Converting MatLAB Code to Matplotlib

Is there a way to convert the following MATLAB code to python code with matplotlib?

function [fitresult, gof] = createFit(x, y, z)
%CREATEFIT(X,Y,Z)
%  Create a fit.
%
%  Data for 'untitled fit 1' fit:
%      X Input: x
%      Y Input: y
%      Z Output: z
%  Output:
%      fitresult : a fit object representing the fit.
%      gof : structure with goodness-of fit info.
%
%  See also FIT, CFIT, SFIT.
%  Auto-generated by MATLAB on 31-Dec-2022 13:53:58
%% Fit: 'untitled fit 1'.
[xData, yData, zData] = prepareSurfaceData( x, y, z );
% Set up fittype and options.
ft = fittype( 'poly22' );
opts = fitoptions( 'Method', 'LinearLeastSquares' );
opts.Normalize = 'on';
opts.Robust = 'Bisquare';
% Fit model to data.
[fitresult, gof] = fit( [xData, yData], zData, ft, opts );
% Plot fit with data.
figure( 'Name', 'untitled fit 1' );
h = plot( fitresult, [xData, yData], zData );
legend( h, 'untitled fit 1', 'z vs. x, y', 'Location', 'NorthEast', 'Interpreter', 'none' );
% Label axes
xlabel( 'x', 'Interpreter', 'none' );
ylabel( 'y', 'Interpreter', 'none' );
zlabel( 'z', 'Interpreter', 'none' );
grid on

Answer 1

[Naeimeh N]

You can convert any piece of matlab code to python. In this case you can use the scipy.optimize.curve_fit function to fit a polynomial curve to the data, and then use the matplotlib library to plot the results.