def test_03_02_circle(self):
'''Test the module on a uniform circle'''
i,j = np.mgrid[-50:51,-50:51]
labels = (np.sqrt(i*i+j*j) <= 40).astype(int)
m, workspace = self.run_module(
np.ones(labels.shape), labels, wants_workspace=True)
assert isinstance(workspace, cpw.Workspace)
bins = labels * (1 + (np.sqrt(i*i+j*j) / 10).astype(int))
for bin in range(1,5):
data = m.get_current_measurement(OBJECT_NAME,
feature_frac_at_d(bin, 4))
self.assertEqual(len(data), 1)
area = (float(bin) * 2.0 - 1.0)/16.0
self.assertTrue(data[0] > area - .1)
self.assertTrue(data[0] < area + .1)
heatmap = workspace.image_set.get_image(
HEAT_MAP_NAME + M.F_FRAC_AT_D).pixel_data
data = data.astype(heatmap.dtype)
self.assertEqual(mode(heatmap[bins == bin])[0], data[0])
data = m.get_current_measurement(OBJECT_NAME,
feature_mean_frac(bin, 4))
self.assertEqual(len(data), 1)
self.assertAlmostEqual(data[0], 1, 2)
heatmap = workspace.image_set.get_image(
HEAT_MAP_NAME + M.F_MEAN_FRAC).pixel_data
data = data.astype(heatmap.dtype)
self.assertEqual(mode(heatmap[bins == bin])[0], data[0])
data = m.get_current_measurement(OBJECT_NAME,
feature_radial_cv(bin, 4))
self.assertEqual(len(data), 1)
self.assertAlmostEqual(data[0], 0, 2)
heatmap = workspace.image_set.get_image(
HEAT_MAP_NAME + M.F_RADIAL_CV).pixel_data
data = data.astype(heatmap.dtype)
self.assertEqual(mode(heatmap[bins == bin])[0], data[0])
def test_03_07_two_circles(self):
i,j = np.mgrid[-50:51,-50:51]
i, j = [np.hstack((x,x)) for x in i, j]
d = np.sqrt(i*i+j*j)
labels = (d <= 40).astype(int)
labels[:, (j.shape[1]/2):] *= 2
img = np.zeros(labels.shape)
img[labels == 1] = 1
img[labels == 2] = d[labels == 2] / 40
m, workspace = self.run_module(
img, labels, wants_workspace=True)
assert isinstance(workspace, cpw.Workspace)
bins = (labels != 0) * (1 + (np.sqrt(i*i+j*j) / 10).astype(int))
for bin in range(1,5):
data = m.get_current_measurement(OBJECT_NAME,
feature_frac_at_d(bin, 4))
self.assertEqual(len(data), 2)
area = (float(bin) * 2.0 - 1.0)/16.0
bin_d = (float(bin) - .5) * 8 / 21
self.assertLess(np.abs(data[0] - area), .1)
self.assertLess(np.abs(data[1] - area * bin_d), .1)
heatmap = workspace.image_set.get_image(
HEAT_MAP_NAME + M.F_FRAC_AT_D).pixel_data
data = data.astype(heatmap.dtype)
for label in 1, 2:
mask = (bins == bin) & (labels == label)
self.assertEqual(mode(heatmap[mask]), data[label-1])
data = m.get_current_measurement(OBJECT_NAME,
feature_mean_frac(bin, 4))
self.assertEqual(len(data), 2)
self.assertAlmostEqual(data[0], 1, 2)
heatmap = workspace.image_set.get_image(
HEAT_MAP_NAME + M.F_MEAN_FRAC).pixel_data
data = data.astype(heatmap.dtype)
for label in 1, 2:
mask = (bins == bin) & (labels == label)
self.assertEqual(mode(heatmap[mask]), data[label-1])
data = m.get_current_measurement(OBJECT_NAME,
feature_radial_cv(bin, 4))
self.assertEqual(len(data), 2)
self.assertAlmostEqual(data[0], 0, 2)
heatmap = workspace.image_set.get_image(
HEAT_MAP_NAME + M.F_RADIAL_CV).pixel_data
data = data.astype(heatmap.dtype)
for label in 1, 2:
mask = (bins == bin) & (labels == label)
self.assertEqual(mode(heatmap[mask]), data[label-1])
def test_01_02_two_modes(self):
result = mode([1, 2, 2, 3, 3])
self.assertEqual(len(result), 2)
self.assertIn(2, result)
self.assertIn(3, result)
def test_01_01_single_mode(self):
result = mode([1, 1, 2])
self.assertEqual(len(result), 1)
self.assertEqual(result[0], 1)
def test_00_00_empty(self):
self.assertEqual(len(mode(np.zeros(0))), 0)
