`tlc.client.reduce.reduction_method`¶

Base classes for dimensionality reducers.

Module Contents¶

Classes¶

Class	Description
`ReducerArgs`	Arguments specific to the reduction method.
`ReductionMethod`	Perform dimensionality reduction on columns of tables.

API¶

class ReducerArgs¶

Bases: typing.TypedDict

Arguments specific to the reduction method.

Initialize self. See help(type(self)) for accurate signature.

source_embedding_column: str | None = None¶: The name of the column containing the unreduced embedding in the input table. If None, all columns are considered .

target_embedding_column: str | None = None¶: The name of the column containing the reduced embedding in the output table. If None, the column is named after the input column.

retain_source_embedding_column: bool = None¶: Whether to retain the source embedding column in the output table (default False).

class ReductionMethod( reducer_args: tlc.client.reduce.reduction_method._ReducerArgsType | None = None, )¶

Bases: abc.ABC, typing.Generic[tlc.client.reduce.reduction_method._ReducerArgsType]

Perform dimensionality reduction on columns of tables.

Dimensionality reduction is accomplished by creating derived tables of the appropriate type (e.g., UMAPTable) which apply the reduction method to the input tables.

Params reducer_args:: A dictionary of arguments which are specific to the reduction method.

abstract default_args() → tlc.client.reduce.reduction_method._ReducerArgsType¶

fit_and_apply_reduction( producer: Table, consumers: list[Table] = [], ) → dict[Url, Url]¶

abstract fit_reduction_method( table: Table, column: str, ) → Url¶

abstract apply_reduction_method( table: Table, fit_table_url: Url, column: str, ) → Url | None¶

tlc.client.reduce.reduction_method¶

Module Contents¶

Classes¶

API¶

`tlc.client.reduce.reduction_method`¶