def colors(self):
if self._colors is None:
from Orange.widgets.utils.colorpalette import ColorPaletteGenerator
self._colors = ColorPaletteGenerator.palette(self)
colors = self.attributes.get('colors')
if colors:
self._colors[:len(colors)] = [hex_to_color(color) for color in colors]
self._colors.flags.writeable = False
return self._colors
def colors(self):
if self._colors is None:
if "colors" in self.attributes:
self._colors = np.array([hex_to_color(col) for col in self.attributes["colors"]], dtype=np.uint8)
else:
from Orange.widgets.utils.colorpalette import ColorPaletteGenerator
self._colors = ColorPaletteGenerator.palette(self)
self._colors.flags.writeable = False
return self._colors
def colors(self):
if self._colors is None:
from Orange.widgets.utils.colorpalette import ColorPaletteGenerator
self._colors = ColorPaletteGenerator.palette(self)
colors = self.attributes.get('colors')
if colors:
self._colors[:len(colors)] = [
hex_to_color(color) for color in colors
]
self._colors.flags.writeable = False
return self._colors
def colors(self):
if self._colors is None:
if "colors" in self.attributes:
self._colors = np.array(
[hex_to_color(col) for col in self.attributes["colors"]],
dtype=np.uint8)
else:
from Orange.widgets.utils.colorpalette import \
ColorPaletteGenerator
self._colors = ColorPaletteGenerator.palette(self)
self._colors.flags.writeable = False
return self._colors
def colors(self):
if self._colors is not None:
colors = np.array(self._colors)
elif not self.values:
colors = np.zeros((0, 3)) # to match additional colors in vstacks
else:
from Orange.widgets.utils.colorpalette import ColorPaletteGenerator
default = tuple(ColorPaletteGenerator.palette(self))
colors = self.attributes.get('colors', ())
colors = tuple(hex_to_color(color) for color in colors) \
+ default[len(colors):]
colors = np.array(colors)
colors.flags.writeable = False
return colors
def _get_colors(self):
"""
Defines colors for values. If colors match in all models use the union
otherwise use standard colors.
"""
all_colors_values = self._all_color_values()
base_color, base_values = all_colors_values[0]
for c, v in all_colors_values[1:]:
if not self._colors_match(base_color, base_values, c, v):
base_color = []
break
# replace base_color if longer
if len(v) > len(base_color):
base_color = c
base_values = v
if len(base_color) != len(self.class_values):
return ColorPaletteGenerator.palette(len(self.class_values))
# reorder colors to widgets order
colors = [None] * len(self.class_values)
for c, v in zip(base_color, base_values):
colors[self.class_values.index(v)] = c
return colors
def test_colors_diff_domain(self):
"""
Test whether the color selection for values is correct.
"""
# pylint: disable=protected-access
self.send_signal(self.widget.Inputs.data, self.iris)
# case 1: two domains one subset other
idom = self.iris.domain
dom1 = Domain(
idom.attributes,
DiscreteVariable(idom.class_var.name, idom.class_var.values))
dom2 = Domain(
idom.attributes,
DiscreteVariable(idom.class_var.name, idom.class_var.values[:2]))
iris1 = self.iris[:100].transform(dom1)
iris2 = self.iris[:100].transform(dom2)
predictor_iris1 = ConstantLearner()(iris1)
predictor_iris2 = ConstantLearner()(iris2)
self.send_signal(self.widget.Inputs.predictors, predictor_iris1)
self.send_signal(self.widget.Inputs.predictors, predictor_iris2, 1)
colors = self.widget._get_colors()
np.testing.assert_array_equal(colors, iris1.domain.class_var.colors)
# case 2: two domains one subset other - different color order
idom = self.iris.domain
colors = idom.class_var.colors[::-1]
dom1 = Domain(
idom.attributes,
DiscreteVariable(idom.class_var.name, idom.class_var.values))
dom2 = Domain(
idom.attributes,
DiscreteVariable(idom.class_var.name, idom.class_var.values[:2]))
dom1.class_var.colors = colors
dom2.class_var.colors = colors[:2]
iris1 = self.iris[:100].transform(dom1)
iris2 = self.iris[:100].transform(dom2)
predictor_iris1 = ConstantLearner()(iris1)
predictor_iris2 = ConstantLearner()(iris2)
self.send_signal(self.widget.Inputs.predictors, predictor_iris1)
self.send_signal(self.widget.Inputs.predictors, predictor_iris2, 1)
colors = self.widget._get_colors()
np.testing.assert_array_equal(colors, iris1.domain.class_var.colors)
# case 3: domain color, values miss-match - use default colors
idom = self.iris.domain
dom1 = Domain(
idom.attributes,
DiscreteVariable(idom.class_var.name, idom.class_var.values))
dom2 = Domain(
idom.attributes,
DiscreteVariable(idom.class_var.name, idom.class_var.values))
dom1.class_var.colors = dom1.class_var.colors[::-1]
iris1 = self.iris.transform(dom1)
iris2 = self.iris.transform(dom2)
predictor_iris1 = ConstantLearner()(iris1)
predictor_iris2 = ConstantLearner()(iris2)
self.send_signal(self.widget.Inputs.predictors, predictor_iris1)
self.send_signal(self.widget.Inputs.predictors, predictor_iris2, 1)
colors = self.widget._get_colors()
np.testing.assert_array_equal(colors, ColorPaletteGenerator.palette(3))
# case 4: two domains different values order, matching colors
idom = self.iris.domain
# this way we know that default colors are not used
colors = ColorPaletteGenerator.palette(5)[2:]
dom1 = Domain(
idom.attributes,
DiscreteVariable(idom.class_var.name, idom.class_var.values))
dom2 = Domain(
idom.attributes,
DiscreteVariable(idom.class_var.name, idom.class_var.values[::-1]))
dom1.class_var.colors = colors
dom2.class_var.colors = colors[::-1] # colors mixed same than values
iris1 = self.iris[:100].transform(dom1)
iris2 = self.iris[:100].transform(dom2)
predictor_iris1 = ConstantLearner()(iris1)
predictor_iris2 = ConstantLearner()(iris2)
self.send_signal(self.widget.Inputs.predictors, predictor_iris1)
self.send_signal(self.widget.Inputs.predictors, predictor_iris2, 1)
colors = self.widget._get_colors()
np.testing.assert_array_equal(colors, iris1.domain.class_var.colors)
