# How to smooth the matlab plot to get the desired plot shape?

2 visualizaciones (últimos 30 días)
Haya Ali el 24 de Jul. de 2023
Comentada: Haya Ali el 25 de Jul. de 2023
Is there a way to change figure one to figure 2 (like the lines I draw in red and black color) without changing the values of y1 and y2? Please help.
Figure 1:
Figure 2:
Below is my code
clear all; close all; clc;
x= [0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1];
y1 = [0 0.0833 0.1583 0.2167 0.1500 0.3250 0.3750 0.3000 0.5917 0.3750 0.5000];
y2= [ 0 0 0.0167 0.0750 0.1000 0.0917 0.1167 0.1583 0.1083 0.2000 0.1833];
figure
plot (x,y1,'o')
hold on
plot (x,y2,'o')
Xi = 0:0.005:1;
Yi = pchip(x,y1,Xi);
Yi_spline = spline(x,y1,Xi);
h(1) = plot(Xi,Yi,'-','color',lines(1));
h(2) = plot(Xi, Yi_spline, '--', 'color', lines(1));
Yj = pchip(x,y2,Xi);
Yj_spline = spline(x, y2, Xi);
h(3) = plot(Xi,Yj,'-','color',[0.85, 0.325, 0.098]);
h(4) = plot(Xi,Yj_spline,'--','color',[0.85, 0.325, 0.098]);
legend(h, "Yi pchip", "Yi spline", "Yj pchip", "Yj spline", "location", "NW")
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Angelo Yeo el 24 de Jul. de 2023
https://www.mathworks.com/help/releases/R2023a/matlab/ref/movmean.html
x= [0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1];
y1 = [0 0.0833 0.1583 0.2167 0.1500 0.3250 0.3750 0.3000 0.5917 0.3750 0.5000];
y2= [ 0 0 0.0167 0.0750 0.1000 0.0917 0.1167 0.1583 0.1083 0.2000 0.1833];
figure
plot (x,y1,'o')
hold on
plot (x,y2,'o')
dt = 0.005;
Xi = 0:dt:1;
Yi = pchip(x,y1,Xi);
Yi_spline = spline(x,y1,Xi);
h(1) = plot(Xi,Yi,'-','color',lines(1));
h(2) = plot(Xi, Yi_spline, '--', 'color', lines(1));
Yj = pchip(x,y2,Xi);
Yj_spline = spline(x, y2, Xi);
h(3) = plot(Xi,Yj,'-','color',[0.85, 0.325, 0.098]);
h(4) = plot(Xi,Yj_spline,'--','color',[0.85, 0.325, 0.098]);
%% Smoothing
Yi_smooth = movmean(Yi_spline, 100);
Yj_smooth = movmean(Yj_spline, 100);
h(5) = plot(Xi, Yi_smooth, 'r','linewidth',2);
h(6) = plot(Xi, Yj_smooth, 'k','linewidth',2);
legend(h, "Yi pchip", "Yi spline", "Yj pchip", "Yj spline", "Yi smoothed", "Yj smoothed", "location", "NW")
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Angelo Yeo el 24 de Jul. de 2023
I agree with @Image Analyst. What's your intention, @Haya Ali?
Anyways, if you insist that the resultant curve should pass (0, 0), you can think of something like curve fitting for a quadratic polynomial without a bias term.
clear; close all; clc;
x= [0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1];
y1 = [0 0.0833 0.1583 0.2167 0.1500 0.3250 0.3750 0.3000 0.5917 0.3750 0.5000];
y2= [ 0 0 0.0167 0.0750 0.1000 0.0917 0.1167 0.1583 0.1083 0.2000 0.1833];
figure
plot (x,y1,'o')
hold on
plot (x,y2,'o')
dt = 0.005;
Xi = 0:dt:1;
Yi = pchip(x,y1,Xi);
Yi_spline = spline(x,y1,Xi);
h(1) = plot(Xi,Yi,'-','color',lines(1));
h(2) = plot(Xi, Yi_spline, '--', 'color', lines(1));
Yj = pchip(x,y2,Xi);
Yj_spline = spline(x, y2, Xi);
h(3) = plot(Xi,Yj,'-','color',[0.85, 0.325, 0.098]);
h(4) = plot(Xi,Yj_spline,'--','color',[0.85, 0.325, 0.098]);
legend(h, "Yi pchip", "Yi spline", "Yj pchip", "Yj spline", "location", "NW")
% Set up fittype and options.
[xData, yData] = prepareCurveData( Xi, Yi_spline );
ft = fittype( 'p1*x^2+p2*x', 'independent', 'x');
opts = fitoptions( 'Method', 'NonlinearLeastSquares' );
opts.StartPoint = [0, 0];
Yi_fit = fit( xData, yData, ft, opts );
[xData, yData] = prepareCurveData( Xi, Yj_spline );
ft = fittype( 'p1*x^2+p2*x', 'independent', 'x');
opts = fitoptions( 'Method', 'NonlinearLeastSquares' );
opts.StartPoint = [0, 0];
Yj_fit = fit( xData, yData, ft, opts );
h(5) = plot(Xi, Yi_fit.p1*Xi.^2 + Yi_fit.p2*Xi,'r','linewidth', 2);
h(6) = plot(Xi, Yj_fit.p1*Xi.^2 + Yj_fit.p2*Xi,'k','linewidth', 2);
legend(h, "Yi pchip", "Yi spline", "Yj pchip", "Yj spline", "Yi smoothed", "Yj smoothed", "location", "NW")
Haya Ali el 25 de Jul. de 2023
Actually I was recommended to take avergae of my results 100 times ti smooth my original plot. I didnt want to spend many days on one graph that is why I am trying to get a plot that is smoothest. Thank you so much for your help.

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