Matlab can't handle data - matlab

Question

I've been working on the processing 2 lists of 855 4000x4000 matrices. Here is a list of 855 matrices of some value, another one is a list of coordinates (another 855 4000x4000 matrices). It's important to do it within the one cycle, in order to not to have thousands of useless variables. For every file, it cuts (read put NaN where I don't need data) coordinates data, then it cuts data related to the coordinates. Then it gathers all the values into one matrix. The code is:
for x = 1:length(list_with_par)
cd 'D:\Coord'
par_lon = ncread(list_with_coordinates(x,:), 'longitude');
par_lon(par_lon>=15) = nan;
par_lon(par_lon<=-18) = nan;
par_lat = ncread(list_with_coordinates(x,:), 'latitude');
par_lat(par_lon>=84) = nan;
par_lat(par_lon<=76) = nan;
cd 'D:\Par'
par = ncread(list_with_par(x,:), 'PAR');
for i = 1:size(ncread(list_with_par(x,:),'PAR'),1) %size(,1)
for z = 1:size(ncread(list_with_par(x,:),'PAR'),2) %size(,2)
if isnan(par_lon(i,z))
par(i,z) = nan;
end
if isnan(par_lat(i,z))
par(i,z) = nan;
end
end
end
if size(par,2) < size(PAR_main,2)
left_cells = size(PAR_main,2) - size(par,2);
temp_cell = NaN(4865,left_cells);
C2 = cat(2,par,temp_cell);
end
if size(par,2) == size(PAR_main,2)
C2 = par(:,:,1);
end
PAR_main(:,:,x) = C2(:,:,1);
end
But suddenly an error pops up after 4-5 hours of processing.
Error using netcdflib
The NetCDF library encountered an error during execution of 'open' function - 'HDF error (NC_EHDFERR)'.
Error in netcdf.open (line 67)
[varargout{:}] = netcdflib ( 'open', filename, varargin{1} );
Error in internal.matlab.imagesci.nc/openToRead (line 1278)
this.ncRootid = netcdf.open(this.Filename,'NOWRITE');
Error in internal.matlab.imagesci.nc (line 121)
this.openToRead();
Error in ncread (line 61)
ncObj = internal.matlab.imagesci.nc(ncFile);
What might be an issue?

Answer 1

I'm not really familiar with ncread (and associated functions), but there two things that jump out at me that appear to be very inefficient:
In your loops over 'i' and 'z', is there a reason to read in the data again to determine its size instead of just using the 'par' variable that you already saved?
for i = 1:size(par,1)
for z = 1:size(par,2)
For that matter, unless I am missing something specific to this set of functions, you should be able to skip the loops over 'i' and 'z' completely and vectorize the calculation:
par(isnan(par_lon))= nan;
par(isnan(par_lat)) = nan;
This is certainly significantly slowing down your code. It is hard to say beyond that, but I could definitely see how having millions of extraneous file reads could cause some issues with either temporary file addresses, etc.) or memory leaks.