Extracting Data field of a Series in HTML file
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In an HTML file, there is a section like this :
series: [{
name: 'Numbers',
color: '#33CCFF',
lineWidth: 5,
data: [45,78,84,91,111,125,178,231,274,283,303,333] }],
How to extract the 'data' field into an array in a matlab code ?
There are many such series' in that same HTML file with different 'name' fields. For example, name: 'Total Value', 'Log Scale', 'Base Value' etc.
4 个评论
Mohammad Sami
2020-4-7
are you parsing the html in Matlab as char array ? regexp is for string, cellstr or char data.
you can easily change the pattern to name: \'Numbers\'
采纳的回答
per isakson
2020-4-7
编辑:per isakson
2020-5-9
I misunderstood your question. This is a bit of overkill.
Assumptions
- the string, series:, always indicates the start of a block of interest
I created a sample file, cssm.txt, which I uploaded. (Matlab Answers doesn't allow the extension .html ).
This script reads all blocks
%%
chr = fileread('cssm.txt');
cac = regexp( chr, '(?<=series\:)[^\}]+\}\],', 'match' );
%%
len = length( cac );
series(1,len) = struct( 'name','', 'color','', 'lineWidth',[], 'data',[] );
for jj = 1 : len
txt = regexp( cac{jj}, '(?<=name\:)[^,]+', 'match', 'once' );
txt(txt== '''') = [];
series(jj).name = matlab.lang.makeValidName( txt );
txt = regexp( cac{jj}, '(?<=color\:)[^,]+', 'match', 'once' );
txt(txt== '''') = [];
series(jj).color = txt;
txt = regexp( cac{jj}, '(?<=lineWidth\:)[^},]+', 'match', 'once' );
series(jj).lineWidth = str2double( txt );
txt = regexp( cac{jj}, '(?<=data\:)[^}]+', 'match', 'once' );
series(jj).data = str2num( txt ); %#ok<ST2NM>
end
and extract "series which matches name='Numbers'. Not the other series'."
>> series(strcmp({series.name},'Numbers')).data
ans =
45 78 84 91 111 125 178 231 274 283 303 333
In response to comment below
Assumptions
- the string, series:, always indicates the start of a block of interest
- the string, }], indicates the end of a block of interest
- all html-files of interest are named index.html
- all files named index.html are of interest
- all html-files of interest are in subfolders under a root-folder, ...\finCase
- every html-file, index.html, contains exactly one block that has a specific value of the field name:, e.g. Numbers
The overkill is still there. However, reading and parsing four html-files (copies of cssm.txt ) takes less than 10ms.
Try
>> client_data = read_client_data( 'd:\m\cssm\finCase', 'index.html', 'Numbers' )
client_data =
4×2 cell array
{'anderson' } {1×9 double}
{'kim-j-clijsters'} {1×10 double}
{'paul-judd' } {1×11 double}
{'simmi' } {1×12 double}
>>
where (in one m-file)
function client_data = read_client_data( root, file, name )
sad = dir( fullfile( root, '**', file ) );
len = length( sad );
client_data = cell( len, 2 );
for jj = 1 : len
cac = strsplit( sad(jj).folder, filesep );
client = cac{end};
series = read_one_file_( fullfile( sad(jj).folder, sad(jj).name ) );
client_data(jj,:) = { client, series(strcmp({series.name},name)).data };
end
end
function series = read_one_file_( file )
chr = fileread( fullfile( file ) );
cac = regexp( chr, '(?<=series\:)[^\}]+\}\],', 'match' );
len = length( cac );
series(1,len) = struct( 'name','', 'color','', 'lineWidth',[], 'data',[] );
for jj = 1 : len
txt = regexp( cac{jj}, '(?<=name\:)[^,]+', 'match', 'once' );
txt(txt== '''') = [];
series(jj).name = strtrim( txt );
txt = regexp( cac{jj}, '(?<=color\:)[^,]+', 'match', 'once' );
txt(txt== '''') = [];
series(jj).color = txt;
txt = regexp( cac{jj}, '(?<=lineWidth\:)[^},]+', 'match', 'once' );
series(jj).lineWidth = str2double( txt );
txt = regexp( cac{jj}, '(?<=data\:)[^}]+', 'match', 'once' );
series(jj).data = str2num( txt ); %#ok<ST2NM>
end
end
TODO: add error handling and comments
10 个评论
per isakson
2020-5-9
A nice thing with standards is that there are so many to chose between. Null (or NULL) is a special marker used in Structured Query Language to indicate that a data value does not exist in the database [Wikipedia]. However, Matlab doesn't honor Null.
Replace the statement
series(jj).data = str2num( txt ); %#ok<ST2NM>
by
out = textscan( txt , '%f' ...
, 'CollectOutput' , true ...
, 'Delimiter' , ',' ...
, 'EmptyValue' , 0 ...
, 'TreatAsEmpty' , 'null' ...
, 'Whitespace' , ' \t[]' );
series(jj).data = reshape( out{:}, 1,[] );
and read about textscan in the documentation.
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