Calculation precision changed in 2020b?
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Hiroyuki Kato
am 13 Okt. 2020
Kommentiert: Jan
am 23 Okt. 2020
I am encountering a precision error with Matlab2020b, which I did not have in version 2016b.
I have 78-dimension vector x (attached). if I do the following, even though the result should be 0, I get a complex number as a result from acos calculation:
> y = x;
> acos(dot(x,y)/sqrt(sum(x.^2)*sum(y.^2)))
ans = 0.0000e+00 + 2.1073e-08i
In Matlab2016b, I know that using "norm" function caused a precision error and acos(dot(x,y)/(norm(x)*norm(y)) gave a complex number.
Back then, the use of sqrt(sum(x.^2)*sum(y.^2)) was a recommended method to avoid this issue. (as summarized in this page: https://stackoverflow.com/questions/36093673/why-do-i-get-a-complex-number-using-acos)
This method has been working fine in 2016b, but now with exactly the same code I have the complex number issue coming back in 2020b.
Was there a change in the precision of calculation in the newer version of matlab? If so, is there any good work around to avoid this issue?
Thanks,
Hiroyuki
1 Kommentar
Bruno Luong
am 15 Okt. 2020
Bearbeitet: Bruno Luong
am 15 Okt. 2020
"In Matlab2016b, I know that using "norm" function caused a precision error and acos(dot(x,y)/(norm(x)*norm(y)) gave a complex number.
Back then, the use of sqrt(sum(x.^2)*sum(y.^2)) was a recommended method to avoid this issue. (as summarized in this page: https://stackoverflow.com/questions/36093673/why-do-i-get-a-complex-number-using-acos)
This method has been working fine in 2016b, but now with exactly the same code I have the complex number issue coming back in 2020b."
Pure luck. None of the observation has rigorous justification.
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Bruno Luong
am 15 Okt. 2020
Bearbeitet: Bruno Luong
am 15 Okt. 2020
This is a robust code.
theta = acos(max(min(dot(x,y)/sqrt(sum(x.^2)*sum(y.^2)),1),-1))
Note it returns 0 for x or y is 0. One might prefer NaN because correlation is undefined.
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Weitere Antworten (2)
Jan
am 20 Okt. 2020
The ACOS function is numerically instable at 0 and pi.
SUM is instable at all. A trivial example: sum([1, 1e17, -1]) .There are different approaches to increase the accuracy of the summation, see https://www.mathworks.com/matlabcentral/fileexchange/26800-xsum
There is a similar approach for a stabilized DOT product, but the problem of ACOS will still exist. To determine the angle between two vectors, use a stable ATAN2 method, see https://www.mathworks.com/matlabcentral/answers/471918-angle-between-2-3d-straight-lines#answer_383392
4 Kommentare
Paul
am 22 Okt. 2020
I think you have an error in angle2. Should it not be:
angle2 = 2*atan(norm(norm(x)*y - norm(y)*x)/norm(norm(x)*y + norm(y)*x))
Uday Pradhan
am 15 Okt. 2020
Bearbeitet: Uday Pradhan
am 16 Okt. 2020
Hi Hiroyuki,
If you check (in R2020b):
>> X = dot(x,y) - sqrt(sum(x.^2)*sum(y.^2))
ans =
1.776356839400250e-15
where as in R2016b, we get:
>> dot(x,y) - sqrt(sum(x.^2)*sum(y.^2))
ans =
0
Hence, in R2020b, we get:
>> acos(X)
ans =
0.000000000000000e+00 + 2.107342425544702e-08i
This is because the numerator dot(x,y) is "greater" than the denominator sqrt(sum(x.^2)*sum(y.^2)) albeit by a very small margin and hence the fraction X becomes greater than 1 and thus acos(X) gives complex value.
To avoid this my suggestion would be to establish a threshold precision to measure equality of two variables, for example you could have a check function so that if abs(x-y) < 1e-12 then x = y
function [a,b] = check(x,y)
if abs(x-y) < 1e-12
a = x;
b = a;
end
end
Now, you can do [a,b] = check(x,y) and then call acos(a/b). This will also help in any other function where numerical precision can cause problems.
Hope this helps!
10 Kommentare
Paul
am 19 Okt. 2020
If you look further down in dot.m (2019a) to the section used when dim is specified, you will see that there is a path to
c = sum(conj(a).*b,dim)
even if a and b are both vectors and are isreal. For example
dot(1:3,1:3,1)
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