umap-learn 0.5.5-foss-2023a

Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction.

Accessing umap-learn 0.5.5-foss-2023a

To load the module for umap-learn 0.5.5-foss-2023a please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load bear-apps/2023a
module load umap-learn/0.5.5-foss-2023a

BEAR Apps Version

2023a

Architectures

EL8-icelake

The listed architectures consist of two parts: 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

• pynndescent 0.5.11
• umap-learn-0.5.5

More Information

For more information visit the umap-learn website.

Dependencies

This version of umap-learn has a direct dependency on: foss/2023a LLVM/16.0.6-GCCcore-12.3.0 numba/0.58.1-foss-2023a Python/3.11.3-GCCcore-12.3.0 scikit-learn/1.3.1-gfbf-2023a SciPy-bundle/2023.07-gfbf-2023a tqdm/4.66.1-GCCcore-12.3.0

Required By

This version of umap-learn is a direct dependent of: DynaMight/0.0.0.20240319.eef4aa6-foss-2023a-CUDA-12.1.1

Other Versions

These versions of umap-learn are available on the BEAR systems (BlueBEAR and BEAR Cloud VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Last modified on 3rd March 2025