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sillywalk

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Library for maximum likelihood principal component analysis for AnyBody models

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::sillywalk

Usage Tracking

1.1.1
1.1.0
1.0.2
1.0.1
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Downloads (Last 6 months): 0

Description

sillywalk is a Python library for statistical modeling of human motion and anthropometric data with the AnyBody Modeling System. It implements Maximum Likelihood Principal Component Analysis (ML‑PCA) to learn compact, low‑dimensional models from datasets, predict missing or individualized signals from partial inputs, and export those predictions as AnyScript include files that plug directly into AnyBody models.

About

Summary

Library for maximum likelihood principal component analysis for AnyBody models

Last Updated

Dec 28, 2025 at 22:33

License

MIT

Total Downloads

170

Supported Platforms

noarch