MATLAB读取文件

Question

我在读取文件时遇到了困难，基本上，我想摆脱不必要的文本，只打印一个只涉及数字的矩阵。

1 1 -1 1 -1 1 1

1 -1 1 -1 1 1

斯格夫

1 1 1

子虚乌有

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=文本扫描(d，'%f %f'，'headerLines'，3:5)

关闭(D)

但这是行不通的，因为我只需要为文本扫描输入一个数字，例如，'3'，这将去掉前3行，但我想具体地去掉第三行和第五行。也许还有别的方法来读取数据？如能提供帮助，将不胜感激:)

*请注意，在第一行文本和第二行数字之间有一行空行。

Answer 1

通过fileread读取该文件，用regexp将其拆分，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{:}].';

这里最重要的一点是，当textscan遇到一个不包含数字的行时，它会返回一个空矩阵，所以当您连接生成的向量时，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

Answer 2

有一种方法可以做到：

1. 用大蜥蜴
2. 按所需形式选择单元格数组或矩阵。
3. 选择删除值无效的行
4. 单击“导入”

如果你必须让它自动化，你可以让入口蜥蜴为你做代码生成。

下面是importw火龙在名为test.txt的文件中对数据使用时生成的(相当冗长的)代码

%% 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;