def main(): # example from https://github.com/marinkaz/scikit-fusion import numpy as np from AnyQt.QtWidgets import QApplication R12 = np.random.rand(50, 100) R32 = np.random.rand(100, 150) R33 = np.random.rand(150, 150) R13 = np.random.rand(50, 150) t1 = fusion.ObjectType('Users', 10) t2 = fusion.ObjectType('Movies', 30) t3 = fusion.ObjectType('Actors', 40) relations = [fusion.Relation(R12, t1, t2, name='like'), fusion.Relation(R13, t1, t3, name='are fans of'), fusion.Relation(R12, t1, t2, name='don\'t like'), fusion.Relation(R33, t3, t3, name='married to'), fusion.Relation(R32, t2, t3, name='feature')] G = fusion.FusionGraph() for rel in relations: G.add_relation(rel) fuser = fusion.Dfmf() fuser.fuse(G) app = QApplication([]) w = OWChaining() w.on_fuser_change(FittedFusionGraph(fuser)) w.show() app.exec()
def main(): from AnyQt.QtWidgets import QApplication t1 = fusion.ObjectType('Users', 10) t2 = fusion.ObjectType('Movies', 30) t3 = fusion.ObjectType('Actors', 40) # test that MeanFuser completes correctly R = np.ma.array([[1, 1, 0], [3, 0, 0]], mask=[[0, 0, 1], [0, 1, 1]], dtype=float) rel = fusion.Relation(R, t1, t2) assert (MeanFuser(0).complete(rel) == [[1, 1, 5 / 3], [3, 1, 5 / 3]]).all() assert (MeanFuser(1).complete(rel) == [[1, 1, 1], [3, 3, 3]]).all() assert (MeanFuser(2).complete(rel) == [[1, 1, 5 / 3], [3, 5 / 3, 5 / 3]]).all() R1 = np.ma.array(np.random.random((20, 20))) R2 = np.ma.array(np.random.random((40, 40)), mask=np.random.random((40, 40)) > .8) relations = [ fusion.Relation(R1, t1, t2, name='like'), fusion.Relation(R2, t3, t2, name='feature in'), ] G = fusion.FusionGraph() G.add_relations_from(relations) app = QApplication([]) w = OWMeanFuser() w.on_fusion_graph_change(G) w.show() app.exec()
def main(): """ A simple test. """ app = QApplication([]) def _on_selected_points(points): print(len(points), points) xAxis = { 'type': 'category', 'data': ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'] } yAxis = { 'type': 'value' } series = [{ 'data': [820, 932, 901, 934, 1290, 1330, 1320], 'type': 'line' }] options = { 'xAxis': xAxis, 'yAxis': yAxis, 'series': series } w = Echarts(debug=True) w.chart(options=options) w.show() app.exec()
def main(): from Orange.data import Table, Domain, ContinuousVariable, StringVariable words = 'hey~mr. tallyman tally~me banana daylight come and me wanna go home' words = np.array([w.replace('~', ' ') for w in words.split()], dtype=object, ndmin=2).T weights = np.random.random((len(words), 1)) data = np.zeros((len(words), 0)) metas = [] for i, w in enumerate(weights.T): data = np.column_stack((data, words, w)) metas = metas + [StringVariable('Topic' + str(i)), ContinuousVariable('weights')] domain = Domain([], metas=metas) table = Table.from_numpy(domain, X=np.zeros((len(words), 0)), metas=data) app = QApplication(['']) w = OWWordCloud() w.on_topic_change(table) domain = Domain([], metas=[StringVariable('text')]) data = Corpus(domain=domain, metas=np.array([[' '.join(words.flat)]])) # data = Corpus.from_numpy(domain, X=np.zeros((1, 0)), metas=np.array([[' '.join(words.flat)]])) w.on_corpus_change(data) w.show() app.exec()
def main(): from Orange.data import Table, Domain, ContinuousVariable, StringVariable words = 'hey~mr. tallyman tally~me banana daylight come and me wanna go home' words = np.array([w.replace('~', ' ') for w in words.split()], dtype=object, ndmin=2).T weights = np.random.random((len(words), 1)) data = np.zeros((len(words), 0)) metas = [] for i, w in enumerate(weights.T): data = np.column_stack((data, words, w)) metas = metas + [ StringVariable('Topic' + str(i)), ContinuousVariable('weights') ] domain = Domain([], metas=metas) table = Table.from_numpy(domain, X=np.zeros((len(words), 0)), metas=data) app = QApplication(['']) w = OWWordCloud() w.on_topic_change(table) domain = Domain([], metas=[StringVariable('text')]) data = Corpus(domain=domain, metas=np.array([[' '.join(words.flat)]])) # data = Corpus.from_numpy(domain, X=np.zeros((1, 0)), metas=np.array([[' '.join(words.flat)]])) w.on_corpus_change(data) w.handleNewSignals() w.show() app.exec()
def main(): from AnyQt.QtWidgets import QApplication t1 = fusion.ObjectType('Users', 10) t2 = fusion.ObjectType('Movies', 30) t3 = fusion.ObjectType('Actors', 40) # test that MeanFuser completes correctly R = np.ma.array([[1, 1, 0], [3, 0, 0]], mask=[[0, 0, 1], [0, 1, 1]], dtype=float) rel = fusion.Relation(R, t1, t2) assert (MeanFuser(0).complete(rel) == [[1, 1, 5/3], [3, 1, 5/3]]).all() assert (MeanFuser(1).complete(rel) == [[1, 1, 1], [3, 3, 3]]).all() assert (MeanFuser(2).complete(rel) == [[1, 1, 5/3], [3, 5/3, 5/3]]).all() R1 = np.ma.array(np.random.random((20, 20))) R2 = np.ma.array(np.random.random((40, 40)), mask=np.random.random((40,40)) > .8) relations = [ fusion.Relation(R1, t1, t2, name='like'), fusion.Relation(R2, t3, t2, name='feature in'), ] G = fusion.FusionGraph() G.add_relations_from(relations) app = QApplication([]) w = OWMeanFuser() w.on_fusion_graph_change(G) w.show() app.exec()
def main(): # example from https://github.com/marinkaz/scikit-fusion import numpy as np from AnyQt.QtWidgets import QApplication R12 = np.random.rand(50, 100) R32 = np.random.rand(100, 150) R33 = np.random.rand(150, 150) R13 = np.random.rand(50, 150) t1 = fusion.ObjectType('Users', 10) t2 = fusion.ObjectType('Movies', 30) t3 = fusion.ObjectType('Actors', 40) relations = [ fusion.Relation(R12, t1, t2, name='like'), fusion.Relation(R13, t1, t3, name='are fans of'), fusion.Relation(R12, t1, t2, name='don\'t like'), fusion.Relation(R33, t3, t3, name='married to'), fusion.Relation(R32, t2, t3, name='feature') ] G = fusion.FusionGraph() for rel in relations: G.add_relation(rel) fuser = fusion.Dfmf() fuser.fuse(G) app = QApplication([]) w = OWChaining() w.on_fuser_change(FittedFusionGraph(fuser)) w.show() app.exec()
def main(): from AnyQt.QtWidgets import QApplication app = QApplication([]) w = OWOracleSQL() w.show() app.exec()
def main(args=sys.argv): from AnyQt.QtWidgets import QApplication app = QApplication(args) w = SelectEncodingsWidget( headingText="Select encodings visible in text encoding menus") w.show() w.activateWindow() app.exec()
def main(): from AnyQt.QtWidgets import QApplication a = QApplication([]) ow = GeoCodeFromFile() ow.show() ow.raise_() a.exec() ow.saveSettings()
def main(): app = QApplication([]) widget = OWSentimentAnalysis() corpus = Corpus.from_file('book-excerpts') corpus = corpus[:3] widget.set_corpus(corpus) widget.show() app.exec()
def main(): app = QApplication([]) widget = OWSentimentAnalysis() corpus = Corpus.from_file('bookexcerpts') corpus = corpus[:3] widget.set_corpus(corpus) widget.show() app.exec()
def main(): from sklearn.datasets import make_blobs import numpy as np from AnyQt.QtWidgets import QApplication from orangecontrib.datafusion.models import FittedFusionGraph from orangecontrib.datafusion.widgets.owmeanfuser import MeanFuser X, y = make_blobs(100, 3, centers=2, center_box=(-100, 100), cluster_std=10) X = X.astype(int) X += abs(X.min()) nrows, ncols, _ = X.max(0) R1 = np.zeros((nrows + 1, ncols + 1)) R1[X[:, 0], X[:, 1]] = X[:, 2] R1 = np.ma.array((R1 - R1.min()) / (R1.max() - R1.min())) _, ncols, nrows = X.max(0) R2 = np.zeros((nrows + 1, ncols + 1)) R2[X[:, 2], X[:, 1]] = X[:, 0] R2 = np.ma.array((R2 - R2.min()) / (R2.max() - R2.min())) t1 = fusion.ObjectType('Users', 10) t2 = fusion.ObjectType('Movies', 30) t3 = fusion.ObjectType('Actors', 40) relations = [ fusion.Relation(R1, t1, t2, name='like'), fusion.Relation(R2, t3, t2, name='feature in'), ] G = fusion.FusionGraph() for relation in relations: relation.data.mask = np.random.rand(*relation.data.shape) > .8 G.add_relation(relation) fuserF = fusion.Dfmf() fuserF.fuse(G) from copy import deepcopy G = deepcopy(G) fuserC = fusion.Dfmc() fuserC.name = 'My dfmc<3' fuserC.fuse(G) app = QApplication([]) w = OWCompletionScoring() w.on_fuser_change(FittedFusionGraph(fuserF), fuserF.__class__.__name__) w.on_fuser_change(FittedFusionGraph(fuserC), fuserC.__class__.__name__) w.on_fuser_change(MeanFuser(0), 'meanfuser0') w.on_fuser_change(MeanFuser(1), 'meanfuser1') w.on_fuser_change(MeanFuser(2), 'meanfuser2') for i, relation in enumerate(relations, 1): w.on_relation_change(Relation(relation), i) w.show() app.exec()
def main(): # pragma: no cover import sys from AnyQt.QtWidgets import QApplication a = QApplication(sys.argv) ow = OWKMeans() d = Table("iris.tab") ow.set_data(d) ow.show() a.exec() ow.saveSettings()
def ephys_session_form(session_dict: dict) -> dict: root = QApplication(sys.argv) sForm0 = EphysSessionForm() sForm0.session_dict = dict_to_dstr(session_dict) sForm0.build() sForm = pyforms.start_app(sForm0, parent_win=root, geometry=(200, 200, 600, 400)) # sForm.build() root.exec() return dstring_to_dict(sForm.form_data)
def session_form(mouse_name: str = '') -> dict: root = QApplication(sys.argv) sForm = pyforms.start_app(SessionForm, parent_win=root, geometry=(200, 200, 600, 400)) sForm._mouseWeight.label = sForm._mouseWeight.label.format(mouse_name) root.exec() if sForm.valid_form_data: return sForm.form_data else: return -1
def main(): # pragma: no cover import sys from AnyQt.QtWidgets import QApplication a = QApplication(sys.argv) ow = OWKMeans() d = Table(sys.argv[1] if len(sys.argv) > 1 else "iris.tab") ow.set_data(d) ow.show() a.exec() ow.saveSettings()
def main(): # pragma: no cover """Simple test for manual inspection of the widget""" import sys from AnyQt.QtWidgets import QApplication a = QApplication(sys.argv) table = Table("zoo") ow = OWCreateClass() ow.show() ow.set_data(table) a.exec() ow.saveSettings()
def main(): from AnyQt.QtWidgets import QApplication a = QApplication([]) ow = OWChoropleth() ow.show() ow.raise_() data = Table("India_census_district_population") ow.set_data(data) a.exec() ow.saveSettings()
def test_main(): from AnyQt.QtWidgets import QApplication a = QApplication([]) ow = OWChoropleth() ow.show() ow.raise_() data = Table('philadelphia-crime') ow.set_data(data) a.exec() ow.saveSettings()
def main(): from AnyQt.QtWidgets import QApplication a = QApplication([]) ow = OWGeocoding() ow.show() ow.raise_() data = Table('philadelphia-crime') print(data[:10]) ow.set_data(data) a.exec() ow.saveSettings()
def main(): # pragma: no cover from AnyQt.QtWidgets import QApplication a = QApplication(sys.argv) c = ColorPaletteDlg(None) c.createContinuousPalette("continuousPalette", "Continuous Palette") c.createDiscretePalette("discPalette", "Discrete Palette") box = c.createBox("otherColors", "Colors") c.createColorButton(box, "Canvas", "Canvas") c.createColorButton(box, "Grid", "Grid") c.setColorSchemas() c.show() a.exec()
def main(): from AnyQt.QtWidgets import QApplication a = QApplication([]) ow = OWGeocoding() ow.show() ow.raise_() data = Table('/home/jk/PycharmProjects/orange3/geo/small_airports.csv') print(data[:10]) ow.set_data(data) a.exec() ow.saveSettings()
def main(): corpus = Corpus.from_file('book-excerpts') vect = BowVectorizer() corpus_vect = vect.transform(corpus) app = QApplication([]) widget = OWWordEnrichment() widget.set_data(corpus_vect) subset_corpus = corpus_vect[:10] widget.set_data_selected(subset_corpus) widget.handleNewSignals() widget.show() app.exec()
def main(argv=None): # pragma: no cover app = QApplication(list(argv or sys.argv)) argv = app.arguments() w = OWFilter() if len(argv) > 1: filename = argv[1] else: filename = "brown-selected" # bad example data = Orange.data.Table(filename) w.set_data(data) w.show() w.raise_() app.exec() w.saveSettings() w.onDeleteWidget()
def test_main(): from AnyQt.QtWidgets import QApplication from Orange.modelling import KNNLearner as Learner a = QApplication([]) ow = OWMap() ow.show() ow.raise_() data = Table('philadelphia-crime') ow.set_data(data) QTimer.singleShot(10, lambda: ow.set_learner(Learner())) ow.handleNewSignals() a.exec() ow.saveSettings()
def main(): """ A simple test. """ app = QApplication([]) def _on_selected_points(points): print(len(points), points) w = Highchart(enable_zoom=True, enable_select='xy+', selection_callback=_on_selected_points, debug=True) w.chart(dict(series=[dict(data=np.random.random((100, 2)))]), credits_text='BTYB Yours Truly', title_text='Foo plot', chart_type='scatter') w.show() app.exec()
def main(argv=None): import sys from orangecontrib.imageanalytics.import_images import ImportImages from orangecontrib.imageanalytics.image_embedder import ImageEmbedder if argv is None: argv = sys.argv argv = list(argv) app = QApplication(argv) if len(argv) > 1: image_dir = argv[1] else: raise ValueError("Provide the image directory as the first argument.") import_images = ImportImages() images, err = import_images(image_dir) image_embedder = ImageEmbedder() embeddings, _, _ = image_embedder(images) ow = OWImageGrid() ow.show() ow.raise_() ow.set_data(Orange.data.Table(embeddings)) rval = app.exec() ow.saveSettings() ow.onDeleteWidget() return rval
def main(argv=None): # pragma: no cover # pylint: disable=import-outside-toplevel import sys from AnyQt.QtWidgets import QGraphicsScene, QMenu from AnyQt.QtGui import QBrush app = QApplication(argv or sys.argv) scene = QGraphicsScene() view = GraphicsWidgetView(scene) scene.setParent(view) view.setContextMenuPolicy(Qt.CustomContextMenu) def context(pos): menu = QMenu(view) menu.addActions(view.actions()) a = menu.addAction("Aspect mode") am = QMenu(menu) am.addAction("Ignore", lambda: view.setAspectMode(Qt.IgnoreAspectRatio)) am.addAction("Keep", lambda: view.setAspectMode(Qt.KeepAspectRatio)) am.addAction("Keep by expanding", lambda: view.setAspectMode(Qt.KeepAspectRatioByExpanding)) a.setMenu(am) menu.popup(view.viewport().mapToGlobal(pos)) view.customContextMenuRequested.connect(context) w = QGraphicsWidget() w.setPreferredSize(500, 500) palette = w.palette() palette.setBrush(palette.Window, QBrush(Qt.red, Qt.BDiagPattern)) w.setPalette(palette) w.setAutoFillBackground(True) scene.addItem(w) view.setCentralWidget(w) view.show() return app.exec()
def main(argv=None): import sys import sip argv = sys.argv[1:] if argv is None else argv if argv: filename = argv[0] else: filename = "heart_disease" data = Table(filename) app = QApplication([]) w = OWRadviz() w.set_data(data) w.set_subset_data(data[::10]) w.handleNewSignals() w.show() w.raise_() r = app.exec() w.set_data(None) w.saveSettings() sip.delete(w) del w return r
def main(argv=None): import sys import sip argv = sys.argv[1:] if argv is None else argv if argv: filename = argv[0] else: filename = "iris" data = Table(filename) app = QApplication([]) w = OWLinearProjection() w.set_data(data) w.set_subset_data(data[::10]) w.handleNewSignals() w.show() w.raise_() r = app.exec() w.set_data(None) w.saveSettings() sip.delete(w) del w return r
def main(): from AnyQt.QtWidgets import QApplication from Orange.modelling import KNNLearner as Learner a = QApplication([]) ow = OWMap() ow.show() ow.raise_() data = Table("India_census_district_population") ow.set_data(data) QTimer.singleShot(10, lambda: ow.set_learner(Learner())) ow.handleNewSignals() a.exec() ow.saveSettings()
def main(argv=None): import sys if argv is None: argv = sys.argv argv = list(argv) a = QApplication(argv) if len(argv) > 1: filename = argv[1] else: filename = "heart_disease" ow = OWScatterPlot() ow.show() ow.raise_() data = Orange.data.Table(filename) ow.set_data(data) ow.set_subset_data(data[:30]) ow.handleNewSignals() rval = a.exec() ow.set_data(None) ow.set_subset_data(None) ow.handleNewSignals() ow.saveSettings() ow.onDeleteWidget() return rval
def main(argv): app = QApplication(argv) mw = QMainWindow() dock = CollapsibleDockWidget() w1 = QTreeView() w1.header().hide() w2 = QToolButton() w2.setFixedSize(38, 200) dock.setExpandedWidget(w1) dock.setCollapsedWidget(w2) mw.addDockWidget(Qt.LeftDockWidgetArea, dock) mw.setCentralWidget(QTextEdit()) mw.show() a = QAction("Expand", mw, checkable=True, shortcut=QKeySequence(Qt.ControlModifier | Qt.Key_D)) a.triggered[bool].connect(dock.setExpanded) mw.addAction(a) return app.exec()
def main(argv=None): app = QApplication(list(argv if argv is not None else sys.argv)) argv = app.arguments() if len(argv) > 1: filename = argv[1] else: filename = "iris.tab" data = Orange.data.Table(filename) def pred_error(data, *args, **kwargs): raise ValueError pred_error.domain = data.domain pred_error.name = "To err is human" if data.domain.has_discrete_class: predictors = [ Orange.classification.SVMLearner(probability=True)(data), Orange.classification.LogisticRegressionLearner()(data), pred_error, ] elif data.domain.has_continuous_class: predictors = [ Orange.regression.RidgeRegressionLearner(alpha=1.0)(data), Orange.regression.LinearRegressionLearner()(data), pred_error, ] else: predictors = [pred_error] w = OWPredictions() w.show() w.raise_() w.set_data(data) for i, pred in enumerate(predictors): w.set_predictor(pred, i) w.handleNewSignals() app.exec() w.set_data(None) w.handleNewSignals() for i in range(len(predictors)): w.set_predictor(None, i) w.handleNewSignals() w.saveSettings() return 0
def main(argv=None): # pragma: no cover app = QApplication(list(argv or sys.argv)) argv = app.arguments() w = OWFilter() if len(argv) > 1: filename = argv[1] data = Orange.data.Table(filename) else: X = np.random.exponential(size=(1000, 1050)) - 1 X[X < 0] = 0 data = Orange.data.Table.from_numpy(None, X) w.set_data(data) w.show() w.raise_() app.exec() w.saveSettings() w.onDeleteWidget()
def main(argv=sys.argv): app = QApplication(list(argv)) argv = app.arguments() if len(argv) > 1: filename = argv[1] else: filename = "iris.tab" data = Orange.data.Table(filename) def pred_error(data, *args, **kwargs): raise ValueError pred_error.domain = data.domain pred_error.name = "To err is human" if data.domain.has_discrete_class: predictors = [ Orange.classification.SVMLearner(probability=True)(data), Orange.classification.LogisticRegressionLearner()(data), pred_error ] elif data.domain.has_continuous_class: predictors = [ Orange.regression.RidgeRegressionLearner(alpha=1.0)(data), Orange.regression.LinearRegressionLearner()(data), pred_error ] else: predictors = [pred_error] w = OWPredictions() w.show() w.raise_() w.set_data(data) for i, pred in enumerate(predictors): w.set_predictor(pred, i) w.handleNewSignals() app.exec() w.set_data(None) w.handleNewSignals() for i in range(len(predictors)): w.set_predictor(None, i) w.handleNewSignals() w.saveSettings() return 0
def main(argv=None): app = QApplication(list(argv) if argv else []) argv = app.arguments() if len(argv) > 1: filename = argv[1] else: filename = "brown-selected" data = Orange.data.Table(filename) w = OWReshape() w.show() w.raise_() w.set_data(data) w.handleNewSignals() app.exec() w.set_data(None) w.handleNewSignals() w.onDeleteWidget() return 0
def main(argv=None): from AnyQt.QtWidgets import QApplication logging.basicConfig(level=logging.DEBUG) app = QApplication(list(argv) if argv else []) argv = app.arguments() if len(argv) > 1: filename = argv[1] else: filename = "zoo-with-images" data = Table(filename) widget = OWImageEmbedding() widget.show() assert QSignalSpy(widget.blockingStateChanged).wait() widget.set_data(data) widget.handleNewSignals() app.exec() widget.set_data(None) widget.handleNewSignals() widget.saveSettings() widget.onDeleteWidget() return 0
def main(): from Orange.data import Table, Domain, StringVariable words = np.column_stack([ 'Slovenia Slovenia SVN USA Iraq Iraq Iraq Iraq France FR'.split(), 'Slovenia Slovenia SVN France FR Austria NL GB GB GB'.split(), 'Alabama AL Texas TX TX TX MS Montana US-MT MT'.split(), ]) metas = [ StringVariable('World'), StringVariable('Europe'), StringVariable('USA'), ] domain = Domain([], metas=metas) table = Table.from_numpy(domain, X=np.zeros((len(words), 0)), metas=words) app = QApplication(['']) w = OWGeoMap() w.on_data(table) w.show() app.exec()
def main(): # example from https://github.com/marinkaz/scikit-fusion import numpy as np from AnyQt.QtWidgets import QApplication R12 = np.random.rand(50, 100) R22 = np.random.rand(100, 100) R13 = np.random.rand(50, 40) R31 = np.random.rand(40, 50) R23 = np.random.rand(100, 40) R23 = np.random.rand(100, 40) R24 = np.random.rand(100, 40) R34 = np.random.rand(40, 40) t1 = fusion.ObjectType('Users', 10) t2 = fusion.ObjectType('Actors', 20) t3 = fusion.ObjectType('Movies', 30) t4 = fusion.ObjectType('Genres', 40) relations = [fusion.Relation(R12, t1, t2, name='like'), fusion.Relation(R13, t1, t3, name='rated'), fusion.Relation(R13, t1, t3, name='mated'), fusion.Relation(R23, t2, t3, name='play in'), fusion.Relation(R31, t3, t1), fusion.Relation(R24, t2, t4, name='prefer'), fusion.Relation(R34, t3, t4, name='belong to'), fusion.Relation(R22, t2, t2, name='married to')] app = QApplication(['asdf']) w = OWFusionGraph() w.show() def _add_next_relation(event, id=iter(range(len(relations))), relation=iter(map(Relation, relations))): try: w.on_relation_change(next(relation), next(id)) except StopIteration: w.killTimer(w.timer_id) w.on_relation_change(None, 4) # Remove relation #4 w.timerEvent = _add_next_relation w.timer_id = w.startTimer(500) app.exec()
def test_model(): app = QApplication([]) view = QTableView( sortingEnabled=True ) data = Orange.data.Table("lenses") model = TableModel(data) view.setModel(model) view.show() view.raise_() return app.exec()
def main(argv=None): import sys argv = sys.argv[1:] if argv is None else argv if argv: filename = argv[0] else: filename = "iris" data = Table(filename) app = QApplication([]) w = OWLinearProjection() w.set_data(data) w.set_subset_data(data[::10]) w.handleNewSignals() w.show() w.raise_() app.exec() w.set_data(None) w.saveSettings() del w
def test_main(): a = QApplication(sys.argv) ow = OWDataTable() iris = Table("iris") brown = Table("brown-selected") housing = Table("housing") ow.show() ow.raise_() ow.set_dataset(iris, iris.name) ow.set_dataset(brown, brown.name) ow.set_dataset(housing, housing.name) rval = a.exec() # ow.saveSettings() return rval
def main(argv=None): # pragma: no cover from AnyQt.QtWidgets import QApplication app = QApplication(argv or []) argv = app.arguments() w = OWEditDomain() if len(argv) > 1: filename = argv[1] else: filename = "iris" data = Orange.data.Table(filename) w.set_data(data) w.show() w.raise_() rval = app.exec() w.set_data(None) w.saveSettings() w.onDeleteWidget() return rval
def main(argv=None): # noqa import argparse from AnyQt.QtWidgets import QApplication app = QApplication(argv if argv is not None else []) argv = app.arguments() parser = argparse.ArgumentParser() parser.add_argument( "--config", metavar="CLASSNAME", default="orangecanvas.config.default", help="The configuration namespace to use" ) args = parser.parse_args(argv[1:]) config_ = name_lookup(args.config) config_ = config_() config_.init() config.set_default(config_) dlg = AddonManagerDialog() dlg.start(config_) dlg.show() dlg.raise_() return app.exec()
painter.setRenderHint(QPainter.Antialiasing) for prop, color in zip(curr_class_dist, self.color_schema): if prop == 0: continue painter.setPen(QPen(QBrush(color), pw)) to_x = x + prop * width line = QLineF(x, baseline, to_x, baseline) painter.drawLine(line) x = to_x painter.restore() painter.restore() if __name__ == "__main__": from PyQt4.QtGui import QApplication from Orange.classification import CN2Learner data = Table("iris") learner = CN2Learner() model = learner(data) model.instances = data a = QApplication([]) ow = OWRuleViewer() ow.set_classifier(model) ow.show() a.exec()
self.update_tweets_num(len(result) if result else 0) self.corpus = result self.set_text_features() def update_tweets_num(self, num=0): self.tweets_info_label.setText(self.tweets_info.format(num)) def set_text_features(self): self.Warning.no_text_fields.clear() if not self.text_includes: self.Warning.no_text_fields() if self.corpus is not None: vars_ = [var for var in self.corpus.domain.metas if var.name in self.text_includes] self.corpus.set_text_features(vars_ or None) self.send(IO.CORPUS, self.corpus) @gui_require('api', 'key_missing') def send_report(self): for task in self.api.search_history: self.report_items(task) if __name__ == '__main__': app = QApplication([]) widget = OWTwitter() widget.show() app.exec() widget.saveSettings()