def test_double_conversions(self):
output = efr.fit_improved_B2AC(self.points.copy())
general_1 = c2gconv.conic_to_general_1(output.copy())
general_2 = c2gconv.conic_to_general_2(output.copy())
general_3 = c2gconv.conic_to_general_reference(output.copy())
e_1 = B2ACEllipse(*general_1)
e_2 = B2ACEllipse(*general_2)
e_3 = B2ACEllipse(*general_3)
# Test correct center point.
assert np.linalg.norm(self.e.center_point - e_1.center_point) < 1
# assert np.linalg.norm(self.e.center_point - e_2.center_point) < 1
assert np.linalg.norm(self.e.center_point - e_3.center_point) < 1
# Test correct radii.
assert np.linalg.norm(max(self.e.radii) - max(e_1.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_1.radii)) < 0.25
# assert np.linalg.norm(max(self.e.radii) - max(e_2.radii)) < 0.25
# assert np.linalg.norm(min(self.e.radii) - min(e_2.radii)) < 0.25
assert np.linalg.norm(max(self.e.radii) - max(e_3.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_3.radii)) < 0.25
# Test overlap
assert overlap(self.e, e_1) > 0.98
assert overlap(e_1, self.e) > 0.98
# assert overlap(self.e, e_2) > 0.98
# assert overlap(e_2, self.e) > 0.98
assert overlap(self.e, e_3) > 0.98
assert overlap(e_3, self.e) > 0.98
def test_double_conversions(self):
output = efr.fit_improved_B2AC(self.points.copy())
general_1 = c2gconv.conic_to_general_1(output.copy())
general_2 = c2gconv.conic_to_general_2(output.copy())
general_3 = c2gconv.conic_to_general_reference(output.copy())
e_1 = B2ACEllipse(*general_1)
e_2 = B2ACEllipse(*general_2)
e_3 = B2ACEllipse(*general_3)
# Test correct center point.
assert np.linalg.norm(self.e.center_point - e_1.center_point) < 1
# assert np.linalg.norm(self.e.center_point - e_2.center_point) < 1
assert np.linalg.norm(self.e.center_point - e_3.center_point) < 1
# Test correct radii.
assert np.linalg.norm(max(self.e.radii) - max(e_1.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_1.radii)) < 0.25
# assert np.linalg.norm(max(self.e.radii) - max(e_2.radii)) < 0.25
# assert np.linalg.norm(min(self.e.radii) - min(e_2.radii)) < 0.25
assert np.linalg.norm(max(self.e.radii) - max(e_3.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_3.radii)) < 0.25
# Test overlap
assert overlap(self.e, e_1) > 0.98
assert overlap(e_1, self.e) > 0.98
# assert overlap(self.e, e_2) > 0.98
# assert overlap(e_2, self.e) > 0.98
assert overlap(self.e, e_3) > 0.98
assert overlap(e_3, self.e) > 0.98
def test_fit_ext_float_version(self):
output = fitext.fit_ellipse_float(self.points.copy())
e_fitted = B2ACEllipse(*output)
assert np.linalg.norm(self.e.center_point - e_fitted.center_point) < 1
assert np.linalg.norm(max(self.e.radii) - max(e_fitted.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_fitted.radii)) < 0.25
assert overlap(self.e, e_fitted) > 0.98
assert overlap(e_fitted, self.e) > 0.98
def test_fit_ext_float_version(self):
output = fitext.fit_ellipse_float(self.points.copy())
e_fitted = B2ACEllipse(*output)
assert np.linalg.norm(self.e.center_point - e_fitted.center_point) < 1
assert np.linalg.norm(max(self.e.radii) - max(e_fitted.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_fitted.radii)) < 0.25
assert overlap(self.e, e_fitted) > 0.98
assert overlap(e_fitted, self.e) > 0.98
def test_fit_double_version(self):
output = fit_improved_B2AC_double(self.points.copy())
output = c2gconv.conic_to_general_1(output)
e_fitted = B2ACEllipse(*output)
assert np.linalg.norm(self.e.center_point - e_fitted.center_point) < 1
assert np.linalg.norm(max(self.e.radii) - max(e_fitted.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_fitted.radii)) < 0.25
assert overlap(self.e, e_fitted) > 0.98
assert overlap(e_fitted, self.e) > 0.98
def test_fit_double_version(self):
output = fit_improved_B2AC_double(self.points.copy())
output = c2gconv.conic_to_general_1(output)
e_fitted = B2ACEllipse(*output)
assert np.linalg.norm(self.e.center_point - e_fitted.center_point) < 1
assert np.linalg.norm(max(self.e.radii) - max(e_fitted.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_fitted.radii)) < 0.25
assert overlap(self.e, e_fitted) > 0.98
assert overlap(e_fitted, self.e) > 0.98
def test_fit_int_version_1(self):
output = fit_improved_B2AC_int(self.points.copy())
ellipse_data = c2gconv.conic_to_general_int(output, return_float=True, verbose=True)
e_fitted = B2ACEllipse(*ellipse_data)
assert np.linalg.norm(self.e.center_point - e_fitted.center_point) < 1
assert np.linalg.norm(max(self.e.radii) - max(e_fitted.radii)) < 1
assert np.linalg.norm(min(self.e.radii) - min(e_fitted.radii)) < 1
assert overlap(self.e, e_fitted) > 0.95
assert overlap(e_fitted, self.e) > 0.95
def test_fit_ref(self):
points = self.points.copy()
output = efr.fit_improved_B2AC(points)
general_form = c2gconv.conic_to_general_1(output)
e_fitted = B2ACEllipse(*general_form)
assert np.linalg.norm(self.e.center_point - e_fitted.center_point) < 1
assert np.linalg.norm(max(self.e.radii) - max(e_fitted.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_fitted.radii)) < 0.25
assert overlap(self.e, e_fitted) > 0.98
assert overlap(e_fitted, self.e) > 0.98
def test_fit_ref(self):
points = self.points.copy()
output = efr.fit_improved_B2AC(points)
general_form = c2gconv.conic_to_general_1(output)
e_fitted = B2ACEllipse(*general_form)
assert np.linalg.norm(self.e.center_point - e_fitted.center_point) < 1
assert np.linalg.norm(max(self.e.radii) - max(e_fitted.radii)) < 0.25
assert np.linalg.norm(min(self.e.radii) - min(e_fitted.radii)) < 0.25
assert overlap(self.e, e_fitted) > 0.98
assert overlap(e_fitted, self.e) > 0.98
def test_py_and_ext_similarity(self):
output = fitext.fit_ellipse_int(self.points.copy())
e_ext = B2ACEllipse(*output)
points, x_mean, y_mean = remove_mean_values(self.points.copy())
output = fit_improved_B2AC_int(points)
ellipse_data = c2gconv.conic_to_general_int(output, return_float=True, verbose=True)
e_py = B2ACEllipse(*ellipse_data)
e_py.center_point += (x_mean, y_mean)
assert overlap(e_ext, e_py) > 0.99
assert overlap(e_py, e_ext) > 0.99
def test_fit_int_version_2(self):
points, x_mean, y_mean = remove_mean_values(self.points.copy())
output = fit_improved_B2AC_int(points)
ellipse_data = c2gconv.conic_to_general_int(output, return_float=True, verbose=True)
e_fitted = B2ACEllipse(*ellipse_data)
e_fitted.center_point += (x_mean, y_mean)
print(e_fitted)
assert np.linalg.norm(self.e.center_point - e_fitted.center_point) < 1.0
assert np.linalg.norm(max(self.e.radii) - max(e_fitted.radii)) < 0.1
assert np.linalg.norm(min(self.e.radii) - min(e_fitted.radii)) < 0.1
assert overlap(self.e, e_fitted) > 0.98
assert overlap(e_fitted, self.e) > 0.98
