Basic example using mock data

adaptive_filter_mock_data_example.py

import numpy as np
import padasip as pa
import matplotlib.pylab as plt

# prep data
N = 200  # the overall time series size
n = 5  # size of sample we want to feed into the filter
s = np.random.random(N)  # generate the source input
d = np.zeros(N)  # initialize the target array
for k in range((n-1), N):
    d[k] = 2*s[k] + 0.9*s[k-1] - 2*s[k-2] + 0.3*s[k-3] + 100*s[k-4]
    
d = d[4: ]
x = pa.input_from_history(s, n)  # prep the input to filter

# prep and train the filter
f = pa.filters.FilterLMS(mu=0.4, n=n) 
y, e, w = f.run(d, x)