Polynomial Equation Parameters

I have some 2D sampling points for which I need the polynomial equation. I only found something like this: from scipy.interpolate import barycentric_interpolate // x and y are give

Solution 1:

numpy.polyfit

Fit a polynomial p(x) = p[0] * x**deg + ... + p[deg] of degree deg to points (x, y). Returns a vector of coefficients p that minimises the squared error.

Example from the docs:

>>>x = np.array([0.0, 1.0, 2.0, 3.0,  4.0,  5.0])>>>y = np.array([0.0, 0.8, 0.9, 0.1, -0.8, -1.0])>>>z = np.polyfit(x, y, 3)>>>z
array([ 0.08703704, -0.81349206,  1.69312169, -0.03968254])

Solution 2:

with scipy.optimize.curve_fit one can fit arbitrary functions and obtain its coefficients