hssm 0.2.2-foss-2023a

HSSM - Hierarchical Sequential Sampling Modeling is a Python toolbox that provides a seamless combination of state-of-the-art likelihood approximation methods with the wider ecosystem of probabilistic programming languages.

Accessing hssm 0.2.2-foss-2023a

To load the module for hssm 0.2.2-foss-2023a please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load bear-apps/2023a
module load hssm/0.2.2-foss-2023a

BEAR Apps Version

2023a

Architectures

EL8-cascadelake — EL8-icelake — EL8-sapphirerapids

The listed architectures consist of two part: OS-CPU. The OS used is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.

Extensions

• arviz 0.18.0
• bambi 0.13.0
• cachetools 5.1.0
• dm-tree-0.1.8
• fastprogress 1.0.3
• formulae 0.5.0
• graphviz 0.20.1
• hddm_wfpt 0.1.4
• hssm 0.2.2
• huggingface_hub 0.23.0
• multipledispatch 1.0.0
• numpyro 0.15.0
• onnx 1.16.0
• pymc 5.14.0
• pytensor 2.20.0
• rich 13.7.1
• ssm_simulators 0.7.2

More Information

For more information visit the hssm website.

Dependencies

This version of hssm has a direct dependency on: ArviZ/0.16.1-foss-2023a foss/2023a Graphviz/8.1.0-GCCcore-12.3.0 jax/0.4.25-gfbf-2023a ONNX/1.15.0-gfbf-2023a poetry/1.5.1-GCCcore-12.3.0 PyTensor/2.17.1-gfbf-2023a Python/3.11.3-GCCcore-12.3.0 PyYAML/6.0-GCCcore-12.3.0 scikit-learn/1.3.1-gfbf-2023a Seaborn/0.13.2-gfbf-2023a tqdm/4.66.1-GCCcore-12.3.0

Last modified on 14th August 2024