def test_nt(self):
p = np.ones((2, 3))
nt0, nt1 = 100, 200
pa0 = mdtd._make_4d_peak_array_test_data(p, p, p, p, p, nt=nt0)
pa1 = mdtd._make_4d_peak_array_test_data(p, p, p, p, p, nt=nt1)
assert len(pa0[0, 0][:, 0]) == nt0
assert len(pa1[0, 0][:, 0]) == nt1
def test_semi_len_ratio_lim(self):
xf, yf = np.ones((2, 3)) * 200, np.ones((2, 3)) * 210
semi00, semi01 = np.ones((2, 3)) * 100, np.ones((2, 3)) * 100
semi10, semi11 = np.ones((2, 3)) * 100, np.ones((2, 3)) * 190
rot = np.zeros((2, 3))
peak_array = mdtd._make_4d_peak_array_test_data(xf,
yf,
semi00,
semi01,
rot,
nt=20)
peak_array1 = mdtd._make_4d_peak_array_test_data(xf,
yf,
semi10,
semi11,
rot,
nt=20)
for iy, ix in np.ndindex(xf.shape):
peak_array[iy, ix] = np.vstack(
(peak_array[iy, ix], peak_array1[iy, ix]))
ellipse_array0, inlier_array0 = ret.get_ellipse_model_ransac(
peak_array,
xf=200,
yf=210,
rf_lim=20,
semi_len_min=95,
semi_len_max=195,
semi_len_ratio_lim=1.11,
min_samples=15,
max_trails=200,
)
ellipse_array1, inlier_array1 = ret.get_ellipse_model_ransac(
peak_array,
xf=200,
yf=210,
rf_lim=20,
semi_len_min=95,
semi_len_max=195,
semi_len_ratio_lim=2.0,
min_samples=15,
max_trails=200,
)
semi_len_ratio_list = []
for iy, ix in np.ndindex(xf.shape):
if ellipse_array1[iy, ix] is not None:
semi0, semi1 = ellipse_array1[iy, ix][2:4]
semi_len_ratio = max(semi0, semi1) / min(semi0, semi1)
semi_len_ratio_list.append(semi_len_ratio)
semi_len_ratio_list = np.array(semi_len_ratio_list)
assert (semi_len_ratio_list > 1.8).any()
def test_rf_lim(self):
xf, yf = np.ones((2, 3)) * 200, np.ones((2, 3)) * 210
np.random.seed(7)
semi0 = np.random.randint(90, 110, size=(2, 3))
semi1 = np.random.randint(130, 140, size=(2, 3))
rot = np.zeros((2, 3))
peak_array = mdtd._make_4d_peak_array_test_data(
xf, yf, semi0, semi1, rot, nt=20
)
ellipse_array0, inlier_array0 = ret.get_ellipse_model_ransac(
peak_array,
xf=200,
yf=210,
rf_lim=20,
semi_len_min=80,
semi_len_max=150,
semi_len_ratio_lim=1.7,
min_samples=15,
max_trails=20,
)
ellipse_array1, inlier_array1 = ret.get_ellipse_model_ransac(
peak_array,
xf=200,
yf=210,
rf_lim=20,
semi_len_min=80,
semi_len_max=150,
semi_len_ratio_lim=1.01,
min_samples=15,
max_trails=20,
)
for iy, ix in np.ndindex(xf.shape):
ellipse_params0 = ellipse_array0[iy, ix]
ellipse_params1 = ellipse_array1[iy, ix]
assert ellipse_params0 != ellipse_params1
def test_semi_lengths(self):
xf, yf = np.ones((2, 3)) * 200, np.ones((2, 3)) * 210
np.random.seed(7)
semi0 = np.random.randint(90, 110, size=(2, 3))
semi1 = np.random.randint(130, 140, size=(2, 3))
rot = np.zeros((2, 3))
peak_array = mdtd._make_4d_peak_array_test_data(
xf, yf, semi0, semi1, rot, nt=20
)
ellipse_array, inlier_array = ret.get_ellipse_model_ransac(
peak_array,
xf=200,
yf=210,
rf_lim=20,
semi_len_min=80,
semi_len_max=150,
semi_len_ratio_lim=1.7,
min_samples=15,
max_trails=20,
)
for iy, ix in np.ndindex(xf.shape):
semi_min = min(ellipse_array[iy, ix][2], ellipse_array[iy, ix][3])
semi_max = max(ellipse_array[iy, ix][2], ellipse_array[iy, ix][3])
assert approx(semi_min, abs=0.01) == semi0[iy, ix]
assert approx(semi_max, abs=0.01) == semi1[iy, ix]
def test_rotation(self):
rot0, rot1 = np.zeros((2, 3)), np.ones((2, 3)) * np.pi / 2
xf, yf = np.ones((2, 3)), np.ones((2, 3))
semi0, semi1 = np.ones((2, 3)) * 5, np.ones((2, 3))
pa0 = mdtd._make_4d_peak_array_test_data(xf,
yf,
semi0,
semi1,
rot0,
nt=1000)
pa1 = mdtd._make_4d_peak_array_test_data(xf,
yf,
semi0,
semi1,
rot1,
nt=1000)
assert not np.array_equal(pa0, pa1)
def test_simple(self):
xc, yc = np.ones((2, 3)), np.ones((2, 3))
semi0, semi1 = np.ones((2, 3)), np.ones((2, 3))
rot = np.zeros((2, 3))
peak_array = mdtd._make_4d_peak_array_test_data(xc, yc, semi0, semi1, rot)
ellipse_array, inlier_array = ret.get_ellipse_model_ransac(
peak_array, max_trails=50
)
assert ellipse_array.shape == xc.shape
assert inlier_array.shape == xc.shape
def test_semi_lengths(self):
semi0 = np.random.randint(10, 20, size=(2, 3))
semi1 = np.random.randint(10, 20, size=(2, 3))
xf, yf, rot = np.ones((2, 3)) * 10, np.ones((2, 3)), np.zeros((2, 3))
peak_array0 = mdtd._make_4d_peak_array_test_data(xf,
yf,
semi0,
semi0,
rot,
nt=1000)
peak_array1 = mdtd._make_4d_peak_array_test_data(xf,
yf,
semi1,
semi1,
rot,
nt=1000)
for iy, ix in np.ndindex(xf.shape):
semi0_max = semi0[iy, ix] + xf[iy, ix]
assert approx(peak_array0[iy, ix][:, 1].max()) == semi0_max
semi1_max = semi1[iy, ix] + yf[iy, ix]
assert approx(peak_array1[iy, ix][:, 0].max()) == semi1_max
def test_xf_yf(self):
xf = np.random.randint(10, 20, size=(2, 3))
yf = np.random.randint(39, 60, size=(2, 3))
semi0, semi1, rot = np.ones((2, 3)), np.ones((2, 3)), np.ones((2, 3))
peak_array = mdtd._make_4d_peak_array_test_data(xf,
yf,
semi0,
semi1,
rot,
nt=1000)
for iy, ix in np.ndindex(xf.shape):
x_pos_mean = peak_array[iy, ix][:, 1].mean()
assert approx(x_pos_mean, abs=0.01) == xf[iy, ix]
y_pos_mean = peak_array[iy, ix][:, 0].mean()
assert approx(y_pos_mean, abs=0.01) == yf[iy, ix]
def test_xc_yc(self):
np.random.seed(7)
xf = np.random.randint(90, 100, size=(2, 3))
yf = np.random.randint(110, 120, size=(2, 3))
semi0, semi1 = np.ones((2, 3)) * 60, np.ones((2, 3)) * 60
rot = np.zeros((2, 3))
peak_array = mdtd._make_4d_peak_array_test_data(xf,
yf,
semi0,
semi1,
rot,
nt=20)
ellipse_array0, inlier_array0 = ret.get_ellipse_model_ransac(
peak_array,
xf=95,
yf=115,
rf_lim=20,
semi_len_min=50,
semi_len_max=65,
semi_len_ratio_lim=1.2,
min_samples=15,
max_trails=20,
)
ellipse_array1, inlier_array1 = ret.get_ellipse_model_ransac(
peak_array,
xf=10,
yf=12,
rf_lim=20,
semi_len_min=50,
semi_len_max=65,
semi_len_ratio_lim=1.2,
min_samples=15,
max_trails=20,
)
for iy, ix in np.ndindex(xf.shape):
assert approx(xf[iy, ix], abs=0.0005) == ellipse_array0[iy, ix][1]
assert approx(yf[iy, ix], abs=0.0005) == ellipse_array0[iy, ix][0]
assert inlier_array0[iy, ix].all()
assert ellipse_array1[iy, ix] is None
assert inlier_array1[iy, ix] is None
def get_simple_ellipse_signal_peak_array():
"""Get a signal and peak array of an ellipse.
Returns
-------
signal, peak_array : HyperSpy Signal2D, NumPy array
Examples
--------
>>> s, peak_array = pxm.dummy_data.get_simple_ellipse_signal_peak_array()
>>> s.add_peak_array_as_markers(peak_array, color='blue', size=30)
"""
xc = np.random.randint(95, 105, size=(4, 5))
yc = np.random.randint(95, 105, size=(4, 5))
semi0 = np.random.randint(55, 60, size=(4, 5))
semi1 = np.random.randint(75, 80, size=(4, 5))
rot = np.random.random(size=(4, 5)) * np.pi
peak_array = mdtd._make_4d_peak_array_test_data(xc, yc, semi0, semi1, rot)
s = Diffraction2D(np.zeros((4, 5, 200, 200)))
return s, peak_array
def test_residual_threshold(self):
xyf, semi = np.ones((2, 3)) * 100, np.ones((2, 3)) * 90
rot = np.zeros((2, 3))
peak_array = mdtd._make_4d_peak_array_test_data(xyf,
xyf,
semi,
semi,
rot,
nt=20)
for iy, ix in np.ndindex(xyf.shape):
peak_array[iy, ix] = np.vstack((peak_array[iy, ix], [100, 5]))
ellipse_array0, inlier_array0 = ret.get_ellipse_model_ransac(
peak_array,
xf=100,
yf=100,
semi_len_min=85,
semi_len_max=95,
semi_len_ratio_lim=1.1,
residual_threshold=1,
max_trails=100,
min_samples=15,
)
ellipse_array1, inlier_array1 = ret.get_ellipse_model_ransac(
peak_array,
xf=100,
yf=100,
semi_len_min=85,
semi_len_max=95,
semi_len_ratio_lim=1.1,
residual_threshold=5,
max_trails=100,
min_samples=15,
)
for iy, ix in np.ndindex(xyf.shape):
inlier0 = inlier_array0[iy, ix]
inlier1 = inlier_array1[iy, ix]
assert inlier0.sum() == 20
assert inlier1.sum() == 21
def test_simple(self):
xf, yf = np.ones((2, 3)), np.ones((2, 3))
semi0, semi1, rot = np.ones((2, 3)), np.ones((2, 3)), np.ones((2, 3))
peak_array = mdtd._make_4d_peak_array_test_data(
xf, yf, semi0, semi1, rot)
assert peak_array.shape == xf.shape
