def test_extracts_mean_value(self):
img1 = np.zeros((64, 128))
img1[24:48, 65:100] = 1
img1[36:48, 65:100] = 2
extractor = poly.GridValueExtractor(np.arange(128), np.arange(64))
extractor.add_image(img1)
coords = np.array([
[0.0, 0.0],
[5.0, 0.0],
[5.0, 5.0],
[0.0, 5.0],
])
values = extractor.extract_values(coords)
np.testing.assert_almost_equal(values, [0.0])
coords = np.array([
[65.1, 24.1],
[65.1, 46.9],
[99.9, 46.9],
[99.9, 24.1],
])
values = extractor.extract_values(coords)
np.testing.assert_almost_equal(values, [1.5])
def test_equivalent_but_faster(self):
img1 = np.random.rand(64, 128)
img2 = np.random.rand(64, 128)
x = np.arange(64)
y = np.arange(128)
extractor = poly.GridValueExtractor(y, x)
extractor.add_image(img1)
extractor.add_image(img2)
coords = np.array([
[0.0, 0.0],
[10, 0.0],
[10, 10],
[20, 10],
[20, 20],
[0.0, 20.0],
])
mask = poly.mask_in_polygon(coords, y, x)
exp1 = np.mean(img1[mask])
exp2 = np.mean(img2[mask])
res1, res2 = extractor.extract_values(coords)
self.assertAlmostEqual(res1, exp1, places=4)
self.assertAlmostEqual(res2, exp2, places=4)
coords = np.array([
[70.0, 0.0],
[80.0, 0.0],
[80.0, 10.0],
[90.0, 10.0],
[90.0, 20.0],
[70.0, 20.0],
])
mask = poly.mask_in_polygon(coords, y, x)
exp1 = np.mean(img1[mask])
exp2 = np.mean(img2[mask])
res1, res2 = extractor.extract_values(coords)
self.assertAlmostEqual(res1, exp1, places=4)
self.assertAlmostEqual(res2, exp2, places=4)
def test_extract_outside_image_default_value(self):
img1 = np.zeros((64, 128))
img1[24:48, 65:100] = 1
img1[36:48, 65:100] = 2
extractor = poly.GridValueExtractor(np.arange(128), np.arange(64))
extractor.add_image(img1)
coords = np.array([
[-2, 0],
[-1, 0],
[-1, -1],
[-2, -1],
])
values = extractor.extract_values(coords)
np.testing.assert_almost_equal(values, [np.nan])
values = extractor.extract_values(coords, fill_value=-1)
np.testing.assert_almost_equal(values, [-1])
def test_can_extract_different_values(self):
img1 = np.zeros((64, 128))
img1[24:48, 65:100] = 1
img1[36:48, 65:100] = 2
extractor = poly.GridValueExtractor(np.arange(128), np.arange(64))
extractor.add_image(img1)
coords = np.array([
[65.1, 24.1],
[65.1, 46.9],
[99.9, 46.9],
[99.9, 24.1],
])
values = extractor.extract_values(coords, func=np.min)
np.testing.assert_almost_equal(values, [1.0])
values = extractor.extract_values(coords, func=np.max)
np.testing.assert_almost_equal(values, [2.0])
def test_extracts_equivalent_mask_right_side(self):
x = np.arange(64)
y = np.arange(128)
extractor = poly.GridValueExtractor(y, x)
coords = np.array([
[70.0, 0.0],
[80.0, 0.0],
[80.0, 10.0],
[90.0, 10.0],
[90.0, 20.0],
[70.0, 20.0],
])
mask1 = poly.mask_in_polygon(coords, y, x)
mask2 = extractor.extract_mask(coords)
self.assertTrue(np.any(mask1))
self.assertTrue(np.any(mask2))
self.assertTrue(np.all(mask1 == mask2))
def test_segment_and_extract_values(self):
img1 = np.zeros((64, 128))
img1[32, 72] = 50
img1[48, 12] = 100
img1[24, 32] = 25
img1[32, 24] = 75
extractor = poly.GridValueExtractor(np.arange(128), np.arange(64))
extractor.add_image(img1)
coords = extractor.segment_peaks(img1)
exp_coords = np.array([
[12, 48],
[24, 32],
[72, 32],
[32, 24],
])
np.testing.assert_almost_equal(coords, exp_coords)
values = extractor.extract_points(coords)[0]
np.testing.assert_almost_equal(values, [100, 75, 50, 25])
def test_segment_and_extract_masks(self):
img1 = np.zeros((64, 128))
img1[32, 72] = 50
img1[48, 12] = 100
img1[24, 32] = 25
img1[32, 24] = 75
extractor = poly.GridValueExtractor(np.arange(128), np.arange(64))
extractor.add_image(img1)
coords = extractor.segment_circles(img1, radius=5)
# Make sure the circles are centered where they should be
exp_centers = [
np.array([12, 48]),
np.array([24, 32]),
np.array([72, 32]),
np.array([32, 24]),
]
exp_values = [100, 75, 50, 25]
self.assertEqual(len(coords), len(exp_centers))
for coord, exp_center in zip(coords, exp_centers):
self.assertEqual(coord.shape, (50, 2))
res_center = np.mean(coord, axis=0)
np.testing.assert_almost_equal(res_center, exp_center)
# Make sure extracting the circles gives the peak value
self.assertEqual(len(coords), len(exp_values))
for coord, exp_value in zip(coords, exp_values):
max_value = extractor.extract_values(coord, func=np.max)[0]
self.assertEqual(max_value, exp_value)