def test_collinear_segments(self):
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, 1]), np.array([0, 0, 2.]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, -1]), np.array([0, 0, -2.]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, -2]), np.array([0, 0, -1.]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
a = (np.array([0., 0, 0]), np.array([1, 1, 1]))
b = (np.array([2., 2, 2]), np.array([3, 3, 3.]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
a = (np.array([0., 0, 0]), np.array([1, 1, 1]))
b = (np.array([0.5, 0.5, 0.5]), np.array([0.7, 0.7, 0.7]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
def test_collinear_segments(self):
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, 1]), np.array([0, 0, 2.]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, -1]), np.array([0, 0, -2.]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, -2]), np.array([0, 0, -1.]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
a = (np.array([0., 0, 0]), np.array([1, 1, 1]))
b = (np.array([2., 2, 2]), np.array([3, 3, 3.]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
a = (np.array([0., 0, 0]), np.array([1, 1, 1]))
b = (np.array([0.5, 0.5, 0.5]), np.array([0.7, 0.7, 0.7]))
self.assertAlmostEqual(ftuv.line_segments_collinearity(a, b), 1)
def test_normal_angle(self):
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, 1]), np.array([0., 1, 1]))
x = np.linspace(0.01, 4, 500)
for f in x:
col = ftuv.line_segments_collinearity(a, (b[0] * f, b[1] * f))
self.assertLess(col, 0.6)
self.assertGreater(col, 0.)
def test_normal_angle(self):
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, 1]), np.array([0., 1, 1]))
x = np.linspace(0.01, 4, 500)
for f in x:
col = ftuv.line_segments_collinearity(a, (b[0] * f, b[1] * f))
self.assertLess(col, 0.6)
self.assertGreater(col, 0.)
def plot_distance(self):
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
x = np.linspace(0.01, 10, 5000)
y = []
for d in x:
b0 = a[1] + np.array([0, 1., 0.]) * d
b = b0, b0 + np.array([0., 0, 1])
y.append(ftuv.line_segments_collinearity(a, b))
import matplotlib.pyplot as plt
plt.title("distance")
plt.plot(x, y)
plt.show()
def test_distance(self):
#score decreases with increasing distance, but stays above 0
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
x = np.linspace(0.01, 10, 5000)
y_old = 1
for d in x:
b0 = a[1] + np.array([0, 1., 0.]) * d
b = b0, b0 + np.array([0., 0, 1])
y = ftuv.line_segments_collinearity(a, b)
self.assertLess(y, y_old)
self.assertGreater(y, 0)
y_old = y
def plot_normal(self):
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, 1]), np.array([0., 1, 1]))
x = np.linspace(0.01, 4, 5000)
y = []
for f in x:
y.append(ftuv.line_segments_collinearity(a, (b[0] * f, b[1] * f)))
import matplotlib.pyplot as plt
plt.title("normal")
plt.plot(x, y)
plt.show()
assert False
def plot_distance(self):
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
x = np.linspace(0.01, 10, 5000)
y = []
for d in x:
b0 = a[1] + np.array([0, 1., 0.]) * d
b = b0, b0 + np.array([0., 0, 1])
y.append(ftuv.line_segments_collinearity(a, b))
import matplotlib.pyplot as plt
plt.title("distance")
plt.plot(x, y)
plt.show()
def test_distance(self):
# score decreases with increasing distance, but stays above 0
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
x = np.linspace(0.01, 10, 5000)
y_old = 1
for d in x:
b0 = a[1] + np.array([0, 1., 0.]) * d
b = b0, b0 + np.array([0., 0, 1])
y = ftuv.line_segments_collinearity(a, b)
self.assertLess(y, y_old)
self.assertGreater(y, 0)
y_old = y
def plot_normal(self):
a = (np.array([0., 0, 0]), np.array([0, 0, 1]))
b = (np.array([0., 0, 1]), np.array([0., 1, 1]))
x = np.linspace(0.01, 4, 5000)
y = []
for f in x:
y.append(ftuv.line_segments_collinearity(a, (b[0] * f, b[1] * f)))
import matplotlib.pyplot as plt
plt.title("normal")
plt.plot(x, y)
plt.show()
assert False
