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TS-PCA

A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature.

Installation

In a virtualenv (see these instructions if you need to create one):

pip3 install ts-pca

Dependencies

• scikit-learn
• pandas
• jax
• scipy
• numpy
• matplotlib
• optax

Releases

Version	Released	Bullseye Python 3.9	Bookworm Python 3.11	Trixie Python 3.13	Files
0.0.12	2026-02-20
ts_pca-0.0.12-py3-none-any.whl (30 KB)
0.0.11	2026-02-20
ts_pca-0.0.11-py3-none-any.whl (30 KB)
0.0.10	2026-02-20
ts_pca-0.0.10-py3-none-any.whl (30 KB)
0.0.9	2026-02-20
ts_pca-0.0.9-py3-none-any.whl (30 KB)
0.0.8	2026-02-20
ts_pca-0.0.8-py3-none-any.whl (30 KB)
0.0.7	2026-02-20
ts_pca-0.0.7-py3-none-any.whl (30 KB)
0.0.6	2026-02-20
ts_pca-0.0.6-py3-none-any.whl (30 KB)
0.0.5	2026-02-10
ts_pca-0.0.5-py3-none-any.whl (29 KB)
0.0.4	2026-02-10
ts_pca-0.0.4-py3-none-any.whl (29 KB)
0.0.3	2026-02-06
ts_pca-0.0.3-py3-none-any.whl (29 KB)
0.0.2	2026-01-07
ts_pca-0.0.2-py3-none-any.whl (24 KB)
0.0.1	2026-01-07
ts_pca-0.0.1-py3-none-any.whl (24 KB)

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