GUI Dashboard Export
Topological ML Toolkit includes a lightweight dashboard exporter for inspection, CI artifacts, and demos.
Status: Active prototype. It writes a static, self-contained HTML file. It is not a hosted application server and does not require Plotly, React, PyTorch, TensorFlow, or Triton.
Why A Static Dashboard
Topology is easier to understand when the diagram, feature matrix, and metadata are visible together. A static export is useful because it can be:
- opened locally from disk;
- uploaded as a CI artifact;
- attached to benchmark output;
- linked from project documentation;
- reviewed without installing a frontend stack.
Example
import numpy as np
import topoml
points = np.array([[0.0, 0.0], [0.2, 0.0], [1.0, 0.0]])
diagram = topoml.persistent_homology(points, max_dim=0, max_radius=2.0)
features = topoml.PHFeaturizer(max_dim=0, radii=[0.0, 0.5]).fit_transform([points])
topoml.write_dashboard(
"artifacts/dashboard.html",
title="Topology inspection",
diagram=diagram,
feature_matrix=features,
metadata={"dataset": "example"},
)
Dashboard Contents
The generated page contains:
- summary metrics;
- persistence diagram rows;
- feature matrix rows;
- metadata as formatted JSON.
flowchart LR
A["Point cloud"] --> B["Persistence diagram"]
A --> C["PHFeaturizer"]
B --> D["Static dashboard"]
C --> D
E["Metadata"] --> D
D --> F["Local inspection or CI artifact"]
Claim Boundary
The dashboard exporter is a GUI support layer. It does not claim interactive notebook widgets, cloud hosting, WebGL rendering, or framework integration. Those can be added later behind tests and examples.