https://pypi.org/project/ts-pca/ Recent updates to the Python Package Index for TS-PCA en https://pypi.org/project/ts-pca/0.0.12/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Fri, 20 Feb 2026 11:08:58 GMT https://pypi.org/project/ts-pca/0.0.11/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Fri, 20 Feb 2026 11:05:09 GMT https://pypi.org/project/ts-pca/0.0.10/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Fri, 20 Feb 2026 10:58:39 GMT https://pypi.org/project/ts-pca/0.0.9/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Fri, 20 Feb 2026 10:49:11 GMT https://pypi.org/project/ts-pca/0.0.8/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Fri, 20 Feb 2026 10:38:10 GMT https://pypi.org/project/ts-pca/0.0.7/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Fri, 20 Feb 2026 10:25:30 GMT https://pypi.org/project/ts-pca/0.0.6/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Fri, 20 Feb 2026 10:11:35 GMT https://pypi.org/project/ts-pca/0.0.5/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Tue, 10 Feb 2026 10:19:28 GMT https://pypi.org/project/ts-pca/0.0.4/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Tue, 10 Feb 2026 10:12:58 GMT https://pypi.org/project/ts-pca/0.0.3/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Fri, 06 Feb 2026 19:18:14 GMT https://pypi.org/project/ts-pca/0.0.2/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Wed, 07 Jan 2026 13:47:54 GMT https://pypi.org/project/ts-pca/0.0.1/ A package for unsupervised representation and principal component analysis of irregularly sampled time series with variable size relying on the shape analysis literature. samuel.gruffaz@ens-paris-saclay.fr, thibaut.germain@ens-paris-saclay.fr Wed, 07 Jan 2026 13:00:39 GMT