pythonsmoothingnoisekalman-filter

Reducing noise on Data

I have 2 lists with data points in them.

x = ["bunch of data points"]
y = ["bunch of data points"]

I've generated a graph using matplotlib in python

import matplotlib.pyplot as plt

plt.plot(x, y, linewidth=2, linestyle="-", c="b")
plt.show()
plt.close()

Would I be able to reduce the noise on the data? Would a Kalman filter work here?

enter image description here

Solution

  • It depends how you define the "noise" and how it is caused. Since you didn't provide much information about your case, I'll take your question as "how to make the curve smooth". Kalman filter can do this, but it's too complex, I'd prefer simple IIR filter

    import matplotlib.pyplot as plt
import numpy as np

mu, sigma = 0, 500

x = np.arange(1, 100, 0.1)  # x axis
z = np.random.normal(mu, sigma, len(x))  # noise
y = x ** 2 + z  # data
plt.plot(x, y, linewidth=2, linestyle="-", c="b")  # it includes some noise

    enter image description here

    After filter

    from scipy.signal import lfilter

n = 15  # the larger n is, the smoother curve will be
b = [1.0 / n] * n
a = 1
yy = lfilter(b, a, y)
plt.plot(x, yy, linewidth=2, linestyle="-", c="b")  # smooth by filter

    enter image description here

    lfilter is a function from scipy.signal.

    By the way, if you do want to use Kalman filter for smoothing, scipy also provides an example. Kalman filter should also work on this case, just not so necessary.