analysis.dimensionality_reduction.pacmap_dim_reduction

Methods for dimensionality reduction using PaCMAP.

Functions

plot_pacmap_feature_scatter(data, features)

Plot scatter of PaCMAP embedding colored by the given features.

run_pacmap(data)

Run Pairwise Controlled Manifold Approximation (PaCMAP) on simulation data.
run_pacmap(data: DataFrame) → tuple[DataFrame, PaCMAP][source]

Run Pairwise Controlled Manifold Approximation (PaCMAP) on simulation data.

Parameters:

data – Simulated fiber data.

Returns:

Dataframe with PaCMAP emebdding appended and the PaCMAP object.

plot_pacmap_feature_scatter(data: DataFrame, features: dict, save_location: str | None = None, save_key: str = 'pacmap_feature_scatter.png') → None[source]

Plot scatter of PaCMAP embedding colored by the given features.

Parameters:

  • data – PaCMAP results data.

  • features – Map of feature name to coloring.

  • save_location – Location for output file (local path or S3 bucket).

  • save_key – Name key for output file.