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发表于 2002-8-16 23:07:44
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来自 北京
回复: 【求助】数据的输入问题
我现在给你一个读取带文件头的txt文件的例子,这是我再写论文时经常用到的,你先看明白了,有什么问题在来问我!
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 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, errmsg, nxtindex] = sscanf(line, '%f');
% One slight problem: If the first character of the line is 'e',
% then this will scan as 0.00e+00. We can trap this case specifically
% by using the 'next index' output: in the case of a stripped 'e' the next
% index is one, indicating zero characters read. See the help
% entry for 'sscanf' for more information on this output
% parameter. 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)|(nxtindex==1)
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, errmsg, nxtindex] = 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!
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