def test_srsf_conversion(self):
"""Converts to srsf and pull backs"""
initial = self.unimodal_samples(-1)
converted = from_srsf(to_srsf(self.unimodal_samples), initial=initial)
# Distances between original samples and s -> to_srsf -> from_srsf
distances = np.diag(metric(converted, self.unimodal_samples))
np.testing.assert_allclose(distances, 0, atol=8e-3)
def test_from_srsf(self):
"""Test from srsf"""
# Checks SRSF conversion
srsf = from_srsf(self.dummy_sample)
data_matrix = [[[0.], [-0.23449228], [-0.83464009], [-1.38200046],
[-1.55623723], [-1.38200046], [-0.83464009],
[-0.23449228], [0.]]]
np.testing.assert_almost_equal(data_matrix, srsf.data_matrix)
def animate(i):
if i < 100:
p = i / 100
pp = 1 - p
else:
pp = (i - 100) / 100
p = 1 - pp
#print(a,b,c, d)
ff = from_srsf(p * q + pp * q2)
line.set_data(ff.sample_points[0], ff.data_matrix.squeeze())
if i < 100:
j = i
else:
j = 199 - i
line.set_color(color[j])
return line,
q = to_srsf(fd)
q2 = to_srsf(fd2)
cmap = clr.LinearSegmentedColormap.from_list('custom cmap', ['C0','C1'])
v = [.25, .5, .75]
color = cmap(v)
plt.figure("srsf-geodesic")
q.plot(label="$q_1$", linewidth=2)
q2.plot(label="$q_2$", linewidth=2)
for m, c in zip(v, color):
y = (1 - m)*q + m*q2
y.plot(color=c)
plt.legend()
plt.tight_layout()
plt.figure("geodesic")
fd.plot(label="$f_1$", linewidth=2)
fd2.plot(label="$f_2$", linewidth=2)
for m, c in zip(v, color):
y = (1 - m)*q + m*q2
from_srsf(y).plot(color=c)
plt.legend()
plt.tight_layout()
plt.show()