Reporting API

qca.generate_report(model=None, sufficiency_results=None, necessity_results=None, solution=None, fit_result=None, path=None, consistency_threshold=0.75, coverage_threshold=0.10, max_rows=10, include_minimization=True)

Generate a compact text report for a PyQCA model or fit result.

fit_result can be a QCAFitResult. For convenience, generate_report(fit_result) is also accepted.

Parameters:

• model (Any | None)

• sufficiency_results (DataFrame | None)

• necessity_results (DataFrame | None)

• solution (Any | None)

• fit_result (Any | None)

• path (str | Path | None)

• consistency_threshold (float)

• coverage_threshold (float)

• max_rows (int)

• include_minimization (bool)

Return type:

str

qca.generate_markdown_report(obj, *, path=None, title=None, include_metadata=True, max_rows=20)

Generate an automated Markdown report for a model, fit result, or sweep.

Parameters:

• obj (Any)

• path (str | Path | None)

• title (str | None)

• include_metadata (bool)

• max_rows (int)

Return type:

str

qca.to_latex_table(obj, *, table='solutions', path=None, caption=None, label=None, max_rows=None, index=False)

Export one object table as a simple LaTeX tabular environment.

Parameters:

• obj (Any)

• table (str)

• path (str | Path | None)

• caption (str | None)

• label (str | None)

• max_rows (int | None)

• index (bool)

Return type:

str

qca.collect_reproducibility_metadata(obj=None, *, name=None, extra=None)

Collect JSON-serializable reproducibility metadata for an analysis object.

Parameters:

• obj (Any | None)

• name (str | None)

• extra (Mapping[str, Any] | None)

Return type:

dict[str, Any]

class qca.ExperimentLogger(path)

Append-only JSONL experiment logger.

Parameters:

path (str | Path)

log(obj=None, *, name=None, notes=None, extra=None)

Append one experiment record and return the stored metadata.

Parameters:

• obj (Any | None)

• name (str | None)

• notes (str | None)

• extra (Mapping[str, Any] | None)

Return type:

dict[str, Any]

read()

Read all JSONL records from the experiment log.

Return type:

list[dict[str, Any]]

qca.log_experiment(obj, path, *, name=None, notes=None, extra=None)

Append one experiment record to path.

Parameters:

• obj (Any | None)

• path (str | Path)

• name (str | None)

• notes (str | None)

• extra (Mapping[str, Any] | None)

Return type:

dict[str, Any]

class qca.JupyterSummary(title, text, html)

Small display object with plain text and HTML representations.

Parameters:

• title (str)

• text (str)

• html (str)

qca.jupyter_summary(obj, *, title=None, max_rows=8)

Build a compact summary suitable for notebooks.

Parameters:

• obj (Any)

• title (str | None)

• max_rows (int)

Return type:

JupyterSummary