def plot_itakura(n_timestamps_1, n_timestamps_2, max_slope=1., ax=None):
region = itakura_parallelogram(n_timestamps_1, n_timestamps_2, max_slope)
max_slope, min_slope = _get_itakura_slopes(n_timestamps_1, n_timestamps_2,
max_slope)
if ax is None:
_, ax = ax.subplots(1,
1,
figsize=(n_timestamps_1 / 2, n_timestamps_2 / 2))
mask = np.zeros((n_timestamps_2, n_timestamps_1))
for i, (j, k) in enumerate(region.T):
mask[j:k, i] = 1.
ax.imshow(mask, origin='lower', cmap='Wistia')
sz = max(n_timestamps_1, n_timestamps_2)
x = np.arange(-1, sz + 1)
low_max_line = ((n_timestamps_2 - 1) - max_slope * (n_timestamps_1 - 1)) +\
max_slope * np.arange(-1, sz + 1)
up_min_line = ((n_timestamps_2 - 1) - min_slope * (n_timestamps_1 - 1)) +\
min_slope * np.arange(-1, sz + 1)
diag = (n_timestamps_2 - 1) / (n_timestamps_1 - 1) * np.arange(-1, sz + 1)
ax.plot(x, diag, 'black', lw=1)
ax.plot(x, max_slope * np.arange(-1, sz + 1), 'b', lw=1.5)
ax.plot(x, min_slope * np.arange(-1, sz + 1), 'r', lw=1.5)
ax.plot(x, low_max_line, 'g', lw=1.5)
ax.plot(x, up_min_line, 'y', lw=1.5)
for i in range(n_timestamps_1):
for j in range(n_timestamps_2):
ax.plot(i, j, 'o', color='green', ms=1)
ax.set_xticks(np.arange(-.5, max(n_timestamps_1, n_timestamps_2), 1),
minor=True)
ax.set_yticks(np.arange(-.5, max(n_timestamps_1, n_timestamps_2), 1),
minor=True)
ax.grid(which='minor', color='b', linestyle='--', linewidth=1)
ax.set_xlim((-0.5, n_timestamps_1 - 0.5))
ax.set_ylim((-0.5, n_timestamps_2 - 0.5))
return ax
def test_actual_results_itakura_parallelogram(params, arr_desired):
"""Test that the actual results are the expected ones."""
arr_actual = itakura_parallelogram(**params)
np.testing.assert_allclose(arr_actual, arr_desired, atol=1e-5, rtol=0.)
def test_parameter_check_itakura_parallelogram(params, error, err_msg):
"""Test parameter validation."""
with pytest.raises(error, match=re.escape(err_msg)):
itakura_parallelogram(**params)
plt.subplot(2, 2, 2)
plt.pcolor(timestamps_1, timestamps_2, matrix_sakoechiba.T,
edgecolors='k', cmap='Greys')
plt.xlabel('x', fontsize=12)
plt.ylabel('y', fontsize=12)
plt.title("{0}\nDTW(x, y) = {1:.2f}".format('sakoechiba', dtw_sakoechiba),
fontsize=14)
# Dynamic Time Warping: itakura
slope = 1.2
dtw_itakura, path_itakura = dtw(
x, y, dist='square', method='itakura',
options={'max_slope': slope}, return_path=True
)
parallelogram = itakura_parallelogram(n_timestamps_1, n_timestamps_2,
max_slope=slope)
matrix_itakura = np.zeros((n_timestamps_1 + 1, n_timestamps_2 + 1))
for i in range(n_timestamps_1):
matrix_itakura[i, np.arange(*parallelogram[:, i])] = 0.5
matrix_itakura[tuple(path_itakura)] = 1.
plt.subplot(2, 2, 3)
plt.pcolor(timestamps_1, timestamps_2, matrix_itakura.T,
edgecolors='k', cmap='Greys')
plt.xlabel('x', fontsize=12)
plt.ylabel('y', fontsize=12)
plt.title("{0}\nDTW(x, y) = {1:.2f}".format('itakura', dtw_itakura),
fontsize=14)
# Dynamic Time Warping: multiscale
resolution, radius = 5, 2
dtw_multiscale, path_multiscale = dtw(
matrix_sakoechiba,
edgecolors='k',
cmap='Greys')
plt.xlabel('x', fontsize=20, labelpad=-10)
plt.ylabel('y', fontsize=20, labelpad=-10)
plt.title("{0}\nDTW(x, y) = {1:.2f}".format('sakoechiba', dtw_sakoechiba),
fontsize=16)
# Dynamic Time Warping: itakura
dtw_itakura, path_itakura = dtw(x,
y,
dist='square',
method='itakura',
options={'max_slope': 2.},
return_path=True)
parallelogram = itakura_parallelogram(n_timestamps, max_slope=2.)
matrix_itakura = np.zeros((n_timestamps + 1, n_timestamps + 1))
for i in range(n_timestamps):
matrix_itakura[i, np.arange(*parallelogram[:, i])] = 0.5
matrix_itakura[tuple(path_itakura)[::-1]] = 1.
plt.subplot(2, 2, 3)
plt.pcolor(timestamps,
timestamps,
matrix_itakura,
edgecolors='k',
cmap='Greys')
plt.xlabel('x', fontsize=20, labelpad=-10)
plt.ylabel('y', fontsize=20, labelpad=-10)
plt.title("{0}\nDTW(x, y) = {1:.2f}".format('itakura', dtw_itakura),
fontsize=16)