Speed comparison between polyfit and A\y

2 Ansichten (letzte 30 Tage)
Karthik
Karthik am 20 Jun. 2012
I have a program where I am fitting a straight line to a set of data repeatedly over a million times. I wanted to get the most efficient possible code for doing this and thought polyfit would be the way to go. Surprisingly I found that polyfit is about 60 times slower than a simple A\y type estimation. I used the code below to test this out. Why is polyfit so slow ?
X = 0:50;
Y = X + 0.3 + randn(size(X));
N = 1000;
tic
for count = 1:N
temp = polyfit(X,Y,1);
end
tm = toc;
disp(sprintf('Polyfit too %g ms per call',tm/N/1e3));
tic
for count = 1:N
temp = [ones(length(X),1) ,reshape(X,length(X),1)] \ reshape(Y,length(Y),1);
end
tm = toc;
disp(sprintf('A\\y too %g ms per call',tm/N/1e3));
The output is
Polyfit took 614.351 micro seconds per call
A\y took 10.2792 micro seconds per call
Karthik
  1 Kommentar
Sean de Wolski
Sean de Wolski am 20 Jun. 2012
If you:
>>edit polyfit
You'll see that it's a big fancy wrapper for A\b.

Melden Sie sich an, um zu kommentieren.

Akzeptierte Antwort

per isakson
per isakson am 20 Jun. 2012
Study the performance of the code with the function, profile. Thus
profile on
code under test
profile viewer
Note especially that this line is dark red
0.97 1000 72 elseif warnIfLargeConditionNumber(R)

Weitere Antworten (0)

Kategorien

Mehr zu Linear and Nonlinear Regression finden Sie in Help Center und File Exchange

Produkte

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by