validators - bossanova

Shared validators and converters for container attrs classes.

Functions:

Name	Description
`convert_corr_to_dict`	Convert correlation specification to dictionary format.
`is_choice_str`	Build a validator for a string constrained to a fixed set of choices.
`is_conf_level`	Validate that a value is a normalized confidence level in (0, 1).
`is_ndarray`	Validate that a value is a numpy ndarray.
`is_nonnegative_int`	Validate that a value is a non-negative integer.
`is_optional_conf_level`	Validate that a value is a normalized confidence level or None.
`is_optional_int`	Validate that a value is an int or None.
`is_optional_ndarray`	Validate that a value is a numpy ndarray or None.
`is_optional_positive_int`	Validate that a value is a positive integer or None.
`is_optional_sparse_csc`	Validate that a value is a scipy.sparse.csc_matrix or None.
`is_optional_str`	Validate that a value is a string or None.
`is_optional_str_key_dict`	Validate that a value is a dict with string keys or None.
`is_optional_tuple_of_str`	Validate that a value is a tuple of strings or None.
`is_positive_int`	Validate that a value is a positive integer.
`is_tuple_of_str`	Validate that a value is a tuple of strings.
`normalize_conf_level`	Normalize conf_level to a float in (0, 1).
`normalize_optional_conf_level`	Normalize an optional confidence level.
`to_factor_dict`	Convert factor dict values from lists to tuples.
`to_frozen_dict`	Ensure dict values are tuples where applicable.
`to_optional_tuple`	Convert an optional list of strings to a tuple.
`to_tuple`	Convert list to tuple for immutability.
`to_tuple_of_tuples`	Convert dict values to tuples for immutability.
`validate_correlations`	Validate correlation values are in [-1, 1].
`validate_sigma`	Validate sigma is non-negative.
`validate_slope_sds`	Validate slope SDs are non-negative.

Functions¶

convert_corr_to_dict¶

convert_corr_to_dict(corr: float | dict[tuple[str, str], float], slope_sds: dict[str, float]) -> dict[tuple[str, str], float]

Convert correlation specification to dictionary format.

Parameters:

Name	Type	Description	Default
`corr`	`float \| dict[tuple[str, str], float]`	Correlation as single value or dict.	required
`slope_sds`	`dict[str, float]`	Dictionary of slope SDs (to determine term names).	required

Returns:

Type	Description
`dict[tuple[str, str], float]`	Dictionary mapping term pairs to correlations.

is_choice_str¶

is_choice_str(choices: tuple[str, ...])

Build a validator for a string constrained to a fixed set of choices.

is_conf_level¶

is_conf_level(instance: object, attribute: object, value: object) -> None

Validate that a value is a normalized confidence level in (0, 1).

is_ndarray¶

is_ndarray(instance: object, attribute: object, value: object) -> None

Validate that a value is a numpy ndarray.

is_nonnegative_int¶

is_nonnegative_int(instance: object, attribute: object, value: object) -> None

Validate that a value is a non-negative integer.

is_optional_conf_level¶

is_optional_conf_level(instance: object, attribute: object, value: object) -> None

Validate that a value is a normalized confidence level or None.

is_optional_int¶

is_optional_int(instance: object, attribute: object, value: object) -> None

Validate that a value is an int or None.

is_optional_ndarray¶

is_optional_ndarray(instance: object, attribute: object, value: object) -> None

Validate that a value is a numpy ndarray or None.

is_optional_positive_int¶

is_optional_positive_int(instance: object, attribute: object, value: object) -> None

Validate that a value is a positive integer or None.

is_optional_sparse_csc¶

is_optional_sparse_csc(instance: object, attribute: object, value: object) -> None

Validate that a value is a scipy.sparse.csc_matrix or None.

is_optional_str¶

is_optional_str(instance: object, attribute: object, value: object) -> None

Validate that a value is a string or None.

is_optional_str_key_dict¶

is_optional_str_key_dict(instance: object, attribute: object, value: object) -> None

Validate that a value is a dict with string keys or None.

is_optional_tuple_of_str¶

is_optional_tuple_of_str(instance: object, attribute: object, value: object) -> None

Validate that a value is a tuple of strings or None.

is_positive_int¶

is_positive_int(instance: object, attribute: object, value: object) -> None

Validate that a value is a positive integer.

is_tuple_of_str¶

is_tuple_of_str(instance: object, attribute: object, value: object) -> None

Validate that a value is a tuple of strings.

normalize_conf_level¶

normalize_conf_level(conf_level: float | int | str) -> float

Normalize conf_level to a float in (0, 1).

Float in (0, 1): returned as-is (e.g. 0.95)
Float in (0, 1): returned as-is (e.g. 0.95)
Int or float in (1, 100): divided by 100 (e.g. 95 -> 0.95)
String with optional % suffix: parsed and normalized (e.g. "95%" -> 0.95, "0.95" -> 0.95)

Parameters:

Name	Type	Description	Default
`conf_level`	`float \| int \| str`	Confidence level in any supported format.	required

Returns:

Type	Description
`float`	Confidence level as a float strictly between 0 and 1 (exclusive).

normalize_optional_conf_level¶

normalize_optional_conf_level(conf_level: float | int | str | None) -> float | None

Normalize an optional confidence level.

to_factor_dict¶

to_factor_dict(val: Any) -> dict[str, tuple[str, ...]]

Convert factor dict values from lists to tuples.

to_frozen_dict¶

to_frozen_dict(val: Any) -> dict

Ensure dict values are tuples where applicable.

to_optional_tuple¶

to_optional_tuple(value: tuple[str, ...] | list[str] | None) -> tuple[str, ...] | None

Convert an optional list of strings to a tuple.

to_tuple¶

to_tuple(value: tuple[str, ...] | list[str]) -> tuple[str, ...]

Convert list to tuple for immutability.

to_tuple_of_tuples¶

to_tuple_of_tuples(value: dict[str, tuple[str, ...] | list[str]] | None) -> dict[str, tuple[str, ...]]

Convert dict values to tuples for immutability.

validate_correlations¶

validate_correlations(instance: Any, attribute: Any, value: dict[tuple[str, str], float]) -> None

Validate correlation values are in [-1, 1].

validate_sigma¶

validate_sigma(instance: Any, attribute: Any, value: float) -> None

Validate sigma is non-negative.

validate_slope_sds¶

validate_slope_sds(instance: Any, attribute: Any, value: dict[str, float]) -> None

Validate slope SDs are non-negative.