Progress bars can be used to track long-running matlab programs where alternatives (e.g. displaying progress information in the console) are infeasible.
Progress bars can be group in windows, and organized independently or as a stack (for e.g. nested for-loops). Each bar displays a parameter name, the current value of that parameter out of a maximum, and an estimated remaining time for that bar.
The code is OO, so progress bar windows are created with
pr = Progress();
Organizing bars as a (FILO) stack makes it easier to add, update, and remove them:
pr.push_bar('parameter name', min, max);
where pr.set(value) sets the bar at the top of the stack. Alternatively, bars can be updated by name:
pr.set('parameter name', value);
and reset to their minimum value:
At each call to pr.set, timing data is collected, and a polynomial is fitted to the data, giving a good estimation of remaining time for processes that are of complexity O(N) or O(N^2). Higher degree polynomials can be used if a task is known not to be in these classes.
Closing a progress bar window manually (i.e. clicking on the X) produces an error - similar to ctrl-c.
The package also includes an automatic code generation tool for adding progress functionality with minimum fuss. This pre-processes an annotated matlab script and adds the necessary boilerplate code. Scripts can be annotated like this:
reptitions = 40;
for i=1:repititions %%p1
parameters_values = [1 2 3 5 10];
for j=1:numel(parameter_values) %%p2
where %%p# indicates a level of nesting, that will be reflected in the progress bar stack.
Furthermore, by including a (slightly awkward-looking) line at the top of a script:
the annotated script can be run as normal (i.e. by typing the script name) and the pre-processing will be invoked automatically - emitting the script with added boilerplate code into a temporary file, then executing this file in the base workspace, then deleting it. This makes the addition of progress bars quite transparent.
The latest addition to the functionality is that some custom code can now be executed upon request during execution. For example, when finding some results in a 100-repetition loop, we could include some code to plot the results for all of the repetitions so far. This lets us check up on the experiment whenever we like (e.g. see the results for the first 10 repetitions), without having to regularly plot graphs or wait until the entire experiment is complete. This can be easily achieved by adding this at the end of the original script:
for current_value=1:100 %%p1
results(current_value) = experiment(current_value);
%%finalise (this tag shows that all the following code should be executed when a button is pressed)
Lots of additional documentation and an example script are included.
Richard Stapenhurst (2021). Progress Bars (https://www.mathworks.com/matlabcentral/fileexchange/28179-progress-bars), MATLAB Central File Exchange. Retrieved .
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