- Migrate .wiki/ to .github/wiki/ (GCI standard for public repos)
- Add _Sidebar.md for GitHub Wiki navigation
- Update wiki-sync.yml to reference .github/wiki/ path
- Remove .markdownlintignore (covered by .vscode/settings.json)
- Migrate .allow-ai-terms to ALLOW_AI_TERMS_REPOS in pre-commit hook
- Expand .gitignore with full IDE and AI agent directory list
- Update README project structure reference
Five wiki pages covering Data Collection, ML Crunching, Architecture, Data
Sources, and Research Notes. GitHub Actions workflow syncs .wiki/ to the
GitHub Wiki on push to main. Adds .markdownlintignore and VS Code settings
to exclude .claude/ from lint checks. Adds .allow-ai-terms to allow the
.claude/ directory path reference in lint ignore files.
Replaces the original JS calibration library with a pure Python pipeline
for collecting and back-calculating solar depression angles from human-verified
Fajr and Isha prayer sightings.
What this does:
- src/pipeline.py: master pipeline; fetches iCal + manual records, back-calculates
angles via PyEphem, applies quality filters, exports two clean CSVs
- src/collect/openfajr.py: parses the OpenFajr Birmingham iCal feed (~4,018 records)
- src/collect/verified_sightings.py: manually compiled records from peer-reviewed
studies (Egypt, Saudi Arabia, Malaysia, Indonesia, UK, USA, Canada, and more)
- src/angle_calc.py: PyEphem back-calculation with atmospheric refraction
- src/elevation.py: Open-Elevation API batch lookup
Datasets generated:
- data/processed/fajr_angles.csv: 4,105 confirmed Fajr records, 35 locations,
latitude range -37.8 to 53.7 degrees, date range 1985-2026
- data/processed/isha_angles.csv: 43 confirmed Isha records, 20+ locations
Also includes:
- notebooks/01_exploratory_analysis.ipynb: latitude, TOY, elevation pattern analysis
- research/: academic paper summaries (not training data)
- data/raw/sources.md: full citation table for all data sources
Weighted least-squares calibration of Islamic prayer time depression
angles from observed mosque announcement data. Uses golden-section
search to minimize the sum of squared residuals independently for
Fajr and Isha. Internal Jean Meeus solar ephemeris — zero runtime
dependencies.
API: calibrateAngles, scoreAngles, predictFajr, predictIsha.
Full TypeScript, dual CJS/ESM via tsup.
32 ESM tests, 6 CJS tests, all passing on Node 20/22/24.
