diff --git a/README.md b/README.md index 45d0b0c1..b05f2d61 100644 --- a/README.md +++ b/README.md @@ -41,7 +41,7 @@ Below, we show how to use the Nelder-Mead strategy to optimise a benchmark repr ```python # Import summit from summit.benchmarks import SnarBenchmark -from summit.strategies import NelderMead, MultitoSingleObjective +from summit.strategies import SOBO, MultitoSingleObjective from summit.run import Runner # Instantiate the benchmark @@ -53,15 +53,23 @@ transform = MultitoSingleObjective( ) # Set up the strategy, passing in the optimisation domain and transform -nm = NelderMead(exp.domain, transform=transform) +nm = SOBO(exp.domain, transform=transform) # Use the runner to run closed loop experiments r = Runner( strategy=nm, experiment=exp,max_iterations=50 ) r.run() + +# Make a pareto plot comparing both objectives +r.experiment.pareto_plot(ax=ax) ``` +
+ +
+ + ## Documentation The documentation for summit can be found [here](https://gosummit.readthedocs.io/en/latest/index.html). diff --git a/static/pareto.png b/static/pareto.png new file mode 100644 index 00000000..e904b05c Binary files /dev/null and b/static/pareto.png differ