Fitting in Chebyshev basis — Scipy lecture notes
scipy-lectures.org › intro › numpyFitting in Chebyshev basis. ¶. Plot noisy data and their polynomial fit in a Chebyshev basis. import numpy as np import matplotlib.pyplot as plt np.random.seed(0) x = np.linspace(-1, 1, 2000) y = np.cos(x) + 0.3*np.random.rand(2000) p = np.polynomial.Chebyshev.fit(x, y, 90) plt.plot(x, y, 'r.') plt.plot(x, p(x), 'k-', lw=3) plt.show() Total ...
Chebyshev polynomials - Wikipedia
en.wikipedia.org › wiki › Chebyshev_polynomialsThe abundance of the theorems and identities inherited from Fourier series make the Chebyshev polynomials important tools in numeric analysis; for example they are the most popular general purpose basis functions used in the spectral method, often in favor of trigonometric series due to generally faster convergence for continuous functions ...