tlc.core.objects.tables.from_table.pacmap_table#

A Table where a column from the input Table has been dimensionally reduced by the PaCMAP algorithm.

Module Contents#

Classes#

Class

Description

PaCMAPTable

A procedural table where a column in the input table column has been has dimensionally reduced by the PaCMAP algorithm.

Data#

Data

Description

pacmap

API#

tlc.core.objects.tables.from_table.pacmap_table.pacmap = _lazy_import(...)#
class tlc.core.objects.tables.from_table.pacmap_table.PaCMAPTable(url: tlc.core.url.Url | None = None, created: str | None = None, description: str | None = None, row_cache_url: tlc.core.url.Url | None = None, row_cache_populated: bool | None = None, input_table_url: tlc.core.url.Url | tlc.core.objects.table.Table | None = None, source_embedding_column: str | None = None, target_embedding_column: str | None = None, retain_source_embedding_column: bool | None = None, fit_table_url: tlc.core.objects.table.Table | tlc.core.url.Url | None = None, model_url: tlc.core.url.Url | None = None, n_components: int | None = None, n_neighbors: int | None = None, MN_ratio: float | None = None, FP_ratio: float | None = None, distance: str | None = None, lr: float | None = None, num_iters: int | None = None, verbose: bool | None = None, apply_pca: bool | None = None, random_state: int | None = None, init_parameters: Any = None, standard_scaler_normalize: bool | None = None, input_tables: list[tlc.core.url.Url] | None = None)#

Bases: tlc.core.objects.tables.from_table.dimensional_reduction_table._DimensionalReductionTable

A procedural table where a column in the input table column has been has dimensionally reduced by the PaCMAP algorithm.

Creates a derived table with a new column containing the dimensionally reduced data.

Parameters:

  • input_table_url – The input table to apply the dimensionality reduction to

  • source_embedding_column – The column in the input table to apply dimensionality reduction to

  • target_embedding_column – The name of the new column to create in the output table

  • retain_source_embedding_column – Whether to retain the source column in the input table, defaults to False

  • standard_scaler_normalize – Whether to apply the sklearn standard scaler to input before reducing, defaults to False

  • fit_table_url – The table to use for fitting reduction transform. If not specified, the input table is used.

  • model_url – The URL to store/load the reducer model file. If empty, no model is saved.

  • n_components – The dimension of the output embedding

  • random_state – The random seed for the reducer algorithm

algorithm_name = PaCMAP#