smoothstate
Fast, dependency-light smoothing of state probabilities for Python, built for Polars.
smoothstate provides focused smoothing primitives for model-evaluation workflows. It was created to support the smooth calibration machinery in rtichoke without requiring a general-purpose survival-modeling stack at runtime.
The package currently includes:
smooth_binary_state()for smoothing binary state probabilities over a continuous predictor.smooth_state_cox()for time-dependent smoothing with a complementary log-log transformed probability, a 3-knot restricted cubic spline, and a secondary Cox model.
The Cox implementation is continuously validated against Python lifelines and R survival::coxph(). In the current GitHub Actions benchmark it reproduces the reference curves to numerical precision while running roughly 26–39× faster than lifelines for this deliberately narrow workload.
Installation
uv add smoothstate
Until the first PyPI release is published, install directly from GitHub:
uv add git+https://github.com/uriahf/smoothstate
Documentation
See the Great Docs site for the user guide, implementation details, benchmarks, and API reference.
1 maintainer
Metadata
1 maintainer
Release files for smoothstate 0.1.1
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Source distribution (sdist)
| File | Size | Uploaded | |
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| smoothstate-0.1.1.tar.gz | 12.3 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| smoothstate-0.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.4 kB
Release files / smoothstate-0.1.1.tar.gz
| Download URL | smoothstate-0.1.1.tar.gz |
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| Size | 12.3 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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| Size | 6.1 kB |
| Tags | Python 3 |
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