Matlab function for cumulative power
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Is there a function in MATLAB that generates the following matrix for a given scalar r, where each row behaves somewhat like a power analog of the CUMSUM function?:
1 r r^2 r^3 ... r^n
0 1 r r^2 ... r^(n-1)
0 0 1 r ... r^(n-2)
...
0 0 0 0 ... 1
1 commentaire
Rik
le 24 Mar 2020
I doubt there is a direct function. Have you tried writing one yourself?
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This code does what you ask without loops.
%define inputs
r=9;
n=4;
[a,b]=meshgrid(0:n);
exponents=a-b;
exponents(exponents<0)=NaN;
result=r.^exponents;
result(isnan(result))=0;
5 commentaires
Birdman
le 24 Mar 2020
This code is slower than mine although you avoided nested for loops.
Rik
le 24 Mar 2020
Strange. I did a tic,toc to check and mine was about twice as fast, but with the code below yours is 10 times faster. It probably also depends on n and r.
r=9;n=4;
timeit(@() option_loop(r,n))
timeit(@() option_grid(r,n))
function A=option_loop(r,n)
A=zeros(n+1,n+1);
for i=1:size(A,1)
for j=1:size(A,2)
if (j-i)<0
A(i,j)=0;
else
A(i,j)=r^(j-i);
end
end
end
end
function result=option_grid(r,n)
[a,b]=meshgrid(0:n);
exponents=a-b;
exponents(exponents<0)=NaN;
result=r.^exponents;
result(isnan(result))=0;
end
Birdman
le 24 Mar 2020
Your answer is neat but my point is there is no reason to avoid nested for loops because there is no dramatic time consumption.
Rik
le 24 Mar 2020
This is actually a nice illustration of the fact that a non-loop version isn't always faster. In this case (at least on my computer with Windows 10 and R2019a) the looped version is faster up to about n=30. For huge values of n there may very well be a tangible benefit (or if this code is going to be run very often).
clc,clear
r=9;
n_list=[1:100 200:100:1000];
t=zeros(2,numel(n_list));
for it=1:size(t,2)
n=n_list(it);
t(1,it)=timeit(@() option_loop(r,n));
t(2,it)=timeit(@() option_grid(r,n));
end
figure(1),clf(1)
plot(n_list,t(1,:),n_list,t(2,:))
legend({'loop','grid'})
xlabel('n'),ylabel('time')
Herr K
le 24 Mar 2020
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