veriflow.scores.continuous

Continuous verification scores.

For verification of non-probabilistic (deterministic) forecasts, and historical simulations of continuous variables.

For reference, see: https://scores.readthedocs.io/en/stable/included.html#continuous.

Classes

ContinuousScores(config)	Implementation for CRPS for probabilistic forecasts, expressed as cdf.
ContinuousScoresConfig(*[, reduce_dims, ...])	Configure multiple continuous scores.

class veriflow.scores.continuous.ContinuousScores(config)

Implementation for CRPS for probabilistic forecasts, expressed as cdf.

Parameters:

config (ContinuousScoresConfig)

kind: str = 'continuous_scores'

config_class

alias of ContinuousScoresConfig

supported_data_types: ClassVar[set[DataType]] = {DataType.observed_historical, DataType.simulated_forecast_single, DataType.simulated_historical}

config: ContinuousScoresConfig

compute(obs, sim)

Compute any number of continous scores.

Parameters:

• obs (DataArray)

• sim (DataArray)

Return type:

Dataset

classmethod from_config(raw_config)

Initialize class from config dict.

Parameters:

raw_config (dict[str, Any])

Return type:

Self

validate_and_compute(obs, sim)

Validate and compute.

Parameters:

• obs (DataArray)

• sim (DataArray)

Return type:

DataArray | Dataset

class veriflow.scores.continuous.ContinuousScoresConfig(*, reduce_dims=<factory>, score_adapter, general, verification_pair_ids=[], scores, **extra_data)

Configure multiple continuous scores.

Parameters:

• reduce_dims (list[Literal[StandardDim.station, StandardDim.forecast_reference_time, StandardDim.lead_time, StandardDim.time]])

• score_adapter (Literal[ScoreKind.continuous_scores])

• general (Annotated[GeneralInfoConfig, SkipJsonSchema()])

• verification_pair_ids (list[str])

• scores (list[SupportedContinuousScore])

• extra_data (Any)

score_adapter: Literal[ScoreKind.continuous_scores]

scores: list[SupportedContinuousScore]

validate_nse()

Validate that if nse in scores, reduce_dims is not empty.

Return type:

ContinuousScoresConfig

property lead_times: LeadTimes | None

property preserve_dims: list[StandardDim]

The dimensions to preserve.

validate_reduce_dims()

Validate that reduce_dims only contains either forecast or historical dimensions.

Return type:

ReduceDimsHistoricalOrForecast

verification_pair_ids_valid()

Check provided filter for verification pairs contains valid ids.

Return type:

Self

property verification_pairs: list[VerificationPair]

The configured variable pairs.

If the verification_pairs element is configured for the score, filter only these ids from the verification_pairs defined in general config.

general

verification_pair_ids

reduce_dims