Using trapz just for positive areas

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Simone Speltoni
Simone Speltoni 2021 年 6 月 9 日
コメント済み: Star Strider 2021 年 6 月 9 日
Hi, I already tried to solve my problem by looking at this answer https://it.mathworks.com/matlabcentral/answers/254940-how-to-find-the-area-between-the-x-axis-and-positive-section-of-a-graph, but without success, I guess because I'm missing how to link y-data to x-data. My goal consists of getting just the portion of area under a curve (which is not a function) and above the x-axis, then a positive area. For example:
clear all
close all
xA=0:4;
A=[-2 -1 2 3 4]; %if one considers this as a polygonal chain,
%positive area is equal to 6.66, negative area -1.665
plot(xA,A,'o');
grid on
hold on
Valpos = find(A>=0);
posArea = trapz(xA(Valpos),A(Valpos)); %(positive area) =6
integral=trapz(A); %(positive area)-(negative area)=5
%polyfit to build a curve with "A" data
[pA,~,muA] = polyfit(xA, A, 4);
fA = polyval(pA,xA,[],muA);
plot(xA,fA);
trapzinterpolaz=trapz(fA); %(positive area)-(negative area)=5
I understand how trapz works, and it's right to get these results (6 as positive area and 5 if one considers negative trapezoids too). Anyway, what I would like to have is considering data in A as a function, because in this case I would get 6.66 as positive area, and -1.665 as negative area. Basically, I'm missing the positive area between x=1 and x=2 IF the A data were a function. Any advice? thanks!

採用された回答

Star Strider
Star Strider 2021 年 6 月 9 日
I would just use interp1 to interpolate the data, then use trapz to integrate it. The resolution of ‘xi’ determines the precision of the integrated result. (I use the default length of 100 here.)
xA=0:4;
A=[-2 -1 2 3 4]; %if one considers this as a polygonal chain,
%positive area is equal to 6.66, negative area -1.665
plot(xA,A,'o');
grid on
hold on
Valpos = find(A>=0);
posArea = trapz(xA(Valpos),A(Valpos)); %(positive area) =6
integral=trapz(A); %(positive area)-(negative area)=5
%polyfit to build a curve with "A" data
[pA,~,muA] = polyfit(xA, A, 4);
fA = polyval(pA,xA,[],muA);
plot(xA,fA);
trapzinterpolaz=trapz(fA); %(positive area)-(negative area)=5
xi = linspace(min(xA), max(xA)); % Interpolation Vector
Ai = interp1(xA,A,xi,'linear'); % Interpolated Data
posIdx = Ai>0; % Logical Index Of Positive 'A' Values
areaPos = trapz(xi(posIdx), Ai(posIdx)) % Positive Area
areaPos = 6.6638
areaNeg = trapz(xi(~posIdx), Ai(~posIdx)) % Negative ARea
areaNeg = -1.6664
.
  2 件のコメント
Simone Speltoni
Simone Speltoni 2021 年 6 月 9 日
Thank you very much for your help!
Star Strider
Star Strider 2021 年 6 月 9 日
As always, my pleasure!

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その他の回答 (1 件)

Joel Lynch
Joel Lynch 2021 年 6 月 9 日
You need to use more fine-grid X data in polyval to get test points at y=0.
xA_fine = linspace(xA(1),xA(end),100);
fA_fine = polyval(pA,xA_fine,[],muA);
% Full Integral
trapz( xA_fine, fA_fine )
% Just positive Values (logical indicies)
idx = fA_fine>=0;
trapz( xA_fine(idx), fA_fine(idx) )
% Just positive Values (using a starting index)
i = find(fA_fine>=0,1)
trapz( xA_fine(i:end), fA_fine(i:end) )
Also note: multiple ways to get values greater than zero. The first is to use logical indices, the second is to find the first place and integrate from there. The second only works when the function is always increasing. The first may run into problems if there are multiple y=0 cross-overs, depending on how xA_fine is defined.
  1 件のコメント
Simone Speltoni
Simone Speltoni 2021 年 6 月 9 日
Thank you Joel, this approach is very useful too!

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