.removeItem(self.circle_item)\n            self.circle_item = None\n\n        if self.circle_item is not None:\n            points, _ = self.master.get_anchors()\n            if points is None:\n                return\n\n            r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))\n            self.circle_item.setRect(QRectF(-r, -r, 2 * r, 2 * r))\n            color = self.plot_widget.palette().color(QPalette.Disabled, QPalette.Text)\n            pen = pg.mkPen(color, width=1, cosmetic=True)\n            self.circle_item.setPen(pen)\n\n\nPlacement = Enum(\"Placement\", dict(Circular=0, LDA=1, PCA=2), type=int,\n                 qualname=\"Placement\")\n\n\nclass OWLinearProjection(OWAnchorProjectionWidget):\n    name = \"Linear Projection\"\n    description = \"A multi-axis projection of data onto \" \\\n                  \"a two-dimensional plane.\"\n    icon = \"icons/LinearProjection.svg\"\n    priority = 240\n    keywords = \"linear projection\"\n\n    Projection_name = {Placement.Circular: \"Circular Placement\",\n                       Placement.LDA: \"Linear Discriminant Analysis\",\n                       Placement.PCA: \"Principal Component Analysis\"}\n\n    settings_version = 6\n\n    placement = Setting(Placement.Circular)\n    selected_vars = ContextSetting([])\n    vizrank = SettingProvider(LinearProjectionVizRank)\n    GRAPH_CLASS = OWLinProjGraph\n    graph = SettingProvider(OWLinProjGraph)\n\n    class Error(OWAnchorProjectionWidget.Error):\n        no_cont_features = Msg(\"Plotting requires numeric features\")\n\n    class Information(OWAnchorProjectionWidget.Information):\n        no_lda = Msg(\"LDA placement is disabled due to unsuitable target.\\n{}\")\n\n    def _add_controls(self):\n        box = gui.vBox(self.controlArea, box=\"Features\")\n        self._add_controls_variables(box)\n        self._add_controls_placement(box)\n        super()._add_controls()\n        self.gui.add_control(\n            self._effects_box, gui.hSlider, \"Hide radius:\", master=self.graph,\n            value=\"hide_radius\", minValue=0, maxValue=100, step=10,\n            createLabel=False, callback=self.__radius_slider_changed\n        )\n\n    def _add_controls_variables(self, box):\n        self.model_selected = VariableSelectionModel(self.selected_vars)\n        variables_selection(box, self, self.model_selected)\n        self.model_selected.selection_changed.connect(\n            self.__model_selected_changed)\n        self.vizrank, self.btn_vizrank = LinearProjectionVizRank.add_vizrank(\n            None, self, \"Suggest Features\", self.__vizrank_set_attrs)\n        box.layout().addWidget(self.btn_vizrank)\n\n    def _add_controls_placement(self, box):\n        self.radio_placement = gui.radioButtonsInBox(\n            box, self, \"placement\",\n            btnLabels=[self.Projection_name[x] for x in Placement],\n            callback=self.__placement_radio_changed\n        )\n\n    def _add_buttons(self):\n        self.gui.box_zoom_select(self.buttonsArea)\n        gui.auto_send(self.buttonsArea, self, \"auto_commit\")\n\n    @property\n    def continuous_variables(self):\n        if self.data is None or self.data.domain is None:\n            return []\n        dom = self.data.domain\n        return [v for v in chain(dom.variables, dom.metas) if v.is_continuous]\n\n    @property\n    def effective_variables(self):\n        return self.selected_vars\n\n    @property\n    def effective_data(self):\n        cvs = None\n        if self.placement == Placement.LDA:\n            cvs = self.data.domain.class_vars\n        return self.data.transform(Domain(self.effective_variables, cvs))\n\n    def __vizrank_set_attrs(self, attrs):\n        if not attrs:\n            return\n        self.selected_vars[:] = attrs\n        # Ugly, but the alternative is to have yet another signal to which\n        # the view will have to connect\n        self.model_selected.selection_changed.emit()\n\n    def __model_selected_changed(self):\n        self.projection = None\n        self._check_options()\n        self.init_projection()\n        self.setup_plot()\n        self.commit.deferred()\n\n    def __placement_radio_changed(self):\n        self.controls.graph.hide_radius.setEnabled(\n            self.placement != Placement.Circular)\n        self.projection = self.projector = None\n        self._init_vizrank()\n        self.init_projection()\n        self.setup_plot()\n        self.commit.deferred()\n\n    def __radius_slider_changed(self):\n        self.graph.update_radius()\n\n    def colors_changed(self):\n        super().colors_changed()\n        self._init_vizrank()\n\n    @OWAnchorProjectionWidget.Inputs.data\n    def set_data(self, data):\n        super().set_data(data)\n        self._check_options()\n        self._init_vizrank()\n        self.init_projection()\n\n    def _check_options(self):\n        buttons = self.radio_placement.buttons\n        for btn in buttons:\n            btn.setEnabled(True)\n\n        problem = None\n        if self.data is not None:\n            if (class_var := self.data.domain.class_var) is None:\n                problem = \"Current data has no target variable\"\n            elif not class_var.is_discrete:\n                problem = f\"{class_var.name} is not categorical\"\n            elif (nclasses := len(distinct := np.unique(self.data.Y))) == 0:\n                problem = f\"Data has no defined values for {class_var.name}\"\n            elif nclasses < 3:\n                vals = \" and \".join(f\"'{class_var.values[int(i)]}'\" for i in distinct)\n                problem = \\\n                    f\"Data contains just {['one', 'two'][nclasses - 1]} distinct \" \\\n                    f\"{pl(nclasses, 'value')} ({vals}) for '{class_var.name}'; \" \\\n                    \"at least three are required.\"\n        if problem is None:\n            self.Information.no_lda.clear()\n        else:\n            self.Information.no_lda(problem)\n            buttons[Placement.LDA].setEnabled(False)\n            if self.placement == Placement.LDA:\n                self.placement = Placement.Circular\n\n        self.controls.graph.hide_radius.setEnabled(\n            self.placement != Placement.Circular)\n\n    def _init_vizrank(self):\n        is_enabled, msg = False, \"\"\n        if self.data is None:\n            msg = \"There is no data.\"\n        elif self.attr_color is None:\n            msg = \"Color variable has to be selected\"\n        elif self.attr_color.is_continuous and \\\n                self.placement == Placement.LDA:\n            msg = \"Suggest Features does not work for Linear \" \\\n                  \"Discriminant Analysis Projection when \" \\\n                  \"continuous color variable is selected.\"\n        elif len([v for v in self.continuous_variables\n                  if v is not self.attr_color]) < 3:\n            msg = \"Not enough available continuous variables\"\n        elif np.sum(np.all(np.isfinite(self.data.X), axis=1)) < 2:\n            msg = \"Not enough valid data instances\"\n        else:\n            is_enabled = \\\n                not np.isnan(self.data.get_column(self.attr_color)).all()\n        self.btn_vizrank.setToolTip(msg)\n        self.btn_vizrank.setEnabled(is_enabled)\n        if is_enabled:\n            self.vizrank.initialize()\n\n    def check_data(self):\n        def error(err):\n            err()\n            self.data = None\n\n        super().check_data()\n        if self.data is not None:\n            if not len(self.continuous_variables):\n                error(self.Error.no_cont_features)\n\n    def init_attr_values(self):\n        super().init_attr_values()\n        self.selected_vars[:] = self.continuous_variables[:3]\n        self.model_selected[:] = self.continuous_variables\n\n    def init_projection(self):\n        if self.placement == Placement.Circular:\n            self.projector = CircularPlacement()\n        elif self.placement == Placement.LDA:\n            self.projector = LDA(solver=\"eigen\", n_components=2)\n        elif self.placement == Placement.PCA:\n            self.projector = PCA(n_components=2)\n            self.projector.component = 2\n            self.projector.preprocessors = PCA.preprocessors + [Normalize()]\n\n        super().init_projection()\n\n    def get_coordinates_data(self):\n        def normalized(a):\n            span = np.max(a, axis=0) - np.min(a, axis=0)\n            span[span == 0] = 1\n            return (a - np.mean(a, axis=0)) / span\n\n        embedding = self.get_embedding()\n        if embedding is None:\n            return None, None\n        norm_emb = normalized(embedding[self.valid_data])\n        return (norm_emb.ravel(), np.zeros(len(norm_emb), dtype=float)) \\\n            if embedding.shape[1] == 1 else norm_emb.T\n\n    def _get_send_report_caption(self):\n        def projection_name():\n            return self.Projection_name[self.placement]\n\n        return report.render_items_vert((\n            (\"Projection\", projection_name()),\n            (\"Color\", self._get_caption_var_name(self.attr_color)),\n            (\"Label\", self._get_caption_var_name(self.attr_label)),\n            (\"Shape\", self._get_caption_var_name(self.attr_shape)),\n            (\"Size\", self._get_caption_var_name(self.attr_size)),\n            (\"Jittering\", self.graph.jitter_size != 0 and\n             \"{} %\".format(self.graph.jitter_size))))\n\n    @classmethod\n    def migrate_settings(cls, settings_, version):\n        if version < 2:\n            settings_[\"point_width\"] = settings_[\"point_size\"]\n        if version < 3:\n            settings_graph = {}\n            settings_graph[\"jitter_size\"] = settings_[\"jitter_value\"]\n            settings_graph[\"point_width\"] = settings_[\"point_width\"]\n            settings_graph[\"alpha_value\"] = settings_[\"alpha_value\"]\n            settings_graph[\"class_density\"] = settings_[\"class_density\"]\n            settings_[\"graph\"] = settings_graph\n        if version < 4:\n            if \"radius\" in settings_:\n                settings_[\"graph\"][\"hide_radius\"] = settings_[\"radius\"]\n            if \"selection_indices\" in settings_ and \\\n                    settings_[\"selection_indices\"] is not None:\n                selection = settings_[\"selection_indices\"]\n                settings_[\"selection\"] = [(i, 1) for i, selected in\n                                          enumerate(selection) if selected]\n        if version < 5:\n            if \"placement\" in settings_ and \\\n                    settings_[\"placement\"] not in Placement:\n                settings_[\"placement\"] = Placement.Circular\n\n    @classmethod\n    def migrate_context(cls, context, version):\n        values = context.values\n        if version < 2:\n            domain = context.ordered_domain\n            c_domain = [t for t in context.ordered_domain if t[1] == 2]\n            d_domain = [t for t in context.ordered_domain if t[1] == 1]\n            for d, old_val, new_val in ((domain, \"color_index\", \"attr_color\"),\n                                        (d_domain, \"shape_index\", \"attr_shape\"),\n                                        (c_domain, \"size_index\", \"attr_size\")):\n                index = context.values[old_val][0] - 1\n                values[new_val] = (d[index][0], d[index][1] + 100) \\\n                    if 0 <= index < len(d) else None\n        if version < 3:\n            values[\"graph\"] = {\n                \"attr_color\": values[\"attr_color\"],\n                \"attr_shape\": values[\"attr_shape\"],\n                \"attr_size\": values[\"attr_size\"]\n            }\n        if version == 3:\n            values[\"attr_color\"] = values[\"graph\"][\"attr_color\"]\n            values[\"attr_size\"] = values[\"graph\"][\"attr_size\"]\n            values[\"attr_shape\"] = values[\"graph\"][\"attr_shape\"]\n            values[\"attr_label\"] = values[\"graph\"][\"attr_label\"]\n        if version < 6 and \"selected_vars\" in values:\n            values[\"selected_vars\"] = (values[\"selected_vars\"], -3)\n\n    # for backward compatibility with settings < 6, pull the enum from global\n    # namespace into class\n    Placement = Placement\n\n\ndef column_data(table, var, dtype):\n    dtype = np.dtype(dtype)\n    col = table.get_column(var)\n    if dtype != col.dtype:\n        col = col.astype(dtype)\n    if col.base is not None:\n        col = col.copy()\n    return col\n\n\nclass CircularPlacement(LinearProjector):\n    def get_components(self, X, Y):\n        # Return circular axes for linear projection\n        n_axes = X.shape[1]\n        if n_axes == 1:\n            axes_angle = [0]\n        elif n_axes == 2:\n            axes_angle = [0, np.pi / 2]\n        else:\n            axes_angle = np.linspace(0, 2 * np.pi, n_axes,\n                                     endpoint=False)\n        return np.vstack((np.cos(axes_angle), np.sin(axes_angle)))\n\n\nif __name__ == \"__main__\":  # pragma: no cover\n    iris = Table(\"iris\")\n    WidgetPreview(OWLinearProjection).run(set_data=iris,\n                                          set_subset_data=iris[::10])\n",
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                        "section": "class LinearProjectionVizRank(VizRankDialog, OWComponent):"
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                                "content": "        n_cont_var = len([v for v in master.continuous_variables",
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                                "content": "                          if v is not master.attr_color])",
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                            "name": "LinearProjectionVizRank.check_preconditions",
                            "content": "class LinearProjectionVizRank(VizRankDialog, OWComponent):\n    captionTitle = \"Score Plots\"\n    n_attrs = Setting(3)\n    minK = 10\n\n    attrsSelected = Signal([])\n    _AttrRole = next(gui.OrangeUserRole)\n\n    def __init__(self, master):\n        # Add the spin box for a number of attributes to take into account.\n        VizRankDialog.__init__(self, master)\n        OWComponent.__init__(self, master)\n\n        box = gui.hBox(self)\n        max_n_attrs = len(master.model_selected)\n        self.n_attrs_spin = gui.spin(\n            box, self, \"n_attrs\", 3, max_n_attrs, label=\"Number of variables: \",\n            controlWidth=50, alignment=Qt.AlignRight, callback=self._n_attrs_changed)\n        gui.rubber(box)\n        self.last_run_n_attrs = None\n        self.attr_color = master.attr_color\n        self.attrs = []\n\n    def initialize(self):\n        super().initialize()\n        self.n_attrs_spin.setDisabled(False)\n        self.attr_color = self.master.attr_color\n\n    def before_running(self):\n        \"\"\"\n        Disable the spin for number of attributes before running and\n        enable afterwards. Also, if the number of attributes is different than\n        in the last run, reset the saved state (if it was paused).\n        \"\"\"\n        if self.n_attrs != self.last_run_n_attrs:\n            self.saved_state = None\n            self.saved_progress = 0\n        if self.saved_state is None:\n            self.scores = []\n            self.rank_model.clear()\n        self.last_run_n_attrs = self.n_attrs\n        self.n_attrs_spin.setDisabled(True)\n\n    def stopped(self):\n        self.n_attrs_spin.setDisabled(False)\n\n    def check_preconditions(self):\n        master = self.master\n        if not super().check_preconditions():\n            return False\n        elif not master.btn_vizrank.isEnabled():\n            return False\n        n_cont_var = len([v for v in master.continuous_variables\n                          if v is not master.attr_color])\n        self.n_attrs_spin.setMaximum(n_cont_var)\n        self.n_attrs_spin.setValue(self.n_attrs)\n        return True\n\n    def state_count(self):\n        n_all_attrs = len(self.attrs)\n        if not n_all_attrs:\n            return 0\n        n_attrs = self.n_attrs\n        return factorial(n_all_attrs) // (2 * factorial(n_all_attrs - n_attrs) * n_attrs)\n\n    def iterate_states(self, state):\n        if state is None:  # on the first call, compute order\n            self.attrs = self._score_heuristic()\n            state = list(range(self.n_attrs))\n        else:\n            state = list(state)\n\n        def combinations(n, s):\n            while True:\n                yield s\n                for up, _ in enumerate(s):\n                    s[up] += 1\n                    if up + 1 == len(s) or s[up] < s[up + 1]:\n                        break\n                    s[up] = up\n                if s[-1] == n:\n                    break\n\n        for c in combinations(len(self.attrs), state):\n            for p in islice(permutations(c[1:]), factorial(len(c) - 1) // 2):\n                yield (c[0], ) + p\n\n    def compute_score(self, state):\n        master = self.master\n        data = master.data\n        domain = Domain([self.attrs[i] for i in state], data.domain.class_vars)\n        projection = master.projector(data.transform(domain))\n        ec = projection(data).X\n        y = column_data(data, self.attr_color, dtype=float)\n        if ec.shape[0] < self.minK:\n            return None\n        n_neighbors = min(self.minK, len(ec) - 1)\n        knn = NearestNeighbors(n_neighbors=n_neighbors).fit(ec)\n        ind = knn.kneighbors(return_distance=False)\n        # pylint: disable=invalid-unary-operand-type\n        if self.attr_color.is_discrete:\n            return -np.sum(y[ind] == y.reshape(-1, 1)) / n_neighbors / len(y)\n        return -r2_score(y, np.mean(y[ind], axis=1)) * (len(y) / len(data))\n\n    def bar_length(self, score):\n        return max(0, -score)\n\n    def _score_heuristic(self):\n        def normalized(a):\n            span = np.max(a, axis=0) - np.min(a, axis=0)\n            span[span == 0] = 1\n            return (a - np.mean(a, axis=0)) / span\n\n        domain = self.master.data.domain\n        attr_color = self.master.attr_color\n        domain = Domain(\n            attributes=[v for v in chain(domain.variables, domain.metas)\n                        if v.is_continuous and v is not attr_color],\n            class_vars=attr_color\n        )\n        data = self.master.data.transform(domain).copy()\n        with data.unlocked():\n            data.X = normalized(data.X)\n        relief = ReliefF if attr_color.is_discrete else RReliefF\n        weights = relief(n_iterations=100, k_nearest=self.minK)(data)\n        results = sorted(zip(weights, domain.attributes), key=lambda x: (-x[0], x[1].name))\n        return [attr for _, attr in results]\n\n    def row_for_state(self, score, state):\n        attrs = [self.attrs[i] for i in state]\n        item = QStandardItem(\", \".join(a.name for a in attrs))\n        item.setData(attrs, self._AttrRole)\n        return [item]\n\n    def on_selection_changed(self, selected, deselected):\n        if not selected.indexes():\n            return\n        attrs = selected.indexes()[0].data(self._AttrRole)\n        self.selectionChanged.emit([attrs])\n\n    def _n_attrs_changed(self):\n        if self.n_attrs != self.last_run_n_attrs or self.saved_state is None:\n            self.button.setText(\"Start\")\n        else:\n            self.button.setText(\"Continue\")\n        self.button.setEnabled(self.check_preconditions())",
                            "ast_type_str": "ClassDef",
                            "start_lineno": 87,
                            "end_lineno": 97,
                            "parent": {
                                "file_name": "Orange/widgets/visualize/owlinearprojection.py",
                                "type": "class",
                                "name": "LinearProjectionVizRank",
                                "content": "class LinearProjectionVizRank(VizRankDialog, OWComponent):\n    captionTitle = \"Score Plots\"\n    n_attrs = Setting(3)\n    minK = 10\n\n    attrsSelected = Signal([])\n    _AttrRole = next(gui.OrangeUserRole)\n\n    def __init__(self, master):\n        # Add the spin box for a number of attributes to take into account.\n        VizRankDialog.__init__(self, master)\n        OWComponent.__init__(self, master)\n\n        box = gui.hBox(self)\n        max_n_attrs = len(master.model_selected)\n        self.n_attrs_spin = gui.spin(\n            box, self, \"n_attrs\", 3, max_n_attrs, label=\"Number of variables: \",\n            controlWidth=50, alignment=Qt.AlignRight, callback=self._n_attrs_changed)\n        gui.rubber(box)\n        self.last_run_n_attrs = None\n        self.attr_color = master.attr_color\n        self.attrs = []\n\n    def initialize(self):\n        super().initialize()\n        self.n_attrs_spin.setDisabled(False)\n        self.attr_color = self.master.attr_color\n\n    def before_running(self):\n        \"\"\"\n        Disable the spin for number of attributes before running and\n        enable afterwards. Also, if the number of attributes is different than\n        in the last run, reset the saved state (if it was paused).\n        \"\"\"\n        if self.n_attrs != self.last_run_n_attrs:\n            self.saved_state = None\n            self.saved_progress = 0\n        if self.saved_state is None:\n            self.scores = []\n            self.rank_model.clear()\n        self.last_run_n_attrs = self.n_attrs\n        self.n_attrs_spin.setDisabled(True)\n\n    def stopped(self):\n        self.n_attrs_spin.setDisabled(False)\n\n    def check_preconditions(self):\n        master = self.master\n        if not super().check_preconditions():\n            return False\n        elif not master.btn_vizrank.isEnabled():\n            return False\n        n_cont_var = len([v for v in master.continuous_variables\n                          if v is not master.attr_color])\n        self.n_attrs_spin.setMaximum(n_cont_var)\n        self.n_attrs_spin.setValue(self.n_attrs)\n        return True\n\n    def state_count(self):\n        n_all_attrs = len(self.attrs)\n        if not n_all_attrs:\n            return 0\n        n_attrs = self.n_attrs\n        return factorial(n_all_attrs) // (2 * factorial(n_all_attrs - n_attrs) * n_attrs)\n\n    def iterate_states(self, state):\n        if state is None:  # on the first call, compute order\n            self.attrs = self._score_heuristic()\n            state = list(range(self.n_attrs))\n        else:\n            state = list(state)\n\n        def combinations(n, s):\n            while True:\n                yield s\n                for up, _ in enumerate(s):\n                    s[up] += 1\n                    if up + 1 == len(s) or s[up] < s[up + 1]:\n                        break\n                    s[up] = up\n                if s[-1] == n:\n                    break\n\n        for c in combinations(len(self.attrs), state):\n            for p in islice(permutations(c[1:]), factorial(len(c) - 1) // 2):\n                yield (c[0], ) + p\n\n    def compute_score(self, state):\n        master = self.master\n        data = master.data\n        domain = Domain([self.attrs[i] for i in state], data.domain.class_vars)\n        projection = master.projector(data.transform(domain))\n        ec = projection(data).X\n        y = column_data(data, self.attr_color, dtype=float)\n        if ec.shape[0] < self.minK:\n            return None\n        n_neighbors = min(self.minK, len(ec) - 1)\n        knn = NearestNeighbors(n_neighbors=n_neighbors).fit(ec)\n        ind = knn.kneighbors(return_distance=False)\n        # pylint: disable=invalid-unary-operand-type\n        if self.attr_color.is_discrete:\n            return -np.sum(y[ind] == y.reshape(-1, 1)) / n_neighbors / len(y)\n        return -r2_score(y, np.mean(y[ind], axis=1)) * (len(y) / len(data))\n\n    def bar_length(self, score):\n        return max(0, -score)\n\n    def _score_heuristic(self):\n        def normalized(a):\n            span = np.max(a, axis=0) - np.min(a, axis=0)\n            span[span == 0] = 1\n            return (a - np.mean(a, axis=0)) / span\n\n        domain = self.master.data.domain\n        attr_color = self.master.attr_color\n        domain = Domain(\n            attributes=[v for v in chain(domain.variables, domain.metas)\n                        if v.is_continuous and v is not attr_color],\n            class_vars=attr_color\n        )\n        data = self.master.data.transform(domain).copy()\n        with data.unlocked():\n            data.X = normalized(data.X)\n        relief = ReliefF if attr_color.is_discrete else RReliefF\n        weights = relief(n_iterations=100, k_nearest=self.minK)(data)\n        results = sorted(zip(weights, domain.attributes), key=lambda x: (-x[0], x[1].name))\n        return [attr for _, attr in results]\n\n    def row_for_state(self, score, state):\n        attrs = [self.attrs[i] for i in state]\n        item = QStandardItem(\", \".join(a.name for a in attrs))\n        item.setData(attrs, self._AttrRole)\n        return [item]\n\n    def on_selection_changed(self, selected, deselected):\n        if not selected.indexes():\n            return\n        attrs = selected.indexes()[0].data(self._AttrRole)\n        self.selectionChanged.emit([attrs])\n\n    def _n_attrs_changed(self):\n        if self.n_attrs != self.last_run_n_attrs or self.saved_state is None:\n            self.button.setText(\"Start\")\n        else:\n            self.button.setText(\"Continue\")\n        self.button.setEnabled(self.check_preconditions())",
                                "ast_type_str": "ClassDef",
                                "start_lineno": 41,
                                "end_lineno": 186,
                                "parent": null
                            }
                        },
                        {
                            "file_name": "Orange/widgets/visualize/owlinearprojection.py",
                            "type": "class",
                            "name": "LinearProjectionVizRank",
                            "content": "class LinearProjectionVizRank(VizRankDialog, OWComponent):\n    captionTitle = \"Score Plots\"\n    n_attrs = Setting(3)\n    minK = 10\n\n    attrsSelected = Signal([])\n    _AttrRole = next(gui.OrangeUserRole)\n\n    def __init__(self, master):\n        # Add the spin box for a number of attributes to take into account.\n        VizRankDialog.__init__(self, master)\n        OWComponent.__init__(self, master)\n\n        box = gui.hBox(self)\n        max_n_attrs = len(master.model_selected)\n        self.n_attrs_spin = gui.spin(\n            box, self, \"n_attrs\", 3, max_n_attrs, label=\"Number of variables: \",\n            controlWidth=50, alignment=Qt.AlignRight, callback=self._n_attrs_changed)\n        gui.rubber(box)\n        self.last_run_n_attrs = None\n        self.attr_color = master.attr_color\n        self.attrs = []\n\n    def initialize(self):\n        super().initialize()\n        self.n_attrs_spin.setDisabled(False)\n        self.attr_color = self.master.attr_color\n\n    def before_running(self):\n        \"\"\"\n        Disable the spin for number of attributes before running and\n        enable afterwards. Also, if the number of attributes is different than\n        in the last run, reset the saved state (if it was paused).\n        \"\"\"\n        if self.n_attrs != self.last_run_n_attrs:\n            self.saved_state = None\n            self.saved_progress = 0\n        if self.saved_state is None:\n            self.scores = []\n            self.rank_model.clear()\n        self.last_run_n_attrs = self.n_attrs\n        self.n_attrs_spin.setDisabled(True)\n\n    def stopped(self):\n        self.n_attrs_spin.setDisabled(False)\n\n    def check_preconditions(self):\n        master = self.master\n        if not super().check_preconditions():\n            return False\n        elif not master.btn_vizrank.isEnabled():\n            return False\n        n_cont_var = len([v for v in master.continuous_variables\n                          if v is not master.attr_color])\n        self.n_attrs_spin.setMaximum(n_cont_var)\n        self.n_attrs_spin.setValue(self.n_attrs)\n        return True\n\n    def state_count(self):\n        n_all_attrs = len(self.attrs)\n        if not n_all_attrs:\n            return 0\n        n_attrs = self.n_attrs\n        return factorial(n_all_attrs) // (2 * factorial(n_all_attrs - n_attrs) * n_attrs)\n\n    def iterate_states(self, state):\n        if state is None:  # on the first call, compute order\n            self.attrs = self._score_heuristic()\n            state = list(range(self.n_attrs))\n        else:\n            state = list(state)\n\n        def combinations(n, s):\n            while True:\n                yield s\n                for up, _ in enumerate(s):\n                    s[up] += 1\n                    if up + 1 == len(s) or s[up] < s[up + 1]:\n                        break\n                    s[up] = up\n                if s[-1] == n:\n                    break\n\n        for c in combinations(len(self.attrs), state):\n            for p in islice(permutations(c[1:]), factorial(len(c) - 1) // 2):\n                yield (c[0], ) + p\n\n    def compute_score(self, state):\n        master = self.master\n        data = master.data\n        domain = Domain([self.attrs[i] for i in state], data.domain.class_vars)\n        projection = master.projector(data.transform(domain))\n        ec = projection(data).X\n        y = column_data(data, self.attr_color, dtype=float)\n        if ec.shape[0] < self.minK:\n            return None\n        n_neighbors = min(self.minK, len(ec) - 1)\n        knn = NearestNeighbors(n_neighbors=n_neighbors).fit(ec)\n        ind = knn.kneighbors(return_distance=False)\n        # pylint: disable=invalid-unary-operand-type\n        if self.attr_color.is_discrete:\n            return -np.sum(y[ind] == y.reshape(-1, 1)) / n_neighbors / len(y)\n        return -r2_score(y, np.mean(y[ind], axis=1)) * (len(y) / len(data))\n\n    def bar_length(self, score):\n        return max(0, -score)\n\n    def _score_heuristic(self):\n        def normalized(a):\n            span = np.max(a, axis=0) - np.min(a, axis=0)\n            span[span == 0] = 1\n            return (a - np.mean(a, axis=0)) / span\n\n        domain = self.master.data.domain\n        attr_color = self.master.attr_color\n        domain = Domain(\n            attributes=[v for v in chain(domain.variables, domain.metas)\n                        if v.is_continuous and v is not attr_color],\n            class_vars=attr_color\n        )\n        data = self.master.data.transform(domain).copy()\n        with data.unlocked():\n            data.X = normalized(data.X)\n        relief = ReliefF if attr_color.is_discrete else RReliefF\n        weights = relief(n_iterations=100, k_nearest=self.minK)(data)\n        results = sorted(zip(weights, domain.attributes), key=lambda x: (-x[0], x[1].name))\n        return [attr for _, attr in results]\n\n    def row_for_state(self, score, state):\n        attrs = [self.attrs[i] for i in state]\n        item = QStandardItem(\", \".join(a.name for a in attrs))\n        item.setData(attrs, self._AttrRole)\n        return [item]\n\n    def on_selection_changed(self, selected, deselected):\n        if not selected.indexes():\n            return\n        attrs = selected.indexes()[0].data(self._AttrRole)\n        self.selectionChanged.emit([attrs])\n\n    def _n_attrs_changed(self):\n        if self.n_attrs != self.last_run_n_attrs or self.saved_state is None:\n            self.button.setText(\"Start\")\n        else:\n            self.button.setText(\"Continue\")\n        self.button.setEnabled(self.check_preconditions())",
                            "ast_type_str": "ClassDef",
                            "start_lineno": 41,
                            "end_lineno": 186,
                            "parent": null
                        }
                    ],
                    "added_entities": [],
                    "deleted_entities": []
                }
            ]
        },
        {
            "old_file_content": "# Test methods with long descriptive names can omit docstrings\n# pylint: disable=missing-docstring\nfrom unittest.mock import Mock\nimport numpy as np\n\nfrom AnyQt.QtCore import QItemSelectionModel\n\nfrom Orange.data import Table, Domain, DiscreteVariable, ContinuousVariable\nfrom Orange.widgets.settings import Context\nfrom Orange.widgets.tests.base import (\n    WidgetTest, WidgetOutputsTestMixin, datasets,\n    AnchorProjectionWidgetTestMixin\n)\nfrom Orange.widgets.tests.utils import simulate\nfrom Orange.widgets.visualize.owlinearprojection import (\n    OWLinearProjection, LinearProjectionVizRank, Placement\n)\nfrom Orange.widgets.visualize.utils import run_vizrank\n\n\nclass TestOWLinearProjection(WidgetTest, AnchorProjectionWidgetTestMixin,\n                             WidgetOutputsTestMixin):\n    @classmethod\n    def setUpClass(cls):\n        super().setUpClass()\n        WidgetOutputsTestMixin.init(cls)\n\n        cls.signal_name = OWLinearProjection.Inputs.data\n        cls.signal_data = cls.data\n        cls.same_input_output_domain = False\n\n    def setUp(self):\n        self.widget = self.create_widget(OWLinearProjection)  # type: OWLinearProjection\n\n    def test_nan_plot(self):\n        data = datasets.missing_data_1()\n        self.send_signal(self.widget.Inputs.data, data)\n        simulate.combobox_run_through_all(self.widget.controls.attr_color)\n        simulate.combobox_run_through_all(self.widget.controls.attr_size)\n\n        with data.unlocked():\n            data.X[:, 0] = np.nan\n            data.Y[:] = np.nan\n        self.send_signal(self.widget.Inputs.data, data)\n        self.send_signal(self.widget.Inputs.data_subset, data[2:3])\n        simulate.combobox_run_through_all(self.widget.controls.attr_color)\n        simulate.combobox_run_through_all(self.widget.controls.attr_size)\n\n    def test_buttons(self):\n        for btn in self.widget.radio_placement.buttons[:3]:\n            self.send_signal(self.widget.Inputs.data, self.data)\n            self.assertTrue(btn.isEnabled())\n            btn.click()\n\n    def test_btn_vizrank(self):\n        def check_vizrank(data):\n            self.send_signal(self.widget.Inputs.data, data)\n            if data is not None and data.domain.class_var in \\\n                    self.widget.controls.attr_color.model():\n                self.widget.attr_color = data.domain.class_var\n            if self.widget.btn_vizrank.isEnabled():\n                vizrank = LinearProjectionVizRank(self.widget)\n                states = [state for state in vizrank.iterate_states(None)]\n                self.assertIsNotNone(vizrank.compute_score(states[0]))\n\n        check_vizrank(self.data)\n        check_vizrank(self.data[:, :3])\n        check_vizrank(None)\n        for ds in datasets.datasets():\n            check_vizrank(ds)\n\n    def test_bad_data(self):\n        w = self.widget\n        data = Table(\"iris\")[:20]\n        domain = data.domain\n        domain = Domain(\n            attributes=domain.attributes[:4], class_vars=DiscreteVariable(\"class\", values=(\"a\", )))\n        data = Table.from_numpy(domain=domain, X=data.X, Y=data.Y)\n        self.assertTrue(w.radio_placement.buttons[1].isEnabled())\n        self.send_signal(w.Inputs.data, data)\n        self.assertFalse(w.radio_placement.buttons[1].isEnabled())\n\n    def test_no_data_for_lda(self):\n        buttons = self.widget.radio_placement.buttons\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.radio_placement.buttons[Placement.LDA].click()\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n        output = self.get_output(self.widget.Outputs.components)\n        self.assertTrue(output and len(output) == 2)\n        self.send_signal(self.widget.Inputs.data, Table(\"housing\"))\n        self.assertFalse(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, None)\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n\n    def test_lda_not_enough_distinct(self):\n        buttons = self.widget.radio_placement.buttons\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, self.data[:10])\n        self.assertFalse(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, None)\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, self.data[40:60])\n        self.assertFalse(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, self.data[40:110])\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n\n    def test_data_no_cont_features(self):\n        data = Table(\"titanic\")\n        self.assertFalse(self.widget.Error.no_cont_features.is_shown())\n        self.send_signal(self.widget.Inputs.data, data)\n        self.assertTrue(self.widget.Error.no_cont_features.is_shown())\n        self.send_signal(self.widget.Inputs.data, None)\n        self.assertFalse(self.widget.Error.no_cont_features.is_shown())\n\n    def test_radius(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.radio_placement.buttons[Placement.LDA].click()\n        self.widget.controls.graph.hide_radius.setValue(5)\n\n    def test_invalid_data(self):\n        def assertErrorShown(data, is_shown):\n            self.send_signal(self.widget.Inputs.data, data)\n            self.assertEqual(is_shown, self.widget.Error.no_valid_data.is_shown())\n\n        data = Table(\"iris\")[::30].copy()\n        with data.unlocked():\n            data[:, 0] = np.nan\n        for data, is_shown in zip([None, data, Table(\"iris\")[:30]], [False, True, False]):\n            assertErrorShown(data, is_shown)\n\n    def test_migrate_settings_from_version_1(self):\n        # Settings from Orange 3.4.0\n        settings = {\n            '__version__': 1,\n            'alpha_value': 255,\n            'auto_commit': True,\n            'class_density': False,\n            'context_settings': [\n                Context(attributes={'iris': 1,\n                                    'petal length': 2, 'petal width': 2,\n                                    'sepal length': 2, 'sepal width': 2},\n                        metas={},\n                        ordered_domain=[('sepal length', 2),\n                                        ('sepal width', 2),\n                                        ('petal length', 2),\n                                        ('petal width', 2),\n                                        ('iris', 1)],\n                        time=1504865133.098991,\n                        values={'__version__': 1,\n                                'color_index': (5, -2),\n                                'shape_index': (1, -2),\n                                'size_index': (1, -2),\n                                'variable_state': ({}, -2)})],\n            'jitter_value': 0,\n            'legend_anchor': ((1, 0), (1, 0)),\n            'point_size': 8,\n            'savedWidgetGeometry': None\n        }\n        w = self.create_widget(OWLinearProjection, stored_settings=settings)\n        iris = Table(\"iris\")\n        self.send_signal(w.Inputs.data, iris, widget=w)\n        self.assertEqual(w.graph.point_width, 8)\n        self.assertEqual(w.attr_color, iris.domain[\"iris\"])\n        self.assertEqual(w.attr_shape, iris.domain[\"iris\"])\n        self.assertEqual(w.attr_size, iris.domain[\"sepal length\"])\n\n    def test_set_radius_no_data(self):\n        \"\"\"\n        Widget should not crash when there is no data and radius slider is moved.\n        \"\"\"\n        w = self.widget\n        self.send_signal(w.Inputs.data, None)\n        w.controls.graph.hide_radius.setSliderPosition(3)\n\n    def test_invalidated_model_selected(self):\n        model = self.widget.model_selected\n\n        self.widget.setup_plot = Mock()\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.setup_plot.assert_called_once()\n\n        self.widget.setup_plot.reset_mock()\n        self.widget.selected_vars[:] = self.data.domain[2:3]\n        model.selection_changed.emit()\n        self.widget.setup_plot.assert_called_once()\n\n        self.widget.setup_plot.reset_mock()\n        self.send_signal(self.widget.Inputs.data, self.data[:, 2:])\n        self.widget.setup_plot.assert_not_called()\n\n        self.widget.selected_vars[:] = [self.data.domain[3]]\n        model.selection_changed.emit()\n        self.widget.setup_plot.assert_called_once()\n\n        self.widget.setup_plot.reset_mock()\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.setup_plot.assert_called_once()\n\n    def test_two_classes_dataset(self):\n        self.widget.radio_placement.buttons[1].click()\n        self.send_signal(self.widget.Inputs.data, Table(\"heart_disease\"))\n        self.assertFalse(self.widget.radio_placement.buttons[1].isEnabled())\n\n    def test_unique_name(self):\n        data = Table(\"iris\")\n        new = ContinuousVariable(\"C-y\")\n        d = Table.from_numpy(Domain(list(data.domain.attributes[:3])+[new],\n                                    class_vars=data.domain.class_vars), data.X,\n                             data.Y)\n        self.send_signal(self.widget.Inputs.data, d)\n        output = self.get_output(self.widget.Outputs.annotated_data)\n        metas = [\"C-x (1)\", \"C-y (1)\", \"Selected\"]\n        self.assertEqual([meta.name for meta in output.domain.metas], metas)\n\n\nclass LinProjVizRankTests(WidgetTest):\n    \"\"\"\n    Linear Projection VizRank tests are mostly done without threading.\n    This is because threads created with module coverage are not traced.\n    \"\"\"\n    @classmethod\n    def setUpClass(cls):\n        super().setUpClass()\n        cls.data = Table(\"iris\")\n\n    def setUp(self):\n        self.widget = self.create_widget(OWLinearProjection)\n        self.vizrank = self.widget.vizrank\n\n    def test_discrete_class(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_continuous_class(self):\n        data = Table(\"housing\")[::100]\n        self.send_signal(self.widget.Inputs.data, data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_set_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        prev_selected = self.widget.selected_vars[:]\n        c1 = self.get_output(self.widget.Outputs.components)\n        self.vizrank.toggle()\n        self.process_events(until=lambda: not self.vizrank.keep_running)\n        self.assertEqual(len(self.vizrank.scores), self.vizrank.state_count())\n        self.vizrank.rank_table.selectionModel().select(\n            self.vizrank.rank_model.item(0, 0).index(),\n            QItemSelectionModel.ClearAndSelect\n        )\n        self.assertNotEqual(self.widget.selected_vars, prev_selected)\n        c2 = self.get_output(self.widget.Outputs.components)\n        self.assertNotEqual(c1.domain.attributes, c2.domain.attributes)\n\n\nif __name__ == \"__main__\":\n    import unittest\n    unittest.main()\n",
            "new_file_content": "# Test methods with long descriptive names can omit docstrings\n# pylint: disable=missing-docstring\nfrom unittest.mock import Mock\nimport numpy as np\n\nfrom AnyQt.QtCore import QItemSelectionModel\n\nfrom Orange.data import Table, Domain, DiscreteVariable, ContinuousVariable\nfrom Orange.widgets.settings import Context\nfrom Orange.widgets.tests.base import (\n    WidgetTest, WidgetOutputsTestMixin, datasets,\n    AnchorProjectionWidgetTestMixin\n)\nfrom Orange.widgets.tests.utils import simulate\nfrom Orange.widgets.visualize.owlinearprojection import (\n    OWLinearProjection, LinearProjectionVizRank, Placement\n)\nfrom Orange.widgets.visualize.utils import run_vizrank\n\n\nclass TestOWLinearProjection(WidgetTest, AnchorProjectionWidgetTestMixin,\n                             WidgetOutputsTestMixin):\n    @classmethod\n    def setUpClass(cls):\n        super().setUpClass()\n        WidgetOutputsTestMixin.init(cls)\n\n        cls.signal_name = OWLinearProjection.Inputs.data\n        cls.signal_data = cls.data\n        cls.same_input_output_domain = False\n\n    def setUp(self):\n        self.widget = self.create_widget(OWLinearProjection)  # type: OWLinearProjection\n\n    def test_nan_plot(self):\n        data = datasets.missing_data_1()\n        self.send_signal(self.widget.Inputs.data, data)\n        simulate.combobox_run_through_all(self.widget.controls.attr_color)\n        simulate.combobox_run_through_all(self.widget.controls.attr_size)\n\n        with data.unlocked():\n            data.X[:, 0] = np.nan\n            data.Y[:] = np.nan\n        self.send_signal(self.widget.Inputs.data, data)\n        self.send_signal(self.widget.Inputs.data_subset, data[2:3])\n        simulate.combobox_run_through_all(self.widget.controls.attr_color)\n        simulate.combobox_run_through_all(self.widget.controls.attr_size)\n\n    def test_buttons(self):\n        for btn in self.widget.radio_placement.buttons[:3]:\n            self.send_signal(self.widget.Inputs.data, self.data)\n            self.assertTrue(btn.isEnabled())\n            btn.click()\n\n    def test_btn_vizrank(self):\n        def check_vizrank(data):\n            self.send_signal(self.widget.Inputs.data, data)\n            if data is not None and data.domain.class_var in \\\n                    self.widget.controls.attr_color.model():\n                self.widget.attr_color = data.domain.class_var\n            if self.widget.btn_vizrank.isEnabled():\n                vizrank = LinearProjectionVizRank(self.widget)\n                states = [state for state in vizrank.iterate_states(None)]\n                self.assertIsNotNone(vizrank.compute_score(states[0]))\n\n        check_vizrank(self.data)\n        check_vizrank(self.data[:, :3])\n        check_vizrank(None)\n        for ds in datasets.datasets():\n            check_vizrank(ds)\n\n    def test_bad_data(self):\n        w = self.widget\n        data = Table(\"iris\")[:20]\n        domain = data.domain\n        domain = Domain(\n            attributes=domain.attributes[:4], class_vars=DiscreteVariable(\"class\", values=(\"a\", )))\n        data = Table.from_numpy(domain=domain, X=data.X, Y=data.Y)\n        self.assertTrue(w.radio_placement.buttons[1].isEnabled())\n        self.send_signal(w.Inputs.data, data)\n        self.assertFalse(w.radio_placement.buttons[1].isEnabled())\n\n    def test_no_data_for_lda(self):\n        buttons = self.widget.radio_placement.buttons\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.radio_placement.buttons[Placement.LDA].click()\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n        output = self.get_output(self.widget.Outputs.components)\n        self.assertTrue(output and len(output) == 2)\n        self.send_signal(self.widget.Inputs.data, Table(\"housing\"))\n        self.assertFalse(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, None)\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n\n    def test_lda_not_enough_distinct(self):\n        buttons = self.widget.radio_placement.buttons\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, self.data[:10])\n        self.assertFalse(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, None)\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, self.data[40:60])\n        self.assertFalse(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, self.data[40:110])\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n\n    def test_data_no_cont_features(self):\n        data = Table(\"titanic\")\n        self.assertFalse(self.widget.Error.no_cont_features.is_shown())\n        self.send_signal(self.widget.Inputs.data, data)\n        self.assertTrue(self.widget.Error.no_cont_features.is_shown())\n        self.send_signal(self.widget.Inputs.data, None)\n        self.assertFalse(self.widget.Error.no_cont_features.is_shown())\n\n    def test_radius(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.radio_placement.buttons[Placement.LDA].click()\n        self.widget.controls.graph.hide_radius.setValue(5)\n\n    def test_invalid_data(self):\n        def assertErrorShown(data, is_shown):\n            self.send_signal(self.widget.Inputs.data, data)\n            self.assertEqual(is_shown, self.widget.Error.no_valid_data.is_shown())\n\n        data = Table(\"iris\")[::30].copy()\n        with data.unlocked():\n            data[:, 0] = np.nan\n        for data, is_shown in zip([None, data, Table(\"iris\")[:30]], [False, True, False]):\n            assertErrorShown(data, is_shown)\n\n    def test_migrate_settings_from_version_1(self):\n        # Settings from Orange 3.4.0\n        settings = {\n            '__version__': 1,\n            'alpha_value': 255,\n            'auto_commit': True,\n            'class_density': False,\n            'context_settings': [\n                Context(attributes={'iris': 1,\n                                    'petal length': 2, 'petal width': 2,\n                                    'sepal length': 2, 'sepal width': 2},\n                        metas={},\n                        ordered_domain=[('sepal length', 2),\n                                        ('sepal width', 2),\n                                        ('petal length', 2),\n                                        ('petal width', 2),\n                                        ('iris', 1)],\n                        time=1504865133.098991,\n                        values={'__version__': 1,\n                                'color_index': (5, -2),\n                                'shape_index': (1, -2),\n                                'size_index': (1, -2),\n                                'variable_state': ({}, -2)})],\n            'jitter_value': 0,\n            'legend_anchor': ((1, 0), (1, 0)),\n            'point_size': 8,\n            'savedWidgetGeometry': None\n        }\n        w = self.create_widget(OWLinearProjection, stored_settings=settings)\n        iris = Table(\"iris\")\n        self.send_signal(w.Inputs.data, iris, widget=w)\n        self.assertEqual(w.graph.point_width, 8)\n        self.assertEqual(w.attr_color, iris.domain[\"iris\"])\n        self.assertEqual(w.attr_shape, iris.domain[\"iris\"])\n        self.assertEqual(w.attr_size, iris.domain[\"sepal length\"])\n\n    def test_set_radius_no_data(self):\n        \"\"\"\n        Widget should not crash when there is no data and radius slider is moved.\n        \"\"\"\n        w = self.widget\n        self.send_signal(w.Inputs.data, None)\n        w.controls.graph.hide_radius.setSliderPosition(3)\n\n    def test_invalidated_model_selected(self):\n        model = self.widget.model_selected\n\n        self.widget.setup_plot = Mock()\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.setup_plot.assert_called_once()\n\n        self.widget.setup_plot.reset_mock()\n        self.widget.selected_vars[:] = self.data.domain[2:3]\n        model.selection_changed.emit()\n        self.widget.setup_plot.assert_called_once()\n\n        self.widget.setup_plot.reset_mock()\n        self.send_signal(self.widget.Inputs.data, self.data[:, 2:])\n        self.widget.setup_plot.assert_not_called()\n\n        self.widget.selected_vars[:] = [self.data.domain[3]]\n        model.selection_changed.emit()\n        self.widget.setup_plot.assert_called_once()\n\n        self.widget.setup_plot.reset_mock()\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.setup_plot.assert_called_once()\n\n    def test_two_classes_dataset(self):\n        self.widget.radio_placement.buttons[1].click()\n        self.send_signal(self.widget.Inputs.data, Table(\"heart_disease\"))\n        self.assertFalse(self.widget.radio_placement.buttons[1].isEnabled())\n\n    def test_unique_name(self):\n        data = Table(\"iris\")\n        new = ContinuousVariable(\"C-y\")\n        d = Table.from_numpy(Domain(list(data.domain.attributes[:3])+[new],\n                                    class_vars=data.domain.class_vars), data.X,\n                             data.Y)\n        self.send_signal(self.widget.Inputs.data, d)\n        output = self.get_output(self.widget.Outputs.annotated_data)\n        metas = [\"C-x (1)\", \"C-y (1)\", \"Selected\"]\n        self.assertEqual([meta.name for meta in output.domain.metas], metas)\n\n\nclass LinProjVizRankTests(WidgetTest):\n    \"\"\"\n    Linear Projection VizRank tests are mostly done without threading.\n    This is because threads created with module coverage are not traced.\n    \"\"\"\n    @classmethod\n    def setUpClass(cls):\n        super().setUpClass()\n        cls.data = Table(\"iris\")\n\n    def setUp(self):\n        self.widget = self.create_widget(OWLinearProjection)\n        self.vizrank = self.widget.vizrank\n\n    def test_discrete_class(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_continuous_class(self):\n        data = Table(\"housing\")[::100]\n        self.send_signal(self.widget.Inputs.data, data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_set_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        prev_selected = self.widget.selected_vars[:]\n        c1 = self.get_output(self.widget.Outputs.components)\n        self.vizrank.toggle()\n        self.process_events(until=lambda: not self.vizrank.keep_running)\n        self.assertEqual(len(self.vizrank.scores), self.vizrank.state_count())\n        self.vizrank.rank_table.selectionModel().select(\n            self.vizrank.rank_model.item(0, 0).index(),\n            QItemSelectionModel.ClearAndSelect\n        )\n        self.assertNotEqual(self.widget.selected_vars, prev_selected)\n        c2 = self.get_output(self.widget.Outputs.components)\n        self.assertNotEqual(c1.domain.attributes, c2.domain.attributes)\n\n    def test_vizrank_n_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.vizrank.n_attrs_spin.setValue(4)\n        settings = self.widget.settingsHandler.pack_data(self.widget)\n        widget = self.create_widget(OWLinearProjection,\n                                    stored_settings=settings)\n        self.send_signal(widget.Inputs.data, self.data, widget=widget)\n        self.assertEqual(widget.vizrank.n_attrs_spin.value(),\n                         self.vizrank.n_attrs_spin.value())\n\n\nif __name__ == \"__main__\":\n    import unittest\n    unittest.main()\n",
            "header": {
                "file": {
                    "path": "Orange/widgets/visualize/tests/test_owlinearprojection.py"
                },
                "misc_line": null
            },
            "index_line": {
                "old_commit_hash": "92438d39a",
                "new_commit_hash": "8a9ebd1e3",
                "mode": "100644"
            },
            "is_binary_file": false,
            "binary_line": null,
            "minus_file": {
                "path": "a/Orange/widgets/visualize/tests/test_owlinearprojection.py"
            },
            "plus_file": {
                "path": "b/Orange/widgets/visualize/tests/test_owlinearprojection.py"
            },
            "hunks": [
                {
                    "descriptor": {
                        "old_range": {
                            "start": 256,
                            "length": 6
                        },
                        "new_range": {
                            "start": 256,
                            "length": 16
                        },
                        "section": "class LinProjVizRankTests(WidgetTest):"
                    },
                    "line_group": {
                        "all_lines": [
                            {
                                "content": "        c2 = self.get_output(self.widget.Outputs.components)",
                                "type": "context"
                            },
                            {
                                "content": "        self.assertNotEqual(c1.domain.attributes, c2.domain.attributes)",
                                "type": "context"
                            },
                            {
                                "content": "",
                                "type": "context"
                            },
                            {
                                "content": "    def test_vizrank_n_attrs(self):",
                                "type": "added"
                            },
                            {
                                "content": "        self.send_signal(self.widget.Inputs.data, self.data)",
                                "type": "added"
                            },
                            {
                                "content": "        self.vizrank.n_attrs_spin.setValue(4)",
                                "type": "added"
                            },
                            {
                                "content": "        settings = self.widget.settingsHandler.pack_data(self.widget)",
                                "type": "added"
                            },
                            {
                                "content": "        widget = self.create_widget(OWLinearProjection,",
                                "type": "added"
                            },
                            {
                                "content": "                                    stored_settings=settings)",
                                "type": "added"
                            },
                            {
                                "content": "        self.send_signal(widget.Inputs.data, self.data, widget=widget)",
                                "type": "added"
                            },
                            {
                                "content": "        self.assertEqual(widget.vizrank.n_attrs_spin.value(),",
                                "type": "added"
                            },
                            {
                                "content": "                         self.vizrank.n_attrs_spin.value())",
                                "type": "added"
                            },
                            {
                                "content": "",
                                "type": "added"
                            },
                            {
                                "content": "",
                                "type": "context"
                            },
                            {
                                "content": "if __name__ == \"__main__\":",
                                "type": "context"
                            },
                            {
                                "content": "    import unittest",
                                "type": "context"
                            },
                            {
                                "content": "",
                                "type": "context"
                            }
                        ]
                    },
                    "modified_entities": [
                        {
                            "file_name": "Orange/widgets/visualize/tests/test_owlinearprojection.py",
                            "type": "class",
                            "name": "LinProjVizRankTests",
                            "content": "class LinProjVizRankTests(WidgetTest):\n    \"\"\"\n    Linear Projection VizRank tests are mostly done without threading.\n    This is because threads created with module coverage are not traced.\n    \"\"\"\n    @classmethod\n    def setUpClass(cls):\n        super().setUpClass()\n        cls.data = Table(\"iris\")\n\n    def setUp(self):\n        self.widget = self.create_widget(OWLinearProjection)\n        self.vizrank = self.widget.vizrank\n\n    def test_discrete_class(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_continuous_class(self):\n        data = Table(\"housing\")[::100]\n        self.send_signal(self.widget.Inputs.data, data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_set_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        prev_selected = self.widget.selected_vars[:]\n        c1 = self.get_output(self.widget.Outputs.components)\n        self.vizrank.toggle()\n        self.process_events(until=lambda: not self.vizrank.keep_running)\n        self.assertEqual(len(self.vizrank.scores), self.vizrank.state_count())\n        self.vizrank.rank_table.selectionModel().select(\n            self.vizrank.rank_model.item(0, 0).index(),\n            QItemSelectionModel.ClearAndSelect\n        )\n        self.assertNotEqual(self.widget.selected_vars, prev_selected)\n        c2 = self.get_output(self.widget.Outputs.components)\n        self.assertNotEqual(c1.domain.attributes, c2.domain.attributes)\n\n    def test_vizrank_n_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.vizrank.n_attrs_spin.setValue(4)\n        settings = self.widget.settingsHandler.pack_data(self.widget)\n        widget = self.create_widget(OWLinearProjection,\n                                    stored_settings=settings)\n        self.send_signal(widget.Inputs.data, self.data, widget=widget)\n        self.assertEqual(widget.vizrank.n_attrs_spin.value(),\n                         self.vizrank.n_attrs_spin.value())",
                            "ast_type_str": "ClassDef",
                            "start_lineno": 217,
                            "end_lineno": 267,
                            "parent": null
                        }
                    ],
                    "added_entities": [
                        {
                            "file_name": "Orange/widgets/visualize/tests/test_owlinearprojection.py",
                            "type": "method",
                            "name": "LinProjVizRankTests.test_vizrank_n_attrs",
                            "content": "class LinProjVizRankTests(WidgetTest):\n    \"\"\"\n    Linear Projection VizRank tests are mostly done without threading.\n    This is because threads created with module coverage are not traced.\n    \"\"\"\n    @classmethod\n    def setUpClass(cls):\n        super().setUpClass()\n        cls.data = Table(\"iris\")\n\n    def setUp(self):\n        self.widget = self.create_widget(OWLinearProjection)\n        self.vizrank = self.widget.vizrank\n\n    def test_discrete_class(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_continuous_class(self):\n        data = Table(\"housing\")[::100]\n        self.send_signal(self.widget.Inputs.data, data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_set_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        prev_selected = self.widget.selected_vars[:]\n        c1 = self.get_output(self.widget.Outputs.components)\n        self.vizrank.toggle()\n        self.process_events(until=lambda: not self.vizrank.keep_running)\n        self.assertEqual(len(self.vizrank.scores), self.vizrank.state_count())\n        self.vizrank.rank_table.selectionModel().select(\n            self.vizrank.rank_model.item(0, 0).index(),\n            QItemSelectionModel.ClearAndSelect\n        )\n        self.assertNotEqual(self.widget.selected_vars, prev_selected)\n        c2 = self.get_output(self.widget.Outputs.components)\n        self.assertNotEqual(c1.domain.attributes, c2.domain.attributes)\n\n    def test_vizrank_n_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.vizrank.n_attrs_spin.setValue(4)\n        settings = self.widget.settingsHandler.pack_data(self.widget)\n        widget = self.create_widget(OWLinearProjection,\n                                    stored_settings=settings)\n        self.send_signal(widget.Inputs.data, self.data, widget=widget)\n        self.assertEqual(widget.vizrank.n_attrs_spin.value(),\n                         self.vizrank.n_attrs_spin.value())",
                            "ast_type_str": "ClassDef",
                            "start_lineno": 259,
                            "end_lineno": 267,
                            "parent": {
                                "file_name": "Orange/widgets/visualize/tests/test_owlinearprojection.py",
                                "type": "class",
                                "name": "LinProjVizRankTests",
                                "content": "class LinProjVizRankTests(WidgetTest):\n    \"\"\"\n    Linear Projection VizRank tests are mostly done without threading.\n    This is because threads created with module coverage are not traced.\n    \"\"\"\n    @classmethod\n    def setUpClass(cls):\n        super().setUpClass()\n        cls.data = Table(\"iris\")\n\n    def setUp(self):\n        self.widget = self.create_widget(OWLinearProjection)\n        self.vizrank = self.widget.vizrank\n\n    def test_discrete_class(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_continuous_class(self):\n        data = Table(\"housing\")[::100]\n        self.send_signal(self.widget.Inputs.data, data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_set_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        prev_selected = self.widget.selected_vars[:]\n        c1 = self.get_output(self.widget.Outputs.components)\n        self.vizrank.toggle()\n        self.process_events(until=lambda: not self.vizrank.keep_running)\n        self.assertEqual(len(self.vizrank.scores), self.vizrank.state_count())\n        self.vizrank.rank_table.selectionModel().select(\n            self.vizrank.rank_model.item(0, 0).index(),\n            QItemSelectionModel.ClearAndSelect\n        )\n        self.assertNotEqual(self.widget.selected_vars, prev_selected)\n        c2 = self.get_output(self.widget.Outputs.components)\n        self.assertNotEqual(c1.domain.attributes, c2.domain.attributes)\n\n    def test_vizrank_n_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.vizrank.n_attrs_spin.setValue(4)\n        settings = self.widget.settingsHandler.pack_data(self.widget)\n        widget = self.create_widget(OWLinearProjection,\n                                    stored_settings=settings)\n        self.send_signal(widget.Inputs.data, self.data, widget=widget)\n        self.assertEqual(widget.vizrank.n_attrs_spin.value(),\n                         self.vizrank.n_attrs_spin.value())",
                                "ast_type_str": "ClassDef",
                                "start_lineno": 217,
                                "end_lineno": 267,
                                "parent": null
                            }
                        }
                    ],
                    "deleted_entities": []
                }
            ]
        }
    ],
    "old_commit_hash": "d07762d74208b9cda8e1b263d03133c68158d9b6^",
    "new_commit_hash": "d07762d74208b9cda8e1b263d03133c68158d9b6",
    "commit_message": "Merge pull request #6593 from VesnaT/lin_proj_vizrank_n_attrs\n\nLinear Projection: Update vizrank Number of variables",
    "commit_date": "2023-10-06T10:55:33+02:00",
    "metadata": {}
}
{
    "repo_name": "orange3",
    "new_commit_hash": "d07762d74208b9cda8e1b263d03133c68158d9b6",
    "test_file_codes": [
        "# Test methods with long descriptive names can omit docstrings\n# pylint: disable=missing-docstring\nfrom unittest.mock import Mock\nimport numpy as np\n\nfrom AnyQt.QtCore import QItemSelectionModel\n\nfrom Orange.data import Table, Domain, DiscreteVariable, ContinuousVariable\nfrom Orange.widgets.settings import Context\nfrom Orange.widgets.tests.base import (\n    WidgetTest, WidgetOutputsTestMixin, datasets,\n    AnchorProjectionWidgetTestMixin\n)\nfrom Orange.widgets.tests.utils import simulate\nfrom Orange.widgets.visualize.owlinearprojection import (\n    OWLinearProjection, LinearProjectionVizRank, Placement\n)\nfrom Orange.widgets.visualize.utils import run_vizrank\n\n\nclass TestOWLinearProjection(WidgetTest, AnchorProjectionWidgetTestMixin,\n                             WidgetOutputsTestMixin):\n    @classmethod\n    def setUpClass(cls):\n        super().setUpClass()\n        WidgetOutputsTestMixin.init(cls)\n\n        cls.signal_name = OWLinearProjection.Inputs.data\n        cls.signal_data = cls.data\n        cls.same_input_output_domain = False\n\n    def setUp(self):\n        self.widget = self.create_widget(OWLinearProjection)  # type: OWLinearProjection\n\n    def test_nan_plot(self):\n        data = datasets.missing_data_1()\n        self.send_signal(self.widget.Inputs.data, data)\n        simulate.combobox_run_through_all(self.widget.controls.attr_color)\n        simulate.combobox_run_through_all(self.widget.controls.attr_size)\n\n        with data.unlocked():\n            data.X[:, 0] = np.nan\n            data.Y[:] = np.nan\n        self.send_signal(self.widget.Inputs.data, data)\n        self.send_signal(self.widget.Inputs.data_subset, data[2:3])\n        simulate.combobox_run_through_all(self.widget.controls.attr_color)\n        simulate.combobox_run_through_all(self.widget.controls.attr_size)\n\n    def test_buttons(self):\n        for btn in self.widget.radio_placement.buttons[:3]:\n            self.send_signal(self.widget.Inputs.data, self.data)\n            self.assertTrue(btn.isEnabled())\n            btn.click()\n\n    def test_btn_vizrank(self):\n        def check_vizrank(data):\n            self.send_signal(self.widget.Inputs.data, data)\n            if data is not None and data.domain.class_var in \\\n                    self.widget.controls.attr_color.model():\n                self.widget.attr_color = data.domain.class_var\n            if self.widget.btn_vizrank.isEnabled():\n                vizrank = LinearProjectionVizRank(self.widget)\n                states = [state for state in vizrank.iterate_states(None)]\n                self.assertIsNotNone(vizrank.compute_score(states[0]))\n\n        check_vizrank(self.data)\n        check_vizrank(self.data[:, :3])\n        check_vizrank(None)\n        for ds in datasets.datasets():\n            check_vizrank(ds)\n\n    def test_bad_data(self):\n        w = self.widget\n        data = Table(\"iris\")[:20]\n        domain = data.domain\n        domain = Domain(\n            attributes=domain.attributes[:4], class_vars=DiscreteVariable(\"class\", values=(\"a\", )))\n        data = Table.from_numpy(domain=domain, X=data.X, Y=data.Y)\n        self.assertTrue(w.radio_placement.buttons[1].isEnabled())\n        self.send_signal(w.Inputs.data, data)\n        self.assertFalse(w.radio_placement.buttons[1].isEnabled())\n\n    def test_no_data_for_lda(self):\n        buttons = self.widget.radio_placement.buttons\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.radio_placement.buttons[Placement.LDA].click()\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n        output = self.get_output(self.widget.Outputs.components)\n        self.assertTrue(output and len(output) == 2)\n        self.send_signal(self.widget.Inputs.data, Table(\"housing\"))\n        self.assertFalse(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, None)\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n\n    def test_lda_not_enough_distinct(self):\n        buttons = self.widget.radio_placement.buttons\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, self.data[:10])\n        self.assertFalse(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, None)\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, self.data[40:60])\n        self.assertFalse(buttons[Placement.LDA].isEnabled())\n        self.send_signal(self.widget.Inputs.data, self.data[40:110])\n        self.assertTrue(buttons[Placement.LDA].isEnabled())\n\n    def test_data_no_cont_features(self):\n        data = Table(\"titanic\")\n        self.assertFalse(self.widget.Error.no_cont_features.is_shown())\n        self.send_signal(self.widget.Inputs.data, data)\n        self.assertTrue(self.widget.Error.no_cont_features.is_shown())\n        self.send_signal(self.widget.Inputs.data, None)\n        self.assertFalse(self.widget.Error.no_cont_features.is_shown())\n\n    def test_radius(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.radio_placement.buttons[Placement.LDA].click()\n        self.widget.controls.graph.hide_radius.setValue(5)\n\n    def test_invalid_data(self):\n        def assertErrorShown(data, is_shown):\n            self.send_signal(self.widget.Inputs.data, data)\n            self.assertEqual(is_shown, self.widget.Error.no_valid_data.is_shown())\n\n        data = Table(\"iris\")[::30].copy()\n        with data.unlocked():\n            data[:, 0] = np.nan\n        for data, is_shown in zip([None, data, Table(\"iris\")[:30]], [False, True, False]):\n            assertErrorShown(data, is_shown)\n\n    def test_migrate_settings_from_version_1(self):\n        # Settings from Orange 3.4.0\n        settings = {\n            '__version__': 1,\n            'alpha_value': 255,\n            'auto_commit': True,\n            'class_density': False,\n            'context_settings': [\n                Context(attributes={'iris': 1,\n                                    'petal length': 2, 'petal width': 2,\n                                    'sepal length': 2, 'sepal width': 2},\n                        metas={},\n                        ordered_domain=[('sepal length', 2),\n                                        ('sepal width', 2),\n                                        ('petal length', 2),\n                                        ('petal width', 2),\n                                        ('iris', 1)],\n                        time=1504865133.098991,\n                        values={'__version__': 1,\n                                'color_index': (5, -2),\n                                'shape_index': (1, -2),\n                                'size_index': (1, -2),\n                                'variable_state': ({}, -2)})],\n            'jitter_value': 0,\n            'legend_anchor': ((1, 0), (1, 0)),\n            'point_size': 8,\n            'savedWidgetGeometry': None\n        }\n        w = self.create_widget(OWLinearProjection, stored_settings=settings)\n        iris = Table(\"iris\")\n        self.send_signal(w.Inputs.data, iris, widget=w)\n        self.assertEqual(w.graph.point_width, 8)\n        self.assertEqual(w.attr_color, iris.domain[\"iris\"])\n        self.assertEqual(w.attr_shape, iris.domain[\"iris\"])\n        self.assertEqual(w.attr_size, iris.domain[\"sepal length\"])\n\n    def test_set_radius_no_data(self):\n        \"\"\"\n        Widget should not crash when there is no data and radius slider is moved.\n        \"\"\"\n        w = self.widget\n        self.send_signal(w.Inputs.data, None)\n        w.controls.graph.hide_radius.setSliderPosition(3)\n\n    def test_invalidated_model_selected(self):\n        model = self.widget.model_selected\n\n        self.widget.setup_plot = Mock()\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.setup_plot.assert_called_once()\n\n        self.widget.setup_plot.reset_mock()\n        self.widget.selected_vars[:] = self.data.domain[2:3]\n        model.selection_changed.emit()\n        self.widget.setup_plot.assert_called_once()\n\n        self.widget.setup_plot.reset_mock()\n        self.send_signal(self.widget.Inputs.data, self.data[:, 2:])\n        self.widget.setup_plot.assert_not_called()\n\n        self.widget.selected_vars[:] = [self.data.domain[3]]\n        model.selection_changed.emit()\n        self.widget.setup_plot.assert_called_once()\n\n        self.widget.setup_plot.reset_mock()\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.widget.setup_plot.assert_called_once()\n\n    def test_two_classes_dataset(self):\n        self.widget.radio_placement.buttons[1].click()\n        self.send_signal(self.widget.Inputs.data, Table(\"heart_disease\"))\n        self.assertFalse(self.widget.radio_placement.buttons[1].isEnabled())\n\n    def test_unique_name(self):\n        data = Table(\"iris\")\n        new = ContinuousVariable(\"C-y\")\n        d = Table.from_numpy(Domain(list(data.domain.attributes[:3])+[new],\n                                    class_vars=data.domain.class_vars), data.X,\n                             data.Y)\n        self.send_signal(self.widget.Inputs.data, d)\n        output = self.get_output(self.widget.Outputs.annotated_data)\n        metas = [\"C-x (1)\", \"C-y (1)\", \"Selected\"]\n        self.assertEqual([meta.name for meta in output.domain.metas], metas)\n\n\nclass LinProjVizRankTests(WidgetTest):\n    \"\"\"\n    Linear Projection VizRank tests are mostly done without threading.\n    This is because threads created with module coverage are not traced.\n    \"\"\"\n    @classmethod\n    def setUpClass(cls):\n        super().setUpClass()\n        cls.data = Table(\"iris\")\n\n    def setUp(self):\n        self.widget = self.create_widget(OWLinearProjection)\n        self.vizrank = self.widget.vizrank\n\n    def test_discrete_class(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_continuous_class(self):\n        data = Table(\"housing\")[::100]\n        self.send_signal(self.widget.Inputs.data, data)\n        run_vizrank(self.vizrank.compute_score,\n                    self.vizrank.iterate_states, None,\n                    [], 0, self.vizrank.state_count(), Mock())\n\n    def test_set_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        prev_selected = self.widget.selected_vars[:]\n        c1 = self.get_output(self.widget.Outputs.components)\n        self.vizrank.toggle()\n        self.process_events(until=lambda: not self.vizrank.keep_running)\n        self.assertEqual(len(self.vizrank.scores), self.vizrank.state_count())\n        self.vizrank.rank_table.selectionModel().select(\n            self.vizrank.rank_model.item(0, 0).index(),\n            QItemSelectionModel.ClearAndSelect\n        )\n        self.assertNotEqual(self.widget.selected_vars, prev_selected)\n        c2 = self.get_output(self.widget.Outputs.components)\n        self.assertNotEqual(c1.domain.attributes, c2.domain.attributes)\n\n    def test_vizrank_n_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.vizrank.n_attrs_spin.setValue(4)\n        settings = self.widget.settingsHandler.pack_data(self.widget)\n        widget = self.create_widget(OWLinearProjection,\n                                    stored_settings=settings)\n        self.send_signal(widget.Inputs.data, self.data, widget=widget)\n        self.assertEqual(widget.vizrank.n_attrs_spin.value(),\n                         self.vizrank.n_attrs_spin.value())\n\n\nif __name__ == \"__main__\":\n    import unittest\n    unittest.main()\n"
    ],
    "test_file_names": [
        "test_1.py"
    ],
    "setup_res_code": 0,
    "setup_res_stdout": "Starting Orange installation attempts...\nAttempting installation with Python 3.7...\nCompiling Orange/classification/_tree_scorers.pyx because it changed.\nCompiling Orange/data/_contingency.pyx because it changed.\nCompiling Orange/data/_io.pyx because it changed.\nCompiling Orange/data/_valuecount.pyx because it changed.\nCompiling Orange/data/_variable.pyx because it changed.\nCompiling Orange/distance/_distance.pyx because it changed.\nCompiling Orange/preprocess/_discretize.pyx because it changed.\nCompiling Orange/preprocess/_relieff.pyx because it changed.\nCompiling Orange/projection/_som.pyx because it changed.\n[1/9] Cythonizing Orange/classification/_tree_scorers.pyx\n[2/9] Cythonizing Orange/data/_contingency.pyx\n[3/9] Cythonizing Orange/data/_io.pyx\n[4/9] Cythonizing Orange/data/_valuecount.pyx\n[5/9] Cythonizing Orange/data/_variable.pyx\n[6/9] Cythonizing Orange/distance/_distance.pyx\n[7/9] Cythonizing Orange/preprocess/_discretize.pyx\n[8/9] Cythonizing Orange/preprocess/_relieff.pyx\n[9/9] Cythonizing Orange/projection/_som.pyx\nrunning build_ext\nbuilding 'Orange.classification._simple_tree' extension\ncreating build\ncreating build/temp.linux-x86_64-3.7\ncreating build/temp.linux-x86_64-3.7/Orange\ncreating build/temp.linux-x86_64-3.7/Orange/classification\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/classification/_simple_tree.c -o build/temp.linux-x86_64-3.7/Orange/classification/_simple_tree.o\ncreating build/lib.linux-x86_64-3.7\ncreating build/lib.linux-x86_64-3.7/Orange\ncreating build/lib.linux-x86_64-3.7/Orange/classification\ncc -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/classification/_simple_tree.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/classification/_simple_tree.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.widgets.utils._grid_density' extension\ncreating build/temp.linux-x86_64-3.7/Orange/widgets\ncreating build/temp.linux-x86_64-3.7/Orange/widgets/utils\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/widgets/utils/_grid_density.cpp -o build/temp.linux-x86_64-3.7/Orange/widgets/utils/_grid_density.o\ncreating build/lib.linux-x86_64-3.7/Orange/widgets\ncreating build/lib.linux-x86_64-3.7/Orange/widgets/utils\nc++ -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/widgets/utils/_grid_density.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/widgets/utils/_grid_density.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.classification._tree_scorers' extension\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/classification/_tree_scorers.c -o build/temp.linux-x86_64-3.7/Orange/classification/_tree_scorers.o\ncc -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/classification/_tree_scorers.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/classification/_tree_scorers.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.data._contingency' extension\ncreating build/temp.linux-x86_64-3.7/Orange/data\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/data/_contingency.c -o build/temp.linux-x86_64-3.7/Orange/data/_contingency.o\ncreating build/lib.linux-x86_64-3.7/Orange/data\ncc -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/data/_contingency.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/data/_contingency.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.data._io' extension\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/data/_io.c -o build/temp.linux-x86_64-3.7/Orange/data/_io.o\ncc -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/data/_io.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/data/_io.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.data._valuecount' extension\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/data/_valuecount.c -o build/temp.linux-x86_64-3.7/Orange/data/_valuecount.o\ncc -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/data/_valuecount.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/data/_valuecount.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.data._variable' extension\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/data/_variable.c -o build/temp.linux-x86_64-3.7/Orange/data/_variable.o\ncc -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/data/_variable.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/data/_variable.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.distance._distance' extension\ncreating build/temp.linux-x86_64-3.7/Orange/distance\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/distance/_distance.c -o build/temp.linux-x86_64-3.7/Orange/distance/_distance.o\ncreating build/lib.linux-x86_64-3.7/Orange/distance\ncc -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/distance/_distance.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/distance/_distance.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.preprocess._discretize' extension\ncreating build/temp.linux-x86_64-3.7/Orange/preprocess\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/preprocess/_discretize.c -o build/temp.linux-x86_64-3.7/Orange/preprocess/_discretize.o\ncreating build/lib.linux-x86_64-3.7/Orange/preprocess\ncc -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/preprocess/_discretize.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/preprocess/_discretize.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.preprocess._relieff' extension\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/preprocess/_relieff.cpp -o build/temp.linux-x86_64-3.7/Orange/preprocess/_relieff.o\nc++ -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/preprocess/_relieff.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/preprocess/_relieff.cpython-37m-x86_64-linux-gnu.so\nbuilding 'Orange.projection._som' extension\ncreating build/temp.linux-x86_64-3.7/Orange/projection\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tools/deps/include -I/tools/deps/include/ncursesw -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/include/python3.7m -c Orange/projection/_som.c -o build/temp.linux-x86_64-3.7/Orange/projection/_som.o\ncreating build/lib.linux-x86_64-3.7/Orange/projection\ncc -pthread -shared -L/tools/deps/lib build/temp.linux-x86_64-3.7/Orange/projection/_som.o -L/home/gcpuser/.local/share/uv/python/cpython-3.7.9-linux-x86_64-gnu/lib -lm -lpython3.7m -o build/lib.linux-x86_64-3.7/Orange/projection/_som.cpython-37m-x86_64-linux-gnu.so\ncopying build/lib.linux-x86_64-3.7/Orange/classification/_simple_tree.cpython-37m-x86_64-linux-gnu.so -> Orange/classification\ncopying build/lib.linux-x86_64-3.7/Orange/widgets/utils/_grid_density.cpython-37m-x86_64-linux-gnu.so -> Orange/widgets/utils\ncopying build/lib.linux-x86_64-3.7/Orange/classification/_tree_scorers.cpython-37m-x86_64-linux-gnu.so -> Orange/classification\ncopying build/lib.linux-x86_64-3.7/Orange/data/_contingency.cpython-37m-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-3.7/Orange/data/_io.cpython-37m-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-3.7/Orange/data/_valuecount.cpython-37m-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-3.7/Orange/data/_variable.cpython-37m-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-3.7/Orange/distance/_distance.cpython-37m-x86_64-linux-gnu.so -> Orange/distance\ncopying build/lib.linux-x86_64-3.7/Orange/preprocess/_discretize.cpython-37m-x86_64-linux-gnu.so -> Orange/preprocess\ncopying build/lib.linux-x86_64-3.7/Orange/preprocess/_relieff.cpython-37m-x86_64-linux-gnu.so -> Orange/preprocess\ncopying build/lib.linux-x86_64-3.7/Orange/projection/_som.cpython-37m-x86_64-linux-gnu.so -> Orange/projection\nrunning develop\nrunning egg_info\ncreating Orange3.egg-info\nwriting Orange3.egg-info/PKG-INFO\nwriting dependency_links to Orange3.egg-info/dependency_links.txt\nwriting entry points to Orange3.egg-info/entry_points.txt\nwriting requirements to Orange3.egg-info/requires.txt\nwriting top-level names to Orange3.egg-info/top_level.txt\nwriting manifest file 'Orange3.egg-info/SOURCES.txt'\nreading manifest file 'Orange3.egg-info/SOURCES.txt'\nreading manifest template 'MANIFEST.in'\nadding license file 'LICENSE'\nwriting manifest file 'Orange3.egg-info/SOURCES.txt'\nrunning build_ext\ncopying build/lib.linux-x86_64-3.7/Orange/classification/_simple_tree.cpython-37m-x86_64-linux-gnu.so -> Orange/classification\ncopying build/lib.linux-x86_64-3.7/Orange/widgets/utils/_grid_density.cpython-37m-x86_64-linux-gnu.so -> Orange/widgets/utils\ncopying build/lib.linux-x86_64-3.7/Orange/classification/_tree_scorers.cpython-37m-x86_64-linux-gnu.so -> Orange/classification\ncopying build/lib.linux-x86_64-3.7/Orange/data/_contingency.cpython-37m-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-3.7/Orange/data/_io.cpython-37m-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-3.7/Orange/data/_valuecount.cpython-37m-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-3.7/Orange/data/_variable.cpython-37m-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-3.7/Orange/distance/_distance.cpython-37m-x86_64-linux-gnu.so -> Orange/distance\ncopying build/lib.linux-x86_64-3.7/Orange/preprocess/_discretize.cpython-37m-x86_64-linux-gnu.so -> Orange/preprocess\ncopying build/lib.linux-x86_64-3.7/Orange/preprocess/_relieff.cpython-37m-x86_64-linux-gnu.so -> Orange/preprocess\ncopying build/lib.linux-x86_64-3.7/Orange/projection/_som.cpython-37m-x86_64-linux-gnu.so -> Orange/projection\nCreating /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/Orange3.egg-link (link to .)\nAdding Orange3 3.37.0.dev0+d07762d to easy-install.pth file\nInstalling orange-canvas script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nInstalled /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6\nProcessing dependencies for Orange3==3.37.0.dev0+d07762d\nSearching for xlsxwriter\nReading https://pypi.org/simple/xlsxwriter/\nDownloading https://files.pythonhosted.org/packages/a7/ea/53d1fe468e63e092cf16e2c18d16f50c29851242f9dd12d6a66e0d7f0d02/XlsxWriter-3.2.0-py3-none-any.whl#sha256=ecfd5405b3e0e228219bcaf24c2ca0915e012ca9464a14048021d21a995d490e\nBest match: XlsxWriter 3.2.0\nProcessing XlsxWriter-3.2.0-py3-none-any.whl\nInstalling XlsxWriter-3.2.0-py3-none-any.whl to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages\nAdding XlsxWriter 3.2.0 to easy-install.pth file\nInstalling vba_extract.py script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nInstalled /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/XlsxWriter-3.2.0-py3.7.egg\nSearching for xlrd>=1.2.0\nReading https://pypi.org/simple/xlrd/\nDownloading https://files.pythonhosted.org/packages/a6/0c/c2a72d51fe56e08a08acc85d13013558a2d793028ae7385448a6ccdfae64/xlrd-2.0.1-py2.py3-none-any.whl#sha256=6a33ee89877bd9abc1158129f6e94be74e2679636b8a205b43b85206c3f0bbdd\nBest match: xlrd 2.0.1\nProcessing xlrd-2.0.1-py2.py3-none-any.whl\nInstalling xlrd-2.0.1-py2.py3-none-any.whl to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages\nAdding xlrd 2.0.1 to easy-install.pth file\nInstalling runxlrd.py script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nInstalled /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/xlrd-2.0.1-py3.7.egg\nSearching for xgboost>=1.7.4\nReading https://pypi.org/simple/xgboost/\nDownloading https://files.pythonhosted.org/packages/48/bc/05d7db90d421c5e3d681a12fd1eb087e37bf2e9bbe2b105422d6319ecc92/xgboost-2.1.3-py3-none-manylinux2014_x86_64.whl#sha256=32a43526208fe676527c698cb852e0e9515e6d7294143780e476d335290a131b\nBest match: xgboost 2.1.3\nProcessing xgboost-2.1.3-py3-none-manylinux2014_x86_64.whl\nInstalling xgboost-2.1.3-py3-none-manylinux2014_x86_64.whl to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages\nAdding xgboost 2.1.3 to easy-install.pth file\n\nInstalled /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/xgboost-2.1.3-py3.7-linux-x86_64.egg\nSearching for serverfiles\nReading https://pypi.org/simple/serverfiles/\nDownloading https://files.pythonhosted.org/packages/33/36/794fe1c4ed29b0f56a26d72e956baf0285d8fe9e29faf36797a28a8ad45b/serverfiles-0.3.1.tar.gz#sha256=5e10fc32e758791e3735bc08bce2ed4702a83b1e45ab96c5d59cc8aeecfbebe1\nBest match: serverfiles 0.3.1\nProcessing serverfiles-0.3.1.tar.gz\nWriting /tmp/easy_install-1cy8e60a/serverfiles-0.3.1/setup.cfg\nRunning serverfiles-0.3.1/setup.py -q bdist_egg --dist-dir /tmp/easy_install-1cy8e60a/serverfiles-0.3.1/egg-dist-tmp-2kl_3qlg\ncreating /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/serverfiles-0.3.1-py3.7.egg\nExtracting serverfiles-0.3.1-py3.7.egg to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages\nAdding serverfiles 0.3.1 to easy-install.pth file\n\nInstalled /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/serverfiles-0.3.1-py3.7.egg\nSearching for scipy>=1.9\nReading https://pypi.org/simple/scipy/\nDownloading https://files.pythonhosted.org/packages/d9/7b/2b8ac283cf32465ed08bc20a83d559fe7b174a484781702ba8accea001d6/scipy-1.15.0.tar.gz#sha256=300742e2cc94e36a2880ebe464a1c8b4352a7b0f3e36ec3d2ac006cdbe0219ac\nBest match: scipy 1.15.0\nProcessing scipy-1.15.0.tar.gz\nVerifying Orange installation...\n❌ Orange verification failed\nPython 3.7 installation failed, trying Python 3.8...\nAttempting installation with Python 3.8...\nrunning build_ext\nbuilding 'Orange.classification._simple_tree' extension\ncreating build/temp.linux-x86_64-cpython-38/Orange/classification\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/classification/_simple_tree.c -o build/temp.linux-x86_64-cpython-38/Orange/classification/_simple_tree.o\ncreating build/lib.linux-x86_64-cpython-38/Orange/classification\ncc -pthread -shared -Wl,--exclude-libs,ALL build/temp.linux-x86_64-cpython-38/Orange/classification/_simple_tree.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/classification/_simple_tree.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.widgets.utils._grid_density' extension\ncreating build/temp.linux-x86_64-cpython-38/Orange/widgets/utils\nc++ -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/widgets/utils/_grid_density.cpp -o build/temp.linux-x86_64-cpython-38/Orange/widgets/utils/_grid_density.o\ncreating build/lib.linux-x86_64-cpython-38/Orange/widgets/utils\nc++ -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -pthread -shared build/temp.linux-x86_64-cpython-38/Orange/widgets/utils/_grid_density.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/widgets/utils/_grid_density.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.classification._tree_scorers' extension\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/classification/_tree_scorers.c -o build/temp.linux-x86_64-cpython-38/Orange/classification/_tree_scorers.o\ncc -pthread -shared -Wl,--exclude-libs,ALL build/temp.linux-x86_64-cpython-38/Orange/classification/_tree_scorers.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/classification/_tree_scorers.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.data._contingency' extension\ncreating build/temp.linux-x86_64-cpython-38/Orange/data\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/data/_contingency.c -o build/temp.linux-x86_64-cpython-38/Orange/data/_contingency.o\ncreating build/lib.linux-x86_64-cpython-38/Orange/data\ncc -pthread -shared -Wl,--exclude-libs,ALL build/temp.linux-x86_64-cpython-38/Orange/data/_contingency.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/data/_contingency.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.data._io' extension\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/data/_io.c -o build/temp.linux-x86_64-cpython-38/Orange/data/_io.o\ncc -pthread -shared -Wl,--exclude-libs,ALL build/temp.linux-x86_64-cpython-38/Orange/data/_io.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/data/_io.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.data._valuecount' extension\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/data/_valuecount.c -o build/temp.linux-x86_64-cpython-38/Orange/data/_valuecount.o\ncc -pthread -shared -Wl,--exclude-libs,ALL build/temp.linux-x86_64-cpython-38/Orange/data/_valuecount.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/data/_valuecount.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.data._variable' extension\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/data/_variable.c -o build/temp.linux-x86_64-cpython-38/Orange/data/_variable.o\ncc -pthread -shared -Wl,--exclude-libs,ALL build/temp.linux-x86_64-cpython-38/Orange/data/_variable.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/data/_variable.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.distance._distance' extension\ncreating build/temp.linux-x86_64-cpython-38/Orange/distance\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/distance/_distance.c -o build/temp.linux-x86_64-cpython-38/Orange/distance/_distance.o\ncreating build/lib.linux-x86_64-cpython-38/Orange/distance\ncc -pthread -shared -Wl,--exclude-libs,ALL build/temp.linux-x86_64-cpython-38/Orange/distance/_distance.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/distance/_distance.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.preprocess._discretize' extension\ncreating build/temp.linux-x86_64-cpython-38/Orange/preprocess\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/preprocess/_discretize.c -o build/temp.linux-x86_64-cpython-38/Orange/preprocess/_discretize.o\ncreating build/lib.linux-x86_64-cpython-38/Orange/preprocess\ncc -pthread -shared -Wl,--exclude-libs,ALL build/temp.linux-x86_64-cpython-38/Orange/preprocess/_discretize.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/preprocess/_discretize.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.preprocess._relieff' extension\nc++ -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/preprocess/_relieff.cpp -o build/temp.linux-x86_64-cpython-38/Orange/preprocess/_relieff.o\nc++ -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -pthread -shared build/temp.linux-x86_64-cpython-38/Orange/preprocess/_relieff.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/preprocess/_relieff.cpython-38-x86_64-linux-gnu.so\nbuilding 'Orange.projection._som' extension\ncreating build/temp.linux-x86_64-cpython-38/Orange/projection\ncc -pthread -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -fPIC -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include -I/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/include -I/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/include/python3.8 -c Orange/projection/_som.c -o build/temp.linux-x86_64-cpython-38/Orange/projection/_som.o\ncreating build/lib.linux-x86_64-cpython-38/Orange/projection\ncc -pthread -shared -Wl,--exclude-libs,ALL build/temp.linux-x86_64-cpython-38/Orange/projection/_som.o -L/home/gcpuser/.local/share/uv/python/cpython-3.8.20-linux-x86_64-gnu/lib -lm -o build/lib.linux-x86_64-cpython-38/Orange/projection/_som.cpython-38-x86_64-linux-gnu.so\ncopying build/lib.linux-x86_64-cpython-38/Orange/classification/_simple_tree.cpython-38-x86_64-linux-gnu.so -> Orange/classification\ncopying build/lib.linux-x86_64-cpython-38/Orange/widgets/utils/_grid_density.cpython-38-x86_64-linux-gnu.so -> Orange/widgets/utils\ncopying build/lib.linux-x86_64-cpython-38/Orange/classification/_tree_scorers.cpython-38-x86_64-linux-gnu.so -> Orange/classification\ncopying build/lib.linux-x86_64-cpython-38/Orange/data/_contingency.cpython-38-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-cpython-38/Orange/data/_io.cpython-38-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-cpython-38/Orange/data/_valuecount.cpython-38-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-cpython-38/Orange/data/_variable.cpython-38-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-cpython-38/Orange/distance/_distance.cpython-38-x86_64-linux-gnu.so -> Orange/distance\ncopying build/lib.linux-x86_64-cpython-38/Orange/preprocess/_discretize.cpython-38-x86_64-linux-gnu.so -> Orange/preprocess\ncopying build/lib.linux-x86_64-cpython-38/Orange/preprocess/_relieff.cpython-38-x86_64-linux-gnu.so -> Orange/preprocess\ncopying build/lib.linux-x86_64-cpython-38/Orange/projection/_som.cpython-38-x86_64-linux-gnu.so -> Orange/projection\nrunning develop\nrunning egg_info\nwriting Orange3.egg-info/PKG-INFO\nwriting dependency_links to Orange3.egg-info/dependency_links.txt\nwriting entry points to Orange3.egg-info/entry_points.txt\nwriting requirements to Orange3.egg-info/requires.txt\nwriting top-level names to Orange3.egg-info/top_level.txt\ndependency 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/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative\ndependency /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative\nreading manifest file 'Orange3.egg-info/SOURCES.txt'\nreading manifest template 'MANIFEST.in'\nadding license file 'LICENSE'\nwriting manifest file 'Orange3.egg-info/SOURCES.txt'\nrunning build_ext\ncopying build/lib.linux-x86_64-cpython-38/Orange/classification/_simple_tree.cpython-38-x86_64-linux-gnu.so -> Orange/classification\ncopying build/lib.linux-x86_64-cpython-38/Orange/widgets/utils/_grid_density.cpython-38-x86_64-linux-gnu.so -> Orange/widgets/utils\ncopying build/lib.linux-x86_64-cpython-38/Orange/classification/_tree_scorers.cpython-38-x86_64-linux-gnu.so -> Orange/classification\ncopying build/lib.linux-x86_64-cpython-38/Orange/data/_contingency.cpython-38-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-cpython-38/Orange/data/_io.cpython-38-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-cpython-38/Orange/data/_valuecount.cpython-38-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-cpython-38/Orange/data/_variable.cpython-38-x86_64-linux-gnu.so -> Orange/data\ncopying build/lib.linux-x86_64-cpython-38/Orange/distance/_distance.cpython-38-x86_64-linux-gnu.so -> Orange/distance\ncopying build/lib.linux-x86_64-cpython-38/Orange/preprocess/_discretize.cpython-38-x86_64-linux-gnu.so -> Orange/preprocess\ncopying build/lib.linux-x86_64-cpython-38/Orange/preprocess/_relieff.cpython-38-x86_64-linux-gnu.so -> Orange/preprocess\ncopying build/lib.linux-x86_64-cpython-38/Orange/projection/_som.cpython-38-x86_64-linux-gnu.so -> Orange/projection\nCreating /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/Orange3.egg-link (link to .)\nAdding Orange3 3.37.0.dev0+d07762d to easy-install.pth file\nInstalling orange-canvas script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nInstalled /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6\nProcessing dependencies for Orange3==3.37.0.dev0+d07762d\nSearching for XlsxWriter==3.2.0\nBest match: XlsxWriter 3.2.0\nAdding XlsxWriter 3.2.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for xlrd==2.0.1\nBest match: xlrd 2.0.1\nAdding xlrd 2.0.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for xgboost==2.1.3\nBest match: xgboost 2.1.3\nAdding xgboost 2.1.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for setuptools==75.3.0\nBest match: setuptools 75.3.0\nAdding setuptools 75.3.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for serverfiles==0.3.1\nBest match: serverfiles 0.3.1\nAdding serverfiles 0.3.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for scipy==1.10.1\nBest match: scipy 1.10.1\nAdding scipy 1.10.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for scikit-learn==1.3.2\nBest match: scikit-learn 1.3.2\nAdding scikit-learn 1.3.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for requests==2.32.3\nBest match: requests 2.32.3\nAdding requests 2.32.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for qtconsole==5.6.1\nBest match: qtconsole 5.6.1\nAdding qtconsole 5.6.1 to easy-install.pth file\nInstalling jupyter-qtconsole script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for PyYAML==6.0.2\nBest match: PyYAML 6.0.2\nAdding PyYAML 6.0.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for python-louvain==0.16\nBest match: python-louvain 0.16\nAdding python-louvain 0.16 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pyqtgraph==0.13.3\nBest match: pyqtgraph 0.13.3\nAdding pyqtgraph 0.13.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pygments==2.19.1\nBest match: pygments 2.19.1\nAdding pygments 2.19.1 to easy-install.pth file\nInstalling pygmentize script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pip==24.3.1\nBest match: pip 24.3.1\nAdding pip 24.3.1 to easy-install.pth file\nInstalling pip script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling pip3 script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pandas==2.0.3\nBest match: pandas 2.0.3\nAdding pandas 2.0.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for orange-widget-base==4.22.0\nBest match: orange-widget-base 4.22.0\nAdding orange-widget-base 4.22.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for orange-canvas-core==0.1.35\nBest match: orange-canvas-core 0.1.35\nAdding orange-canvas-core 0.1.35 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for openpyxl==3.1.5\nBest match: openpyxl 3.1.5\nAdding openpyxl 3.1.5 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for openTSNE==1.0.1\nBest match: openTSNE 1.0.1\nAdding openTSNE 1.0.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for numpy==1.24.4\nBest match: numpy 1.24.4\nAdding numpy 1.24.4 to easy-install.pth file\nInstalling f2py script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling f2py3 script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling f2py3.8 script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for networkx==3.1\nBest match: networkx 3.1\nAdding networkx 3.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for matplotlib==3.7.5\nBest match: matplotlib 3.7.5\nAdding matplotlib 3.7.5 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for keyrings.alt==5.0.2\nBest match: keyrings.alt 5.0.2\nAdding keyrings.alt 5.0.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for keyring==25.5.0\nBest match: keyring 25.5.0\nAdding keyring 25.5.0 to easy-install.pth file\nInstalling keyring script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for joblib==1.4.2\nBest match: joblib 1.4.2\nAdding joblib 1.4.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for httpx==0.28.1\nBest match: httpx 0.28.1\nAdding httpx 0.28.1 to easy-install.pth file\nInstalling httpx script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for chardet==5.2.0\nBest match: chardet 5.2.0\nAdding chardet 5.2.0 to easy-install.pth file\nInstalling chardetect script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for catboost==1.2.7\nBest match: catboost 1.2.7\nAdding catboost 1.2.7 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for Bottleneck==1.4.0\nBest match: Bottleneck 1.4.0\nAdding Bottleneck 1.4.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for baycomp==1.0.3\nBest match: baycomp 1.0.3\nAdding baycomp 1.0.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for AnyQt==0.2.0\nBest match: AnyQt 0.2.0\nAdding AnyQt 0.2.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for nvidia-nccl-cu12==2.24.3\nBest match: nvidia-nccl-cu12 2.24.3\nAdding nvidia-nccl-cu12 2.24.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for threadpoolctl==3.5.0\nBest match: threadpoolctl 3.5.0\nAdding threadpoolctl 3.5.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for certifi==2024.12.14\nBest match: certifi 2024.12.14\nAdding certifi 2024.12.14 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for urllib3==2.2.3\nBest match: urllib3 2.2.3\nAdding urllib3 2.2.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for idna==3.10\nBest match: idna 3.10\nAdding idna 3.10 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for charset-normalizer==3.4.1\nBest match: charset-normalizer 3.4.1\nAdding charset-normalizer 3.4.1 to easy-install.pth file\nInstalling normalizer script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for packaging==24.2\nBest match: packaging 24.2\nAdding packaging 24.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for QtPy==2.4.2\nBest match: QtPy 2.4.2\nAdding QtPy 2.4.2 to easy-install.pth file\nInstalling qtpy script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for ipykernel==6.29.5\nBest match: ipykernel 6.29.5\nAdding ipykernel 6.29.5 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for jupyter-client==8.6.3\nBest match: jupyter-client 8.6.3\nAdding jupyter-client 8.6.3 to easy-install.pth file\nInstalling jupyter-kernel script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling jupyter-kernelspec script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling jupyter-run script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for jupyter-core==5.7.2\nBest match: jupyter-core 5.7.2\nAdding jupyter-core 5.7.2 to easy-install.pth file\nInstalling jupyter script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling jupyter-migrate script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling jupyter-troubleshoot script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for traitlets==5.14.3\nBest match: traitlets 5.14.3\nAdding traitlets 5.14.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for tzdata==2024.2\nBest match: tzdata 2024.2\nAdding tzdata 2024.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pytz==2024.2\nBest match: pytz 2024.2\nAdding pytz 2024.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for python-dateutil==2.9.0.post0\nBest match: python-dateutil 2.9.0.post0\nAdding python-dateutil 2.9.0.post0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for typing-extensions==4.12.2\nBest match: typing-extensions 4.12.2\nAdding typing-extensions 4.12.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/setuptools/_vendor\nSearching for qasync==0.27.1\nBest match: qasync 0.27.1\nAdding qasync 0.27.1 to easy-install.pth file\ndetected new path './setuptools/_vendor'\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for dictdiffer==0.9.0\nBest match: dictdiffer 0.9.0\nAdding dictdiffer 0.9.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for requests-cache==1.2.1\nBest match: requests-cache 1.2.1\nAdding requests-cache 1.2.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for commonmark==0.9.1\nBest match: commonmark 0.9.1\nAdding commonmark 0.9.1 to easy-install.pth file\nInstalling cmark script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for docutils==0.20.1\nBest match: docutils 0.20.1\nAdding docutils 0.20.1 to easy-install.pth file\nInstalling docutils script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for et-xmlfile==2.0.0\nBest match: et-xmlfile 2.0.0\nAdding et-xmlfile 2.0.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for importlib-resources==6.4.5\nBest match: importlib-resources 6.4.5\nAdding importlib-resources 6.4.5 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pyparsing==3.1.4\nBest match: pyparsing 3.1.4\nAdding pyparsing 3.1.4 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pillow==10.4.0\nBest match: pillow 10.4.0\nAdding pillow 10.4.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for kiwisolver==1.4.7\nBest match: kiwisolver 1.4.7\nAdding kiwisolver 1.4.7 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for fonttools==4.55.3\nBest match: fonttools 4.55.3\nAdding fonttools 4.55.3 to easy-install.pth file\nInstalling fonttools script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling pyftmerge script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling pyftsubset script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling ttx script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for cycler==0.12.1\nBest match: cycler 0.12.1\nAdding cycler 0.12.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for contourpy==1.1.1\nBest match: contourpy 1.1.1\nAdding contourpy 1.1.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for jaraco.context==6.0.1\nBest match: jaraco.context 6.0.1\nAdding jaraco.context 6.0.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for jaraco.classes==3.4.0\nBest match: jaraco.classes 3.4.0\nAdding jaraco.classes 3.4.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for jeepney==0.8.0\nBest match: jeepney 0.8.0\nAdding jeepney 0.8.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for SecretStorage==3.3.3\nBest match: SecretStorage 3.3.3\nAdding SecretStorage 3.3.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for importlib-metadata==8.5.0\nBest match: importlib-metadata 8.5.0\nAdding importlib-metadata 8.5.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for jaraco.functools==4.1.0\nBest match: jaraco.functools 4.1.0\nAdding jaraco.functools 4.1.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for httpcore==1.0.7\nBest match: httpcore 1.0.7\nAdding httpcore 1.0.7 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for anyio==4.5.2\nBest match: anyio 4.5.2\nAdding anyio 4.5.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for six==1.17.0\nBest match: six 1.17.0\nAdding six 1.17.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for plotly==5.24.1\nBest match: plotly 5.24.1\nAdding plotly 5.24.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for graphviz==0.20.3\nBest match: graphviz 0.20.3\nAdding graphviz 0.20.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for tornado==6.4.2\nBest match: tornado 6.4.2\nAdding tornado 6.4.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pyzmq==26.2.0\nBest match: pyzmq 26.2.0\nAdding pyzmq 26.2.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for psutil==6.1.1\nBest match: psutil 6.1.1\nAdding psutil 6.1.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for nest-asyncio==1.6.0\nBest match: nest-asyncio 1.6.0\nAdding nest-asyncio 1.6.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for matplotlib-inline==0.1.7\nBest match: matplotlib-inline 0.1.7\nAdding matplotlib-inline 0.1.7 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for ipython==8.12.3\nBest match: ipython 8.12.3\nAdding ipython 8.12.3 to easy-install.pth file\nInstalling ipython script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\nInstalling ipython3 script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for debugpy==1.8.11\nBest match: debugpy 1.8.11\nAdding debugpy 1.8.11 to easy-install.pth file\nInstalling debugpy script to /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/bin\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for comm==0.2.2\nBest match: comm 0.2.2\nAdding comm 0.2.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for platformdirs==4.3.6\nBest match: platformdirs 4.3.6\nAdding platformdirs 4.3.6 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for url-normalize==1.4.3\nBest match: url-normalize 1.4.3\nAdding url-normalize 1.4.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for cattrs==24.1.2\nBest match: cattrs 24.1.2\nAdding cattrs 24.1.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for attrs==24.3.0\nBest match: attrs 24.3.0\nAdding attrs 24.3.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for zipp==3.20.2\nBest match: zipp 3.20.2\nAdding zipp 3.20.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for backports.tarfile==1.2.0\nBest match: backports.tarfile 1.2.0\nbackports.tarfile 1.2.0 is already the active version in easy-install.pth\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/setuptools/_vendor\nSearching for more-itertools==10.5.0\nBest match: more-itertools 10.5.0\nAdding more-itertools 10.5.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for cryptography==44.0.0\nBest match: cryptography 44.0.0\nAdding cryptography 44.0.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for h11==0.14.0\nBest match: h11 0.14.0\nAdding h11 0.14.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for exceptiongroup==1.2.2\nBest match: exceptiongroup 1.2.2\nAdding exceptiongroup 1.2.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for sniffio==1.3.1\nBest match: sniffio 1.3.1\nAdding sniffio 1.3.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for tenacity==9.0.0\nBest match: tenacity 9.0.0\nAdding tenacity 9.0.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pexpect==4.9.0\nBest match: pexpect 4.9.0\nAdding pexpect 4.9.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for stack-data==0.6.3\nBest match: stack-data 0.6.3\nAdding stack-data 0.6.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for prompt-toolkit==3.0.48\nBest match: prompt-toolkit 3.0.48\nAdding prompt-toolkit 3.0.48 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pickleshare==0.7.5\nBest match: pickleshare 0.7.5\nAdding pickleshare 0.7.5 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for jedi==0.19.2\nBest match: jedi 0.19.2\nAdding jedi 0.19.2 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for decorator==5.1.1\nBest match: decorator 5.1.1\nAdding decorator 5.1.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for backcall==0.2.0\nBest match: backcall 0.2.0\nAdding backcall 0.2.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for cffi==1.17.1\nBest match: cffi 1.17.1\nAdding cffi 1.17.1 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for ptyprocess==0.7.0\nBest match: ptyprocess 0.7.0\nAdding ptyprocess 0.7.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pure-eval==0.2.3\nBest match: pure-eval 0.2.3\nAdding pure-eval 0.2.3 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for asttokens==3.0.0\nBest match: asttokens 3.0.0\nAdding asttokens 3.0.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for executing==2.1.0\nBest match: executing 2.1.0\nAdding executing 2.1.0 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for wcwidth==0.2.13\nBest match: wcwidth 0.2.13\nAdding wcwidth 0.2.13 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for parso==0.8.4\nBest match: parso 0.8.4\nAdding parso 0.8.4 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nSearching for pycparser==2.22\nBest match: pycparser 2.22\nAdding pycparser 2.22 to easy-install.pth file\n\nUsing /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages\nFinished processing dependencies for Orange3==3.37.0.dev0+d07762d\nVerifying Orange installation...\n✅ Orange installation successful!\nSuccessfully installed orange using Python 3.8\n",
    "setup_res_stderr": "Using CPython 3.7.9\nCreating virtual environment at: .venv\nActivate with: source .venv/bin/activate\nResolved 18 packages in 149ms\nPrepared 18 packages in 1ms\nInstalled 18 packages in 216ms\n + cython==0.29.37\n + exceptiongroup==1.2.2\n + importlib-metadata==6.7.0\n + iniconfig==2.0.0\n + numpy==1.17.5\n + packaging==24.0\n + pluggy==1.2.0\n + pyqt5==5.15.10\n + pyqt5-qt5==5.15.16\n + pyqt5-sip==12.13.0\n + pyqtwebengine==5.15.6\n + pyqtwebengine-qt5==5.15.16\n + pytest==7.4.4\n + setuptools==59.8.0\n + tomli==2.0.1\n + typing-extensions==4.7.1\n + wheel==0.42.0\n + zipp==3.15.0\n  × No solution found when resolving dependencies:\n  ╰─▶ Because the current Python version (3.7.9) does not satisfy Python>=3.8 and all of:\n          pandas>=1.4.0,<=1.4.4\n          pandas>=1.5.1,<=1.5.3\n          pandas>=2.0.1,<=2.0.3\n      depend on Python>=3.8, we can conclude that all of:\n          pandas>=1.4.0,<=1.4.4\n          pandas>=1.5.1,<=1.5.3\n          pandas>=2.0.1,<=2.0.3\n       cannot be used.\n      And because only the following versions of pandas are available:\n          pandas<=1.4.0\n          pandas==1.4.1\n          pandas==1.4.2\n          pandas==1.4.3\n          pandas==1.4.4\n          pandas==1.5.0\n          pandas==1.5.1\n          pandas==1.5.2\n          pandas==1.5.3\n          pandas==2.0.0\n          pandas==2.0.1\n          pandas==2.0.2\n          pandas==2.0.3\n          pandas==2.1.0\n          pandas==2.1.1\n          pandas==2.1.2\n          pandas==2.1.3\n          pandas==2.1.4\n          pandas==2.2.0\n          pandas==2.2.1\n          pandas==2.2.2\n          pandas==2.2.3\n      we can conclude that all of:\n          pandas>=1.4.0,<1.5.0\n          pandas>1.5.0,<2.0.0\n          pandas>2.0.0,<2.1.0\n       cannot be used. (1)\n\n      Because the current Python version (3.7.9) does not satisfy Python>=3.9 and pandas>=2.1.0 depends on Python>=3.9, we can\n      conclude that pandas>=2.1.0 cannot be used.\n      And because we know from (1) that all of:\n          pandas>=1.4.0,<1.5.0\n          pandas>1.5.0,<2.0.0\n          pandas>2.0.0,<2.1.0\n       cannot be used, we can conclude that all of:\n          pandas>=1.4.0,<1.5.0\n          pandas>1.5.0,<2.0.0\n          pandas>2.0.0\n       cannot be used.\n      And because you require one of:\n          pandas>=1.4.0,<1.5.0\n          pandas>1.5.0,<2.0.0\n          pandas>2.0.0\n      we can conclude that your requirements are unsatisfiable.\n\n      hint: Pre-releases are available for `pandas` in the requested range (e.g., 2.2.0rc0), but pre-releases weren't enabled\n      (try: `--prerelease=allow`)\n  × No solution found when resolving dependencies:\n  ╰─▶ Because the current Python version (3.7.9) does not satisfy Python>=3.8 and pyqtgraph>=0.13.1,<=0.13.3 depends on\n      Python>=3.8, we can conclude that pyqtgraph>=0.13.1,<=0.13.3 cannot be used.\n      And because only the following versions of pyqtgraph are available:\n          pyqtgraph<=0.13.1\n          pyqtgraph==0.13.2\n          pyqtgraph==0.13.3\n          pyqtgraph==0.13.4\n          pyqtgraph==0.13.5\n          pyqtgraph==0.13.6\n          pyqtgraph==0.13.7\n      we can conclude that pyqtgraph>=0.13.1,<0.13.4 cannot be used. (1)\n\n      Because the current Python version (3.7.9) does not satisfy Python>=3.9 and pyqtgraph>=0.13.4 depends on Python>=3.9, we\n      can conclude that pyqtgraph>=0.13.4 cannot be used.\n      And because we know from (1) that pyqtgraph>=0.13.1,<0.13.4 cannot be used, we can conclude that pyqtgraph>=0.13.1 cannot\n      be used.\n      And because you require pyqtgraph>=0.13.1, we can conclude that your requirements are unsatisfiable.\nResolved 2 packages in 6ms\nInstalled 2 packages in 13ms\n + psycopg2==2.9.9\n + pymssql==2.3.2\nResolved 5 packages in 22ms\nInstalled 4 packages in 362ms\n + joblib==1.3.2\n + scikit-learn==1.0.2\n + scipy==1.7.3\n + threadpoolctl==3.1.0\nOrange/classification/_simple_tree.c: In function ‘gain_ratio_c’:\nOrange/classification/_simple_tree.c:63:9: warning: implicit declaration of function ‘qsort_r’; did you mean ‘qsort’? [-Wimplicit-function-declaration]\n   63 |         qsort_r(base, nel, size, compar, thunk)\n      |         ^~~~~~~\nOrange/classification/_simple_tree.c:147:9: note: in expansion of macro ‘QSORT_R_FUNC’\n  147 |         QSORT_R_FUNC(examples, size, sizeof(struct Example), (void*) &compar_attr, compar_examples);\n      |         ^~~~~~~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1830,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,\n                 from Orange/classification/_tree_scorers.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_2find_threshold_entropy’:\nOrange/classification/_tree_scorers.c:3426:27: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 3426 |   __pyx_t_7 = ((__pyx_v_N <= __pyx_v_min_leaf) != 0);\n      |                           ^~\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_6find_threshold_MSE’:\nOrange/classification/_tree_scorers.c:4872:27: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 4872 |   __pyx_t_1 = ((__pyx_v_N <= __pyx_v_min_leaf) != 0);\n      |                           ^~\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_8find_binarization_MSE’:\nOrange/classification/_tree_scorers.c:5618:43: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 5618 |           for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) {\n      |                                           ^\nOrange/classification/_tree_scorers.c:5739:39: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 5739 |           __pyx_t_20 = ((__pyx_v_left >= __pyx_v_min_leaf) != 0);\n      |                                       ^~\nOrange/classification/_tree_scorers.c:5745:53: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 5745 |           __pyx_t_20 = (((__pyx_v_N - __pyx_v_left) >= __pyx_v_min_leaf) != 0);\n      |                                                     ^~\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_14compute_predictions_csr’:\nOrange/classification/_tree_scorers.c:7206:41: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 7206 |         for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) {\n      |                                         ^\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_16compute_predictions_csc’:\nOrange/classification/_tree_scorers.c:7863:41: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 7863 |         for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) {\n      |                                         ^\nOrange/classification/_tree_scorers.c:7923:150: warning: comparison of integer expressions of different signedness: ‘__pyx_t_5numpy_int32_t’ {aka ‘int’} and ‘unsigned int’ [-Wsign-compare]\n 7923 |               __pyx_t_16 = (((*((__pyx_t_5numpy_int32_t const  *) ( /* dim=0 */ (__pyx_v_indices.data + __pyx_t_15 * __pyx_v_indices.strides[0]) ))) != __pyx_v_i) != 0);\n      |                                                                                                                                                      ^~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1830,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,\n                 from Orange/data/_contingency.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nOrange/data/_io.c: In function ‘__pyx_pf_6Orange_4data_3_io_sparse_read_float.constprop’:\nOrange/data/_io.c:4120:43: warning: ‘__pyx_v_decs’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 4120 |           __pyx_v_value = ((__pyx_v_value * __pyx_v_decs) + (__pyx_v_c & 0xf));\n      |                            ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/data/_io.c:4318:24: warning: ‘__pyx_v_value’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 4318 |           __pyx_t_10 = PyFloat_FromDouble(__pyx_v_value); if (unlikely(!__pyx_t_10)) __PYX_ERR(0, 223, __pyx_L5_error)\n      |                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\nOrange/data/_io.c:683:40: warning: ‘__pyx_v_attr_index’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n  683 |   #define PyInt_FromLong               PyLong_FromLong\n      |                                        ^~~~~~~~~~~~~~~\nOrange/data/_io.c:1590:7: note: ‘__pyx_v_attr_index’ was declared here\n 1590 |   int __pyx_v_attr_index;\n      |       ^~~~~~~~~~~~~~~~~~\nOrange/data/_io.c:3183:25: warning: ‘__pyx_v_atomp’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3183 |           __pyx_v_atomp = (__pyx_v_atomp + 1);\n      |           ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1830,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,\n                 from Orange/data/_valuecount.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1830,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,\n                 from Orange/distance/_distance.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1830,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,\n                 from Orange/preprocess/_discretize.c:774:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1830,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,\n                 from Orange/preprocess/_relieff.cpp:790:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1830,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,\n                 from Orange/projection/_som.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pw_6Orange_10projection_4_som_5update_hex’:\nOrange/projection/_som.c:3944:7: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3944 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:3943:7: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3943 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pf_6Orange_10projection_4_som_8update_sparse.constprop’:\nOrange/projection/_som.c:5094:7: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 5094 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:5093:7: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 5093 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pw_6Orange_10projection_4_som_1get_winners’:\nOrange/projection/_som.c:3244:223: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3244 |           *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_int16_t *, __pyx_pybuffernd_winners.rcbuffer->pybuffer.buf, __pyx_t_23, __pyx_pybuffernd_winners.diminfo[0].strides, __pyx_t_24, __pyx_pybuffernd_winners.diminfo[1].strides) = __pyx_v_win_y;\n      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/projection/_som.c:2892:7: note: ‘__pyx_v_win_y’ was declared here\n 2892 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:3233:223: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3233 |           *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_int16_t *, __pyx_pybuffernd_winners.rcbuffer->pybuffer.buf, __pyx_t_24, __pyx_pybuffernd_winners.diminfo[0].strides, __pyx_t_23, __pyx_pybuffernd_winners.diminfo[1].strides) = __pyx_v_win_x;\n      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/projection/_som.c:2891:7: note: ‘__pyx_v_win_x’ was declared here\n 2891 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pf_6Orange_10projection_4_som_10update_sparse_hex.constprop’:\nOrange/projection/_som.c:5842:7: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 5842 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:5841:7: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 5841 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pw_6Orange_10projection_4_som_7get_winners_sparse’:\nOrange/projection/_som.c:4871:223: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 4871 |           *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_int16_t *, __pyx_pybuffernd_winners.rcbuffer->pybuffer.buf, __pyx_t_27, __pyx_pybuffernd_winners.diminfo[0].strides, __pyx_t_28, __pyx_pybuffernd_winners.diminfo[1].strides) = __pyx_v_win_y;\n      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/projection/_som.c:4389:7: note: ‘__pyx_v_win_y’ was declared here\n 4389 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:4860:223: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 4860 |           *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_int16_t *, __pyx_pybuffernd_winners.rcbuffer->pybuffer.buf, __pyx_t_28, __pyx_pybuffernd_winners.diminfo[0].strides, __pyx_t_27, __pyx_pybuffernd_winners.diminfo[1].strides) = __pyx_v_win_x;\n      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/projection/_som.c:4388:7: note: ‘__pyx_v_win_x’ was declared here\n 4388 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pw_6Orange_10projection_4_som_3update’:\nOrange/projection/_som.c:3438:7: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3438 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/setuptools/command/easy_install.py:159: EasyInstallDeprecationWarning: easy_install command is deprecated. Use build and pip and other standards-based tools.\n  EasyInstallDeprecationWarning,\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/setuptools/command/install.py:37: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.\n  setuptools.SetuptoolsDeprecationWarning,\nwarning: no files found matching 'README*' under directory 'Orange'\nwarning: no files found matching 'LICENSE' under directory 'Orange'\nwarning: no files found matching '*.basket' under directory 'Orange/datasets'\nwarning: no files found matching '*.svg' under directory 'Orange/canvas'\nwarning: no files found matching '*.js' under directory 'Orange/widgets'\nwarning: no files found matching '*.css' under directory 'Orange/widgets'\nwarning: no files found matching '*.html' under directory 'Orange/widgets'\nwarning: no files found matching '*.svg' under directory 'distribute'\nwarning: no files found matching 'COPYING'\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/pkg_resources/__init__.py:119: PkgResourcesDeprecationWarning:  is an invalid version and will not be supported in a future release\n  PkgResourcesDeprecationWarning,\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/setuptools/command/install.py:37: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.\n  setuptools.SetuptoolsDeprecationWarning,\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.7/site-packages/pkg_resources/__init__.py:119: PkgResourcesDeprecationWarning:  is an invalid version and will not be supported in a future release\n  PkgResourcesDeprecationWarning,\nerror: Couldn't find a setup script in /tmp/easy_install-jrzii248/scipy-1.15.0.tar.gz\nUsing CPython 3.8.20\nCreating virtual environment at: .venv\nActivate with: source .venv/bin/activate\nResolved 15 packages in 65ms\nPrepared 15 packages in 1ms\nInstalled 15 packages in 124ms\n + cython==0.29.37\n + exceptiongroup==1.2.2\n + iniconfig==2.0.0\n + numpy==1.24.4\n + packaging==24.2\n + pluggy==1.5.0\n + pyqt5==5.15.11\n + pyqt5-qt5==5.15.16\n + pyqt5-sip==12.15.0\n + pyqtwebengine==5.15.7\n + pyqtwebengine-qt5==5.15.16\n + pytest==8.3.4\n + setuptools==75.3.0\n + tomli==2.2.1\n + wheel==0.45.1\nResolved 65 packages in 136ms\nInstalled 61 packages in 720ms\n + anyio==4.5.2\n + backports-tarfile==1.2.0\n + baycomp==1.0.3\n + bottleneck==1.4.0\n + catboost==1.2.7\n + certifi==2024.12.14\n + cffi==1.17.1\n + chardet==5.2.0\n + charset-normalizer==3.4.1\n + contourpy==1.1.1\n + cryptography==44.0.0\n + cycler==0.12.1\n + et-xmlfile==2.0.0\n + fonttools==4.55.3\n + graphviz==0.20.3\n + h11==0.14.0\n + httpcore==1.0.7\n + httpx==0.28.1\n + idna==3.10\n + importlib-metadata==8.5.0\n + importlib-resources==6.4.5\n + jaraco-classes==3.4.0\n + jaraco-context==6.0.1\n + jaraco-functools==4.1.0\n + jeepney==0.8.0\n + joblib==1.4.2\n + keyring==25.5.0\n + keyrings-alt==5.0.2\n + kiwisolver==1.4.7\n + matplotlib==3.7.5\n + more-itertools==10.5.0\n + networkx==3.1\n + nvidia-nccl-cu12==2.24.3\n + openpyxl==3.1.5\n + opentsne==1.0.1\n + pandas==2.0.3\n + pillow==10.4.0\n + pip==24.3.1\n + plotly==5.24.1\n + pycparser==2.22\n + pyparsing==3.1.4\n + python-dateutil==2.9.0.post0\n + python-louvain==0.16\n + pytz==2024.2\n + pyyaml==6.0.2\n + requests==2.32.3\n + scikit-learn==1.3.2\n + scipy==1.10.1\n + secretstorage==3.3.3\n + serverfiles==0.3.1\n + six==1.17.0\n + sniffio==1.3.1\n + tenacity==9.0.0\n + threadpoolctl==3.5.0\n + typing-extensions==4.12.2\n + tzdata==2024.2\n + urllib3==2.2.3\n + xgboost==2.1.3\n + xlrd==2.0.1\n + xlsxwriter==3.2.0\n + zipp==3.20.2\nResolved 64 packages in 75ms\nInstalled 41 packages in 194ms\n + anyqt==0.2.0\n + asttokens==3.0.0\n + attrs==24.3.0\n + backcall==0.2.0\n + cattrs==24.1.2\n + comm==0.2.2\n + commonmark==0.9.1\n + debugpy==1.8.11\n + decorator==5.1.1\n + dictdiffer==0.9.0\n + docutils==0.20.1\n + executing==2.1.0\n + ipykernel==6.29.5\n + ipython==8.12.3\n + jedi==0.19.2\n + jupyter-client==8.6.3\n + jupyter-core==5.7.2\n + matplotlib-inline==0.1.7\n + nest-asyncio==1.6.0\n + orange-canvas-core==0.1.35\n + orange-widget-base==4.22.0\n + parso==0.8.4\n + pexpect==4.9.0\n + pickleshare==0.7.5\n + platformdirs==4.3.6\n + prompt-toolkit==3.0.48\n + psutil==6.1.1\n + ptyprocess==0.7.0\n + pure-eval==0.2.3\n + pygments==2.19.1\n + pyqtgraph==0.13.3\n + pyzmq==26.2.0\n + qasync==0.27.1\n + qtconsole==5.6.1\n + qtpy==2.4.2\n + requests-cache==1.2.1\n + stack-data==0.6.3\n + tornado==6.4.2\n + traitlets==5.14.3\n + url-normalize==1.4.3\n + wcwidth==0.2.13\nResolved 2 packages in 2ms\nInstalled 2 packages in 4ms\n + psycopg2==2.9.10\n + pymssql==2.3.2\nOrange/classification/_simple_tree.c: In function ‘gain_ratio_c’:\nOrange/classification/_simple_tree.c:63:9: warning: implicit declaration of function ‘qsort_r’; did you mean ‘qsort’? [-Wimplicit-function-declaration]\n   63 |         qsort_r(base, nel, size, compar, thunk)\n      |         ^~~~~~~\nOrange/classification/_simple_tree.c:147:9: note: in expansion of macro ‘QSORT_R_FUNC’\n  147 |         QSORT_R_FUNC(examples, size, sizeof(struct Example), (void*) &compar_attr, compar_examples);\n      |         ^~~~~~~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h:1940,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h:5,\n                 from Orange/classification/_tree_scorers.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_2find_threshold_entropy’:\nOrange/classification/_tree_scorers.c:3426:27: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 3426 |   __pyx_t_7 = ((__pyx_v_N <= __pyx_v_min_leaf) != 0);\n      |                           ^~\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_6find_threshold_MSE’:\nOrange/classification/_tree_scorers.c:4872:27: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 4872 |   __pyx_t_1 = ((__pyx_v_N <= __pyx_v_min_leaf) != 0);\n      |                           ^~\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_8find_binarization_MSE’:\nOrange/classification/_tree_scorers.c:5618:43: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 5618 |           for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) {\n      |                                           ^\nOrange/classification/_tree_scorers.c:5739:39: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 5739 |           __pyx_t_20 = ((__pyx_v_left >= __pyx_v_min_leaf) != 0);\n      |                                       ^~\nOrange/classification/_tree_scorers.c:5745:53: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 5745 |           __pyx_t_20 = (((__pyx_v_N - __pyx_v_left) >= __pyx_v_min_leaf) != 0);\n      |                                                     ^~\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_14compute_predictions_csr’:\nOrange/classification/_tree_scorers.c:7206:41: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 7206 |         for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) {\n      |                                         ^\nOrange/classification/_tree_scorers.c: In function ‘__pyx_pf_6Orange_14classification_13_tree_scorers_16compute_predictions_csc’:\nOrange/classification/_tree_scorers.c:7863:41: warning: comparison of integer expressions of different signedness: ‘unsigned int’ and ‘int’ [-Wsign-compare]\n 7863 |         for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) {\n      |                                         ^\nOrange/classification/_tree_scorers.c:7923:150: warning: comparison of integer expressions of different signedness: ‘__pyx_t_5numpy_int32_t’ {aka ‘int’} and ‘unsigned int’ [-Wsign-compare]\n 7923 |               __pyx_t_16 = (((*((__pyx_t_5numpy_int32_t const  *) ( /* dim=0 */ (__pyx_v_indices.data + __pyx_t_15 * __pyx_v_indices.strides[0]) ))) != __pyx_v_i) != 0);\n      |                                                                                                                                                      ^~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h:1940,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h:5,\n                 from Orange/data/_contingency.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nOrange/data/_io.c: In function ‘__pyx_pf_6Orange_4data_3_io_sparse_read_float.constprop’:\nOrange/data/_io.c:4120:43: warning: ‘__pyx_v_decs’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 4120 |           __pyx_v_value = ((__pyx_v_value * __pyx_v_decs) + (__pyx_v_c & 0xf));\n      |                            ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/data/_io.c:4318:24: warning: ‘__pyx_v_value’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 4318 |           __pyx_t_10 = PyFloat_FromDouble(__pyx_v_value); if (unlikely(!__pyx_t_10)) __PYX_ERR(0, 223, __pyx_L5_error)\n      |                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\nOrange/data/_io.c:683:40: warning: ‘__pyx_v_attr_index’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n  683 |   #define PyInt_FromLong               PyLong_FromLong\n      |                                        ^~~~~~~~~~~~~~~\nOrange/data/_io.c:1590:7: note: ‘__pyx_v_attr_index’ was declared here\n 1590 |   int __pyx_v_attr_index;\n      |       ^~~~~~~~~~~~~~~~~~\nOrange/data/_io.c:3183:25: warning: ‘__pyx_v_atomp’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3183 |           __pyx_v_atomp = (__pyx_v_atomp + 1);\n      |           ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h:1940,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h:5,\n                 from Orange/data/_valuecount.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h:1940,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h:5,\n                 from Orange/distance/_distance.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h:1940,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h:5,\n                 from Orange/preprocess/_discretize.c:774:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h:1940,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h:5,\n                 from Orange/preprocess/_relieff.cpp:790:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nIn file included from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarraytypes.h:1940,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,\n                 from /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/arrayobject.h:5,\n                 from Orange/projection/_som.c:775:\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n      |  ^~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pw_6Orange_10projection_4_som_5update_hex’:\nOrange/projection/_som.c:3944:7: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3944 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:3943:7: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3943 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pf_6Orange_10projection_4_som_8update_sparse.constprop’:\nOrange/projection/_som.c:5094:7: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 5094 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:5093:7: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 5093 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pw_6Orange_10projection_4_som_3update’:\nOrange/projection/_som.c:3438:7: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3438 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pw_6Orange_10projection_4_som_1get_winners’:\nOrange/projection/_som.c:3244:223: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3244 |           *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_int16_t *, __pyx_pybuffernd_winners.rcbuffer->pybuffer.buf, __pyx_t_23, __pyx_pybuffernd_winners.diminfo[0].strides, __pyx_t_24, __pyx_pybuffernd_winners.diminfo[1].strides) = __pyx_v_win_y;\n      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/projection/_som.c:2892:7: note: ‘__pyx_v_win_y’ was declared here\n 2892 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:3233:223: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 3233 |           *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_int16_t *, __pyx_pybuffernd_winners.rcbuffer->pybuffer.buf, __pyx_t_24, __pyx_pybuffernd_winners.diminfo[0].strides, __pyx_t_23, __pyx_pybuffernd_winners.diminfo[1].strides) = __pyx_v_win_x;\n      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/projection/_som.c:2891:7: note: ‘__pyx_v_win_x’ was declared here\n 2891 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pf_6Orange_10projection_4_som_10update_sparse_hex.constprop’:\nOrange/projection/_som.c:5842:7: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 5842 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:5841:7: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 5841 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c: In function ‘__pyx_pw_6Orange_10projection_4_som_7get_winners_sparse’:\nOrange/projection/_som.c:4871:223: warning: ‘__pyx_v_win_y’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 4871 |           *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_int16_t *, __pyx_pybuffernd_winners.rcbuffer->pybuffer.buf, __pyx_t_27, __pyx_pybuffernd_winners.diminfo[0].strides, __pyx_t_28, __pyx_pybuffernd_winners.diminfo[1].strides) = __pyx_v_win_y;\n      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/projection/_som.c:4389:7: note: ‘__pyx_v_win_y’ was declared here\n 4389 |   int __pyx_v_win_y;\n      |       ^~~~~~~~~~~~~\nOrange/projection/_som.c:4860:223: warning: ‘__pyx_v_win_x’ may be used uninitialized in this function [-Wmaybe-uninitialized]\n 4860 |           *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_int16_t *, __pyx_pybuffernd_winners.rcbuffer->pybuffer.buf, __pyx_t_28, __pyx_pybuffernd_winners.diminfo[0].strides, __pyx_t_27, __pyx_pybuffernd_winners.diminfo[1].strides) = __pyx_v_win_x;\n      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~\nOrange/projection/_som.c:4388:7: note: ‘__pyx_v_win_x’ was declared here\n 4388 |   int __pyx_v_win_x;\n      |       ^~~~~~~~~~~~~\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'test_suite'\n  warnings.warn(msg)\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'test_suite'\n  warnings.warn(msg)\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/setuptools/command/develop.py:41: EasyInstallDeprecationWarning: easy_install command is deprecated.\n!!\n\n        ********************************************************************************\n        Please avoid running ``setup.py`` and ``easy_install``.\n        Instead, use pypa/build, pypa/installer or other\n        standards-based tools.\n\n        See https://github.com/pypa/setuptools/issues/917 for details.\n        ********************************************************************************\n\n!!\n  easy_install.initialize_options(self)\n/home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6/.venv/lib/python3.8/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.\n!!\n\n        ********************************************************************************\n        Please avoid running ``setup.py`` directly.\n        Instead, use pypa/build, pypa/installer or other\n        standards-based tools.\n\n        See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.\n        ********************************************************************************\n\n!!\n  self.initialize_options()\nwarning: no files found matching 'README*' under directory 'Orange'\nwarning: no files found matching 'LICENSE' under directory 'Orange'\nwarning: no files found matching '*.basket' under directory 'Orange/datasets'\nwarning: no files found matching '*.svg' under directory 'Orange/canvas'\nwarning: no files found matching '*.js' under directory 'Orange/widgets'\nwarning: no files found matching '*.css' under directory 'Orange/widgets'\nwarning: no files found matching '*.html' under directory 'Orange/widgets'\nwarning: no files found matching '*.svg' under directory 'distribute'\nwarning: no files found matching 'COPYING'\n",
    "new_commit_res_code": 0,
    "new_commit_res_stdout": "============================= test session starts ==============================\nplatform linux -- Python 3.8.20, pytest-8.3.4, pluggy-1.5.0\nrootdir: /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6\nconfigfile: pyproject.toml\nplugins: anyio-4.5.2, typeguard-4.3.0\ncollected 47 items\n\nr2e_tests/test_1.py sss............................................      [100%]\n\n==================================== PASSES ====================================\n=========================== short test summary info ============================\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_attr_label_metas\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_attr_models\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_bad_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_btn_vizrank\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_buttons\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_class_density\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_data_no_cont_features\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_datasets\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_default_attrs\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_dragging_tooltip\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_embedding_missing_values\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_handle_primitive_metas\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_hidden_effective_variables\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_image_export\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_invalid_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_invalidated_embedding\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_invalidated_model_selected\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_lda_not_enough_distinct\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_manual_move\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_migrate_settings_from_version_1\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_minimum_size\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_msg_base_class\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_nan_plot\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_no_data_for_lda\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_none_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_outputs\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_plot_once\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_radius\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_saved_selection\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_send_report\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_set_radius_no_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_setup_graph\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_sparse_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_subset_data_color\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_two_classes_dataset\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_unique_name\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_visual_settings\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_continuous_class\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_discrete_class\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_image_export\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_minimum_size\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_msg_base_class\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_set_attrs\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_vizrank_n_attrs\nSKIPPED [1] .venv/lib/python3.8/site-packages/orangewidget/tests/base.py:244: image exporting not tested as .widget was not set\nSKIPPED [1] .venv/lib/python3.8/site-packages/orangewidget/tests/base.py:238: minimum size not tested as .widget was not set\nSKIPPED [1] .venv/lib/python3.8/site-packages/orangewidget/tests/base.py:250: msg base class not tested as .widget was not set\n======================== 44 passed, 3 skipped in 10.75s ========================\nWidgets left: 0    Max widgets: 9963 \n\n",
    "new_commit_res_stderr": "",
    "old_commit_res_code": 1,
    "old_commit_res_stdout": "============================= test session starts ==============================\nplatform linux -- Python 3.8.20, pytest-8.3.4, pluggy-1.5.0\nrootdir: /home/gcpuser/buckets/local_repoeval_bucket/repos/orange3_d07762d74208b9cda8e1b263d03133c68158d9b6\nconfigfile: pyproject.toml\nplugins: anyio-4.5.2, typeguard-4.3.0\ncollected 47 items\n\nr2e_tests/test_1.py sss...........................................F      [100%]\n\n=================================== FAILURES ===================================\n___________________ LinProjVizRankTests.test_vizrank_n_attrs ___________________\n\nself = <r2e_tests.test_1.LinProjVizRankTests testMethod=test_vizrank_n_attrs>\n\n    def test_vizrank_n_attrs(self):\n        self.send_signal(self.widget.Inputs.data, self.data)\n        self.vizrank.n_attrs_spin.setValue(4)\n        settings = self.widget.settingsHandler.pack_data(self.widget)\n        widget = self.create_widget(OWLinearProjection,\n                                    stored_settings=settings)\n        self.send_signal(widget.Inputs.data, self.data, widget=widget)\n>       self.assertEqual(widget.vizrank.n_attrs_spin.value(),\n                         self.vizrank.n_attrs_spin.value())\nE       AssertionError: 3 != 4\n\nr2e_tests/test_1.py:266: AssertionError\n==================================== PASSES ====================================\n=========================== short test summary info ============================\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_attr_label_metas\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_attr_models\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_bad_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_btn_vizrank\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_buttons\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_class_density\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_data_no_cont_features\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_datasets\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_default_attrs\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_dragging_tooltip\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_embedding_missing_values\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_handle_primitive_metas\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_hidden_effective_variables\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_image_export\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_invalid_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_invalidated_embedding\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_invalidated_model_selected\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_lda_not_enough_distinct\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_manual_move\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_migrate_settings_from_version_1\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_minimum_size\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_msg_base_class\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_nan_plot\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_no_data_for_lda\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_none_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_outputs\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_plot_once\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_radius\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_saved_selection\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_send_report\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_set_radius_no_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_setup_graph\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_sparse_data\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_subset_data_color\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_two_classes_dataset\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_unique_name\nPASSED r2e_tests/test_1.py::TestOWLinearProjection::test_visual_settings\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_continuous_class\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_discrete_class\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_image_export\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_minimum_size\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_msg_base_class\nPASSED r2e_tests/test_1.py::LinProjVizRankTests::test_set_attrs\nSKIPPED [1] .venv/lib/python3.8/site-packages/orangewidget/tests/base.py:244: image exporting not tested as .widget was not set\nSKIPPED [1] .venv/lib/python3.8/site-packages/orangewidget/tests/base.py:238: minimum size not tested as .widget was not set\nSKIPPED [1] .venv/lib/python3.8/site-packages/orangewidget/tests/base.py:250: msg base class not tested as .widget was not set\nFAILED r2e_tests/test_1.py::LinProjVizRankTests::test_vizrank_n_attrs - Asser...\n=================== 1 failed, 43 passed, 3 skipped in 7.94s ====================\nWidgets left: 0    Max widgets: 9963 \n\n",
    "old_commit_res_stderr": ""
}
Orange/widgets/visualize/owlinearprojection.py Orange/widgets/visualize/tests/test_owlinearprojection.py
We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
[ISSUE]
**Title:** Number of Attributes Spin Box Resets Value After Reloading Settings

**Description:**
When setting the number of attributes using the `n_attrs_spin` control and reloading the widget with stored settings, the spin box does not retain the updated value.

**Example Buggy Code:**
```python
def test_vizrank_n_attrs(self):
    self.send_signal(self.widget.Inputs.data, self.data)
    self.vizrank.n_attrs_spin.setValue(4)
    settings = self.widget.settingsHandler.pack_data(self.widget)
    widget = self.create_widget(OWLinearProjection, stored_settings=settings)
    self.send_signal(widget.Inputs.data, self.data, widget=widget)
    # After reloading, the spin box value should be 4, but it remains 3
```

**Expected Behavior:**
After setting `n_attrs_spin` to 4 and reloading the widget with the stored settings, the spin box should display the value 4.

**Actual Behavior:**
Upon reloading, the spin box reverts to the previous value of 3 instead of retaining the newly set value of 4, causing the test to fail.
[/ISSUE]
--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.

--- BEGIN FILE ---
```
### Orange/widgets/visualize/owlinearprojection.py
"""
Linear Projection widget
------------------------
"""

from itertools import islice, permutations, chain
from math import factorial

import numpy as np

from sklearn.neighbors import NearestNeighbors
from sklearn.metrics import r2_score

from AnyQt.QtGui import QStandardItem, QPalette
from AnyQt.QtCore import Qt, QRectF, QLineF, pyqtSignal as Signal

import pyqtgraph as pg

from Orange.data import Table, Domain
from Orange.preprocess import Normalize
from Orange.preprocess.score import ReliefF, RReliefF
from Orange.projection import PCA, LDA, LinearProjector
from Orange.util import Enum
from Orange.widgets import gui, report
from Orange.widgets.gui import OWComponent
from Orange.widgets.settings import Setting, ContextSetting, SettingProvider
from Orange.widgets.utils.localization import pl
from Orange.widgets.utils.plot import variables_selection
from Orange.widgets.utils.plot.owplotgui import VariableSelectionModel
from Orange.widgets.utils.widgetpreview import WidgetPreview
from Orange.widgets.visualize.utils import VizRankDialog
from Orange.widgets.visualize.utils.component import OWGraphWithAnchors
from Orange.widgets.visualize.utils.plotutils import AnchorItem
from Orange.widgets.visualize.utils.widget import OWAnchorProjectionWidget
from Orange.widgets.widget import Msg


MAX_LABEL_LEN = 20


class LinearProjectionVizRank(VizRankDialog, OWComponent):
    captionTitle = "Score Plots"
    n_attrs = Setting(3)
    minK = 10

    attrsSelected = Signal([])
    _AttrRole = next(gui.OrangeUserRole)

    def __init__(self, master):
        # Add the spin box for a number of attributes to take into account.
        VizRankDialog.__init__(self, master)
        OWComponent.__init__(self, master)

        box = gui.hBox(self)
        max_n_attrs = len(master.model_selected)
        self.n_attrs_spin = gui.spin(
            box, self, "n_attrs", 3, max_n_attrs, label="Number of variables: ",
            controlWidth=50, alignment=Qt.AlignRight, callback=self._n_attrs_changed)
        gui.rubber(box)
        self.last_run_n_attrs = None
        self.attr_color = master.attr_color
        self.attrs = []

    def initialize(self):
        super().initialize()
        self.n_attrs_spin.setDisabled(False)
        self.attr_color = self.master.attr_color

    def before_running(self):
        """
        Disable the spin for number of attributes before running and
        enable afterwards. Also, if the number of attributes is different than
        in the last run, reset the saved state (if it was paused).
        """
        if self.n_attrs != self.last_run_n_attrs:
            self.saved_state = None
            self.saved_progress = 0
        if self.saved_state is None:
            self.scores = []
            self.rank_model.clear()
        self.last_run_n_attrs = self.n_attrs
        self.n_attrs_spin.setDisabled(True)

    def stopped(self):
        self.n_attrs_spin.setDisabled(False)

    def check_preconditions(self):
        master = self.master
        if not super().check_preconditions():
            return False
        elif not master.btn_vizrank.isEnabled():
            return False
        n_cont_var = len([v for v in master.continuous_variables
                          if v is not master.attr_color])
        self.n_attrs_spin.setMaximum(n_cont_var)
        return True

    def state_count(self):
        n_all_attrs = len(self.attrs)
        if not n_all_attrs:
            return 0
        n_attrs = self.n_attrs
        return factorial(n_all_attrs) // (2 * factorial(n_all_attrs - n_attrs) * n_attrs)

    def iterate_states(self, state):
        if state is None:  # on the first call, compute order
            self.attrs = self._score_heuristic()
            state = list(range(self.n_attrs))
        else:
            state = list(state)

        def combinations(n, s):
            while True:
                yield s
                for up, _ in enumerate(s):
                    s[up] += 1
                    if up + 1 == len(s) or s[up] < s[up + 1]:
                        break
                    s[up] = up
                if s[-1] == n:
                    break

        for c in combinations(len(self.attrs), state):
            for p in islice(permutations(c[1:]), factorial(len(c) - 1) // 2):
                yield (c[0], ) + p

    def compute_score(self, state):
        master = self.master
        data = master.data
        domain = Domain([self.attrs[i] for i in state], data.domain.class_vars)
        projection = master.projector(data.transform(domain))
        ec = projection(data).X
        y = column_data(data, self.attr_color, dtype=float)
        if ec.shape[0] < self.minK:
            return None
        n_neighbors = min(self.minK, len(ec) - 1)
        knn = NearestNeighbors(n_neighbors=n_neighbors).fit(ec)
        ind = knn.kneighbors(return_distance=False)
        # pylint: disable=invalid-unary-operand-type
        if self.attr_color.is_discrete:
            return -np.sum(y[ind] == y.reshape(-1, 1)) / n_neighbors / len(y)
        return -r2_score(y, np.mean(y[ind], axis=1)) * (len(y) / len(data))

    def bar_length(self, score):
        return max(0, -score)

    def _score_heuristic(self):
        def normalized(a):
            span = np.max(a, axis=0) - np.min(a, axis=0)
            span[span == 0] = 1
            return (a - np.mean(a, axis=0)) / span

        domain = self.master.data.domain
        attr_color = self.master.attr_color
        domain = Domain(
            attributes=[v for v in chain(domain.variables, domain.metas)
                        if v.is_continuous and v is not attr_color],
            class_vars=attr_color
        )
        data = self.master.data.transform(domain).copy()
        with data.unlocked():
            data.X = normalized(data.X)
        relief = ReliefF if attr_color.is_discrete else RReliefF
        weights = relief(n_iterations=100, k_nearest=self.minK)(data)
        results = sorted(zip(weights, domain.attributes), key=lambda x: (-x[0], x[1].name))
        return [attr for _, attr in results]

    def row_for_state(self, score, state):
        attrs = [self.attrs[i] for i in state]
        item = QStandardItem(", ".join(a.name for a in attrs))
        item.setData(attrs, self._AttrRole)
        return [item]

    def on_selection_changed(self, selected, deselected):
        if not selected.indexes():
            return
        attrs = selected.indexes()[0].data(self._AttrRole)
        self.selectionChanged.emit([attrs])

    def _n_attrs_changed(self):
        if self.n_attrs != self.last_run_n_attrs or self.saved_state is None:
            self.button.setText("Start")
        else:
            self.button.setText("Continue")
        self.button.setEnabled(self.check_preconditions())


class OWLinProjGraph(OWGraphWithAnchors):
    hide_radius = Setting(0)

    @property
    def always_show_axes(self):
        return self.master.placement == Placement.Circular

    @property
    def scaled_radius(self):
        return self.hide_radius / 100 + 1e-5

    def update_radius(self):
        self.update_circle()
        self.update_anchors()

    def set_view_box_range(self):
        def min_max(a, b):
            return (min(np.amin(a), np.amin(b), -1.05),
                    max(np.amax(a), np.amax(b), 1.05))

        points, _ = self.master.get_anchors()
        coords = self.master.get_coordinates_data()
        if points is None or coords is None:
            return

        min_x, max_x = min_max(points[:, 0], coords[0])
        min_y, max_y = min_max(points[:, 1], coords[1])
        rect = QRectF(min_x, min_y, max_x - min_x, max_y - min_y)
        self.view_box.setRange(rect, padding=0.025)

    def update_anchors(self):
        points, labels = self.master.get_anchors()
        if points is None:
            return
        r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))
        if self.anchor_items is None:
            self.anchor_items = []
            for point, label in zip(points, labels):
                anchor = AnchorItem(line=QLineF(0, 0, *point))
                anchor._label.setToolTip(f"<b>{label}</b>")
                label = label[:MAX_LABEL_LEN - 3] + "..." if len(label) > MAX_LABEL_LEN else label
                anchor.setText(label)
                anchor.setFont(self.parameter_setter.anchor_font)

                visible = self.always_show_axes or np.linalg.norm(point) > r
                anchor.setVisible(bool(visible))
                anchor.setPen(pg.mkPen((100, 100, 100)))
                self.plot_widget.addItem(anchor)
                self.anchor_items.append(anchor)
        else:
            for anchor, point, label in zip(self.anchor_items, points, labels):
                anchor.setLine(QLineF(0, 0, *point))
                visible = self.always_show_axes or np.linalg.norm(point) > r
                anchor.setVisible(bool(visible))
                anchor.setFont(self.parameter_setter.anchor_font)

    def update_circle(self):
        super().update_circle()

        if self.always_show_axes:
            self.plot_widget.removeItem(self.circle_item)
            self.circle_item = None

        if self.circle_item is not None:
            points, _ = self.master.get_anchors()
            if points is None:
                return

            r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))
            self.circle_item.setRect(QRectF(-r, -r, 2 * r, 2 * r))
            color = self.plot_widget.palette().color(QPalette.Disabled, QPalette.Text)
            pen = pg.mkPen(color, width=1, cosmetic=True)
            self.circle_item.setPen(pen)


Placement = Enum("Placement", dict(Circular=0, LDA=1, PCA=2), type=int,
                 qualname="Placement")


class OWLinearProjection(OWAnchorProjectionWidget):
    name = "Linear Projection"
    description = "A multi-axis projection of data onto " \
                  "a two-dimensional plane."
    icon = "icons/LinearProjection.svg"
    priority = 240
    keywords = "linear projection"

    Projection_name = {Placement.Circular: "Circular Placement",
                       Placement.LDA: "Linear Discriminant Analysis",
                       Placement.PCA: "Principal Component Analysis"}

    settings_version = 6

    placement = Setting(Placement.Circular)
    selected_vars = ContextSetting([])
    vizrank = SettingProvider(LinearProjectionVizRank)
    GRAPH_CLASS = OWLinProjGraph
    graph = SettingProvider(OWLinProjGraph)

    class Error(OWAnchorProjectionWidget.Error):
        no_cont_features = Msg("Plotting requires numeric features")

    class Information(OWAnchorProjectionWidget.Information):
        no_lda = Msg("LDA placement is disabled due to unsuitable target.\n{}")

    def _add_controls(self):
        box = gui.vBox(self.controlArea, box="Features")
        self._add_controls_variables(box)
        self._add_controls_placement(box)
        super()._add_controls()
        self.gui.add_control(
            self._effects_box, gui.hSlider, "Hide radius:", master=self.graph,
            value="hide_radius", minValue=0, maxValue=100, step=10,
            createLabel=False, callback=self.__radius_slider_changed
        )

    def _add_controls_variables(self, box):
        self.model_selected = VariableSelectionModel(self.selected_vars)
        variables_selection(box, self, self.model_selected)
        self.model_selected.selection_changed.connect(
            self.__model_selected_changed)
        self.vizrank, self.btn_vizrank = LinearProjectionVizRank.add_vizrank(
            None, self, "Suggest Features", self.__vizrank_set_attrs)
        box.layout().addWidget(self.btn_vizrank)

    def _add_controls_placement(self, box):
        self.radio_placement = gui.radioButtonsInBox(
            box, self, "placement",
            btnLabels=[self.Projection_name[x] for x in Placement],
            callback=self.__placement_radio_changed
        )

    def _add_buttons(self):
        self.gui.box_zoom_select(self.buttonsArea)
        gui.auto_send(self.buttonsArea, self, "auto_commit")

    @property
    def continuous_variables(self):
        if self.data is None or self.data.domain is None:
            return []
        dom = self.data.domain
        return [v for v in chain(dom.variables, dom.metas) if v.is_continuous]

    @property
    def effective_variables(self):
        return self.selected_vars

    @property
    def effective_data(self):
        cvs = None
        if self.placement == Placement.LDA:
            cvs = self.data.domain.class_vars
        return self.data.transform(Domain(self.effective_variables, cvs))

    def __vizrank_set_attrs(self, attrs):
        if not attrs:
            return
        self.selected_vars[:] = attrs
        # Ugly, but the alternative is to have yet another signal to which
        # the view will have to connect
        self.model_selected.selection_changed.emit()

    def __model_selected_changed(self):
        self.projection = None
        self._check_options()
        self.init_projection()
        self.setup_plot()
        self.commit.deferred()

    def __placement_radio_changed(self):
        self.controls.graph.hide_radius.setEnabled(
            self.placement != Placement.Circular)
        self.projection = self.projector = None
        self._init_vizrank()
        self.init_projection()
        self.setup_plot()
        self.commit.deferred()

    def __radius_slider_changed(self):
        self.graph.update_radius()

    def colors_changed(self):
        super().colors_changed()
        self._init_vizrank()

    @OWAnchorProjectionWidget.Inputs.data
    def set_data(self, data):
        super().set_data(data)
        self._check_options()
        self._init_vizrank()
        self.init_projection()

    def _check_options(self):
        buttons = self.radio_placement.buttons
        for btn in buttons:
            btn.setEnabled(True)

        problem = None
        if self.data is not None:
            if (class_var := self.data.domain.class_var) is None:
                problem = "Current data has no target variable"
            elif not class_var.is_discrete:
                problem = f"{class_var.name} is not categorical"
            elif (nclasses := len(distinct := np.unique(self.data.Y))) == 0:
                problem = f"Data has no defined values for {class_var.name}"
            elif nclasses < 3:
                vals = " and ".join(f"'{class_var.values[int(i)]}'" for i in distinct)
                problem = \
                    f"Data contains just {['one', 'two'][nclasses - 1]} distinct " \
                    f"{pl(nclasses, 'value')} ({vals}) for '{class_var.name}'; " \
                    "at least three are required."
        if problem is None:
            self.Information.no_lda.clear()
        else:
            self.Information.no_lda(problem)
            buttons[Placement.LDA].setEnabled(False)
            if self.placement == Placement.LDA:
                self.placement = Placement.Circular

        self.controls.graph.hide_radius.setEnabled(
            self.placement != Placement.Circular)

    def _init_vizrank(self):
        is_enabled, msg = False, ""
        if self.data is None:
            msg = "There is no data."
        elif self.attr_color is None:
            msg = "Color variable has to be selected"
        elif self.attr_color.is_continuous and \
                self.placement == Placement.LDA:
            msg = "Suggest Features does not work for Linear " \
                  "Discriminant Analysis Projection when " \
                  "continuous color variable is selected."
        elif len([v for v in self.continuous_variables
                  if v is not self.attr_color]) < 3:
            msg = "Not enough available continuous variables"
        elif np.sum(np.all(np.isfinite(self.data.X), axis=1)) < 2:
            msg = "Not enough valid data instances"
        else:
            is_enabled = \
                not np.isnan(self.data.get_column(self.attr_color)).all()
        self.btn_vizrank.setToolTip(msg)
        self.btn_vizrank.setEnabled(is_enabled)
        if is_enabled:
            self.vizrank.initialize()

    def check_data(self):
        def error(err):
            err()
            self.data = None

        super().check_data()
        if self.data is not None:
            if not len(self.continuous_variables):
                error(self.Error.no_cont_features)

    def init_attr_values(self):
        super().init_attr_values()
        self.selected_vars[:] = self.continuous_variables[:3]
        self.model_selected[:] = self.continuous_variables

    def init_projection(self):
        if self.placement == Placement.Circular:
            self.projector = CircularPlacement()
        elif self.placement == Placement.LDA:
            self.projector = LDA(solver="eigen", n_components=2)
        elif self.placement == Placement.PCA:
            self.projector = PCA(n_components=2)
            self.projector.component = 2
            self.projector.preprocessors = PCA.preprocessors + [Normalize()]

        super().init_projection()

    def get_coordinates_data(self):
        def normalized(a):
            span = np.max(a, axis=0) - np.min(a, axis=0)
            span[span == 0] = 1
            return (a - np.mean(a, axis=0)) / span

        embedding = self.get_embedding()
        if embedding is None:
            return None, None
        norm_emb = normalized(embedding[self.valid_data])
        return (norm_emb.ravel(), np.zeros(len(norm_emb), dtype=float)) \
            if embedding.shape[1] == 1 else norm_emb.T

    def _get_send_report_caption(self):
        def projection_name():
            return self.Projection_name[self.placement]

        return report.render_items_vert((
            ("Projection", projection_name()),
            ("Color", self._get_caption_var_name(self.attr_color)),
            ("Label", self._get_caption_var_name(self.attr_label)),
            ("Shape", self._get_caption_var_name(self.attr_shape)),
            ("Size", self._get_caption_var_name(self.attr_size)),
            ("Jittering", self.graph.jitter_size != 0 and
             "{} %".format(self.graph.jitter_size))))

    @classmethod
    def migrate_settings(cls, settings_, version):
        if version < 2:
            settings_["point_width"] = settings_["point_size"]
        if version < 3:
            settings_graph = {}
            settings_graph["jitter_size"] = settings_["jitter_value"]
            settings_graph["point_width"] = settings_["point_width"]
            settings_graph["alpha_value"] = settings_["alpha_value"]
            settings_graph["class_density"] = settings_["class_density"]
            settings_["graph"] = settings_graph
        if version < 4:
            if "radius" in settings_:
                settings_["graph"]["hide_radius"] = settings_["radius"]
            if "selection_indices" in settings_ and \
                    settings_["selection_indices"] is not None:
                selection = settings_["selection_indices"]
                settings_["selection"] = [(i, 1) for i, selected in
                                          enumerate(selection) if selected]
        if version < 5:
            if "placement" in settings_ and \
                    settings_["placement"] not in Placement:
                settings_["placement"] = Placement.Circular

    @classmethod
    def migrate_context(cls, context, version):
        values = context.values
        if version < 2:
            domain = context.ordered_domain
            c_domain = [t for t in context.ordered_domain if t[1] == 2]
            d_domain = [t for t in context.ordered_domain if t[1] == 1]
            for d, old_val, new_val in ((domain, "color_index", "attr_color"),
                                        (d_domain, "shape_index", "attr_shape"),
                                        (c_domain, "size_index", "attr_size")):
                index = context.values[old_val][0] - 1
                values[new_val] = (d[index][0], d[index][1] + 100) \
                    if 0 <= index < len(d) else None
        if version < 3:
            values["graph"] = {
                "attr_color": values["attr_color"],
                "attr_shape": values["attr_shape"],
                "attr_size": values["attr_size"]
            }
        if version == 3:
            values["attr_color"] = values["graph"]["attr_color"]
            values["attr_size"] = values["graph"]["attr_size"]
            values["attr_shape"] = values["graph"]["attr_shape"]
            values["attr_label"] = values["graph"]["attr_label"]
        if version < 6 and "selected_vars" in values:
            values["selected_vars"] = (values["selected_vars"], -3)

    # for backward compatibility with settings < 6, pull the enum from global
    # namespace into class
    Placement = Placement


def column_data(table, var, dtype):
    dtype = np.dtype(dtype)
    col = table.get_column(var)
    if dtype != col.dtype:
        col = col.astype(dtype)
    if col.base is not None:
        col = col.copy()
    return col


class CircularPlacement(LinearProjector):
    def get_components(self, X, Y):
        # Return circular axes for linear projection
        n_axes = X.shape[1]
        if n_axes == 1:
            axes_angle = [0]
        elif n_axes == 2:
            axes_angle = [0, np.pi / 2]
        else:
            axes_angle = np.linspace(0, 2 * np.pi, n_axes,
                                     endpoint=False)
        return np.vstack((np.cos(axes_angle), np.sin(axes_angle)))


if __name__ == "__main__":  # pragma: no cover
    iris = Table("iris")
    WidgetPreview(OWLinearProjection).run(set_data=iris,
                                          set_subset_data=iris[::10])

```
--- END FILE ---

Please first localize the bug based on the issue statement, and then generate *SEARCH/REPLACE* edits to fix the issue.

Every *SEARCH/REPLACE* edit must use this format:
1. The file path
2. The start of search block: <<<<<<< SEARCH
3. A contiguous chunk of lines to search for in the existing source code
4. The dividing line: =======
5. The lines to replace into the source code
6. The end of the replace block: >>>>>>> REPLACE

Here is an example:

```python
### mathweb/flask/app.py
<<<<<<< SEARCH
from flask import Flask
=======
import math
from flask import Flask
>>>>>>> REPLACE
```
</solution>

Please note that the *SEARCH/REPLACE* edit REQUIRES PROPER INDENTATION. If you would like to add the line '        print(x)', you must fully write that out, with all those spaces before the code!
Wrap each *SEARCH/REPLACE* edit in a code block as shown in the example above. If you have multiple *SEARCH/REPLACE* edits, use a separate code block for each one.
[ISSUE]
**Title:** Number of Attributes Spin Box Resets Value After Reloading Settings

**Description:**
When setting the number of attributes using the `n_attrs_spin` control and reloading the widget with stored settings, the spin box does not retain the updated value.

**Example Buggy Code:**
```python
def test_vizrank_n_attrs(self):
    self.send_signal(self.widget.Inputs.data, self.data)
    self.vizrank.n_attrs_spin.setValue(4)
    settings = self.widget.settingsHandler.pack_data(self.widget)
    widget = self.create_widget(OWLinearProjection, stored_settings=settings)
    self.send_signal(widget.Inputs.data, self.data, widget=widget)
    # After reloading, the spin box value should be 4, but it remains 3
```

**Expected Behavior:**
After setting `n_attrs_spin` to 4 and reloading the widget with the stored settings, the spin box should display the value 4.

**Actual Behavior:**
Upon reloading, the spin box reverts to the previous value of 3 instead of retaining the newly set value of 4, causing the test to fail.
[/ISSUE]
{
    "TestOWLinearProjection.test_attr_label_metas": "PASSED",
    "TestOWLinearProjection.test_attr_models": "PASSED",
    "TestOWLinearProjection.test_bad_data": "PASSED",
    "TestOWLinearProjection.test_btn_vizrank": "PASSED",
    "TestOWLinearProjection.test_buttons": "PASSED",
    "TestOWLinearProjection.test_class_density": "PASSED",
    "TestOWLinearProjection.test_data_no_cont_features": "PASSED",
    "TestOWLinearProjection.test_datasets": "PASSED",
    "TestOWLinearProjection.test_default_attrs": "PASSED",
    "TestOWLinearProjection.test_dragging_tooltip": "PASSED",
    "TestOWLinearProjection.test_embedding_missing_values": "PASSED",
    "TestOWLinearProjection.test_handle_primitive_metas": "PASSED",
    "TestOWLinearProjection.test_hidden_effective_variables": "PASSED",
    "TestOWLinearProjection.test_image_export": "PASSED",
    "TestOWLinearProjection.test_invalid_data": "PASSED",
    "TestOWLinearProjection.test_invalidated_embedding": "PASSED",
    "TestOWLinearProjection.test_invalidated_model_selected": "PASSED",
    "TestOWLinearProjection.test_lda_not_enough_distinct": "PASSED",
    "TestOWLinearProjection.test_manual_move": "PASSED",
    "TestOWLinearProjection.test_migrate_settings_from_version_1": "PASSED",
    "TestOWLinearProjection.test_minimum_size": "PASSED",
    "TestOWLinearProjection.test_msg_base_class": "PASSED",
    "TestOWLinearProjection.test_nan_plot": "PASSED",
    "TestOWLinearProjection.test_no_data_for_lda": "PASSED",
    "TestOWLinearProjection.test_none_data": "PASSED",
    "TestOWLinearProjection.test_outputs": "PASSED",
    "TestOWLinearProjection.test_plot_once": "PASSED",
    "TestOWLinearProjection.test_radius": "PASSED",
    "TestOWLinearProjection.test_saved_selection": "PASSED",
    "TestOWLinearProjection.test_send_report": "PASSED",
    "TestOWLinearProjection.test_set_radius_no_data": "PASSED",
    "TestOWLinearProjection.test_setup_graph": "PASSED",
    "TestOWLinearProjection.test_sparse_data": "PASSED",
    "TestOWLinearProjection.test_subset_data_color": "PASSED",
    "TestOWLinearProjection.test_two_classes_dataset": "PASSED",
    "TestOWLinearProjection.test_unique_name": "PASSED",
    "TestOWLinearProjection.test_visual_settings": "PASSED",
    "LinProjVizRankTests.test_continuous_class": "PASSED",
    "LinProjVizRankTests.test_discrete_class": "PASSED",
    "LinProjVizRankTests.test_image_export": "PASSED",
    "LinProjVizRankTests.test_minimum_size": "PASSED",
    "LinProjVizRankTests.test_msg_base_class": "PASSED",
    "LinProjVizRankTests.test_set_attrs": "PASSED",
    "LinProjVizRankTests.test_vizrank_n_attrs": "PASSED"
}
diff --git a/Orange/widgets/visualize/owlinearprojection.py b/Orange/widgets/visualize/owlinearprojection.py
index 3ac282b69..7054726d8 100644
--- a/Orange/widgets/visualize/owlinearprojection.py
+++ b/Orange/widgets/visualize/owlinearprojection.py
@@ -93,6 +93,7 @@ class LinearProjectionVizRank(VizRankDialog, OWComponent):
         n_cont_var = len([v for v in master.continuous_variables
                           if v is not master.attr_color])
         self.n_attrs_spin.setMaximum(n_cont_var)
+        self.n_attrs_spin.setValue(self.n_attrs)
         return True
 
     def state_count(self):

{"Orange/widgets/visualize/owlinearprojection.py": "\"\"\"\nLinear Projection widget\n------------------------\n\"\"\"\n\nfrom itertools import islice, permutations, chain\nfrom math import factorial\n\nimport numpy as np\n\nfrom sklearn.neighbors import NearestNeighbors\nfrom sklearn.metrics import r2_score\n\nfrom AnyQt.QtGui import QStandardItem, QPalette\nfrom AnyQt.QtCore import Qt, QRectF, QLineF, pyqtSignal as Signal\n\nimport pyqtgraph as pg\n\nfrom Orange.data import Table, Domain\nfrom Orange.preprocess import Normalize\nfrom Orange.preprocess.score import ReliefF, RReliefF\nfrom Orange.projection import PCA, LDA, LinearProjector\nfrom Orange.util import Enum\nfrom Orange.widgets import gui, report\nfrom Orange.widgets.gui import OWComponent\nfrom Orange.widgets.settings import Setting, ContextSetting, SettingProvider\nfrom Orange.widgets.utils.localization import pl\nfrom Orange.widgets.utils.plot import variables_selection\nfrom Orange.widgets.utils.plot.owplotgui import VariableSelectionModel\nfrom Orange.widgets.utils.widgetpreview import WidgetPreview\nfrom Orange.widgets.visualize.utils import VizRankDialog\nfrom Orange.widgets.visualize.utils.component import OWGraphWithAnchors\nfrom Orange.widgets.visualize.utils.plotutils import AnchorItem\nfrom Orange.widgets.visualize.utils.widget import OWAnchorProjectionWidget\nfrom Orange.widgets.widget import Msg\n\n\nMAX_LABEL_LEN = 20\n\n\nclass LinearProjectionVizRank(VizRankDialog, OWComponent):\n    captionTitle = \"Score Plots\"\n    n_attrs = Setting(3)\n    minK = 10\n\n    attrsSelected = Signal([])\n    _AttrRole = next(gui.OrangeUserRole)\n\n    def __init__(self, master):\n        # Add the spin box for a number of attributes to take into account.\n        VizRankDialog.__init__(self, master)\n        OWComponent.__init__(self, master)\n\n        box = gui.hBox(self)\n        max_n_attrs = len(master.model_selected)\n        self.n_attrs_spin = gui.spin(\n            box, self, \"n_attrs\", 3, max_n_attrs, label=\"Number of variables: \",\n            controlWidth=50, alignment=Qt.AlignRight, callback=self._n_attrs_changed)\n        gui.rubber(box)\n        self.last_run_n_attrs = None\n        self.attr_color = master.attr_color\n        self.attrs = []\n\n    def initialize(self):\n        super().initialize()\n        self.n_attrs_spin.setDisabled(False)\n        self.attr_color = self.master.attr_color\n\n    def before_running(self):\n        \"\"\"\n        Disable the spin for number of attributes before running and\n        enable afterwards. Also, if the number of attributes is different than\n        in the last run, reset the saved state (if it was paused).\n        \"\"\"\n        if self.n_attrs != self.last_run_n_attrs:\n            self.saved_state = None\n            self.saved_progress = 0\n        if self.saved_state is None:\n            self.scores = []\n            self.rank_model.clear()\n        self.last_run_n_attrs = self.n_attrs\n        self.n_attrs_spin.setDisabled(True)\n\n    def stopped(self):\n        self.n_attrs_spin.setDisabled(False)\n\n    def check_preconditions(self):\n        master = self.master\n        if not super().check_preconditions():\n            return False\n        elif not master.btn_vizrank.isEnabled():\n            return False\n        n_cont_var = len([v for v in master.continuous_variables\n                          if v is not master.attr_color])\n        self.n_attrs_spin.setMaximum(n_cont_var)\n        return True\n\n    def state_count(self):\n        n_all_attrs = len(self.attrs)\n        if not n_all_attrs:\n            return 0\n        n_attrs = self.n_attrs\n        return factorial(n_all_attrs) // (2 * factorial(n_all_attrs - n_attrs) * n_attrs)\n\n    def iterate_states(self, state):\n        if state is None:  # on the first call, compute order\n            self.attrs = self._score_heuristic()\n            state = list(range(self.n_attrs))\n        else:\n            state = list(state)\n\n        def combinations(n, s):\n            while True:\n                yield s\n                for up, _ in enumerate(s):\n                    s[up] += 1\n                    if up + 1 == len(s) or s[up] < s[up + 1]:\n                        break\n                    s[up] = up\n                if s[-1] == n:\n                    break\n\n        for c in combinations(len(self.attrs), state):\n            for p in islice(permutations(c[1:]), factorial(len(c) - 1) // 2):\n                yield (c[0], ) + p\n\n    def compute_score(self, state):\n        master = self.master\n        data = master.data\n        domain = Domain([self.attrs[i] for i in state], data.domain.class_vars)\n        projection = master.projector(data.transform(domain))\n        ec = projection(data).X\n        y = column_data(data, self.attr_color, dtype=float)\n        if ec.shape[0] < self.minK:\n            return None\n        n_neighbors = min(self.minK, len(ec) - 1)\n        knn = NearestNeighbors(n_neighbors=n_neighbors).fit(ec)\n        ind = knn.kneighbors(return_distance=False)\n        # pylint: disable=invalid-unary-operand-type\n        if self.attr_color.is_discrete:\n            return -np.sum(y[ind] == y.reshape(-1, 1)) / n_neighbors / len(y)\n        return -r2_score(y, np.mean(y[ind], axis=1)) * (len(y) / len(data))\n\n    def bar_length(self, score):\n        return max(0, -score)\n\n    def _score_heuristic(self):\n        def normalized(a):\n            span = np.max(a, axis=0) - np.min(a, axis=0)\n            span[span == 0] = 1\n            return (a - np.mean(a, axis=0)) / span\n\n        domain = self.master.data.domain\n        attr_color = self.master.attr_color\n        domain = Domain(\n            attributes=[v for v in chain(domain.variables, domain.metas)\n                        if v.is_continuous and v is not attr_color],\n            class_vars=attr_color\n        )\n        data = self.master.data.transform(domain).copy()\n        with data.unlocked():\n            data.X = normalized(data.X)\n        relief = ReliefF if attr_color.is_discrete else RReliefF\n        weights = relief(n_iterations=100, k_nearest=self.minK)(data)\n        results = sorted(zip(weights, domain.attributes), key=lambda x: (-x[0], x[1].name))\n        return [attr for _, attr in results]\n\n    def row_for_state(self, score, state):\n        attrs = [self.attrs[i] for i in state]\n        item = QStandardItem(\", \".join(a.name for a in attrs))\n        item.setData(attrs, self._AttrRole)\n        return [item]\n\n    def on_selection_changed(self, selected, deselected):\n        if not selected.indexes():\n            return\n        attrs = selected.indexes()[0].data(self._AttrRole)\n        self.selectionChanged.emit([attrs])\n\n    def _n_attrs_changed(self):\n        if self.n_attrs != self.last_run_n_attrs or self.saved_state is None:\n            self.button.setText(\"Start\")\n        else:\n            self.button.setText(\"Continue\")\n        self.button.setEnabled(self.check_preconditions())\n\n\nclass OWLinProjGraph(OWGraphWithAnchors):\n    hide_radius = Setting(0)\n\n    @property\n    def always_show_axes(self):\n        return self.master.placement == Placement.Circular\n\n    @property\n    def scaled_radius(self):\n        return self.hide_radius / 100 + 1e-5\n\n    def update_radius(self):\n        self.update_circle()\n        self.update_anchors()\n\n    def set_view_box_range(self):\n        def min_max(a, b):\n            return (min(np.amin(a), np.amin(b), -1.05),\n                    max(np.amax(a), np.amax(b), 1.05))\n\n        points, _ = self.master.get_anchors()\n        coords = self.master.get_coordinates_data()\n        if points is None or coords is None:\n            return\n\n        min_x, max_x = min_max(points[:, 0], coords[0])\n        min_y, max_y = min_max(points[:, 1], coords[1])\n        rect = QRectF(min_x, min_y, max_x - min_x, max_y - min_y)\n        self.view_box.setRange(rect, padding=0.025)\n\n    def update_anchors(self):\n        points, labels = self.master.get_anchors()\n        if points is None:\n            return\n        r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))\n        if self.anchor_items is None:\n            self.anchor_items = []\n            for point, label in zip(points, labels):\n                anchor = AnchorItem(line=QLineF(0, 0, *point))\n                anchor._label.setToolTip(f\"<b>{label}</b>\")\n                label = label[:MAX_LABEL_LEN - 3] + \"...\" if len(label) > MAX_LABEL_LEN else label\n                anchor.setText(label)\n                anchor.setFont(self.parameter_setter.anchor_font)\n\n                visible = self.always_show_axes or np.linalg.norm(point) > r\n                anchor.setVisible(bool(visible))\n                anchor.setPen(pg.mkPen((100, 100, 100)))\n                self.plot_widget.addItem(anchor)\n                self.anchor_items.append(anchor)\n        else:\n            for anchor, point, label in zip(self.anchor_items, points, labels):\n                anchor.setLine(QLineF(0, 0, *point))\n                visible = self.always_show_axes or np.linalg.norm(point) > r\n                anchor.setVisible(bool(visible))\n                anchor.setFont(self.parameter_setter.anchor_font)\n\n    def update_circle(self):\n        super().update_circle()\n\n        if self.always_show_axes:\n            self.plot_widget.removeItem(self.circle_item)\n            self.circle_item = None\n\n        if self.circle_item is not None:\n            points, _ = self.master.get_anchors()\n            if points is None:\n                return\n\n            r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))\n            self.circle_item.setRect(QRectF(-r, -r, 2 * r, 2 * r))\n            color = self.plot_widget.palette().color(QPalette.Disabled, QPalette.Text)\n            pen = pg.mkPen(color, width=1, cosmetic=True)\n            self.circle_item.setPen(pen)\n\n\nPlacement = Enum(\"Placement\", dict(Circular=0, LDA=1, PCA=2), type=int,\n                 qualname=\"Placement\")\n\n\nclass OWLinearProjection(OWAnchorProjectionWidget):\n    name = \"Linear Projection\"\n    description = \"A multi-axis projection of data onto \" \\\n                  \"a two-dimensional plane.\"\n    icon = \"icons/LinearProjection.svg\"\n    priority = 240\n    keywords = \"linear projection\"\n\n    Projection_name = {Placement.Circular: \"Circular Placement\",\n                       Placement.LDA: \"Linear Discriminant Analysis\",\n                       Placement.PCA: \"Principal Component Analysis\"}\n\n    settings_version = 6\n\n    placement = Setting(Placement.Circular)\n    selected_vars = ContextSetting([])\n    vizrank = SettingProvider(LinearProjectionVizRank)\n    GRAPH_CLASS = OWLinProjGraph\n    graph = SettingProvider(OWLinProjGraph)\n\n    class Error(OWAnchorProjectionWidget.Error):\n        no_cont_features = Msg(\"Plotting requires numeric features\")\n\n    class Information(OWAnchorProjectionWidget.Information):\n        no_lda = Msg(\"LDA placement is disabled due to unsuitable target.\\n{}\")\n\n    def _add_controls(self):\n        box = gui.vBox(self.controlArea, box=\"Features\")\n        self._add_controls_variables(box)\n        self._add_controls_placement(box)\n        super()._add_controls()\n        self.gui.add_control(\n            self._effects_box, gui.hSlider, \"Hide radius:\", master=self.graph,\n            value=\"hide_radius\", minValue=0, maxValue=100, step=10,\n            createLabel=False, callback=self.__radius_slider_changed\n        )\n\n    def _add_controls_variables(self, box):\n        self.model_selected = VariableSelectionModel(self.selected_vars)\n        variables_selection(box, self, self.model_selected)\n        self.model_selected.selection_changed.connect(\n            self.__model_selected_changed)\n        self.vizrank, self.btn_vizrank = LinearProjectionVizRank.add_vizrank(\n            None, self, \"Suggest Features\", self.__vizrank_set_attrs)\n        box.layout().addWidget(self.btn_vizrank)\n\n    def _add_controls_placement(self, box):\n        self.radio_placement = gui.radioButtonsInBox(\n            box, self, \"placement\",\n            btnLabels=[self.Projection_name[x] for x in Placement],\n            callback=self.__placement_radio_changed\n        )\n\n    def _add_buttons(self):\n        self.gui.box_zoom_select(self.buttonsArea)\n        gui.auto_send(self.buttonsArea, self, \"auto_commit\")\n\n    @property\n    def continuous_variables(self):\n        if self.data is None or self.data.domain is None:\n            return []\n        dom = self.data.domain\n        return [v for v in chain(dom.variables, dom.metas) if v.is_continuous]\n\n    @property\n    def effective_variables(self):\n        return self.selected_vars\n\n    @property\n    def effective_data(self):\n        cvs = None\n        if self.placement == Placement.LDA:\n            cvs = self.data.domain.class_vars\n        return self.data.transform(Domain(self.effective_variables, cvs))\n\n    def __vizrank_set_attrs(self, attrs):\n        if not attrs:\n            return\n        self.selected_vars[:] = attrs\n        # Ugly, but the alternative is to have yet another signal to which\n        # the view will have to connect\n        self.model_selected.selection_changed.emit()\n\n    def __model_selected_changed(self):\n        self.projection = None\n        self._check_options()\n        self.init_projection()\n        self.setup_plot()\n        self.commit.deferred()\n\n    def __placement_radio_changed(self):\n        self.controls.graph.hide_radius.setEnabled(\n            self.placement != Placement.Circular)\n        self.projection = self.projector = None\n        self._init_vizrank()\n        self.init_projection()\n        self.setup_plot()\n        self.commit.deferred()\n\n    def __radius_slider_changed(self):\n        self.graph.update_radius()\n\n    def colors_changed(self):\n        super().colors_changed()\n        self._init_vizrank()\n\n    @OWAnchorProjectionWidget.Inputs.data\n    def set_data(self, data):\n        super().set_data(data)\n        self._check_options()\n        self._init_vizrank()\n        self.init_projection()\n\n    def _check_options(self):\n        buttons = self.radio_placement.buttons\n        for btn in buttons:\n            btn.setEnabled(True)\n\n        problem = None\n        if self.data is not None:\n            if (class_var := self.data.domain.class_var) is None:\n                problem = \"Current data has no target variable\"\n            elif not class_var.is_discrete:\n                problem = f\"{class_var.name} is not categorical\"\n            elif (nclasses := len(distinct := np.unique(self.data.Y))) == 0:\n                problem = f\"Data has no defined values for {class_var.name}\"\n            elif nclasses < 3:\n                vals = \" and \".join(f\"'{class_var.values[int(i)]}'\" for i in distinct)\n                problem = \\\n                    f\"Data contains just {['one', 'two'][nclasses - 1]} distinct \" \\\n                    f\"{pl(nclasses, 'value')} ({vals}) for '{class_var.name}'; \" \\\n                    \"at least three are required.\"\n        if problem is None:\n            self.Information.no_lda.clear()\n        else:\n            self.Information.no_lda(problem)\n            buttons[Placement.LDA].setEnabled(False)\n            if self.placement == Placement.LDA:\n                self.placement = Placement.Circular\n\n        self.controls.graph.hide_radius.setEnabled(\n            self.placement != Placement.Circular)\n\n    def _init_vizrank(self):\n        is_enabled, msg = False, \"\"\n        if self.data is None:\n            msg = \"There is no data.\"\n        elif self.attr_color is None:\n            msg = \"Color variable has to be selected\"\n        elif self.attr_color.is_continuous and \\\n                self.placement == Placement.LDA:\n            msg = \"Suggest Features does not work for Linear \" \\\n                  \"Discriminant Analysis Projection when \" \\\n                  \"continuous color variable is selected.\"\n        elif len([v for v in self.continuous_variables\n                  if v is not self.attr_color]) < 3:\n            msg = \"Not enough available continuous variables\"\n        elif np.sum(np.all(np.isfinite(self.data.X), axis=1)) < 2:\n            msg = \"Not enough valid data instances\"\n        else:\n            is_enabled = \\\n                not np.isnan(self.data.get_column(self.attr_color)).all()\n        self.btn_vizrank.setToolTip(msg)\n        self.btn_vizrank.setEnabled(is_enabled)\n        if is_enabled:\n            self.vizrank.initialize()\n\n    def check_data(self):\n        def error(err):\n            err()\n            self.data = None\n\n        super().check_data()\n        if self.data is not None:\n            if not len(self.continuous_variables):\n                error(self.Error.no_cont_features)\n\n    def init_attr_values(self):\n        super().init_attr_values()\n        self.selected_vars[:] = self.continuous_variables[:3]\n        self.model_selected[:] = self.continuous_variables\n\n    def init_projection(self):\n        if self.placement == Placement.Circular:\n            self.projector = CircularPlacement()\n        elif self.placement == Placement.LDA:\n            self.projector = LDA(solver=\"eigen\", n_components=2)\n        elif self.placement == Placement.PCA:\n            self.projector = PCA(n_components=2)\n            self.projector.component = 2\n            self.projector.preprocessors = PCA.preprocessors + [Normalize()]\n\n        super().init_projection()\n\n    def get_coordinates_data(self):\n        def normalized(a):\n            span = np.max(a, axis=0) - np.min(a, axis=0)\n            span[span == 0] = 1\n            return (a - np.mean(a, axis=0)) / span\n\n        embedding = self.get_embedding()\n        if embedding is None:\n            return None, None\n        norm_emb = normalized(embedding[self.valid_data])\n        return (norm_emb.ravel(), np.zeros(len(norm_emb), dtype=float)) \\\n            if embedding.shape[1] == 1 else norm_emb.T\n\n    def _get_send_report_caption(self):\n        def projection_name():\n            return self.Projection_name[self.placement]\n\n        return report.render_items_vert((\n            (\"Projection\", projection_name()),\n            (\"Color\", self._get_caption_var_name(self.attr_color)),\n            (\"Label\", self._get_caption_var_name(self.attr_label)),\n            (\"Shape\", self._get_caption_var_name(self.attr_shape)),\n            (\"Size\", self._get_caption_var_name(self.attr_size)),\n            (\"Jittering\", self.graph.jitter_size != 0 and\n             \"{} %\".format(self.graph.jitter_size))))\n\n    @classmethod\n    def migrate_settings(cls, settings_, version):\n        if version < 2:\n            settings_[\"point_width\"] = settings_[\"point_size\"]\n        if version < 3:\n            settings_graph = {}\n            settings_graph[\"jitter_size\"] = settings_[\"jitter_value\"]\n            settings_graph[\"point_width\"] = settings_[\"point_width\"]\n            settings_graph[\"alpha_value\"] = settings_[\"alpha_value\"]\n            settings_graph[\"class_density\"] = settings_[\"class_density\"]\n            settings_[\"graph\"] = settings_graph\n        if version < 4:\n            if \"radius\" in settings_:\n                settings_[\"graph\"][\"hide_radius\"] = settings_[\"radius\"]\n            if \"selection_indices\" in settings_ and \\\n                    settings_[\"selection_indices\"] is not None:\n                selection = settings_[\"selection_indices\"]\n                settings_[\"selection\"] = [(i, 1) for i, selected in\n                                          enumerate(selection) if selected]\n        if version < 5:\n            if \"placement\" in settings_ and \\\n                    settings_[\"placement\"] not in Placement:\n                settings_[\"placement\"] = Placement.Circular\n\n    @classmethod\n    def migrate_context(cls, context, version):\n        values = context.values\n        if version < 2:\n            domain = context.ordered_domain\n            c_domain = [t for t in context.ordered_domain if t[1] == 2]\n            d_domain = [t for t in context.ordered_domain if t[1] == 1]\n            for d, old_val, new_val in ((domain, \"color_index\", \"attr_color\"),\n                                        (d_domain, \"shape_index\", \"attr_shape\"),\n                                        (c_domain, \"size_index\", \"attr_size\")):\n                index = context.values[old_val][0] - 1\n                values[new_val] = (d[index][0], d[index][1] + 100) \\\n                    if 0 <= index < len(d) else None\n        if version < 3:\n            values[\"graph\"] = {\n                \"attr_color\": values[\"attr_color\"],\n                \"attr_shape\": values[\"attr_shape\"],\n                \"attr_size\": values[\"attr_size\"]\n            }\n        if version == 3:\n            values[\"attr_color\"] = values[\"graph\"][\"attr_color\"]\n            values[\"attr_size\"] = values[\"graph\"][\"attr_size\"]\n            values[\"attr_shape\"] = values[\"graph\"][\"attr_shape\"]\n            values[\"attr_label\"] = values[\"graph\"][\"attr_label\"]\n        if version < 6 and \"selected_vars\" in values:\n            values[\"selected_vars\"] = (values[\"selected_vars\"], -3)\n\n    # for backward compatibility with settings < 6, pull the enum from global\n    # namespace into class\n    Placement = Placement\n\n\ndef column_data(table, var, dtype):\n    dtype = np.dtype(dtype)\n    col = table.get_column(var)\n    if dtype != col.dtype:\n        col = col.astype(dtype)\n    if col.base is not None:\n        col = col.copy()\n    return col\n\n\nclass CircularPlacement(LinearProjector):\n    def get_components(self, X, Y):\n        # Return circular axes for linear projection\n        n_axes = X.shape[1]\n        if n_axes == 1:\n            axes_angle = [0]\n        elif n_axes == 2:\n            axes_angle = [0, np.pi / 2]\n        else:\n            axes_angle = np.linspace(0, 2 * np.pi, n_axes,\n                                     endpoint=False)\n        return np.vstack((np.cos(axes_angle), np.sin(axes_angle)))\n\n\nif __name__ == \"__main__\":  # pragma: no cover\n    iris = Table(\"iris\")\n    WidgetPreview(OWLinearProjection).run(set_data=iris,\n                                          set_subset_data=iris[::10])\n"}
A user will ask you to solve a task. You should first draft your thinking process (inner monologue). Then, generate the solution.

Your response format must follow the template below:
<think>
Your thoughts or/and draft, like working through an exercise on scratch paper. Be as casual and as long as you want until you are confident to generate a correct solution.
</think>
<solution>
Final solution presented to the user.
</solution>
system
We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
[ISSUE]
**Title:** Number of Attributes Spin Box Resets Value After Reloading Settings

**Description:**
When setting the number of attributes using the `n_attrs_spin` control and reloading the widget with stored settings, the spin box does not retain the updated value.

**Example Buggy Code:**
```python
def test_vizrank_n_attrs(self):
    self.send_signal(self.widget.Inputs.data, self.data)
    self.vizrank.n_attrs_spin.setValue(4)
    settings = self.widget.settingsHandler.pack_data(self.widget)
    widget = self.create_widget(OWLinearProjection, stored_settings=settings)
    self.send_signal(widget.Inputs.data, self.data, widget=widget)
    # After reloading, the spin box value should be 4, but it remains 3
```

**Expected Behavior:**
After setting `n_attrs_spin` to 4 and reloading the widget with the stored settings, the spin box should display the value 4.

**Actual Behavior:**
Upon reloading, the spin box reverts to the previous value of 3 instead of retaining the newly set value of 4, causing the test to fail.
[/ISSUE]
--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.

--- BEGIN FILE ---
```
### Orange/widgets/visualize/owlinearprojection.py
"""
Linear Projection widget
------------------------
"""

from itertools import islice, permutations, chain
from math import factorial

import numpy as np

from sklearn.neighbors import NearestNeighbors
from sklearn.metrics import r2_score

from AnyQt.QtGui import QStandardItem, QPalette
from AnyQt.QtCore import Qt, QRectF, QLineF, pyqtSignal as Signal

import pyqtgraph as pg

from Orange.data import Table, Domain
from Orange.preprocess import Normalize
from Orange.preprocess.score import ReliefF, RReliefF
from Orange.projection import PCA, LDA, LinearProjector
from Orange.util import Enum
from Orange.widgets import gui, report
from Orange.widgets.gui import OWComponent
from Orange.widgets.settings import Setting, ContextSetting, SettingProvider
from Orange.widgets.utils.localization import pl
from Orange.widgets.utils.plot import variables_selection
from Orange.widgets.utils.plot.owplotgui import VariableSelectionModel
from Orange.widgets.utils.widgetpreview import WidgetPreview
from Orange.widgets.visualize.utils import VizRankDialog
from Orange.widgets.visualize.utils.component import OWGraphWithAnchors
from Orange.widgets.visualize.utils.plotutils import AnchorItem
from Orange.widgets.visualize.utils.widget import OWAnchorProjectionWidget
from Orange.widgets.widget import Msg


MAX_LABEL_LEN = 20


class LinearProjectionVizRank(VizRankDialog, OWComponent):
    captionTitle = "Score Plots"
    n_attrs = Setting(3)
    minK = 10

    attrsSelected = Signal([])
    _AttrRole = next(gui.OrangeUserRole)

    def __init__(self, master):
        # Add the spin box for a number of attributes to take into account.
        VizRankDialog.__init__(self, master)
        OWComponent.__init__(self, master)

        box = gui.hBox(self)
        max_n_attrs = len(master.model_selected)
        self.n_attrs_spin = gui.spin(
            box, self, "n_attrs", 3, max_n_attrs, label="Number of variables: ",
            controlWidth=50, alignment=Qt.AlignRight, callback=self._n_attrs_changed)
        gui.rubber(box)
        self.last_run_n_attrs = None
        self.attr_color = master.attr_color
        self.attrs = []

    def initialize(self):
        super().initialize()
        self.n_attrs_spin.setDisabled(False)
        self.attr_color = self.master.attr_color

    def before_running(self):
        """
        Disable the spin for number of attributes before running and
        enable afterwards. Also, if the number of attributes is different than
        in the last run, reset the saved state (if it was paused).
        """
        if self.n_attrs != self.last_run_n_attrs:
            self.saved_state = None
            self.saved_progress = 0
        if self.saved_state is None:
            self.scores = []
            self.rank_model.clear()
        self.last_run_n_attrs = self.n_attrs
        self.n_attrs_spin.setDisabled(True)

    def stopped(self):
        self.n_attrs_spin.setDisabled(False)

    def check_preconditions(self):
        master = self.master
        if not super().check_preconditions():
            return False
        elif not master.btn_vizrank.isEnabled():
            return False
        n_cont_var = len([v for v in master.continuous_variables
                          if v is not master.attr_color])
        self.n_attrs_spin.setMaximum(n_cont_var)
        return True

    def state_count(self):
        n_all_attrs = len(self.attrs)
        if not n_all_attrs:
            return 0
        n_attrs = self.n_attrs
        return factorial(n_all_attrs) // (2 * factorial(n_all_attrs - n_attrs) * n_attrs)

    def iterate_states(self, state):
        if state is None:  # on the first call, compute order
            self.attrs = self._score_heuristic()
            state = list(range(self.n_attrs))
        else:
            state = list(state)

        def combinations(n, s):
            while True:
                yield s
                for up, _ in enumerate(s):
                    s[up] += 1
                    if up + 1 == len(s) or s[up] < s[up + 1]:
                        break
                    s[up] = up
                if s[-1] == n:
                    break

        for c in combinations(len(self.attrs), state):
            for p in islice(permutations(c[1:]), factorial(len(c) - 1) // 2):
                yield (c[0], ) + p

    def compute_score(self, state):
        master = self.master
        data = master.data
        domain = Domain([self.attrs[i] for i in state], data.domain.class_vars)
        projection = master.projector(data.transform(domain))
        ec = projection(data).X
        y = column_data(data, self.attr_color, dtype=float)
        if ec.shape[0] < self.minK:
            return None
        n_neighbors = min(self.minK, len(ec) - 1)
        knn = NearestNeighbors(n_neighbors=n_neighbors).fit(ec)
        ind = knn.kneighbors(return_distance=False)
        # pylint: disable=invalid-unary-operand-type
        if self.attr_color.is_discrete:
            return -np.sum(y[ind] == y.reshape(-1, 1)) / n_neighbors / len(y)
        return -r2_score(y, np.mean(y[ind], axis=1)) * (len(y) / len(data))

    def bar_length(self, score):
        return max(0, -score)

    def _score_heuristic(self):
        def normalized(a):
            span = np.max(a, axis=0) - np.min(a, axis=0)
            span[span == 0] = 1
            return (a - np.mean(a, axis=0)) / span

        domain = self.master.data.domain
        attr_color = self.master.attr_color
        domain = Domain(
            attributes=[v for v in chain(domain.variables, domain.metas)
                        if v.is_continuous and v is not attr_color],
            class_vars=attr_color
        )
        data = self.master.data.transform(domain).copy()
        with data.unlocked():
            data.X = normalized(data.X)
        relief = ReliefF if attr_color.is_discrete else RReliefF
        weights = relief(n_iterations=100, k_nearest=self.minK)(data)
        results = sorted(zip(weights, domain.attributes), key=lambda x: (-x[0], x[1].name))
        return [attr for _, attr in results]

    def row_for_state(self, score, state):
        attrs = [self.attrs[i] for i in state]
        item = QStandardItem(", ".join(a.name for a in attrs))
        item.setData(attrs, self._AttrRole)
        return [item]

    def on_selection_changed(self, selected, deselected):
        if not selected.indexes():
            return
        attrs = selected.indexes()[0].data(self._AttrRole)
        self.selectionChanged.emit([attrs])

    def _n_attrs_changed(self):
        if self.n_attrs != self.last_run_n_attrs or self.saved_state is None:
            self.button.setText("Start")
        else:
            self.button.setText("Continue")
        self.button.setEnabled(self.check_preconditions())


class OWLinProjGraph(OWGraphWithAnchors):
    hide_radius = Setting(0)

    @property
    def always_show_axes(self):
        return self.master.placement == Placement.Circular

    @property
    def scaled_radius(self):
        return self.hide_radius / 100 + 1e-5

    def update_radius(self):
        self.update_circle()
        self.update_anchors()

    def set_view_box_range(self):
        def min_max(a, b):
            return (min(np.amin(a), np.amin(b), -1.05),
                    max(np.amax(a), np.amax(b), 1.05))

        points, _ = self.master.get_anchors()
        coords = self.master.get_coordinates_data()
        if points is None or coords is None:
            return

        min_x, max_x = min_max(points[:, 0], coords[0])
        min_y, max_y = min_max(points[:, 1], coords[1])
        rect = QRectF(min_x, min_y, max_x - min_x, max_y - min_y)
        self.view_box.setRange(rect, padding=0.025)

    def update_anchors(self):
        points, labels = self.master.get_anchors()
        if points is None:
            return
        r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))
        if self.anchor_items is None:
            self.anchor_items = []
            for point, label in zip(points, labels):
                anchor = AnchorItem(line=QLineF(0, 0, *point))
                anchor._label.setToolTip(f"<b>{label}</b>")
                label = label[:MAX_LABEL_LEN - 3] + "..." if len(label) > MAX_LABEL_LEN else label
                anchor.setText(label)
                anchor.setFont(self.parameter_setter.anchor_font)

                visible = self.always_show_axes or np.linalg.norm(point) > r
                anchor.setVisible(bool(visible))
                anchor.setPen(pg.mkPen((100, 100, 100)))
                self.plot_widget.addItem(anchor)
                self.anchor_items.append(anchor)
        else:
            for anchor, point, label in zip(self.anchor_items, points, labels):
                anchor.setLine(QLineF(0, 0, *point))
                visible = self.always_show_axes or np.linalg.norm(point) > r
                anchor.setVisible(bool(visible))
                anchor.setFont(self.parameter_setter.anchor_font)

    def update_circle(self):
        super().update_circle()

        if self.always_show_axes:
            self.plot_widget.removeItem(self.circle_item)
            self.circle_item = None

        if self.circle_item is not None:
            points, _ = self.master.get_anchors()
            if points is None:
                return

            r = self.scaled_radius * np.max(np.linalg.norm(points, axis=1))
            self.circle_item.setRect(QRectF(-r, -r, 2 * r, 2 * r))
            color = self.plot_widget.palette().color(QPalette.Disabled, QPalette.Text)
            pen = pg.mkPen(color, width=1, cosmetic=True)
            self.circle_item.setPen(pen)


Placement = Enum("Placement", dict(Circular=0, LDA=1, PCA=2), type=int,
                 qualname="Placement")


class OWLinearProjection(OWAnchorProjectionWidget):
    name = "Linear Projection"
    description = "A multi-axis projection of data onto " \
                  "a two-dimensional plane."
    icon = "icons/LinearProjection.svg"
    priority = 240
    keywords = "linear projection"

    Projection_name = {Placement.Circular: "Circular Placement",
                       Placement.LDA: "Linear Discriminant Analysis",
                       Placement.PCA: "Principal Component Analysis"}

    settings_version = 6

    placement = Setting(Placement.Circular)
    selected_vars = ContextSetting([])
    vizrank = SettingProvider(LinearProjectionVizRank)
    GRAPH_CLASS = OWLinProjGraph
    graph = SettingProvider(OWLinProjGraph)

    class Error(OWAnchorProjectionWidget.Error):
        no_cont_features = Msg("Plotting requires numeric features")

    class Information(OWAnchorProjectionWidget.Information):
        no_lda = Msg("LDA placement is disabled due to unsuitable target.\n{}")

    def _add_controls(self):
        box = gui.vBox(self.controlArea, box="Features")
        self._add_controls_variables(box)
        self._add_controls_placement(box)
        super()._add_controls()
        self.gui.add_control(
            self._effects_box, gui.hSlider, "Hide radius:", master=self.graph,
            value="hide_radius", minValue=0, maxValue=100, step=10,
            createLabel=False, callback=self.__radius_slider_changed
        )

    def _add_controls_variables(self, box):
        self.model_selected = VariableSelectionModel(self.selected_vars)
        variables_selection(box, self, self.model_selected)
        self.model_selected.selection_changed.connect(
            self.__model_selected_changed)
        self.vizrank, self.btn_vizrank = LinearProjectionVizRank.add_vizrank(
            None, self, "Suggest Features", self.__vizrank_set_attrs)
        box.layout().addWidget(self.btn_vizrank)

    def _add_controls_placement(self, box):
        self.radio_placement = gui.radioButtonsInBox(
            box, self, "placement",
            btnLabels=[self.Projection_name[x] for x in Placement],
            callback=self.__placement_radio_changed
        )

    def _add_buttons(self):
        self.gui.box_zoom_select(self.buttonsArea)
        gui.auto_send(self.buttonsArea, self, "auto_commit")

    @property
    def continuous_variables(self):
        if self.data is None or self.data.domain is None:
            return []
        dom = self.data.domain
        return [v for v in chain(dom.variables, dom.metas) if v.is_continuous]

    @property
    def effective_variables(self):
        return self.selected_vars

    @property
    def effective_data(self):
        cvs = None
        if self.placement == Placement.LDA:
            cvs = self.data.domain.class_vars
        return self.data.transform(Domain(self.effective_variables, cvs))

    def __vizrank_set_attrs(self, attrs):
        if not attrs:
            return
        self.selected_vars[:] = attrs
        # Ugly, but the alternative is to have yet another signal to which
        # the view will have to connect
        self.model_selected.selection_changed.emit()

    def __model_selected_changed(self):
        self.projection = None
        self._check_options()
        self.init_projection()
        self.setup_plot()
        self.commit.deferred()

    def __placement_radio_changed(self):
        self.controls.graph.hide_radius.setEnabled(
            self.placement != Placement.Circular)
        self.projection = self.projector = None
        self._init_vizrank()
        self.init_projection()
        self.setup_plot()
        self.commit.deferred()

    def __radius_slider_changed(self):
        self.graph.update_radius()

    def colors_changed(self):
        super().colors_changed()
        self._init_vizrank()

    @OWAnchorProjectionWidget.Inputs.data
    def set_data(self, data):
        super().set_data(data)
        self._check_options()
        self._init_vizrank()
        self.init_projection()

    def _check_options(self):
        buttons = self.radio_placement.buttons
        for btn in buttons:
            btn.setEnabled(True)

        problem = None
        if self.data is not None:
            if (class_var := self.data.domain.class_var) is None:
                problem = "Current data has no target variable"
            elif not class_var.is_discrete:
                problem = f"{class_var.name} is not categorical"
            elif (nclasses := len(distinct := np.unique(self.data.Y))) == 0:
                problem = f"Data has no defined values for {class_var.name}"
            elif nclasses < 3:
                vals = " and ".join(f"'{class_var.values[int(i)]}'" for i in distinct)
                problem = \
                    f"Data contains just {['one', 'two'][nclasses - 1]} distinct " \
                    f"{pl(nclasses, 'value')} ({vals}) for '{class_var.name}'; " \
                    "at least three are required."
        if problem is None:
            self.Information.no_lda.clear()
        else:
            self.Information.no_lda(problem)
            buttons[Placement.LDA].setEnabled(False)
            if self.placement == Placement.LDA:
                self.placement = Placement.Circular

        self.controls.graph.hide_radius.setEnabled(
            self.placement != Placement.Circular)

    def _init_vizrank(self):
        is_enabled, msg = False, ""
        if self.data is None:
            msg = "There is no data."
        elif self.attr_color is None:
            msg = "Color variable has to be selected"
        elif self.attr_color.is_continuous and \
                self.placement == Placement.LDA:
            msg = "Suggest Features does not work for Linear " \
                  "Discriminant Analysis Projection when " \
                  "continuous color variable is selected."
        elif len([v for v in self.continuous_variables
                  if v is not self.attr_color]) < 3:
            msg = "Not enough available continuous variables"
        elif np.sum(np.all(np.isfinite(self.data.X), axis=1)) < 2:
            msg = "Not enough valid data instances"
        else:
            is_enabled = \
                not np.isnan(self.data.get_column(self.attr_color)).all()
        self.btn_vizrank.setToolTip(msg)
        self.btn_vizrank.setEnabled(is_enabled)
        if is_enabled:
            self.vizrank.initialize()

    def check_data(self):
        def error(err):
            err()
            self.data = None

        super().check_data()
        if self.data is not None:
            if not len(self.continuous_variables):
                error(self.Error.no_cont_features)

    def init_attr_values(self):
        super().init_attr_values()
        self.selected_vars[:] = self.continuous_variables[:3]
        self.model_selected[:] = self.continuous_variables

    def init_projection(self):
        if self.placement == Placement.Circular:
            self.projector = CircularPlacement()
        elif self.placement == Placement.LDA:
            self.projector = LDA(solver="eigen", n_components=2)
        elif self.placement == Placement.PCA:
            self.projector = PCA(n_components=2)
            self.projector.component = 2
            self.projector.preprocessors = PCA.preprocessors + [Normalize()]

        super().init_projection()

    def get_coordinates_data(self):
        def normalized(a):
            span = np.max(a, axis=0) - np.min(a, axis=0)
            span[span == 0] = 1
            return (a - np.mean(a, axis=0)) / span

        embedding = self.get_embedding()
        if embedding is None:
            return None, None
        norm_emb = normalized(embedding[self.valid_data])
        return (norm_emb.ravel(), np.zeros(len(norm_emb), dtype=float)) \
            if embedding.shape[1] == 1 else norm_emb.T

    def _get_send_report_caption(self):
        def projection_name():
            return self.Projection_name[self.placement]

        return report.render_items_vert((
            ("Projection", projection_name()),
            ("Color", self._get_caption_var_name(self.attr_color)),
            ("Label", self._get_caption_var_name(self.attr_label)),
            ("Shape", self._get_caption_var_name(self.attr_shape)),
            ("Size", self._get_caption_var_name(self.attr_size)),
            ("Jittering", self.graph.jitter_size != 0 and
             "{} %".format(self.graph.jitter_size))))

    @classmethod
    def migrate_settings(cls, settings_, version):
        if version < 2:
            settings_["point_width"] = settings_["point_size"]
        if version < 3:
            settings_graph = {}
            settings_graph["jitter_size"] = settings_["jitter_value"]
            settings_graph["point_width"] = settings_["point_width"]
            settings_graph["alpha_value"] = settings_["alpha_value"]
            settings_graph["class_density"] = settings_["class_density"]
            settings_["graph"] = settings_graph
        if version < 4:
            if "radius" in settings_:
                settings_["graph"]["hide_radius"] = settings_["radius"]
            if "selection_indices" in settings_ and \
                    settings_["selection_indices"] is not None:
                selection = settings_["selection_indices"]
                settings_["selection"] = [(i, 1) for i, selected in
                                          enumerate(selection) if selected]
        if version < 5:
            if "placement" in settings_ and \
                    settings_["placement"] not in Placement:
                settings_["placement"] = Placement.Circular

    @classmethod
    def migrate_context(cls, context, version):
        values = context.values
        if version < 2:
            domain = context.ordered_domain
            c_domain = [t for t in context.ordered_domain if t[1] == 2]
            d_domain = [t for t in context.ordered_domain if t[1] == 1]
            for d, old_val, new_val in ((domain, "color_index", "attr_color"),
                                        (d_domain, "shape_index", "attr_shape"),
                                        (c_domain, "size_index", "attr_size")):
                index = context.values[old_val][0] - 1
                values[new_val] = (d[index][0], d[index][1] + 100) \
                    if 0 <= index < len(d) else None
        if version < 3:
            values["graph"] = {
                "attr_color": values["attr_color"],
                "attr_shape": values["attr_shape"],
                "attr_size": values["attr_size"]
            }
        if version == 3:
            values["attr_color"] = values["graph"]["attr_color"]
            values["attr_size"] = values["graph"]["attr_size"]
            values["attr_shape"] = values["graph"]["attr_shape"]
            values["attr_label"] = values["graph"]["attr_label"]
        if version < 6 and "selected_vars" in values:
            values["selected_vars"] = (values["selected_vars"], -3)

    # for backward compatibility with settings < 6, pull the enum from global
    # namespace into class
    Placement = Placement


def column_data(table, var, dtype):
    dtype = np.dtype(dtype)
    col = table.get_column(var)
    if dtype != col.dtype:
        col = col.astype(dtype)
    if col.base is not None:
        col = col.copy()
    return col


class CircularPlacement(LinearProjector):
    def get_components(self, X, Y):
        # Return circular axes for linear projection
        n_axes = X.shape[1]
        if n_axes == 1:
            axes_angle = [0]
        elif n_axes == 2:
            axes_angle = [0, np.pi / 2]
        else:
            axes_angle = np.linspace(0, 2 * np.pi, n_axes,
                                     endpoint=False)
        return np.vstack((np.cos(axes_angle), np.sin(axes_angle)))


if __name__ == "__main__":  # pragma: no cover
    iris = Table("iris")
    WidgetPreview(OWLinearProjection).run(set_data=iris,
                                          set_subset_data=iris[::10])

```
--- END FILE ---

Please first localize the bug based on the issue statement, and then generate *SEARCH/REPLACE* edits to fix the issue.

Every *SEARCH/REPLACE* edit must use this format:
1. The file path
2. The start of search block: <<<<<<< SEARCH
3. A contiguous chunk of lines to search for in the existing source code
4. The dividing line: =======
5. The lines to replace into the source code
6. The end of the replace block: >>>>>>> REPLACE

Here is an example:

```python
### mathweb/flask/app.py
<<<<<<< SEARCH
from flask import Flask
=======
import math
from flask import Flask
>>>>>>> REPLACE
```
</solution>

Please note that the *SEARCH/REPLACE* edit REQUIRES PROPER INDENTATION. If you would like to add the line '        print(x)', you must fully write that out, with all those spaces before the code!
Wrap each *SEARCH/REPLACE* edit in a code block as shown in the example above. If you have multiple *SEARCH/REPLACE* edits, use a separate code block for each one.
user