DTW y DDTW

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import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from dtaidistance import dtw
from dtaidistance import dtw_visualisation as dtwvis

from utils import DDTW

np.random.seed(777)

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data1 = np.array([12.0 * np.sin(i / 2.1) + 20 for i in range(30)])
data2 = np.array([10.0 * np.sin(i / 2.0) + np.random.rand() for i in range(30)])

plt.figure(figsize=(12, 4))

# Gráfica de formas de onda
plt.plot(data1, label="data1", color="k")
plt.plot(data2, label="data2", color="r")
plt.legend()
plt.show()

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d, paths = dtw.warping_paths(
    data1,
    data2,
    window=25,
)
best_path = dtw.best_path(paths)
dtwvis.plot_warpingpaths(data1, data2, paths, best_path)

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γ_mat, arrows, ddtw = DDTW(np.array(data1), np.array(data2))

sns.set(rc={"figure.figsize": (18, 15)})
sns.set(font="IPAexGothic")
ax = sns.heatmap(-1 * γ_mat, cmap="YlGnBu")
ax.set_title(f"DDTW = {ddtw}")
ax.invert_xaxis()
ax.invert_yaxis()
ax.set_xlabel("w2")
ax.set_ylabel("w2")
plt.show()