Revival/04 docs - #7
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- pyproject.toml (PEP 621, setuptools backend) replaces setup.py, requirements.txt and install.md; version read from predspot.__version__; optional extras: `contour` (geojsoncontour) and `dev` (pytest, ruff, build) - src/ layout so tests always run against the installed package - ruff lint + format configuration; code base formatted and lint-clean - CI workflow: ruff, pytest with coverage on Python 3.10-3.13, build + twine check of the distribution - Publish workflow: on a v* tag, verify tag == package version, build and upload to PyPI via trusted publishing (no stored token) - CHANGELOG.md, CONTRIBUTING.md, MANIFEST.in; README badges and install docs Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01FtZdc2gGrDh4PGSLyT9yRE
- crime_mapping.load_study_area("City, State, Country") geocodes a place
with osmnx and returns its boundary polygon as a GeoDataFrame ready for
Dataset / the create_grid* functions; osmnx is an optional extra
(`predspot[osm]`), points instead of polygons raise a clear error
- New predspot.synthetic module: generate_crimes(study_area, ...) draws
events from a Gaussian-hotspot + uniform-background spatial mixture and an
inhomogeneous temporal intensity (linear trend, annual cycle, day-of-week
and hour-of-day profiles) sampled by thinning; works with any study area
polygon in any CRS; reproducible with `seed`; can return hotspot centres
- pipeline.generate_testdata now delegates to the synthetic generator
- Tests for both features (osmnx mocked; an opt-in network test is run with
PREDSPOT_NETWORK_TESTS=1); README/CHANGELOG/CONTRIBUTING updated
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FtZdc2gGrDh4PGSLyT9yRE
- mkdocs.yml with Material theme, mkdocstrings API pages generated from the docstrings, autorefs cross-references, Mermaid, tabs and admonitions - New content: home, installation, quickstart, a user guide (how it works, data & study areas, grids & mapping, feature engineering, prediction & evaluation), API reference per module, changelog/contributing (included from the repo files) and a citing page; figures generated with the synthetic generator; every code example was executed - Docstrings converted from Sphinx roles to mkdocstrings cross-references - Docs workflow: strict build on PRs, deploy to the gh-pages branch on pushes to master (replaces the committed Sphinx HTML) - `docs` extra in pyproject; README points to the site Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01FtZdc2gGrDh4PGSLyT9yRE
- crime_mapping.get_city_shape(place_query): thin wrapper around osmnx.geocode_to_gdf returning the raw city shape (tests included) - PredictionPipeline.evaluate accepts a list of scorings and returns a DataFrame from a single time series CV pass - examples/natal.ipynb: end-to-end walkthrough on Natal with synthetic data (study area from OSM, synthetic events, grids, KDE vs QuadratCount, bandwidth comparison, features, pipeline evaluation, recursive forecasts, hotspot recovery check); examples/build_natal_notebook.py regenerates it - README reorganised: framework section summarising Chapter 3 of the thesis with Figures 7-12 (docs/assets/thesis), thesis linked in Resources, Status moved to the end - Documentation: the home page is now generated from the README (docs/hooks/readme.py) and the notebook is rendered via mkdocs-jupyter under "Examples" Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01FtZdc2gGrDh4PGSLyT9yRE
Revival 5/5: framework README, Natal example notebook and get_city_shape
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