# Use Sparkle for algorithm selection

These steps can also be found as a Bash script in `Examples/selection.sh`

## Initialise the Sparkle platform

`Commands/initialise.py`

## Add instances

Add instance files (in this case in CNF format) in a given directory, without running solvers or feature extractors yet

`Commands/add_instances.py Examples/Resources/Instances/PTN/`

## Add solvers

Add solvers (here for SAT solving) with a wrapper containing the executable name of the solver and a string of command line parameters, without running the solvers yet

Each solver directory should contain the solver executable and a wrapper

`Commands/add_solver.py --deterministic 0 Examples/Resources/Solvers/CSCCSat/`

`Commands/add_solver.py --deterministic 0 Examples/Resources/Solvers/PbO-CCSAT-Generic/`

`Commands/add_solver.py --deterministic 0 Examples/Resources/Solvers/MiniSAT/`

## Add feature extractor

Similarly, add a feature extractor, without immediately running it on the instances

`Commands/add_feature_extractor.py Examples/Resources/Extractors/SAT-features-competition2012_revised_without_SatELite_sparkle/`

## Compute features

Compute features for all the instances; add the `--parallel` option to run in parallel

`Commands/compute_features.py`

## Run the solvers

Run the solvers on all instances; add the `--parallel` option to run in parallel

`Commands/run_solvers.py`

## Construct a portfolio selector

To make sure feature computation and solver performance computation are done before constructing the portfolio use the `sparkle_wait` command

`Commands/sparkle_wait.py`

Construct a portfolio selector, using the previously computed features and the results of running the solvers

`Commands/construct_sparkle_portfolio_selector.py`

## Generate a report

Generate an experimental report detailing the experimental procedure and performance information; this will be located at `Components/Sparkle-latex-generator/Sparkle_Report.pdf`

`Commands/generate_report.py`

## Run the portfolio selector (e.g. on a test set)

### Run on a single instance

Run the portfolio selector on a *single* testing instance; the result will be printed to the command line

`Commands/run_sparkle_portfolio_selector.py Examples/Resources/Instances/PTN2/plain7824.cnf`

### Run on an instance set

Run the portfolio selector on a testing instance *set*

`Commands/run_sparkle_portfolio_selector.py Examples/Resources/Instances/PTN2/`

## Generate a report including results on the test set

Wait for the portfolio selector to be done running on the testing instance set

`Commands/sparkle_wait.py`

Generate an experimental report that includes the results on the test set, and as before the experimental procedure and performance information; this will be located at `Components/Sparkle-latex-generator/Sparkle_Report_For_Test.pdf`

`Commands/generate_report.py`

By default the `generate_report` command will create a report for the most recent instance set. To generate a report for an older instance set, the desired instance set can be specified with: `--test-case-directory Test_Cases/PTN2/`