reading in data using matlab

suppose you have a large data file containing elements of a matrix.

The original matrix has dimensions

uzy(1:orng,1:grn)

Then it is likely that the program dumps the matrix using nested loops:

do a=1,orng

do b=1,grn

write(*,*) uzy(a,b)

enddo

To read the data back in vectorally,

for a=1:orng

%disp([1+grn*(a-1) grn*a size(1+grn*(a-1):grn*a)])

uzy(1:grn,a)=uzy_raw(1+grn*(a-1):grn*a);

end

If the original matrix had dimensions

A(1:orng,1:grn,1:blu)

Then it is likely that the program dumps the matrix using nested for loops:

for a=1:orng

for b=1:grn

for c=1:blu

write(*,*) A(a,b,c)

end

[Note: normally, it would be more efficient to vectorize the inner most loop, but their may be other constraints (like complex-valued elements, or matrix dimensions are large)]

Now we want to re-construct the matrix in matlab from the output file. First, load the data:

raw_data = load('outputfile.dat');

[Note: this will not be useable if outputfile.dat exceeds 100 Mb. Then you'd need to read in line by line?]

now raw_data is of size orng*grn*blu and we need to convert to a matrix of the form A(1:orng,1:grn,1:blu)

for a=1:orng

for b=1:grn

disp([(blu*grn*(a-1)+(b-1)*blu+1) (blu*grn*(a-1)+(b-1)*blu+blu)])

A=raw_data((blu*grn*(a-1)+(b-1)*blu+1):(blu*grn*(a-1)+(b-1)*blu+blu));

end

for c = 1:num_freq

for a = 1:num_gain

for b = 1:n_open

f = b+n_open*(a-1) + num_gain*n_open*(c-1);

trans_complex(b,:,a,c)=trans_raw(f,1:n_open)+i*trans_raw(f,n_open+1:2*n_open);

end

Fortran write:

do q=1,nopen

do p=1,nmax

do a=1,nz

write(*,*) jflux(q,p,a)

enddo

Matlab read

for a=1:n_open % input channels

for b = 1:nmax % interior channels

indx = b+nmax*(a-1)

disp([1+nz*(indx-1) nz*indx])

% jflux(a,b,(1:nz)) = jraw(,1);

end

Fortran write:

do d=1,nmax

do a=1,nz

write(*,*) wdist(a,d)

enddo

Matlab read:

for intrior=1:nmax

disp([((intrior-1)*siz+1) (intrior*siz)])

%w=wraw(((intrior-1)*siz+1):(intrior*siz));

end