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Reporting and reproducibility workflow

Frozen R source: reference/vignettes/articles/reporting-reproducibility-workflow.Rmd

This page is the Python migration companion for the corresponding gpbiometrics 2.0.0 article. The original R article is retained verbatim in reference/vignettes/; this companion identifies the matching Python API so the scientific workflow can be reproduced without hiding the reference implementation.

Python API crosswalk

The frozen R article calls the following exported functions; all are available under the same names in gpbiometricspy:

  • gp.add_gazepoint_decision(...)
  • gp.audit_gazepoint_preregistration_consistency(...)
  • gp.create_gazepoint_analysis_decision_log(...)
  • gp.create_gazepoint_analysis_manifest(...)
  • gp.create_gazepoint_audit_index(...)
  • gp.create_gazepoint_audit_report_section(...)
  • gp.create_gazepoint_biometrics_checklist(...)
  • gp.create_gazepoint_biometrics_methods_text(...)
  • gp.create_gazepoint_biometrics_report_tables(...)
  • gp.create_gazepoint_methods_section(...)
  • gp.create_gazepoint_preregistration_checklist(...)
  • gp.create_gazepoint_preregistration_template(...)
  • gp.create_gazepoint_qc_supplement(...)
  • gp.create_gazepoint_release_checklist(...)
  • gp.create_gazepoint_reproducibility_statement(...)
  • gp.create_gazepoint_sidecar_template(...)
  • gp.export_gazepoint_audit_trail_markdown(...)
  • gp.export_gazepoint_biometrics_report_bundle(...)
  • gp.generate_gazepoint_manifest(...)
  • gp.summarise_gazepoint_decision_log(...)
  • gp.summarize_gazepoint_preregistration_readiness(...)
  • gp.write_gazepoint_biometrics_report_tables(...)
  • gp.write_gazepoint_decision_log(...)
import gpbiometricspy as gp

# Example entry point from this workflow
# result = gp.add_gazepoint_decision(...)

Interpretation

Use the same conservative physiological interpretation as the R package: derived biometric features are signal-processing outputs and do not directly establish emotion, stress, cognition, preference, health status, or diagnosis.

Executable Python companion

The frozen R call crosswalk above is retained for completeness. The following companion is an executable end-to-end Python workflow using synthetic/public data and the same scientific domain. It is also executed by the test suite.

Run from the repository root:

python examples/tutorials/reporting-reproducibility-workflow.py

from __future__ import annotations
from _shared import *
d=demo(300); log=gp.create_gazepoint_analysis_decision_log(study_id='tutorial',analyst='example'); methods=gp.create_gazepoint_biometrics_methods_text(data=d); repro=gp.create_gazepoint_reproducibility_statement(decision_log={'decisions':log},package_version=gp.__version__)
with tempfile.TemporaryDirectory() as td: bundle=gp.export_gazepoint_biometrics_report_bundle(output_dir=td,prefix='tutorial',tables={'sample':d.head(10)},text={'methods':methods,'reproducibility':repro},overwrite=True)
finish('reporting-reproducibility-workflow',decision_log=log,bundle=bundle)