Sum two plots and plot the result
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Is there a simple way to take the sum of two plots that overlap and plot the result? X and Y are the same length for both.
1 个评论
Rik
2019-9-7
The easiest way is to sum the data itself:
Z=X+Y;
plot(t,X,t,Y,t,Z)
采纳的回答
Star Strider
2019-9-7
One approach (assuming that they are functions of the same independent variable vector, so in addition to being the same lengths, they are evaluated at the same values of the independent variable):
XplusY = sum([X(:),Y(:)],2);
This creates a column vector result, since we don’t know the sizes of the original ‘X’ and ‘Y’. If you want it as a row vector, transpose it.
To sum only the values where ‘X’ is greater than or equal to ‘Y’:
L = X >= Y;
XL = X(L);
YL = Y(L);
XplusY = sum([XL(:),YL(:)],2);
since I am not certain what ‘overlap’ means here.
9 个评论
Matthew Rotondaro
2019-9-7
Rik
2019-9-7
Then you will have to interpolate one or both to a shared x, after which you will be able to add them up.
Star Strider
2019-9-7
If they don’t have a common independent variable, you can’t sum them and get a meaningful result.
You will have to create a common independent variable for both, then use interp1 to interpolate both of them to it. Then you could sum the interpolated curves.
Example —
Xi = linspace(1.2, 3.4, 50);
X = exp(-((Xi-2.1)/0.5).^2);
Yi = linspace(2.3, 3.4, 50);
Y = exp(-((Yi-2.9)/0.2).^2);
figure
plot(Xi, X, Yi, Y)
grid
XiYi = [Xi(:); Yi(:)];
Ci = linspace(min(XiYi), max(XiYi), 150);
Xq = interp1(Xi(:), X(:), Ci(:), 'linear','extrap');
Yq = interp1(Yi(:), Y(:), Ci(:), 'linear','extrap');
Sq = sum([Xq(:) Yq(:)],2);
figure
plot(Ci, Xq, Ci, Yq, Ci, Sq)
grid
Experiment to get the result you want.
Matthew Rotondaro
2019-9-7
Star Strider
2019-9-8
As always, my pleasure!
Susmita Panda
2021-5-24
But the in the summation plot, the second also starts from starting rather it should have a delay?
Niko
2023-7-5
What if they are both independent, i.e. same y and x "measurements", but with different density points (x-axis is more denser on one with higher resolution in a smaller window than the other)?
Star Strider
2023-7-5
With respect to different independent variable ranges, the interpolation is still necessary, however they can only be summed in the ranges where all the curves exist. All the curves would need to be truncated to those limits, then the interpolated values summed, ignoring regions where they do not all overlap.
With respect to different resulutions, it is preferable to interpolate the higher resolution signal to match the values in the lower resolution signal. This avoids the problem of creating data in the lower resolution isgnal where none previously existed, as would be the problem if the lower resolution signal were interpolated to match the higher resolution signal, since the exact behaviour of the lower resolution signal at those points is obviously not known.
.
Rik
2023-7-6
You might consider performing a moving average before downsampling. Otherwise you may introduce other effects (consider the situation where one of the curves is a sine and the resolution of the other curve is equal to the period of the sine).
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