mixle.utils.hvis.front module

The one front door (design review R1): call one thing, get coordinates + receipts.

hvis.map(data) runs the whole pipeline the package’s pieces add up to: fit or accept a model, compose the direct layout (model_map() – deterministic, occlusion- resolved, optionally refined by t-SNE from the model-decided arrangement), and attach every receipt so “make it make sense” is a property of the RETURNED OBJECT, not of the user’s diligence:

  • per-point uncertainty channels a plot can encode directly: posterior_entropy (mixed membership) and typicality (log-density percentile; low = the model finds this point odd);

  • nerve + nerve_health – the learned cover’s topology (loops, disconnection);

  • fit_health – does the MODEL describe the DATA (merged/shattered regimes, fiber calibration);

  • render_health – does the MAP describe the MODEL (trustworthiness/continuity);

  • zoom(components) – the hierarchy: re-chart a regime group with its own fibers, aligned back to the parent (residual reported, never silently rotated);

  • summary() – every diagnosis in one plain-text block.

htsne/humap remain the optimizer-flavored escape hatches; this is the default reading.

class Map(base, posterior_entropy=<factory>, typicality=<factory>, nerve=<factory>, nerve_health=<factory>, fit_health=<factory>, render_health=<factory>, merge_tree=<factory>, zoom_alignment_rms=None, _data=<factory>, _params=<factory>)[source]

Bases: object

A finished map: coordinates, anchors, per-point uncertainty, and every receipt.

Parameters:
property diagnosis: list[str]

Every receipt’s findings, one flat list – empty means no receipt has a complaint.

zoom(components)[source]

Re-chart one regime group with its own fibers: the sub-mixture over components maps the points they dominate, then the child layout is rigidly aligned (rotation/translation + uniform scale) onto those points’ PARENT positions – continuity is measured (zoom_alignment_rms), never assumed. Component indices in the child are positional within components.

Parameters:

components (list[int])

Return type:

Map

hvis_map(data, mix_model=None, emb_dim=2, *, spread=0.35, chart='linear', occlusion=True, refine=False, goals=None, health=True, holdout=None, field_weights=None, max_components=50, dpm_max_its=200, seed=None, refine_kwargs=None)[source]

One call, one finished map (see module docstring). Deterministic unless a DPM must be fit.

goals (anchoring / partial labels / axis objectives) require the optimizer pass, so passing them implies refine=True. health=False skips the receipt computations (they are cheap and subsampled; skip only in tight loops).

Parameters:
Return type:

Map