Skip to main content

A program to represents a set of variables and their conditional dependencies via a directed acyclic graph.

Project description

GitHub Release GitHub Issues or Pull Requests GitHub Downloads (all assets, all releases) PyPI - Downloads

BN Modeller

An open-source application designed to facilitate feature dependency modeling and evaluation using Bayesian Networks.

User Guide

You can obtain user guides for BN Modeller application with the following link https://digiratory.github.io/bayes_model/. It covers various aspects of using BN Modeller, including data analysis workflows, best practices, and more.

Instalation

From sources

You can install this project from sources by cloning this repository and installing it using pip:

git clone https://github.com/Digiratory/bayes_model.git && cd bayes_model
pip install .

Using PyPI

You can install this project using pip:

pip install bn_modeller

Using executable file (windows only)

You can download the latest Windows executable from the BN Modeller GitHub Releases page.

Graphviz

A Graphviz error could arise. To solve the problem install and add the Graphviz executables on your systems' PATH as follows:

Windows
  1. Install windows package from: https://graphviz.org/download/ (Linux and Mac instructions can be found here as well)
  2. Install python graphviz package
  3. Press the Windows key
  4. Type in the search box: edit environment variables for your account
  5. Select Path
  6. Click Edit… button
  7. Click New
  8. Add 'bin' folder to User path in environment variables manager (e.g: C:\Program Files (x86)\Graphviz2.38\bin)
  9. Add location dot.exe to System Path (e.g: C:\Program Files (x86)\Graphviz2.38\bin\dot.exe)
  10. Click OK and OK again

Once have done that, restart your python IDE (if it is open). If this was running in a CMD prompt (e.g. Anaconda Command prompt), restart this prompt as well to make sure the prompt finds the new environment variables.

https://pygraphviz.github.io/documentation/stable/install.html

Linux
sudo apt-get update && sudo apt-get install graphviz graphviz-dev

Launch Application

To launch the application installed with pip, run:

bn_modeller

If you have downloaded BN Modeller using the Windows executable, simply double-click the bn_modeller.exe file located in the directory.

Build

Build Executable file for Windows

  1. Install pyinstaller
  2. Execute the following command:
pyinstaller bn_modeller.exe.spec

Troubleshooting

High storage utilization on Windows 10/11

This high storage utilization probably caused by WindowsSearch Engine. To mitigate the problem you should disable the indexing of content for .sqlite files as following.

  1. Press Win to open Start Menu and type in Index.
  2. Click on Indexing Options.
  3. On this next screen, hit Advanced > (Tab) File Types. For extention .sqlite select "Index Properties Only".

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

bn_modeller-1.0.0.tar.gz (96.2 kB view details)

Uploaded Source

Built Distribution

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

bn_modeller-1.0.0-py3-none-any.whl (114.3 kB view details)

Uploaded Python 3

File details

Details for the file bn_modeller-1.0.0.tar.gz.

File metadata

  • Download URL: bn_modeller-1.0.0.tar.gz
  • Upload date:
  • Size: 96.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for bn_modeller-1.0.0.tar.gz
Algorithm Hash digest
SHA256 e8f2273c6eb0dd3de4283f2bfce63b948119c15445d9b2d4e354e48eede0cdd3
MD5 cc1da8fcccd3c86b946e9b16ba305d5f
BLAKE2b-256 06e63fba8ecfbe6515800745d76ec2d12091d27d87c74cbc81d6dc5fb2804832

See more details on using hashes here.

Provenance

The following attestation bundles were made for bn_modeller-1.0.0.tar.gz:

Publisher: python-publish.yml on Digiratory/bayes_model

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file bn_modeller-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: bn_modeller-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 114.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for bn_modeller-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 6fd6bc556519dcebebe6dd87720e71b21ec53952aab36576cebff8ec40e637fe
MD5 36ea66b29aa021c3b210741da839abcf
BLAKE2b-256 52d36f98f37c9b39f2de4af807741560be573ec7f30eb7de0d6836e3c53d34ab

See more details on using hashes here.

Provenance

The following attestation bundles were made for bn_modeller-1.0.0-py3-none-any.whl:

Publisher: python-publish.yml on Digiratory/bayes_model

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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