TurbulenceThresholds

class rojak.orchestrator.configuration.TurbulenceThresholds(*, light=None, light_to_moderate=None, moderate=None, moderate_to_severe=None, severe=None)

Threshold value for each turbulence severity, used to determine whether a diagnostic value counts as that severity

Values may be percentiles (when used to configure a calibration run, see TurbulenceIntensityThresholds) or raw diagnostic values (when computed from a calibration run and reused for evaluation). At least one severity must be set, and the set severities must be in strictly ascending order (see check_values_increasing()).

Parameters:

• light (float | None)

• light_to_moderate (float | None)

• moderate (float | None)

• moderate_to_severe (float | None)

• severe (float | None)

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

Return type:

None

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
check_values_increasing()	Validate that at least one severity is set, and that the set severities are in ascending order
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
from_yaml(path)	Load and validate an instance of this model from a YAML file
get_bounds(severity, mode)	Bounds identifying severity: a diagnostic value falls in this severity if it lies within these bounds
get_by_severity(severity)	The threshold value configured for severity, or None if it was not set
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])	!!! abstract "Usage Documentation"
model_dump_json(*[, indent, ensure_ascii, ...])	!!! abstract "Usage Documentation"
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context)	Populate all_severities from the individual severity fields after construction
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)
validate(value)

Attributes

all_severities	Threshold value for every severity, in TurbulenceSeverity.get_in_ascending_order() order
model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
light
light_to_moderate
moderate
moderate_to_severe
severe