def test_report_widgets_regression(self):
rep = OWReport.get_instance()
data = Table("housing")
widgets = self.regr_widgets
w = self.create_widget(OWRegressionTreeGraph)
mod = TreeRegressionLearner(max_depth=3)(data)
mod.instances = data
w.ctree(mod)
w.create_report_html()
rep.make_report(w)
self._create_report(widgets, rep, data)
def test_report_widgets_regression(self):
rep = OWReport.get_instance()
data = Table("housing")
widgets = self.regr_widgets
w = self.create_widget(OWRegressionTreeGraph)
mod = TreeRegressionLearner(max_depth=3)(data)
mod.instances = data
w.ctree(mod)
w.create_report_html()
rep.make_report(w)
self._create_report(widgets, rep, data)
def test_report_widgets_regression(self):
app = QApplication(sys.argv)
rep = OWReport.get_instance()
data = Table("housing")
widgets = self.regr_widgets
w = OWRegressionTreeGraph()
mod = TreeRegressionLearner(max_depth=3)(data)
mod.instances = data
w.ctree(mod)
w.create_report_html()
rep.make_report(w)
self.assertEqual(len(widgets) + 1, 5)
self._create_report(widgets, rep, data, app)
def test_report_widgets_regression(self):
app = QApplication(sys.argv)
rep = OWReport.get_instance()
data = Table("housing")
widgets = self.regr_widgets
w = OWRegressionTreeGraph()
mod = TreeRegressionLearner(max_depth=3)(data)
mod.instances = data
w.ctree(mod)
w.create_report_html()
rep.make_report(w)
self.assertEqual(len(widgets) + 1, 5)
self._create_report(widgets, rep, data, app)
self.scene.update()
def send_report(self):
if not self.tree:
return
self.report_items((
("Tree size", self.info.text()),
("Edge widths",
("Fixed", "Relative to root", "Relative to parent")[
self.line_width_method])))
self.report_plot(self.scene)
if __name__ == "__main__":
import sys
from PyQt4.QtGui import QApplication
from Orange.data import Table
from Orange.regression.tree import TreeRegressionLearner
a = QApplication(sys.argv)
ow = OWRegressionTreeGraph()
data = Table("housing")
reg = TreeRegressionLearner(max_depth=5)(data)
reg.instances = data
ow.ctree(reg)
ow.show()
ow.raise_()
a.exec_()
ow.saveSettings()
all_instances = self.tree.n_node_samples[0]
max_impurity = self.tree.impurity[0]
for node in self.scene.nodes():
li = [
0.5,
node.num_instances() / all_instances,
node.impurity() / max_impurity
][self.color_index]
node.backgroundBrush = QBrush(
palette[self.color_index].light(180 - li * 150))
self.scene.update()
if __name__ == "__main__":
import sys
from PyQt4.QtGui import QApplication
from Orange.data import Table
from Orange.regression.tree import TreeRegressionLearner
a = QApplication(sys.argv)
ow = OWRegressionTreeGraph()
data = Table("housing")
reg = TreeRegressionLearner(max_depth=5)(data)
reg.instances = data
ow.ctree(reg)
ow.show()
ow.raise_()
a.exec_()
ow.saveSettings()