function [header, data] = hdrload(file) % HDRLOAD Load data from an ASCII file containing a text header. % [header, data] = HDRLOAD('filename.ext') reads a data file % called 'filename.ext', which contains a text header. There % is no default extension; any extensions must be explicitly % supplied. % % The first output, HEADER, is the header information, returned % as a text array. % The second output, DATA, is the data matrix. This data matrix % has the same dimensions as the data in the file, one row per % line of ASCII data in the file. If the data is not regularly % spaced (i.e., each line of ASCII data does not contain the % same number of points), the data is returned as a column % vector. % % Limitations: No line of the text header can begin with % a number. Only one header and data set will be read, % and the header must come before the data. % % See also LOAD, SAVE, SPCONVERT, FSCANF, FPRINTF, STR2MAT. % See also the IOFUN directory. % check number and type of arguments if nargin < 1 error('Function requires one input argument'); elseif ~isstr(file) error('Input argument must be a string representing a filename'); end % Open the file. If this returns a -1, we did not open the file % successfully. fid = fopen(file); if fid==-1 error('File not found or permission denied'); end % Initialize loop variables % We store the number of lines in the header, and the maximum length % of any one line in the header. These are used later in assigning % the 'header' output variable. no_lines = 0; max_line = 0; % We also store the number of columns in the data we read. This way % we can compute the size of the output based on the number of % columns and the total number of data points. ncols = 0; % Finally, we initialize the data to []. data = []; % Start processing. line = fgetl(fid); if ~isstr(line) disp('Warning: file contains no header and no data') end; [data, ncols] = sscanf(line, '%f'); % We loop through the file one line at a time until we find some % data. After that point we stop checking for header information. % This part of the program takes most of the processing time, because % fgetl is relatively slow (compared to fscanf, which we will use % later). while isempty(data) no_lines = no_lines+1; max_line = max([max_line, length(line)]); % Create unique variable to hold this line of text information. % Store the last-read line in this variable. eval(['line', num2str(no_lines), '=line;']); line = fgetl(fid); if ~isstr(line) disp('Warning: file contains no data') break end; [data, ncols] = sscanf(line, '%f'); end % while % Now that we have read in the first line of data, we can skip the % processing that stores header information, and just read in the % rest of the data. data = [data; fscanf(fid, '%f')]; fclose(fid); % Create header output from line information. The number of lines and % the maximum line length are stored explicitly, and each line is % stored in a unique variable using the 'eval' statement within the % loop. Note that, if we knew a priori that the headers were 10 lines % or less, we could use the STR2MAT function and save some work. % First, initialize the header to an array of spaces. header = setstr(' '*ones(no_lines, max_line)); for i = 1:no_lines varname = ['line' num2str(i)]; % Note that we only assign this line variable to a subset of this % row of the header array. We thus ensure that the matrix sizes in % the assignment are equal. eval(['header(i, 1:length(' varname ')) = ' varname ';']); end % Resize output data, based on the number of columns (as returned % from the sscanf of the first line of data) and the total number of % data elements. Since the data was read in row-wise, and MATLAB % stores data in columnwise format, we have to reverse the size % arguments and then transpose the data. If we read in irregularly % spaced data, then the division we are about to do will not work. % Therefore, we will trap the error with an EVAL call; if the reshape % fails, we will just return the data as is. eval('data = reshape(data, ncols, length(data)/ncols)'';', ''); % And we're done!