`brier_score`¶

Import path: earth2studio.statistics.brier_score

Documentation¶

Statistic for calculating the Brier score (BS) of one tensors with respect to another over a set of given dimensions.

If ensemble_dimension is provided, the forecast probability is inferred by averaging over the ensemble members.

Parameters:

reduction_dimensions (list[str]) –

A list of names corresponding to dimensions to perform the statistical reduction over. Example: ['lat', 'lon']
thresholds (ArrayLike) –

A list of the thresholds applied when calculating BS.
ensemble_dimension (str | None, default: None ) –

Ensemble dimension for computation of probabilistic BS. If None (default), forecast is interpreted as deterministic.
batch_update (bool, default: False ) –

Whether to apply batch updates to the BS with each invocation of call. This is particularly useful when data is recieved in a stream of batches. Each invocation of call will return the running BS.

__call__(
    x: Tensor,
    x_coords: CoordSystem,
    y: Tensor,
    y_coords: CoordSystem,
) -> tuple[Tensor, CoordSystem]

Apply metric to data x and y, checking that their coordinates are broadcastable. While reducing over reduction_dims.

Parameters:

x (Tensor) –

Input tensor, typically the forecast or prediction tensor.
x_coords (CoordSystem) –

Ordered dict representing coordinate system that describes the x tensor. reduction_dimensions must be in x_coords, as do ensemble_dimension and spatial_dimensions if provided in constructor.
y (Tensor) –

Input tensor #2 intended to be used as validation data..
y_coords (CoordSystem) –

Ordered dict representing coordinate system that describes the y tensor. reduction_dimensions must be in y_coords, do spatial_dimensions if provided in constructor.

Returns:

tuple[Tensor, CoordSystem] –

Returns root mean squared error tensor with appropriate reduced coordinates.