Experiment Types
Value sweeping runs a simulation for each specified value.
"Radius values": {"steps": 100,"type": "values","field": "radius","values": [0, 1, 2, 3, 4, 5, 6, 7]}
Value sweeping is particularly is useful for multi-parameter sweeps and categorical sampling.
Linspace is one of the most common types of parameter sweeping. Define start, stop, and number of samples to generate an even sampling between two numbers with a set number of datapoints.
"Radius linspace": {"steps": 100,"type": "linspace","field": "radius","start": 0,"stop": 10,"samples": 11}
Instead of using a set number of samples like linspace, arange samples every "increment" between the specified start and stop fields.
"Radius arange": {"steps": 100,"type": "arange","field": "radius","start": 0,"stop": 10,"increment": 0.5}
Monte Carlo sweeping allows random sampling from a custom distribution. Each supported distribution can be customized through the associated parameters. Each parameter defaults to 1 if not defined.
"Radius monte": {"steps": 100,"type": "monte-carlo","field": "radius","samples": 10,// Either combination of distributions and parameters:"distribution": "normal","mean": 1,"std": 1// or"distribution": "log-normal","mu": 1,"sigma": 1// or"distribution": "poisson","rate": 1// or"distribution": "beta","alpha": 1,"beta": 1// or"distribution": "gamma","shape": 1,"scale": 1}
You can run groups of experiments together by adding experiment keys to the runs array of a group definition. The below code, for example, would execute each of our experiments outlined above as sub-experiments of a new experiment:
"Sweep radius": {"steps": 100,"type": "group","runs": ["Radius values", "Radius linspace", "Radius arange", "Radius monte"]}
