def test_threshold_fuzzy(self):
"""Test when a point is in the fuzzy threshold area."""
plugin = Threshold(0.6, fuzzy_factor=self.fuzzy_factor)
result = plugin.process(self.cube)
expected_result_array = np.zeros_like(self.cube.data)
expected_result_array[0][2][2] = 1.0 / 3.0
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_basic(self):
"""Test that the plugin returns an iris.cube.Cube."""
fuzzy_factor = 0.95
threshold = 0.1
plugin = Threshold(threshold, fuzzy_factor=fuzzy_factor)
result = plugin.process(self.cube)
self.assertIsInstance(result, Cube)
def test_threshold_below_fuzzy_miss(self):
"""Test not meeting the threshold in fuzzy below-threshold-mode."""
plugin = Threshold(2.0,
fuzzy_factor=self.fuzzy_factor,
below_thresh_ok=True)
result = plugin.process(self.cube)
expected_result_array = np.ones_like(self.cube.data)
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_threshold_negative(self):
"""Test a point when the threshold is negative."""
plugin = Threshold(-1.0,
fuzzy_factor=self.fuzzy_factor,
below_thresh_ok=True)
result = plugin.process(self.cube)
expected_result_array = np.ones_like(self.cube.data)
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_above_threshold_without_fuzzy_factor(self):
"""Test if the fixed threshold is below the value in the data."""
# Copy the cube as the cube.data is used as the basis for comparison.
cube = self.cube.copy()
plugin = Threshold(0.1)
result = plugin.process(cube)
expected_result_array = self.cube.data
expected_result_array[0][2][2] = 1.0
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_threshold_below_fuzzy(self):
"""Test a point in fuzzy threshold in below-threshold-mode."""
plugin = Threshold(0.6,
fuzzy_factor=self.fuzzy_factor,
below_thresh_ok=True)
result = plugin.process(self.cube)
expected_result_array = np.ones_like(self.cube.data)
expected_result_array[0][2][2] = 2.0 / 3.0
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_threshold(self):
"""Test the basic threshold functionality."""
# Copy the cube as the cube.data is used as the basis for comparison.
cube = self.cube.copy()
fuzzy_factor = 0.95
plugin = Threshold(0.1, fuzzy_factor=fuzzy_factor)
result = plugin.process(cube)
# The single 0.5-valued point => 1.0, so cheat by * 2.0 vs orig data.
expected_result_array = self.cube.data * 2.0
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_threshold_point_nan(self):
"""Test behaviour for a single NaN grid cell."""
# Need to copy the cube as we're adjusting the data.
self.cube.data[0][2][2] = np.NAN
msg = "NaN detected in input cube data"
plugin = Threshold(2.0,
fuzzy_factor=self.fuzzy_factor,
below_thresh_ok=True)
with self.assertRaisesRegexp(ValueError, msg):
plugin.process(self.cube)
def iterate_over_threshold(self, cubelist, threshold):
"""
Iterate over the application of thresholding to multiple cubes.
Args:
cubelist : Iris.cube.CubeList
Cubelist containing cubes to be thresholded.
threshold : float
The threshold that will be applied.
Returns:
cubes : Iris.cube.CubeList
Cubelist after thresholding each cube.
"""
cubes = iris.cube.CubeList([])
for cube in cubelist:
threshold_cube = (BasicThreshold(
threshold,
fuzzy_factor=self.fuzzy_factor,
below_thresh_ok=self.below_thresh_ok).process(cube.copy()))
cubes.append(threshold_cube)
return cubes
def test_below_threshold_without_fuzzy_factor(self):
"""Test if the fixed threshold is above the value in the data."""
plugin = Threshold(0.6)
result = plugin.process(self.cube)
expected_result_array = np.zeros_like(self.cube.data)
self.assertArrayAlmostEqual(result.data, expected_result_array)
def test_threshold_fuzzy_miss_high_threshold(self):
"""Test when a point is not within the fuzzy high threshold area."""
plugin = Threshold(3.0, fuzzy_factor=self.fuzzy_factor)
result = plugin.process(self.cube)
expected_result_array = np.zeros_like(self.cube.data)
self.assertArrayAlmostEqual(result.data, expected_result_array)