There is a newer version of umap-learnUniform 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 0.4.6-foss-2020b
To load the module for umap-learn 0.4.6-foss-2020b please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):
module load umap-learn/0.4.6-foss-2020b
There is a GPU enabled version of this module: umap-learn 0.4.6-fosscuda-2020b
BEAR Apps Version
The listed architectures consist of two part: OS-CPU.
- BlueBEAR: The OS used on BlueBEAR 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.
- BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.
For more information visit the umap-learn website.
This version of umap-learn has a direct dependency on: foss/2020b numba/0.52.0-foss-2020b Python/3.8.6-GCCcore-10.2.0 scikit-learn/0.23.2-foss-2020b SciPy-bundle/2020.11-foss-2020b
This version of umap-learn is a direct dependent of: cell2location/0.05-alpha-foss-2020b
These versions of umap-learn are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.
|Version||BEAR Apps Version|
Last modified on 21st May 2021