def test_threshold_with_other_filter_as_input(self):
# Given
x, y, z = np.mgrid[-1:1:10j, -1:1:10j, -1:1:10j]
s = x * x + y * y + z * z
src = ArraySource(scalar_data=s)
self.e.add_source(src)
scp = CutPlane()
self.e.add_filter(scp)
# When
threshold = Threshold()
self.e.add_filter(threshold)
threshold.set(lower_threshold=0.25,
upper_threshold=0.75,
auto_reset_lower=False,
auto_reset_upper=False)
# Then
output = threshold.get_output_dataset()
self.assertTrue(output is not None)
self.assertTrue(output.is_a('vtkUnstructuredGrid'))
output_range = output.point_data.scalars.range
self.assertTrue(output_range[0] >= 0.25)
self.assertTrue(output_range[1] <= 0.75)
def test_threshold_with_other_filter_as_input(self):
# Given
x, y, z = np.mgrid[-1:1:10j, -1:1:10j, -1:1:10j]
s = x*x + y*y + z*z
src = ArraySource(scalar_data=s)
self.e.add_source(src)
scp = CutPlane()
self.e.add_filter(scp)
# When
threshold = Threshold()
self.e.add_filter(threshold)
threshold.trait_set(
lower_threshold=0.25, upper_threshold=0.75,
auto_reset_lower=False, auto_reset_upper=False
)
# Then
output = threshold.get_output_dataset()
self.assertTrue(output is not None)
self.assertTrue(output.is_a('vtkUnstructuredGrid'))
output_range = output.point_data.scalars.range
self.assertTrue(output_range[0] >= 0.25)
self.assertTrue(output_range[1] <= 0.75)
def test_threshold_filter_threhsold(self):
src = self.make_src()
self.e.add_source(src)
threshold = Threshold()
self.e.add_filter(threshold)
threshold.upper_threshold = 20.0
self.assertTrue(20 >= np.nanmax(threshold.outputs[0].point_data.scalars.to_array()))
return
def test_threshold_filter_threhsold(self):
src = self.make_src()
self.e.add_source(src)
threshold = Threshold()
self.e.add_filter(threshold)
threshold.upper_threshold = 20.
self.assertTrue(20 >= np.nanmax(
threshold.get_output_dataset().point_data.scalars.to_array()))
return
def test_threshold_filter_nan(self):
src = self.make_src(nan=True)
self.e.add_source(src)
threshold = Threshold()
self.e.add_filter(threshold)
self.assertEqual(
np.nanmin(src.scalar_data),
np.nanmin(
threshold.get_output_dataset().point_data.scalars.to_array()))
self.assertEqual(
np.nanmax(src.scalar_data),
np.nanmax(
threshold.get_output_dataset().point_data.scalars.to_array()))
def test_threshold_filter_data_range_changes(self):
# Regression test for GitHub issue #136.
src = self.make_src()
self.e.add_source(src)
threshold = Threshold()
self.e.add_filter(threshold)
# Move from one data range to another non-overlapping range,
# first downwards, then back up.
src.scalar_data = np.linspace(3.0, 5.0, 27).reshape((3, 3, 3))
self.assertAlmostEqual(threshold.lower_threshold, 3.0)
self.assertAlmostEqual(threshold.upper_threshold, 5.0)
src.scalar_data = np.linspace(-5.0, -3.0, 27).reshape((3, 3, 3))
self.assertAlmostEqual(threshold.lower_threshold, -5.0)
self.assertAlmostEqual(threshold.upper_threshold, -3.0)
src.scalar_data = np.linspace(3.0, 5.0, 27).reshape((3, 3, 3))
self.assertAlmostEqual(threshold.lower_threshold, 3.0)
self.assertAlmostEqual(threshold.upper_threshold, 5.0)
# Narrow and widen.
src.scalar_data = np.linspace(4.2, 4.6, 27).reshape((3, 3, 3))
self.assertAlmostEqual(threshold.lower_threshold, 4.2)
self.assertAlmostEqual(threshold.upper_threshold, 4.6)
src.scalar_data = np.linspace(-20.0, 20.0, 27).reshape((3, 3, 3))
self.assertAlmostEqual(threshold.lower_threshold, -20.0)
self.assertAlmostEqual(threshold.upper_threshold, 20.0)
# Shift to a range overlapping the previous one.
src.scalar_data = np.linspace(-10.0, -30.0, 27).reshape((3, 3, 3))
self.assertAlmostEqual(threshold.lower_threshold, -30.0)
self.assertAlmostEqual(threshold.upper_threshold, -10.0)
src.scalar_data = np.linspace(-20.0, 20.0, 27).reshape((3, 3, 3))
self.assertAlmostEqual(threshold.lower_threshold, -20.0)
self.assertAlmostEqual(threshold.upper_threshold, 20.0)
def test_threshold_filter_nan(self):
src = self.make_src(nan=True)
self.e.add_source(src)
threshold = Threshold()
self.e.add_filter(threshold)
self.assertEqual(
np.nanmin(src.scalar_data),
np.nanmin(
threshold.get_output_dataset().point_data.scalars.to_array()
)
)
self.assertEqual(
np.nanmax(src.scalar_data),
np.nanmax(
threshold.get_output_dataset().point_data.scalars.to_array()
)
)
# Recorded script from Mayavi2
from numpy import array
try:
engine = mayavi.engine
except NameError:
from mayavi.api import Engine
engine = Engine()
engine.start()
if len(engine.scenes) == 0:
engine.new_scene()
# -------------------------------------------
from mayavi.filters.threshold import Threshold
threshold = Threshold()
mayavi.add_filter(threshold, ug_waterlevel)
surface_waterlevel = Surface()
mayavi.add_filter(surface2, threshold)
threshold.auto_reset_lower = False
threshold.auto_reset_upper = False
module_manager2 = threshold.children[0]
module_manager2.vector_lut_manager.data_range = array([ 0., 1.])
# Recorded script from Mayavi2
from numpy import array
try:
engine = mayavi.engine
except NameError:
from mayavi.api import Engine
engine = Engine()
engine.start()
if len(engine.scenes) == 0:
engine.new_scene()
# -------------------------------------------
from mayavi.filters.threshold import Threshold
threshold = Threshold()
mayavi.add_filter(threshold, ug_waterlevel)
surface_waterlevel = Surface()
mayavi.add_filter(surface2, threshold)
threshold.auto_reset_lower = False
threshold.auto_reset_upper = False
module_manager2 = threshold.children[0]
module_manager2.vector_lut_manager.data_range = array([0., 1.])
