umap-learn 0.5.3-foss-2022a

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 0.5.3-foss-2022a

To load the module for umap-learn 0.5.3-foss-2022a please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load bear-apps/2022a
module load umap-learn/0.5.3-foss-2022a

BEAR Apps Version




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.


  • pynndescent 0.5.7
  • umap-learn-0.5.3

More Information

For more information visit the umap-learn website.


This version of umap-learn has a direct dependency on: foss/2022a LLVM/12.0.1-GCCcore-11.3.0 numba/0.56.4-foss-2022a Python/3.10.4-GCCcore-11.3.0 scikit-learn/1.1.2-foss-2022a SciPy-bundle/2022.05-foss-2022a tqdm/4.64.0-GCCcore-11.3.0

Required By

This version of umap-learn is a direct dependent of: pySCENIC/0.12.1-foss-2022a scanpy/1.9.1-foss-2022a

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.

Version BEAR Apps Version
0.4.6-foss-2020b 2020b

Last modified on 27th February 2023