Skip to main content

Bayesian Evolutionary Layered Learning Architectures (BELLA) companion

Project description

BELLA-Companion

⚠️🚧🚨 The documentation for this repository is still under development.

Installation

BELLA-Companion is a Python package, and can be installed via pip:

pip install bella-companion

To reproduce BEAST analyses, you will need to have BEAST2 as well as SLURM installed and properly configured on your system, as well as the following BEAST2 packages:

CLI

The CLI entrypoint is bella (see src/bella_companion/cli.py). It requires an .env file to be present in the current working directory defining the settings for the analyses to be run.

Basic usage is as follows:

bella <command> <subcommand> <...>

Where commands and subcommands are as follows:

sim
  generate            Generate synthetic simulation datasets.
  run                 Run BEAST2 analyses on simulated datasets.
  summarize           Summarize BEAST2 log outputs for simulated datasets.
  metrics             Compute and print metrics for simulated datasets.
  plot
    all               Generate plots for all simulation scenarios.
    epi-multitype     Generate plots for the epi-multitype scenario.
    epi-skyline       Generate plots for the epi-skyline scenarios.
    fbd-2traits       Generate plots for the fbd-2traits scenario.
    fbd-no-traits     Generate plots for the fbd-no-traits scenarios.
    scenarios         Generate scenario overview plots.

platyrrhine
  run                 Run BEAST2 analyses on empirical platyrrhine datasets.
  summarize           Summarize BEAST2 log outputs for empirical datasets.
  plot
    all               Generate plots for all platyrrhine datasets.
    estimates         Generate parameter estimate plots.
    trees             Generate tree-mapped parameter estimate plots.
    shap              Generate SHAP plots.

eucovid
  run                 Run BEAST2 analyses on empirical eucovid datasets.
  summarize           Summarize BEAST2 log outputs for empirical datasets.
  plot
    all                       Generate plots for all eucovid datasets.
    likelihood                Generate likelihood distribution plots.
    sankey                    Generate sankey plots.
    trees                     Generate tree plots.
    flights-and-populations   Plots for the flights and populations scenario.
    flights-over-populations  Plots for the flights over populations scenario.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bella_companion-0.1.33.tar.gz (275.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

bella_companion-0.1.33-py3-none-any.whl (309.5 kB view details)

Uploaded Python 3

File details

Details for the file bella_companion-0.1.33.tar.gz.

File metadata

  • Download URL: bella_companion-0.1.33.tar.gz
  • Upload date:
  • Size: 275.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.5

File hashes

Hashes for bella_companion-0.1.33.tar.gz
Algorithm Hash digest
SHA256 8d83395a312dc431f1762125bac01bdf8c3fc45561863084f6c76ad61d2bb7d7
MD5 77adc3cdcb0061fcd436926ae0acc145
BLAKE2b-256 345a9ea06f9b2ac0556d08b65c5b37862b8106b865c509146055d7d781097d7a

See more details on using hashes here.

File details

Details for the file bella_companion-0.1.33-py3-none-any.whl.

File metadata

File hashes

Hashes for bella_companion-0.1.33-py3-none-any.whl
Algorithm Hash digest
SHA256 41e882b319931fbceabb06a3295d35ae65f731a6aecc57ff76c73b8680defb57
MD5 f42ab30f517f206684352b47b25f72d2
BLAKE2b-256 fb24607a3c7d5242317c6af8d9d8343c927606bc912eec62fb8be7d066f1dc6a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page