example.py

import matplotlib.pyplot as plt
import numpy as np
import seaborn
from time import sleep
from matplotlib.animation import FuncAnimation

from one_euro_filter import OneEuroFilter


np.random.seed(1)

# Parameters
frames = 100
start = 0
end = 4 * np.pi
scale = 0.05


# The noisy signal
t = np.linspace(start, end, frames)
x = np.sin(t)
x_noisy = x + np.random.normal(scale=scale, size=len(t))


# The filtered signal
min_cutoff = 0.004
beta = 0.7
x_hat = np.zeros_like(x_noisy)
x_hat[0] = x_noisy[0]
one_euro_filter = OneEuroFilter(
    x_noisy[0],
    min_cutoff=min_cutoff,
    beta=beta
)
for i in range(1, len(t)):
    sleep(0.1)
    x_hat[i] = one_euro_filter(x_noisy[i])
    print(x_hat[i])


# The figure
# https://eli.thegreenplace.net/2016/drawing-animated-gifs-with-matplotlib/
seaborn.set()
fig, ax = plt.subplots(figsize=(12, 6))
ax.set(
    xlim=(start, end),
    ylim=(1.1*(-1-scale), 1.1*(1+scale)),
    xlabel="$t$",
    ylabel="$x$",
)
fig.set_tight_layout(True)
signal, = ax.plot(t[0], x_noisy[0], 'o')
filtered, = ax.plot(t[0], x_hat[0], '-')


def update(i):
    print(i)
    signal.set_data(t[0:i], x_noisy[0:i])
    filtered.set_data(t[0:i], x_hat[0:i])
    return signal, filtered


if __name__ == '__main__':
    # FuncAnimation will call the 'update' function for each frame; here
    # animating over 10 frames, with an interval of 200ms between frames.
    anim = FuncAnimation(fig, update, frames=frames, interval=100)
    anim.save('one_euro_filter.gif', dpi=80, writer='imagemagick')
    # update(frames)
    plt.savefig("one_euro_filter.png", dpi=300)