ezmsg.learn.dim_reduce.incremental_decomp

Classes

class IncrementalDecompSettings(axis='!time', n_components=2, update_interval=0.0, method='pca', batch_size=None, whiten=False, init='random', beta_loss='frobenius', tol=0.001, alpha_W=0.0, alpha_H='same', l1_ratio=0.0, forget_factor=0.7)

Bases: Settings

Parameters:

• axis (str)

• n_components (int)

• update_interval (float)

• method (str)

• batch_size (int | None)

• whiten (bool)

• init (str)

• beta_loss (str)

• tol (float)

• alpha_W (float)

• alpha_H (float | str)

• l1_ratio (float)

• forget_factor (float)

axis: str = '!time'

n_components: int = 2

update_interval: float = 0.0

method: str = 'pca'

batch_size: Optional[int] = None

whiten: bool = False

init: str = 'random'

beta_loss: str = 'frobenius'

tol: float = 0.001

alpha_W: float = 0.0

alpha_H: Union[float, str] = 'same'

l1_ratio: float = 0.0

forget_factor: float = 0.7

__init__(axis='!time', n_components=2, update_interval=0.0, method='pca', batch_size=None, whiten=False, init='random', beta_loss='frobenius', tol=0.001, alpha_W=0.0, alpha_H='same', l1_ratio=0.0, forget_factor=0.7)

Parameters:

• axis (str)

• n_components (int)

• update_interval (float)

• method (str)

• batch_size (int | None)

• whiten (bool)

• init (str)

• beta_loss (str)

• tol (float)

• alpha_W (float)

• alpha_H (float | str)

• l1_ratio (float)

• forget_factor (float)

Return type:

None

class IncrementalDecompTransformer(*args, **kwargs)

Bases: CompositeProcessor[IncrementalDecompSettings, AxisArray, AxisArray]

Automates usage of IncrementalPCATransformer and MiniBatchNMFTransformer by using a WindowTransformer to extract training samples then calls partial_fit on the decomposition transformer.

stateful_op(state, message)

Return type:

tuple[dict[str, tuple[Any, int]], AxisArray]

Parameters:

• state (dict[str, tuple[Any, int]] | None)

• message (AxisArray)

class IncrementalDecompUnit(*args, settings=None, **kwargs)

Bases: BaseTransformerUnit[IncrementalDecompSettings, AxisArray, AxisArray, IncrementalDecompTransformer]

Parameters:

settings (Settings | None)

SETTINGS

alias of IncrementalDecompSettings

class IncrementalDecompSettings(axis='!time', n_components=2, update_interval=0.0, method='pca', batch_size=None, whiten=False, init='random', beta_loss='frobenius', tol=0.001, alpha_W=0.0, alpha_H='same', l1_ratio=0.0, forget_factor=0.7)

Bases: Settings

Parameters:

• axis (str)

• n_components (int)

• update_interval (float)

• method (str)

• batch_size (int | None)

• whiten (bool)

• init (str)

• beta_loss (str)

• tol (float)

• alpha_W (float)

• alpha_H (float | str)

• l1_ratio (float)

• forget_factor (float)

axis: str = '!time'

n_components: int = 2

update_interval: float = 0.0

method: str = 'pca'

batch_size: Optional[int] = None

whiten: bool = False

init: str = 'random'

beta_loss: str = 'frobenius'

tol: float = 0.001

alpha_W: float = 0.0

alpha_H: Union[float, str] = 'same'

l1_ratio: float = 0.0

forget_factor: float = 0.7

__init__(axis='!time', n_components=2, update_interval=0.0, method='pca', batch_size=None, whiten=False, init='random', beta_loss='frobenius', tol=0.001, alpha_W=0.0, alpha_H='same', l1_ratio=0.0, forget_factor=0.7)

Parameters:

• axis (str)

• n_components (int)

• update_interval (float)

• method (str)

• batch_size (int | None)

• whiten (bool)

• init (str)

• beta_loss (str)

• tol (float)

• alpha_W (float)

• alpha_H (float | str)

• l1_ratio (float)

• forget_factor (float)

Return type:

None

class IncrementalDecompTransformer(*args, **kwargs)

Bases: CompositeProcessor[IncrementalDecompSettings, AxisArray, AxisArray]

Automates usage of IncrementalPCATransformer and MiniBatchNMFTransformer by using a WindowTransformer to extract training samples then calls partial_fit on the decomposition transformer.

stateful_op(state, message)

Return type:

tuple[dict[str, tuple[Any, int]], AxisArray]

Parameters:

• state (dict[str, tuple[Any, int]] | None)

• message (AxisArray)

class IncrementalDecompUnit(*args, settings=None, **kwargs)

Bases: BaseTransformerUnit[IncrementalDecompSettings, AxisArray, AxisArray, IncrementalDecompTransformer]

Parameters:

settings (Settings | None)

SETTINGS

alias of IncrementalDecompSettings