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# Author: Gael Varoquaux <gael.varoquaux@normalesup.org>
# Copyright (c) 2010, Enthought, Inc.
# License: BSD Style.
# Standard library imports.
import unittest
import numpy as np
# Local imports.
from mayavi.core.null_engine import NullEngine
# Enthought library imports
from mayavi.filters.threshold import Threshold
from mayavi.filters.cut_plane import CutPlane
from mayavi.sources.array_source import ArraySource
class TestThresholdFilter(unittest.TestCase):
def make_src(self, nan=False):
data = np.empty((3, 3, 3))
if nan:
data[0] = np.nan
data.flat[:] = np.arange(data.size)
return ArraySource(scalar_data=data)
def setUp(self):
"""Initial setting up of test fixture, automatically called by
TestCase before any other test method is invoked"""
e = NullEngine()
# Uncomment to see visualization for debugging etc.
#e = Engine()
e.start()
s = e.new_scene()
self.e = e
self.s = s
self.scene = e.current_scene
return
def tearDown(self):
"""For necessary clean up, automatically called by TestCase
after the test methods have been invoked"""
self.e.stop()
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_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_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_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)
if __name__ == '__main__':
unittest.main()
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