我在阅读文件时遇到了麻烦，基本上，我想以某种方式摆脱不必要的文本，只打印出一个只包含数字的矩阵。
1 1 -1 1 1 -1 -1 1 1 1 -1 1
1 -1 1 -1 -1 1 1 1 1 -1 1 1
sgfgdf
1 1 1 -1 1 -1 1 -1 -1 -1 -1 1
rtydsfdsfds
1 -1 1 -1 -1 -1 1 1 -1 -1 -1 1
1 1 -1 1 1 -1 -1 -1 1 -1 1 -1
1 -1 1 1 1 1 1 -1 -1 -1 1 -1
到目前为止我尝试的是：
d = fopen('transmission_data.txt')
R = textscan(d, '%f %f', 'headerLines', 3:5)
fclose(d)
但这不起作用，因为我只需要为 textscan 输入一个数字，例如“3”，这将摆脱前 3 行，但我想特别摆脱第三和第五行。也许还有其他方法可以读取数据？帮助将不胜感激:)
*请注意，第一行文本和第二行数字之间有一个空行
这是一种方法：
如果您必须自动化它，您可以让 importwizard 为您生成代码。
这是导入向导生成的（相当冗长的）代码，当我在名为 test.txt 的文件中对您的数据使用它时
%% Import data from text file.
% Script for importing data from the following text file:
%
% \\invol-vs-fp1\Users$\d.jaheruddin\MATLAB\test.txt
%
% To extend the code to different selected data or a different text file,
% generate a function instead of a script.
% Auto-generated by MATLAB on 2013/10/08 14:39:30
%% Initialize variables.
filename = 'test.txt';
delimiter = ' ';
%% Read columns of data as strings:
% For more information, see the TEXTSCAN documentation.
formatSpec = '%s%s%s%s%s%s%s%s%s%s%s%s%[^\n\r]';
%% Open the text file.
fileID = fopen(filename,'r');
%% Read columns of data according to format string.
% This call is based on the structure of the file used to generate this
% code. If an error occurs for a different file, try regenerating the code
% from the Import Tool.
dataArray = textscan(fileID, formatSpec, 'Delimiter', delimiter, 'MultipleDelimsAsOne', true, 'ReturnOnError', false);
%% Close the text file.
fclose(fileID);
%% Convert the contents of columns containing numeric strings to numbers.
% Replace non-numeric strings with NaN.
raw = [dataArray{:,1:end-1}];
numericData = NaN(size(dataArray{1},1),size(dataArray,2));
for col=[1,2,3,4,5,6,7,8,9,10,11,12]
% Converts strings in the input cell array to numbers. Replaced non-numeric
% strings with NaN.
rawData = dataArray{col};
for row=1:size(rawData, 1);
% Create a regular expression to detect and remove non-numeric prefixes and
% suffixes.
regexstr = '(?<prefix>.*?)(?<numbers>([-]*(\d+[\,]*)+[\.]{0,1}\d*[eEdD]{0,1}[-+]*\d*[i]{0,1})|([-]*(\d+[\,]*)*[\.]{1,1}\d+[eEdD]{0,1}[-+]*\d*[i]{0,1}))(?<suffix>.*)';
try
result = regexp(rawData{row}, regexstr, 'names');
numbers = result.numbers;
% Detected commas in non-thousand locations.
invalidThousandsSeparator = false;
if any(numbers==',');
thousandsRegExp = '^\d+?(\,\d{3})*\.{0,1}\d*$';
if isempty(regexp(thousandsRegExp, ',', 'once'));
numbers = NaN;
invalidThousandsSeparator = true;
end
end
% Convert numeric strings to numbers.
if ~invalidThousandsSeparator;
numbers = textscan(strrep(numbers, ',', ''), '%f');
numericData(row, col) = numbers{1};
raw{row, col} = numbers{1};
end
catch me
end
end
end
%% Exclude rows with non-numeric cells
J = ~all(cellfun(@(x) (isnumeric(x) || islogical(x)) && ~isnan(x),raw),2); % Find rows with non-numeric cells
raw(J,:) = [];
%% Create output variable
test = cell2mat(raw);
%% Clear temporary variables
clearvars filename delimiter formatSpec fileID dataArray ans raw numericData col rawData row regexstr result numbers invalidThousandsSeparator thousandsRegExp me J;
通过 读取文件fileread，将其拆分regexp并要求textscan查找所有数字：
C = regexp(fileread('transmission_data.txt'), '(\n|\r)*', 'split');
C = C(~cellfun('isempty', C));
D = cellfun(@(c) textscan(c, '%f'), C);
R = [D{:}].';
这里重要的一点是，当textscan遇到不包含数字的行时，它会返回一个空矩阵，因此当您连接结果向量时，您只会得到来自非字符串行的向量。对于您的示例，此代码返回
>> R
R =
1 1 -1 1 1 -1 -1 1 1 1 -1 1
1 -1 1 -1 -1 1 1 1 1 -1 1 1
1 1 1 -1 1 -1 1 -1 -1 -1 -1 1
1 -1 1 -1 -1 -1 1 1 -1 -1 -1 1
1 1 -1 1 1 -1 -1 -1 1 -1 1 -1
1 -1 1 1 1 1 1 -1 -1 -1 1 -1