This is a good candidate for using regular expressions and pattern matching. It would take an hour of your time reading section 2-23 of MATLAB Programming Fundamentals (available here) to get started with regular expressions (as well as quite a bit of experimenting). I develop an example below, which is probably not exactly what you need, because your sample is too short for me to experiment, but I can help you refine the approach.
Assuming that all relevant blocks start with a date/time with the following structure
*11:30 28/05/2008*
we first split the file content in blocks, using this structure as a separator:
% - Read file content in one shot.
content = fileread( 'data.txt' ) ;
% - Split time/data blocks.
pattern = '\*\d\d:\d\d \d\d/\d\d/\d{4}\*' ;
[timeBlocks, dataBlocks] = regexp( content, pattern, 'match', 'split' ) ;
dataBlocks(1) = [] ;
It outputs a cell array of time stamps and a matching cell array of block data:
>> timeBlocks
timeBlocks=
'*11:30 28/05/2008*' '*16:30 28/05/2008*'
>> dataBlocks
dataBlocks =
[1x1459 char] [1x1458 char]
Then we convert date/time data into whatever you need, using e.g. DATEVEC or DATENUM:
dateTime = datevec( timeBlocks, '*HH:MM dd/mm/yyyy' ) ;
which outputs
>> dateTime
dateTime =
2008 5 28 11 30 0
2008 5 28 16 30 0
Finally, we iterate through data blocks and extract data
nBlocks = numel( dataBlocks ) ;
data = cell( nBlocks, 1 ) ;
for bId = 1 : nBlocks
% - Extract days and distances.
pattern = '[\r\n](\S+day).*?Seas.*?to\s+([^m]+)' ;
tokens = regexp( dataBlocks{bId}, pattern, 'tokens' ) ;
tokens = vertcat( tokens{:} ) ;
% - Convert distances to double, and cell array to struct array.
if ~isempty( tokens )
tokens(:,2) = num2cell( str2double( tokens(:,2) )) ;
data{bId} = cell2struct( tokens, {'day', 'distance'}, 2 ) ;
end
end
With that, we get:
>> data
data =
[2x1 struct]
[2x1 struct]
>> data{1}
ans =
2x1 struct array with fields:
day
distance
>> data{1}(1)
ans =
day: 'Wednesday'
distance: 2
>> data{1}(2)
ans =
day: 'Thursday'
distance: 1
This illustrates one way to do it. Pattern matching can be improved, and you will want to modify the structure of the output for it to fit with your needs.
Let me know if you have any question.
PS: the best that you can do to understand is to run the code step by step using the debugger, and see what happens each time a line is executed, e.g. when we get tokens it is a cell array of cell arrays, then we VERTCAT its content to transform it into a simple/flat cell array, then we convert to double its second column, etc.
To use the debugger, set a break point by clicking on the dash at the right of the line number, execute the code (a green arrow will appear, indicating the next line to execute), and click on the Step button. At each step, you can use the command window/workspace/editor (mouse over) to see the state/content of variables.
EDIT: just a few extra explanations about patterns.
The first pattern
pattern = '\*\d\d:\d\d \d\d/\d\d/\d{4}\*'
is fairly easy to understand:
- \* means: the character *; it has to be escaped because the star has a special signification otherwise: it is a quantifier that means "zero or more times the expression that precedes".
- \d means: any digit 0-9
- \d{4} means: four times \d
The second pattern
pattern = '[\r\n](\S+day).*?Seas.*?to\s+([^m]+)' ;
is more complex. REGEXP matches the whole pattern but extracts only the parts in parentheses (called tokens).
- |[\r
