% Example data points
x = [0, 1, 2, 3, 4, 5];
y = [0, 1, 0, 1, 0, 1];
% Fit a cubic spline to the data
cs = spline(x, y);
% Generate a dense set of x values for plotting the spline
x_dense = linspace(min(x), max(x), 100);
y_dense = ppval(cs, x_dense);
% Plotting the original data points and the fitted spline
figure;
plot(x, y, 'ro', 'MarkerFaceColor', 'r', 'DisplayName', 'Data Points'); % Original data points
hold on;
plot(x_dense, y_dense, 'b-', 'DisplayName', 'Cubic Spline'); % Cubic spline
legend show;
xlabel('x');
ylabel('y');
title('Cubic Spline Fitting');
grid on;
Explanation:
- Data Points: Define your data points using vectors x and y.
- spline Function: This MATLAB function computes the cubic spline coefficients for the given data.
- ppval Function: This function evaluates the piecewise polynomial (spline) at the specified points in x_dense.
- Plotting: The plot function is used to visualize the original data points and the fitted spline curve.
Replace x and y with your actual data points. This code will fit a cubic spline to your data and display the result in a plot. If you have any specific requirements or need further details, feel free to ask!
