def main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
import Orange
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = 'iris'
ow = OWPythagorasTree()
data = Orange.data.Table(filename)
if data.domain.has_discrete_class:
from Orange.classification.tree import TreeLearner
else:
from Orange.regression.tree import TreeLearner
model = TreeLearner(max_depth=1000)(data)
model.instances = data
ow.set_tree(model)
ow.show()
ow.raise_()
ow.handleNewSignals()
app.exec_()
sys.exit(0)
def test(argv=sys.argv):
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
import sip
import Orange.distance
w = OWDistanceMap()
w.show()
w.raise_()
data = Orange.data.Table(filename)
dist = Orange.distance.Euclidean(data)
w.set_distances(dist)
w.handleNewSignals()
rval = app.exec_()
w.set_distances(None)
w.saveSettings()
w.onDeleteWidget()
sip.delete(w)
del w
return rval
def test(argv=sys.argv):
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
import sip
import Orange.distance
w = OWDistanceMap()
w.show()
w.raise_()
data = Orange.data.Table(filename)
dist = Orange.distance.Euclidean(data)
w.set_distances(dist)
w.handleNewSignals()
rval = app.exec_()
w.set_distances(None)
w.saveSettings()
w.onDeleteWidget()
sip.delete(w)
del w
return rval
def main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
import Orange
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = 'iris'
ow = OWPythagorasTree()
data = Orange.data.Table(filename)
if data.domain.has_discrete_class:
from Orange.classification.tree import TreeLearner
else:
from Orange.regression.tree import TreeLearner
model = TreeLearner(max_depth=1000)(data)
model.instances = data
ow.set_tree(model)
ow.show()
ow.raise_()
ow.handleNewSignals()
app.exec_()
sys.exit(0)
def main(argv=None):
"""
Test as separate Qt application
:param argv: arguments from console - DataSet name if provided
:return: None
"""
from AnyQt.QtWidgets import QApplication
# PyQt changes argv list in-place
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "housing"
ow = OWSplitInstancesWidget()
ow.show()
ow.raise_()
dataset = Table(filename)
ow.set_data(dataset)
ow.handleNewSignals()
app.exec_()
ow.set_data(None)
ow.handleNewSignals()
ow.onDeleteWidget()
return 0
def main(argv=None):
if argv is None:
argv = sys.argv
import gc
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
data = Orange.data.Table(filename)
w = OWMDS()
w.set_data(data)
w.set_subset_data(data[np.random.choice(len(data), 10)])
w.handleNewSignals()
w.show()
w.raise_()
rval = app.exec_()
w.set_subset_data(None)
w.set_data(None)
w.handleNewSignals()
w.saveSettings()
w.onDeleteWidget()
w.deleteLater()
del w
gc.collect()
app.processEvents()
return rval
def main(argv=None):
if argv is None:
argv = sys.argv
import gc
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
data = Orange.data.Table(filename)
w = OWMDS()
w.set_data(data)
w.set_subset_data(data[np.random.choice(len(data), 10)])
w.handleNewSignals()
w.show()
w.raise_()
rval = app.exec_()
w.set_subset_data(None)
w.set_data(None)
w.handleNewSignals()
w.saveSettings()
w.onDeleteWidget()
w.deleteLater()
del w
gc.collect()
app.processEvents()
return rval
def main(argv=None): # pragma: no cover
from AnyQt.QtWidgets import QApplication
app = QApplication(argv or [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "zoo"
w = OWSelectRows()
w.set_data(Table(filename))
w.show()
app.exec_()
def main(argv=None): # pragma: no cover
from AnyQt.QtWidgets import QApplication
app = QApplication(argv or [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "zoo"
w = OWSelectRows()
w.set_data(Table(filename))
w.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 main(argv=None):
from AnyQt.QtWidgets import QApplication
logging.basicConfig()
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
data = Orange.data.Table(filename)
indices = numpy.random.permutation(len(data))
traindata = data[indices[:-20]]
testdata = data[indices[-20:]]
ow = OWLearningCurveC()
ow.show()
ow.raise_()
ow.set_dataset(traindata)
ow.set_testdataset(testdata)
l1 = Orange.classification.NaiveBayesLearner()
l1.name = "Naive Bayes"
ow.set_learner(l1, 1)
l2 = Orange.classification.LogisticRegressionLearner()
l2.name = "Logistic Regression"
ow.set_learner(l2, 2)
l4 = Orange.classification.SklTreeLearner()
l4.name = "Decision Tree"
ow.set_learner(l4, 3)
ow.handleNewSignals()
app.exec_()
ow.set_dataset(None)
ow.set_testdataset(None)
ow.set_learner(None, 1)
ow.set_learner(None, 2)
ow.set_learner(None, 3)
ow.handleNewSignals()
ow.onDeleteWidget()
return 0
def main(argv=None):
app = QApplication(argv or [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "brown-selected"
w = OWSetEnrichment()
data = Orange.data.Table(filename)
w.setData(data)
w.handleNewSignals()
w.show()
app.exec_()
w.saveSettings()
w.onDeleteWidget()
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):
from AnyQt.QtWidgets import QApplication
logging.basicConfig()
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
data = Orange.data.Table(filename)
indices = numpy.random.permutation(len(data))
traindata = data[indices[:-20]]
testdata = data[indices[-20:]]
ow = OWLearningCurveC()
ow.show()
ow.raise_()
ow.set_dataset(traindata)
ow.set_testdataset(testdata)
l1 = Orange.classification.NaiveBayesLearner()
l1.name = 'Naive Bayes'
ow.set_learner(l1, 1)
l2 = Orange.classification.LogisticRegressionLearner()
l2.name = 'Logistic Regression'
ow.set_learner(l2, 2)
l4 = Orange.classification.SklTreeLearner()
l4.name = "Decision Tree"
ow.set_learner(l4, 3)
ow.handleNewSignals()
app.exec_()
ow.set_dataset(None)
ow.set_testdataset(None)
ow.set_learner(None, 1)
ow.set_learner(None, 2)
ow.set_learner(None, 3)
ow.handleNewSignals()
ow.onDeleteWidget()
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=sys.argv):
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
path = argv[1]
else:
path = None
w = OWImportImages()
w.show()
w.raise_()
if path is not None:
w.setCurrentPath(path)
app.exec_()
w.saveSettings()
w.onDeleteWidget()
return 0
def main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
w = OWSilhouettePlot()
w.show()
w.raise_()
w.set_data(Orange.data.Table(filename))
w.handleNewSignals()
app.exec_()
w.set_data(None)
w.handleNewSignals()
w.onDeleteWidget()
return 0
def main(argv=sys.argv):
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
path = argv[1]
else:
path = None
w = OWImportImages()
w.show()
w.raise_()
if path is not None:
w.setCurrentPath(path)
app.exec_()
w.saveSettings()
w.onDeleteWidget()
return 0
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): # 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=sys.argv):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
w = OWSilhouettePlot()
w.show()
w.raise_()
w.set_data(Orange.data.Table(filename))
w.handleNewSignals()
app.exec_()
w.set_data(None)
w.handleNewSignals()
w.onDeleteWidget()
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
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "geo-gds360"
data = Orange.data.Table(filename)
w = OWFeatureSelection()
w.show()
w.raise_()
w.set_data(data)
rval = app.exec_()
w.set_data(None)
w.saveSettings()
w.onDeleteWidget()
return rval
def main(argv=None):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "geo-gds360"
data = Orange.data.Table(filename)
w = OWFeatureSelection()
w.show()
w.raise_()
w.set_data(data)
rval = app.exec_()
w.set_data(None)
w.saveSettings()
w.onDeleteWidget()
return rval
def main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
w = OWFeatureConstructor()
w.show()
w.raise_()
data = Orange.data.Table(filename)
w.setData(data)
w.handleNewSignals()
app.exec_()
w.setData(None)
w.handleNewSignals()
w.saveSettings()
return 0
def test_main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
data = Orange.data.Table(argv[1])
else:
data = None
w = OWGOEnrichmentAnalysis()
w.show()
w.raise_()
w.setDataset(data)
w.handleNewSignals()
rval = app.exec_()
w.setDataset(None)
w.handleNewSignals()
w.saveSettings()
w.onDeleteWidget()
return rval
def main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv))
args = app.arguments()
if len(args) > 1:
filename = args[1]
else:
filename = "iris"
ow = OWDataSamplerA()
ow.show()
ow.raise_()
dataset = Orange.data.Table(filename)
ow.set_data(dataset)
ow.handleNewSignals()
app.exec_()
ow.set_data(None)
ow.handleNewSignals()
return 0
def test_main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
data = Orange.data.Table(argv[1])
else:
data = None
w = OWGOEnrichmentAnalysis()
w.show()
w.raise_()
w.setDataset(data)
w.handleNewSignals()
rval = app.exec_()
w.setDataset(None)
w.handleNewSignals()
w.saveSettings()
w.onDeleteWidget()
return rval
def main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
w = OWFeatureConstructor()
w.show()
w.raise_()
data = Orange.data.Table(filename)
w.setData(data)
w.handleNewSignals()
app.exec_()
w.setData(None)
w.handleNewSignals()
w.saveSettings()
return 0
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()
def main(argv=None):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
data = Orange.data.Table(filename)
ow = OWLearningCurveA()
ow.show()
ow.raise_()
l1 = Orange.classification.NaiveBayesLearner()
l1.name = "Naive Bayes"
ow.set_learner(l1, 1)
ow.set_dataset(data)
l2 = Orange.classification.LogisticRegressionLearner()
l2.name = "Logistic Regression"
ow.set_learner(l2, 2)
l4 = Orange.classification.SklTreeLearner()
l4.name = "Decision Tree"
ow.set_learner(l4, 3)
ow.handleNewSignals()
app.exec_()
ow.set_dataset(None)
ow.set_learner(None, 1)
ow.set_learner(None, 2)
ow.set_learner(None, 3)
ow.handleNewSignals()
ow.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(argv=sys.argv):
import sip
app = QApplication(argv)
argv = app.arguments()
w = OWImageViewer()
w.show()
w.raise_()
if len(argv) > 1:
data = Orange.data.Table(argv[1])
else:
data = Orange.data.Table('zoo-with-images')
w.setData(data)
rval = app.exec_()
w.saveSettings()
w.onDeleteWidget()
sip.delete(w)
app.processEvents()
return rval
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(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()
def main(argv=sys.argv):
import sip
app = QApplication(argv)
argv = app.arguments()
w = OWImageViewer()
w.show()
w.raise_()
if len(argv) > 1:
data = Orange.data.Table(argv[1])
else:
data = Orange.data.Table('zoo-with-images')
w.setData(data)
rval = app.exec_()
w.saveSettings()
w.onDeleteWidget()
sip.delete(w)
app.processEvents()
return rval
def main(argv=None):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
data = Orange.data.Table(filename)
ow = OWLearningCurveA()
ow.show()
ow.raise_()
l1 = Orange.classification.NaiveBayesLearner()
l1.name = 'Naive Bayes'
ow.set_learner(l1, 1)
ow.set_dataset(data)
l2 = Orange.classification.LogisticRegressionLearner()
l2.name = 'Logistic Regression'
ow.set_learner(l2, 2)
l4 = Orange.classification.SklTreeLearner()
l4.name = "Decision Tree"
ow.set_learner(l4, 3)
ow.handleNewSignals()
app.exec_()
ow.set_dataset(None)
ow.set_learner(None, 1)
ow.set_learner(None, 2)
ow.set_learner(None, 3)
ow.handleNewSignals()
ow.onDeleteWidget()
return 0
def main(argv=None):
from AnyQt.QtWidgets import QApplication
# PyQt changes argv list in-place
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
ow = OWDataSamplerC()
ow.show()
ow.raise_()
dataset = Orange.data.Table(filename)
ow.set_data(dataset)
ow.handleNewSignals()
app.exec_()
ow.set_data(None)
ow.handleNewSignals()
ow.onDeleteWidget()
return 0
def main(argv=None):
from AnyQt.QtWidgets import QApplication
# PyQt changes argv list in-place
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "iris"
ow = OWDataSamplerC()
ow.show()
ow.raise_()
dataset = Orange.data.Table(filename)
ow.set_data(dataset)
ow.handleNewSignals()
app.exec_()
ow.set_data(None)
ow.handleNewSignals()
ow.onDeleteWidget()
return 0
def main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "brown-selected"
w = OWImpute()
w.show()
w.raise_()
data = Orange.data.Table(filename)
w.set_data(data)
w.handleNewSignals()
app.exec_()
w.set_data(None)
w.set_learner(None)
w.handleNewSignals()
w.onDeleteWidget()
return 0
def main(argv=sys.argv):
from AnyQt.QtWidgets import QApplication
app = QApplication(list(argv))
argv = app.arguments()
if len(argv) > 1:
filename = argv[1]
else:
filename = "brown-selected"
w = OWImpute()
w.show()
w.raise_()
data = Orange.data.Table(filename)
w.set_data(data)
w.handleNewSignals()
app.exec_()
w.set_data(None)
w.set_learner(None)
w.handleNewSignals()
w.onDeleteWidget()
return 0
def main(argv=None):
app = QApplication(list(argv) if argv else [])
argv = app.arguments()
parser = argparse.ArgumentParser(description=(
"Run an orange workflow without showing a GUI and exit "
"when it completes.\n\n"
"WARNING: This is experimental as Orange is not designed to run "
"non-interactive."))
parser.add_argument("--log-level",
"-l",
metavar="LEVEL",
type=int,
default=logging.CRITICAL,
dest="log_level")
parser.add_argument("--config",
default="Orange.canvas.config.Config",
type=str)
parser.add_argument("file")
args = parser.parse_args(argv[1:])
log_level = args.log_level
filename = args.file
logging.basicConfig(level=log_level)
cfg_class = utils.name_lookup(args.config)
cfg: config.Config = cfg_class()
config.set_default(cfg)
config.init()
reg = WidgetRegistry()
widget_discovery = cfg.widget_discovery(
reg, cached_descriptions=cache.registry_cache())
widget_discovery.run(cfg.widgets_entry_points())
model = cfg.workflow_constructor()
model.set_runtime_env("basedir",
os.path.abspath(os.path.dirname(filename)))
sigprop = model.findChild(signalmanager.SignalManager)
sigprop.pause() # Pause signal propagation during load
with open(filename, "rb") as f:
model.load_from(f, registry=reg)
# Ensure all widgets are created (this is required for the workflow
# to even start - relies to much on OWWidget behaviour).
for _ in map(model.widget_for_node, model.nodes):
pass
sigprop.resume() # Resume inter-widget signal propagation
def on_finished():
severity = 0
for node in model.nodes:
for msg in node.state_messages():
if msg.contents and msg.severity == msg.Error:
print(msg.contents, msg.message_id, file=sys.stderr)
severity = msg.Error
if severity == UserMessage.Error:
app.exit(1)
else:
app.exit()
sigprop.finished.connect(on_finished)
rval = app.exec_()
model.clear()
# Notify the workflow model to 'close'.
QApplication.sendEvent(model, QEvent(QEvent.Close))
app.processEvents()
return rval
