I need to create a function get_polynom that will take a list of tuples (x1, y1), (x2, y2), …, (xn, yn) representing points and find the coefficients of the polynomial c0, c1, …, cn. I can’t manage to understand the task, the only tip I have is the provided part of the function: Have somebody done something similar? Just a
Tag: polynomials
numpy polynomial.Polynomial.fit() gives different coefficients than polynomial.polyfit()
I do not understand why polynomial.Polynomial.fit() gives coefficients very different from the expected coefficients : Gives : The two first results are OK, and thanks to this answer I understand why the two arrays are in reversed order. However, I do not understand the signification of the third result. The coefficients looks wrong, though the polynomial that I got this
Polynomial fitting with equal number of data points and coefficients
I am currently experimenting with polynomial fitting using jupyter. The function below returns the least-square polynomial of degree m given the data points in xs with corresponding ys. Suppose I have the following six data points and fit a polynomial of degree 5: From my understanding, the resulting curve should pass through every single data point exactly (in fact, the
Why is my target value not the same when I print it out and calculate it with the coefs and intercept?
I have worked on a Polynomial Regression model to predict my target values. The thing is that my prediction , with the “predict” method, make sense, but when I calculate the target variable via the coefs and intercept I get a value way far from the given values of the predict method. If I calculate the y value for x
Extract coefficients and corresponding monomials from a given polynomial in SymPy
Given a symbolic multivariate polynomial P, I need to extract both its coefficients and corresponding monomials as lists: such that P is the dot product of coefficients and monomials, e.g., if P(x,y) = ax**2 + bxy + cy**2 then we should get coeffs = [a, b, c] and monoms = [x**2, x*y, y**2]. Getting the coefficients is easy since the