学习的实验往往会记录大量的原始数据,excel处理起来很不方便,好在都是格式化的,用matlab编写了一个方法,方便自己在不同场景套用。
读写格式化的数据文件(用数据类型table的方法)
% data analysis: 6 contexts;seperation data from different contexts
function contextSeperation(subName)
% subName = '6001_jushanzhong';
%curFile = fopen([subName,'.txt'],'r');
matData = readtable([subName,'.txt']);
% correct error in former recording
errData = matData.Error;
for i = 1 : length(errData)
if errData(i) < - 180
errData(i) = errData(i) + 360;
end
end
matData.correctedErr = errData;
% add new row 'rotation'
matData.bias = matData.RealTarget-matData.ShowTarget;
% add new row 'subjectName'
f = @(x) subName;
cellName = cell(length(errData),1);
cellName = cellfun(f,cellName,'UniformOutput',false);
matData.subName = cellName;
arrCenter = matData.CenterInd;
uniqCenter = unique(arrCenter);
numCenter = length(uniqCenter);
newTrialList = [1:10 1:40 1:10]';
% 按序号分出来
for k = 1 : numCenter
tmpInd = find(arrCenter == uniqCenter(k));
tmpArr = matData(tmpInd,:);
tmpArr.Trial = newTrialList;
writetable(tmpArr,['seperate\',subName,'_',num2str(k),'.txt'],'Delimiter','\t');
end
end
批处理文件夹中所有同类文件
% 读取目录下所有的文件信息
fileList = dir(cd);
listLength = length(fileList);
for i = 1 : listLength
if ~fileList(i).isdir
full_name = [cd,'\',fileList(i).name];
[pathstr,name,ext] = fileparts(full_name); % 获取需要处理的文件文件名和拓展名
if strcmp(ext,'.txt')
contextSeperation(name);
end
end
end
合并文件夹中所有数据文件
之前数据量小的文件一直都用的批处理.bat来合并,最近数据量大了这个功能总是出问题,还是自己写一个比较放心。
fileList = dir(cd);
listLength = length(fileList);
C = [];
for i = 1 : listLength
if ~fileList(i).isdir
full_name = [cd,'\',fileList(i).name];
[pathstr,name,ext] = fileparts(full_name); % 获取需要处理的文件文件名和拓展名
if strcmp(ext,'.txt') % 要拼合的文件类型
tmpTable = readtable(full_name);
if isempty(C)
C = tmpTable;
else
C = [C; tmpTable];
end
end
end
end
writetable(C,'STS_all.txt','Delimiter','\t');
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