def test_3d(self):
"""tests the detection of maxima in 3D."""
img = np.zeros((8, 8, 8), dtype=np.uint8)
local_maxima = np.zeros((8, 8, 8), dtype=np.uint64)
# first maximum: only one pixel
img[1, 1:3, 1:3] = 100
img[2, 2, 2] = 200
img[3, 1:3, 1:3] = 100
local_maxima[2, 2, 2] = 1
# second maximum: three pixels in z-direction
img[5:8, 1, 1] = 200
local_maxima[5:8, 1, 1] = 1
# third: two maxima in 0 and 3.
img[0, 5:8, 5:8] = 200
img[1, 6, 6] = 100
img[2, 5:7, 5:7] = 200
img[0:3, 5:8, 5:8] += 50
local_maxima[0, 5:8, 5:8] = 1
local_maxima[2, 5:7, 5:7] = 1
# four : one maximum in the corner of the square
img[6:8, 6:8, 6:8] = 200
img[7, 7, 7] = 255
local_maxima[7, 7, 7] = 1
out = max_tree_local_maxima(img)
out_bin = out > 0
assert_array_equal(local_maxima, out_bin)
assert np.max(out) == 5
def test_3d(self):
"""tests the detection of maxima in 3D."""
img = np.zeros((8, 8, 8), dtype=np.uint8)
local_maxima = np.zeros((8, 8, 8), dtype=np.uint64)
# first maximum: only one pixel
img[1, 1:3, 1:3] = 100
img[2, 2, 2] = 200
img[3, 1:3, 1:3] = 100
local_maxima[2, 2, 2] = 1
# second maximum: three pixels in z-direction
img[5:8, 1, 1] = 200
local_maxima[5:8, 1, 1] = 1
# third: two maxima in 0 and 3.
img[0, 5:8, 5:8] = 200
img[1, 6, 6] = 100
img[2, 5:7, 5:7] = 200
img[0:3, 5:8, 5:8] += 50
local_maxima[0, 5:8, 5:8] = 1
local_maxima[2, 5:7, 5:7] = 1
# four : one maximum in the corner of the square
img[6:8, 6:8, 6:8] = 200
img[7, 7, 7] = 255
local_maxima[7, 7, 7] = 1
out = max_tree_local_maxima(img)
out_bin = out > 0
assert_array_equal(local_maxima, out_bin)
assert np.max(out) == 5
def test_extrema_float(self):
"specific tests for float type"
data = np.array(
[[0.10, 0.11, 0.13, 0.14, 0.14, 0.15, 0.14, 0.14, 0.13, 0.11],
[0.11, 0.13, 0.15, 0.16, 0.16, 0.16, 0.16, 0.16, 0.15, 0.13],
[0.13, 0.15, 0.40, 0.40, 0.18, 0.18, 0.18, 0.60, 0.60, 0.15],
[0.14, 0.16, 0.40, 0.40, 0.19, 0.19, 0.19, 0.60, 0.60, 0.16],
[0.14, 0.16, 0.18, 0.19, 0.19, 0.19, 0.19, 0.19, 0.18, 0.16],
[0.15, 0.182, 0.18, 0.19, 0.204, 0.20, 0.19, 0.19, 0.18, 0.16],
[0.14, 0.16, 0.18, 0.19, 0.19, 0.19, 0.19, 0.19, 0.18, 0.16],
[0.14, 0.16, 0.80, 0.80, 0.19, 0.19, 0.19, 4.0, 1.0, 0.16],
[0.13, 0.15, 0.80, 0.80, 0.18, 0.18, 0.18, 1.0, 1.0, 0.15],
[0.11, 0.13, 0.15, 0.16, 0.16, 0.16, 0.16, 0.16, 0.15, 0.13]],
dtype=np.float32)
expected_result = np.array(
[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]],
dtype=np.uint8)
# test for local maxima
out = max_tree_local_maxima(data, connectivity=1)
out_bin = out > 0
assert_array_equal(expected_result, out_bin)
assert np.max(out) == 6
def test_local_maxima(self):
"local maxima for various data types"
data = np.array([[10, 11, 13, 14, 14, 15, 14, 14, 13, 11],
[11, 13, 15, 16, 16, 16, 16, 16, 15, 13],
[13, 15, 40, 40, 18, 18, 18, 60, 60, 15],
[14, 16, 40, 40, 19, 19, 19, 60, 60, 16],
[14, 16, 18, 19, 19, 19, 19, 19, 18, 16],
[15, 16, 18, 19, 19, 20, 19, 19, 18, 16],
[14, 16, 18, 19, 19, 19, 19, 19, 18, 16],
[14, 16, 80, 80, 19, 19, 19, 100, 100, 16],
[13, 15, 80, 80, 18, 18, 18, 100, 100, 15],
[11, 13, 15, 16, 16, 16, 16, 16, 15, 13]],
dtype=np.uint8)
expected_result = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]],
dtype=np.uint64)
for dtype in [np.uint8, np.uint64, np.int8, np.int64]:
test_data = data.astype(dtype)
out = max_tree_local_maxima(test_data, connectivity=1)
out_bin = out > 0
assert_array_equal(expected_result, out_bin)
assert out.dtype == expected_result.dtype
assert np.max(out) == 5
P, S = max_tree(test_data)
out = max_tree_local_maxima(test_data,
parent=P,
tree_traverser=S)
assert_array_equal(expected_result, out_bin)
assert out.dtype == expected_result.dtype
assert np.max(out) == 5
def test_local_maxima(self):
"local maxima for various data types"
data = np.array([[10, 11, 13, 14, 14, 15, 14, 14, 13, 11],
[11, 13, 15, 16, 16, 16, 16, 16, 15, 13],
[13, 15, 40, 40, 18, 18, 18, 60, 60, 15],
[14, 16, 40, 40, 19, 19, 19, 60, 60, 16],
[14, 16, 18, 19, 19, 19, 19, 19, 18, 16],
[15, 16, 18, 19, 19, 20, 19, 19, 18, 16],
[14, 16, 18, 19, 19, 19, 19, 19, 18, 16],
[14, 16, 80, 80, 19, 19, 19, 100, 100, 16],
[13, 15, 80, 80, 18, 18, 18, 100, 100, 15],
[11, 13, 15, 16, 16, 16, 16, 16, 15, 13]],
dtype=np.uint8)
expected_result = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]],
dtype=np.uint64)
for dtype in [np.uint8, np.uint64, np.int8, np.int64]:
test_data = data.astype(dtype)
out = max_tree_local_maxima(test_data, connectivity=1)
out_bin = out > 0
assert_array_equal(expected_result, out_bin)
assert out.dtype == expected_result.dtype
assert np.max(out) == 5
P, S = max_tree(test_data)
out = max_tree_local_maxima(test_data,
parent=P,
tree_traverser=S)
assert_array_equal(expected_result, out_bin)
assert out.dtype == expected_result.dtype
assert np.max(out) == 5
def maksimum_tree(image):
image = color.rgb2gray(image)
max_tree = max_tree_local_maxima(image)
fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(8, 8))
ax = axes.ravel()
ax[0].imshow(image, cmap='gray')
ax[0].set_title("Original image")
ax[1].imshow(max_tree, cmap='gray')
ax[1].set_title("Max tree ")
plt.tight_layout()
plt.show()
def test_extrema_float(self):
"specific tests for float type"
data = np.array([[0.10, 0.11, 0.13, 0.14, 0.14, 0.15, 0.14,
0.14, 0.13, 0.11],
[0.11, 0.13, 0.15, 0.16, 0.16, 0.16, 0.16,
0.16, 0.15, 0.13],
[0.13, 0.15, 0.40, 0.40, 0.18, 0.18, 0.18,
0.60, 0.60, 0.15],
[0.14, 0.16, 0.40, 0.40, 0.19, 0.19, 0.19,
0.60, 0.60, 0.16],
[0.14, 0.16, 0.18, 0.19, 0.19, 0.19, 0.19,
0.19, 0.18, 0.16],
[0.15, 0.182, 0.18, 0.19, 0.204, 0.20, 0.19,
0.19, 0.18, 0.16],
[0.14, 0.16, 0.18, 0.19, 0.19, 0.19, 0.19,
0.19, 0.18, 0.16],
[0.14, 0.16, 0.80, 0.80, 0.19, 0.19, 0.19,
4.0, 1.0, 0.16],
[0.13, 0.15, 0.80, 0.80, 0.18, 0.18, 0.18,
1.0, 1.0, 0.15],
[0.11, 0.13, 0.15, 0.16, 0.16, 0.16, 0.16,
0.16, 0.15, 0.13]],
dtype=np.float32)
expected_result = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 1, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]],
dtype=np.uint8)
# test for local maxima
out = max_tree_local_maxima(data, connectivity=1)
out_bin = out > 0
assert_array_equal(expected_result, out_bin)
assert np.max(out) == 6