I'm in a situation where I have to be able to solve an unknown number of simultaneous equations, there could be from two variables to a near unlimited number (practical limits will probably be in the 10-15 area, but this program contains a lot of random events, so ther could potentially be much more).
The equations are all simple linear equations, and there will always be N equations, where N is the number of variables to solve. So the situation is not overly complex, however I need to do this fast (possibly millions of times in s single execution) so I want to try and find the fastest way possible of doing this, I've been pointed to a book called "Introduction to Algorithms", by T.H. cormen, C.E,Leisserson, R.L. Rivest.
And that's given by a psuedocode algorithm that is a factor of 3 faster than methods such as using a matrix inverse. The problem comes when I try to translate the code to C.
I realise this is a pretty complex topic, and most people probably won;t even want to bother wading through the code below, but I'm sorta out of options . If anyone's got some suggestions on other approaches or good sources of relevant information, I'd REALLY love to hear about it.
Anyway, this is the psuedo-code I have:
if anyone actually has the book, it's a fair bit easier to understand there, with the characters and formatting I just can't get in a forum post.
n = rows[L]
for i = 1 to n
do y[i] = b[Pi[i]] - sum(j=1 to i-1) of L[i][j]y[i]
for i = n downto 1
do x[i] = (y[i]-sum(j=i+1 to n) of u[i][j]x[j])/u[i][i]
n = rows[A]
for i = 1 to n
do Pi[i] = i
for k = 1 to n-1
do p = 0
for i = k to n
do if |A[i][k]| > p
k' = i
then error "singular matrix"
exchange Pi[k] <> Pi[k']
for i=1 to n
do exchange A[k][i] <> A[k'][i]
for i=k+1 to n
do A[i][k] = A[i][k]/A[k][k]
for j =k+1 to n
do A[i][j] = A[i][j] - A[i][k]A[k][j]
My attempt at this code is:
I've compressed the two functions into one here, though that's not a problem, in the initial version, the decomposition runs, then solve, I've done the same thing, just in one function call.
int LUPsolve(int rows,float A[rows][rows],float b[rows],float X[rows])
printf("singular Matrix, no possible solutions\n");
//X now contains the solution;
Also, though the psuedo-code for LUP-solve doesn't show it (decom does) the matrices L and U are both combined into A, so that is not the problem with the code. The indexing from 1 rather than 0 may be a problem, but when I go through and edit it to index from 0, it doesn;t work either, so I just keep it like this to maintain continuity with the book.
the input I'm tesing it with is:
done on paper, the output should be 2 and -11, but I actually get 2.64 & -2.28
anyone got an idea what's wrong/any pointers to more resources/pre-coded functions/anything remotely useful. thisis something I really want to be able to do, but my own brain's pretty much worn out on this
big thanks to anyone who's still reading by now