How to import a txt file with specific format

I need to build the data to construct a report with differents fields like s11 s21 and so on.

I have a text files looks similar to the following:

        Frequency / GHz                S1,1/abs,linear                S1,1/arg,degrees
----------------------------------------------------------------------------------------------------------------
                     0.5                      0.23338409                       174.80629
                  0.5055                      0.23355055                       174.72296
                   0.511                      0.23371744                       174.63905
                  0.5165                      0.23388473                       174.55456

        Frequency / GHz                S2,1/abs,linear                S2,1/arg,degrees
----------------------------------------------------------------------------------------------------------------
                     0.5                      0.97077225                       314.88972
                  0.5055                      0.97072179                       314.39626
                   0.511                      0.97067132                       313.90283
                  0.5165                      0.97062083                       313.40943
                   0.522                      0.97057033                       312.91605

Answer 1

[per isakson]

If the entire file fits in memory I recommend that you

• read the entire file as character
• extracts the "numerical chunks" (an appropriate job for regexp). See Lookahead Assertions in Regular Expressions
• convert to double

    >> M = cssm()
    M = 
        [4x3 double]    [5x3 double]

where cssm.m contains

    function  M = cssm()
        num_xpr = '[ 0-9\.\+\-e\r\n]++';
        xpr = ['(?<=([-]{10,}) *[\r\n]+)',num_xpr,'(?=(Frequency)|($))'];
        str = fileread( 'cssm.txt' );
        cac = regexp( str, xpr, 'match' );
        M = cell( 1, length( cac ) ); 
        for jj = 1 : length( cac )
           M{jj} = str2num( cac{jj} ); 
        end
    end

and cssm.txt contains the example of your question

&nbsp

or an alternative implementation:

The magic number 150 is the minimum number of characters that a block of numerical data must contain.

    >> g = read_blocks_of_numerical_data( 'cssm.txt', 150 )
    g = 
        [4x3 double]    [5x3 double]

where read_blocks_of_numerical_data

    function out = read_blocks_of_numerical_data(filespec,block_size,delim)

        narginchk( 2, 3 )
        buffer  = fileread( filespec );

        if nargin == 2 
            del_xpr = '[ ]+';
            trl_xpr = '[ ]*';
        else
            del_xpr = ['([ ]*',delimiter,'[ ]*)'];
            trl_xpr = ['([ ]*',delimiter,'?[ ]*)'];
        end

        num_xpr = '([+-]?(\d+(\.\d*)?)|(\.\d+))';
        sen_xpr = '([EeDd](\+|-)\d{1,3})?';         % optional scientific
        num_xpr = [ num_xpr, sen_xpr ];

        nl_xpr  = '((\r\n)|\n)';

        row_xpr = cat( 2, '(^|', nl_xpr, ')[ ]*('  ...
                        , num_xpr, del_xpr, ')*'   ...
                        , num_xpr, trl_xpr, '(?='  ...
                        , nl_xpr,'|$)'              ); 

        blk_xpr = ['(',row_xpr,')+'];

        blocks  = regexp( buffer, blk_xpr, 'match' );

        is_long = cellfun( @(str) length(str)>=block_size, blocks );

        blocks(not(is_long)) = [];

        out = cell( 1, length( blocks ) ); 
        for jj = 1 : length( blocks )
            out{jj} = str2num( blocks{jj} );        
        end
    end

[Efren Acevedo]

Great Answer! It is really efficient

Answer 2

[Chad Greene]

Use textscan.

fid = fopen('myfile.txt'); 
data = textscan(fid,'%f %f %f','headerlines',2); 
frequency = data{1}; 
S1 = data{2}; 
S2 = data{3};

You'll need to verify that the number of headerlines is correct.

[Efren Acevedo]

yes, but I need to load 4 fields in the same file. The file was exported from CST.

Your answer only build a field but not the three fields.

the format is like that:

        Frequency / GHz                S1,1/abs,linear                S1,1/arg,degrees
----------------------------------------------------------------------------------------------------------------
                     0.5                      0.23338409                       174.80629
                  0.5055                      0.23355055                       174.72296
                   0.511                      0.23371744                       174.63905

       Frequency / GHz                S2,1/abs,linear                S2,1/arg,degrees
----------------------------------------------------------------------------------------------------------------
                     0.5                      0.97077225                       314.88972
                  0.5055                      0.97072179                       314.39626
                   0.511                      0.97067132                       313.90283
                  0.5165                      0.97062083                       313.40943
                   0.522                      0.97057033                       312.91605

        Frequency / GHz                S1,2/abs,linear                S1,2/arg,degrees
----------------------------------------------------------------------------------------------------------------
                     0.5                      0.97077229                        314.9951
                  0.5055                        0.970726                       314.50112
                   0.511                      0.97067948                       314.00717
                  0.5165                      0.97063276                       313.51325
                   0.522                      0.97058584                       313.01937

        Frequency / GHz                S2,2/abs,linear                S2,2/arg,degrees
----------------------------------------------------------------------------------------------------------------
                     0.5                      0.23118246                       275.34126
                  0.5055                      0.23134189                       274.45027
                   0.511                      0.23150193                       273.55911
                  0.5165                      0.23166255                        272.6678
                   0.522                      0.23182371                       271.77636
                  0.5275                       0.2319854                        270.8848
                   0.533                      0.23214756                       269.99316
                  0.5385                      0.23231019                       269.10144

[Chad Greene]

Can you upload the text file so I can see what you mean?