For loop not doing what I want it to

% Create counter for indexing of new table.
counter = 1;

% Create empty table for x coordinates
sampled_x_coord  = [];
sampled_x_coord_table = array2table(sampled_x_coord);

% Create empty table for y coordinates.
sampled_y_coord = [];
sampled_y_coord_table = array2table(sampled_y_coord);

% Create ignore next variable, assign to false for start of loop. 
ignore_next = false; 

for i = 1:height(path_data)
    if ignore_next == true
       ignore_next = false;
    elseif ignore_next == false
        if path_data.time(i) == path_data.time(i + 1)
            sampled_x_coord_table.sampled_x_coord(counter) = ((path_data.x(i) + path_data.x(i + 1)) / 2);
            sampled_y_coord_table.sampled_y_coord(counter) = ((path_data.y(i) + path_data.y(i + 1)) / 2);               
            ignore_next = true;
            counter = counter + 1;
        elseif path_data.time(i) ~= path_data.time(i + 1)
            sampled_x_coord_table.sampled_x_coord(counter) = path_data.x(i);
            sampled_y_coord_table.sampled_y_coord(counter) = path_data.y(i);                             
            ignore_next = false;
            counter = counter + 1;
        end
    end
end

See my for loop above, what I am doing is going through and comapring a time variable in one row to the time variable in the next row. If the time variables are the same, then I'm averaging two x and y coordinate values and using that as my x and y coordinate value. If they are the same, then I want to skip the next row in the table, which is what I do with the ignore_next variable.

If the time variables are different, then I just want to take the x and y coordinate for that row and use that (without any averaging) as my data points.

The for loop works for the first scenario, averaging the two x and y coordinates if the time variables are the same, but if the time variables are differernt, then it creates an empty row in the sampled_x_coord_table and sampled_y_coord_table tables.

Answer 1

[dpb]

TT=table2timetable(path_data);            % convert the table to a time table
TT=retime(TT,unique(TT.time),'mean');     % retime to included times, average identical times

See documentation for timtetable and retime for details, other options...

[Spencer Ferris]

This worked, thanks!