How do I correctly code with polyfit?

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Eduardo Gallegos
Eduardo Gallegos 2022-12-14
编辑： Image Analyst 2022-12-14
Hello everyone, I've been working on this problem for the last hour and I can't find a way to use polyfit and polyval like how they want it in the instructions
(1 pt) Enter the following data
x = 0 : 1 : 8;
y = [47, 12, 0, 40, 30, 36, 60, 110, 156];
(1 pt) Open a figure and plot the data with circle markers.
(3 pts) Use the polyfit() function to compute the coefficients of a 3rd-order fit to this data.
(3 pts) Set x3 = 0 : 0.2 : 8;
Use the polyval() function with the computed coefficients and the x3 vector to compute the y values of the 3rd-
order fit.
(2 pts) Use hold on and grid on.
Then plot the 3rd-order fit on the same figure.
My code
x = 0 : 1 : 8;
y = [47, 12, 0, 40, 30, 36, 60, 110, 156];
figure;
plot(x,y,'o')
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Eduardo Gallegos
Eduardo Gallegos 2022-12-14
Something like this?? Is this right??
x = 0 : 1 : 8;
y = [47, 12, 0, 40, 30, 36, 60, 110, 156];
figure;
plot(x,y,'o')
p = polyfit(x,y,3)
x3 = 0 : 0.2 : 8;
y3 = polyval(p,x3)
hold on;
grid on;
plot(x3,y3)
title('3rd order curve Fit to Data Points')
Jonas
Jonas 2022-12-14
perfect
but please use code format to post code in the forum here (see the most left button in the code tool section)
e.g.
x3 = 0:0.2:8;
instead of
x3 = 0:0.2:8;

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采纳的回答

Image Analyst
Image Analyst 2022-12-14
编辑：Image Analyst 2022-12-14
See my polyfit demo, attached.
Adapt as needed to replace my data with yours, like this:
% Demo to illustrate how to use the polyfit routine to fit data to a polynomial
% and to use polyval() to get estimated (fitted) data from the coefficients that polyfit() returns.
% Initialization steps.
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
x = 0 : 1 : 8;
y = [47, 12, 0, 40, 30, 36, 60, 110, 156];
%============= CUBIC FIT ===================================
% Plot the training set of data.
plot(x, y, 'r.', 'MarkerSize', 40, 'LineWidth', 2);
grid on;
xlabel('X', 'FontSize', fontSize);
ylabel('Y', 'FontSize', fontSize);
title('Cubic Fit', 'FontSize', fontSize);
% Do the regression with polyfit to fit a cubic polynomial.
cubicCefficients = polyfit(x, y, 3)
% The x coefficient, slope, is coefficients(1).
% The constant, the intercept, is coefficients(2).
% Make fit. It does NOT need to have the same
% number of elements as your training set,
% or the same range, though it could if you want.
% Make 500 fitted samples going the whole range of x.
xFit = linspace(min(x), max(x), 500);
% Get the estimated values with polyval()
yFit = polyval(cubicCefficients, xFit);
% Plot the fit
hold on;
plot(xFit, yFit, 'b-', 'LineWidth', 2);
grid on;
legend('Training Set', 'Fit', 'Location', 'Northwest');
caption = sprintf('Cubic Fit. Equation: y = %.2f * x^3 + %.2f * x^2 + %.2f * x + %.2f', ...
cubicCefficients(1), cubicCefficients(2), cubicCefficients(3), cubicCefficients(4));
title(caption, 'FontSize', fontSize);

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