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Add test cases for eigen value functions of structure tensor and hessian matrix

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This commit is contained in:
Johannes Schönberger
2013-11-29 20:42:05 +01:00
parent 53a339e4f4
commit 186e447c25
1 changed files with 51 additions and 16 deletions
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skimage/feature/tests/test_corner.py
+51 -16
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@@ -11,7 +11,8 @@ from skimage.feature import (corner_moravec, corner_harris, corner_shi_tomasi,
corner_subpix, peak_local_max, corner_peaks,
corner_kitchen_rosenfeld, corner_foerstner,
corner_fast, corner_orientations,
structure_tensor, hessian_matrix)
structure_tensor, structure_tensor_eigvals,
hessian_matrix, hessian_matrix_eigvals)
def test_structure_tensor():
@@ -39,21 +40,55 @@ def test_structure_tensor():
square = np.zeros((5, 5))
square[2, 2] = 1
Hxx, Hxy, Hyy = hessian_matrix(square, sigma=0.1)
assert_array_equal(Hxx, np.array([[ 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]]))
assert_array_equal(Hxy, np.array([[ 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0]]))
assert_array_equal(Hyy, np.array([[ 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]]))
assert_array_equal(Hxx, np.array([[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]]))
assert_array_equal(Hxy, np.array([[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]]))
assert_array_equal(Hyy, np.array([[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]]))
def test_structure_tensor_eigvals():
square = np.zeros((5, 5))
square[2, 2] = 1
Axx, Axy, Ayy = structure_tensor(square, sigma=0.1)
l1, l2 = structure_tensor_eigvals(Axx, Axy, Ayy)
assert_array_equal(l1, np.array([[0, 0, 0, 0, 0],
[0, 2, 4, 2, 0],
[0, 4, 0, 4, 0],
[0, 2, 4, 2, 0],
[0, 0, 0, 0, 0]]))
assert_array_equal(l2, np.array([[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]]))
def test_structure_tensor_eigvals():
square = np.zeros((5, 5))
square[2, 2] = 1
Hxx, Hxy, Hyy = hessian_matrix(square, sigma=0.1)
l1, l2 = hessian_matrix_eigvals(Hxx, Hxy, Hyy)
assert_array_equal(l1, np.array([[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]]))
assert_array_equal(l2, np.array([[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]]))
def test_square_image():