def _get_target(scene, painter, buffer, source): try: brush = scene.backgroundBrush() if brush.style() == QtCore.Qt.NoBrush: brush = QtGui.QBrush(scene.palette().color(QtGui.QPalette.Base)) except AttributeError: # not a QGraphicsView/Scene brush = QtGui.QBrush(QtCore.Qt.white) painter.fillRect(buffer.rect(), brush) return QtCore.QRectF(0, 0, source.width(), source.height())
def paint(self, painter, option, index): painter.save() self.drawBackground(painter, option, index) ratio = index.data(TableBarItem.BarRole) if isinstance(ratio, float): if math.isnan(ratio): ratio = None color = None if ratio is not None: if self.color_schema is not None: class_ = index.data(TableClassValueRole) if isinstance(class_, Orange.data.Value) and \ class_.variable.is_discrete and \ not math.isnan(class_): color = self.color_schema[int(class_)] else: color = index.data(self.BarColorRole) if color is None: color = self.color rect = option.rect if ratio is not None: pw = 5 hmargin = 3 + pw / 2 # + half pen width for the round line cap vmargin = 1 textoffset = pw + vmargin * 2 baseline = rect.bottom() - textoffset / 2 width = (rect.width() - 2 * hmargin) * ratio painter.save() painter.setRenderHint(QtGui.QPainter.Antialiasing) painter.setPen(QtGui.QPen(QtGui.QBrush(color), pw, Qt.SolidLine, Qt.RoundCap)) line = QtCore.QLineF( rect.left() + hmargin, baseline, rect.left() + hmargin + width, baseline ) painter.drawLine(line) painter.restore() text_rect = rect.adjusted(0, 0, 0, -textoffset) else: text_rect = rect text = str(index.data(Qt.DisplayRole)) self.drawDisplay(painter, option, text_rect, text) painter.restore()
def update_stats_model(self): # Update the results_model with up to date scores. # Note: The target class specific scores (if requested) are # computed as needed in this method. model = self.score_table.model # clear the table model, but preserving the header labels for r in reversed(range(model.rowCount())): model.takeRow(r) target_index = None if self.data is not None: class_var = self.data.domain.class_var if self.data.domain.has_discrete_class and \ self.class_selection != self.TARGET_AVERAGE: target_index = class_var.values.index(self.class_selection) else: class_var = None errors = [] has_missing_scores = False names = [] for key, slot in self.learners.items(): name = learner_name(slot.learner) names.append(name) head = QStandardItem(name) head.setData(key, Qt.UserRole) results = slot.results if results is not None and results.success: train = QStandardItem("{:.3f}".format( results.value.train_time)) train.setTextAlignment(Qt.AlignRight | Qt.AlignVCenter) train.setData(key, Qt.UserRole) test = QStandardItem("{:.3f}".format(results.value.test_time)) test.setTextAlignment(Qt.AlignRight | Qt.AlignVCenter) test.setData(key, Qt.UserRole) row = [head, train, test] else: row = [head] if isinstance(results, Try.Fail): head.setToolTip(str(results.exception)) head.setText("{} (error)".format(name)) head.setForeground(QtGui.QBrush(Qt.red)) if isinstance(results.exception, DomainTransformationError) \ and self.resampling == self.TestOnTest: self.Error.test_data_incompatible() self.Information.test_data_transformed.clear() else: errors.append("{name} failed with error:\n" "{exc.__class__.__name__}: {exc!s}".format( name=name, exc=slot.results.exception)) if class_var is not None and class_var.is_discrete and \ target_index is not None: if slot.results is not None and slot.results.success: ovr_results = results_one_vs_rest(slot.results.value, target_index) # Cell variable is used immediatelly, it's not stored # pylint: disable=cell-var-from-loop stats = [ Try(scorer_caller(scorer, ovr_results, target=1)) for scorer in self.scorers ] else: stats = None else: stats = slot.stats if stats is not None: for stat, scorer in zip(stats, self.scorers): item = QStandardItem() item.setTextAlignment(Qt.AlignRight | Qt.AlignVCenter) if stat.success: item.setData(float(stat.value[0]), Qt.DisplayRole) else: item.setToolTip(str(stat.exception)) if scorer.name in self.score_table.shown_scores: has_missing_scores = True row.append(item) model.appendRow(row) # Resort rows based on current sorting header = self.score_table.view.horizontalHeader() model.sort(header.sortIndicatorSection(), header.sortIndicatorOrder()) self._set_comparison_headers(names) self.error("\n".join(errors), shown=bool(errors)) self.Warning.scores_not_computed(shown=has_missing_scores)
def _update_stats_model(self): # Update the results_model with up to date scores. # Note: The target class specific scores (if requested) are # computed as needed in this method. model = self.view.model() # clear the table model, but preserving the header labels for r in reversed(range(model.rowCount())): model.takeRow(r) target_index = None if self.data is not None: class_var = self.data.domain.class_var if self.data.domain.has_discrete_class and \ self.class_selection != self.TARGET_AVERAGE: target_index = class_var.values.index(self.class_selection) else: class_var = None errors = [] has_missing_scores = False for key, slot in self.learners.items(): name = learner_name(slot.learner) head = QStandardItem(name) head.setData(key, Qt.UserRole) if isinstance(slot.results, Try.Fail): head.setToolTip(str(slot.results.exception)) head.setText("{} (error)".format(name)) head.setForeground(QtGui.QBrush(Qt.red)) errors.append("{name} failed with error:\n" "{exc.__class__.__name__}: {exc!s}".format( name=name, exc=slot.results.exception)) row = [head] if class_var is not None and class_var.is_discrete and \ target_index is not None: if slot.results is not None and slot.results.success: ovr_results = results_one_vs_rest(slot.results.value, target_index) # Cell variable is used immediatelly, it's not stored # pylint: disable=cell-var-from-loop stats = [ Try(scorer_caller(scorer, ovr_results)) for scorer in self.scorers ] else: stats = None else: stats = slot.stats if stats is not None: for stat in stats: item = QStandardItem() if stat.success: item.setText("{:.3f}".format(stat.value[0])) else: item.setToolTip(str(stat.exception)) has_missing_scores = True row.append(item) model.appendRow(row) self.error("\n".join(errors), shown=bool(errors)) self.Warning.scores_not_computed(shown=has_missing_scores)