feature

Represent a feature object.

__all__ = ['BaseFeature', 'CategoricalFeature', 'ExposedFeature', 'Feature', 'Image', 'Metadata', 'MultivariateAsynchronousTimeSerie', 'MultivariateNumericalFeature', 'MultivariateSynchronousTimeSerie', 'NumericalFeature', 'Token', 'UnivariateAsynchronousTimeSerie', 'UnivariateSynchronousTimeSerie', 'YoloBboxWithClassFeature']

ExposedFeature = ExposedCategoricalFeature | ExposedCategoricalFeatureList | ExposedNumericalFeature | ExposedMultivariateNumericalFeature | ExposedBboxFeatureList | ExposedUnivariateSynchronousTimeSerie | ExposedUnivariateAsynchronousTimeSerie | ExposedMultivariateSynchronousTimeSerie | ExposedMultivariateAsynchronousTimeSerie | ExposedImage | ExposedToken | ExposedYoloBboxWithClassFeature | ExposedMetadata

EXPOSED_FEATURE_TYPE = TypeVar('EXPOSED_FEATURE_TYPE', bound=ExposedFeature)

Feature = NumericalFeature | CategoricalFeature | MultivariateNumericalFeature | UnivariateSynchronousTimeSerie | UnivariateAsynchronousTimeSerie | MultivariateSynchronousTimeSerie | MultivariateAsynchronousTimeSerie | Image | Token | YoloBboxWithClassFeature | Metadata

AbstractDataElement

Represent a schema column, with a name.

Parameters:

Name	Type	Description	Default
name	str		required

name: str

TargetableFeature

A feature that can be a target.

Parameters:

Name	Type	Description	Default
is_target	bool		False

is_target: bool = False

BaseFeature

Base Feature used if no convenient available feature.

as_exposed: ExposedBaseFeature

NumericalFeature as ExposedNumericalFeature.

from_exposed(exposed_feature: ExposedBaseFeature) -> Self

BaseFeature from ExposedBaseFeature.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedBaseFeature) -> Self:
    """BaseFeature from ExposedBaseFeature."""
    return cls(**msgspec_asdict(exposed_feature))

ExplainableFeature

Define a feature object.

Parameters:

Name	Type	Description	Default
preprocessor	SklearnPreprocessor | IdentityPreprocessor	feature preprocessor function used to preprocess the data.	required

preprocessor: TorchPreprocessor | SklearnPreprocessor | IdentityPreprocessor = field(kw_only=True)

as_exposed: EXPOSED_FEATURE_TYPE

Feature as exposed feature.

from_exposed(exposed_feature: EXPOSED_FEATURE_TYPE) -> Self

Feature from exposed feature.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: EXPOSED_FEATURE_TYPE) -> Self:
    """Feature from exposed feature."""
    raise NotImplementedError

NumericalFeature

Numerical feature.

as_exposed: ExposedNumericalFeature

NumericalFeature as ExposedNumericalFeature.

from_exposed(exposed_feature: ExposedNumericalFeature) -> Self

NumericalFeature from ExposedNumericalFeature.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedNumericalFeature) -> Self:
    """NumericalFeature from ExposedNumericalFeature."""
    return cast(Self, cls._from_exposed(exposed_feature))

CategoricalFeature

Categorical feature.

Parameters:

Name	Type	Description	Default
categories	list[Union[str, int, bool]]		required

categories: list[str | int | bool] = field(kw_only=True)

as_exposed: ExposedCategoricalFeature

CategoricalFeature as ExposedCategoricalFeature.

from_exposed(exposed_feature: ExposedCategoricalFeature) -> Self

CategoricalFeature from ExposedCategoricalFeature.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedCategoricalFeature) -> Self:
    """CategoricalFeature from ExposedCategoricalFeature."""
    return cast(Self, cls._from_exposed(exposed_feature))

MultivariateNumericalFeature

MultivariateNumericalFeature feature.

Parameters:

Name	Type	Description	Default
size	int		required
channel_names	list[str] | None		None

size: int = field(kw_only=True)

channel_names: list[str] | None = field(default=None, kw_only=True)

as_exposed: ExposedMultivariateNumericalFeature

MultivariateNumericalFeature as ExposedMultivariateNumericalFeature.

from_exposed(exposed_feature: ExposedMultivariateNumericalFeature) -> Self

MultivariateNumericalFeature from ExposedMultivariateNumericalFeature.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedMultivariateNumericalFeature) -> Self:
    """MultivariateNumericalFeature from ExposedMultivariateNumericalFeature."""
    return cast(Self, cls._from_exposed(exposed_feature))

UnivariateSynchronousTimeSerie

UnivariateSynchronousTimeSerie feature.

Parameters:

Name	Type	Description	Default
size	int		required
mirrored_channel	str | None		None

size: int = field(kw_only=True)

mirrored_channel: str | None = field(default=None, kw_only=True)

as_exposed: ExposedUnivariateSynchronousTimeSerie

UnivariateSynchronousTimeSerie as ExposedUnivariateSynchronousTimeSerie.

from_exposed(exposed_feature: ExposedUnivariateSynchronousTimeSerie) -> Self

UnivariateSynchronousTimeSerie from ExposedUnivariateSynchronousTimeSerie.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedUnivariateSynchronousTimeSerie) -> Self:
    """UnivariateSynchronousTimeSerie from ExposedUnivariateSynchronousTimeSerie."""
    return cast(Self, cls._from_exposed(exposed_feature))

UnivariateAsynchronousTimeSerie

UnivariateSynchronousTimeSerie feature.

Parameters:

Name	Type	Description	Default
size	int		required
mirrored_channel	str | None		None

size: int = field(kw_only=True)

mirrored_channel: str | None = field(default=None, kw_only=True)

as_exposed: ExposedUnivariateAsynchronousTimeSerie

UnivariateAsynchronousTimeSerie as ExposedUnivariateAsynchronousTimeSerie.

from_exposed(exposed_feature: ExposedUnivariateAsynchronousTimeSerie) -> Self

UnivariateAsynchronousTimeSerie from ExposedUnivariateAsynchronousTimeSerie.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedUnivariateAsynchronousTimeSerie) -> Self:
    """UnivariateAsynchronousTimeSerie from ExposedUnivariateAsynchronousTimeSerie."""
    return cast(Self, cls._from_exposed(exposed_feature))

MultivariateSynchronousTimeSerie

MultivariateSynchronousTimeSerie feature.

Parameters:

Name	Type	Description	Default
size	list[int]		required
channel_names	str | None		None

size: list[int] = field(kw_only=True)

channel_names: str | None = field(default=None, kw_only=True)

as_exposed: ExposedMultivariateSynchronousTimeSerie

MultivariateSynchronousTimeSerie as ExposedMultivariateSynchronousTimeSerie.

from_exposed(exposed_feature: ExposedMultivariateSynchronousTimeSerie) -> Self

MultivariateSynchronousTimeSerie from ExposedMultivariateSynchronousTimeSerie.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedMultivariateSynchronousTimeSerie) -> Self:
    """MultivariateSynchronousTimeSerie from ExposedMultivariateSynchronousTimeSerie."""
    return cast(Self, cls._from_exposed(exposed_feature))

MultivariateAsynchronousTimeSerie

MultivariateAsynchronousTimeSerie feature.

Parameters:

Name	Type	Description	Default
size	list[int]		required
channel_names	list[str] | None		None

size: list[int] = field(kw_only=True)

channel_names: list[str] | None = field(default=None, kw_only=True)

as_exposed: ExposedMultivariateAsynchronousTimeSerie

MultivariateAsynchronousTimeSerie as ExposedMultivariateAsynchronousTimeSerie.

from_exposed(exposed_feature: ExposedMultivariateAsynchronousTimeSerie) -> Self

MultivariateAsynchronousTimeSerie from ExposedMultivariateAsynchronousTimeSerie.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedMultivariateAsynchronousTimeSerie) -> Self:
    """MultivariateAsynchronousTimeSerie from ExposedMultivariateAsynchronousTimeSerie."""
    return cast(Self, cls._from_exposed(exposed_feature))

Image

Image feature.

Parameters:

Name	Type	Description	Default
size	tuple[int, ...]		required

size: tuple[int, ...] = field(kw_only=True)

as_exposed: ExposedImage

Image as ExposedImage.

from_exposed(exposed_feature: ExposedImage) -> Self

Image from ExposedImage.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedImage) -> Self:
    """Image from ExposedImage."""
    return cast(Self, cls._from_exposed(exposed_feature))

Token

Token feature.

as_exposed: ExposedToken

Token as ExposedToken.

from_exposed(exposed_feature: ExposedToken) -> Self

Token from ExposedToken.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedToken) -> Self:
    """Token from ExposedToken."""
    return cast(Self, cls._from_exposed(exposed_feature))

YoloBboxWithClassFeature

YoloBboxWithClassFeature feature.

as_exposed: ExposedYoloBboxWithClassFeature

YoloBboxWithClassFeature as ExposedYoloBboxWithClassFeature.

from_exposed(exposed_feature: ExposedYoloBboxWithClassFeature) -> Self

YoloBboxWithClassFeature from ExposedYoloBboxWithClassFeature.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_feature: ExposedYoloBboxWithClassFeature) -> Self:
    """YoloBboxWithClassFeature from ExposedYoloBboxWithClassFeature."""
    return cast(Self, cls._from_exposed(exposed_feature))

Metadata

Metadata.

as_exposed: ExposedMetadata

Generate the corresponding exposed feature.

from_exposed(exposed_metadata: ExposedMetadata) -> Self

Create Metadata from exposed metadata.

Source code in src/xpdeep/dataset/schema/feature/feature.py

@classmethod
def from_exposed(cls, exposed_metadata: ExposedMetadata) -> Self:
    """Create Metadata from exposed metadata."""
    return cls(name=exposed_metadata.name)