List of provided Derived Metrics

List of provided Derived Metrics

The derived metrics listed here use the data returned by the raw level data methods to calculate useful derived metrics. In order to maintain consistency, every derived metric is expected to return only a float. This will become important in the context of aggregation across tests or a submission.

Note

Users can feel free to add their own derived metrics. It is explained in the next section.

These are the following metrics which can be fetched via the API. They are defined in flatland_analysis/metrics.py.

The following classes do not require an init parameters.

They can be used like so:

results = framework.get_level_metrics(
    metrics = [PercentageArrived, PercentageArrivedOntime],
    submission_id = "T12345",
    test_id = 0,
    level_id = 0
)

Method

Description (Describes state at end of episode)

Range

PercentageArrived

Get percentage of agents which have arrived at the destination

[0,1]

PercentageArrivedOntime

Get percentage of agents which have arrived at the destination within the latest arrival time

[0,1]

PercentageDepartedNotArrived

Get percentage of agents which have departed but never reached their destination

[0,1]

PercentageNeverDeparted

Get percentage of agents which never left the starting point

[0,1]

For the following metric classes, an init parameter has to provided. The possible values for the init param are:

  • "mean": returns the mean of the metric in the particular level.

  • "min": returns the min of the metric in the particular level.

  • "max": returns the max of the metric in the particular level.

  • callable(list) -> float: a custom function that takes in an input list, performs some aggregation on it and returns a float.

They can be used in the following way:

results = framework.get_level_metrics(
    metrics = [DelayArrived('mean'), CurrentDelayNotArrived(lambda metrics: float(max(metrics)))],
    submission_id = "T12345",
    test_id = 0,
    level_id = 0
)

Method

Description (Describes state at end of episode)

Range

DelayArrived

Get mean / min / max delay of agents which have arrived at their destinations
(positive delay if arrived after latest arrival and negative if the agent arrived earlier)

(-∞,∞)

CurrentDelayNotArrived

Get mean / min / max value of the projected delay of agents which haven’t arrived at their destinations yet

(0,∞)

LenSPNeverDeparted

Get mean / min/ max value of the length of shortest paths of agents which haven’t departed yet to their destinations.

(0,∞)