There is a newer version of peptA Python library that integrates all the tools necessary to perform research using Positron Emission Particle Tracking (PEPT). The library includes algorithms for the location, identification and tracking of particles, in addition to tools for visualisation and analysis, and utilities allowing the realistic simulation of PEPT data.
Accessing pept 0.1.6-foss-2019b-Python-3.7.4
To load the module for pept 0.1.6-foss-2019b-Python-3.7.4 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):
module load pept/0.1.6-foss-2019b-Python-3.7.4
BEAR Apps Version
EL8-cascadelake — EL8-haswell — Ubuntu20.04-haswell
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.
- hdbscan 0.8.24
- pept 0.1.6
- plotly 4.5.3
- retrying 1.3.3
For more information visit the pept website.
This version of pept has a direct dependency on: foss/2019b matplotlib/3.1.1-foss-2019b-Python-3.7.4 Python/3.7.4-GCCcore-8.3.0 scikit-learn/0.21.3-foss-2019b-Python-3.7.4 SciPy-bundle/2019.10-foss-2019b-Python-3.7.4 tqdm/4.41.1-GCCcore-8.3.0
These versions of pept 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.
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Last modified on 10th March 2020