Skip to main content

Thomas, a library for working with Bayesian Networks.

Project description

Coverage Status Build Status badge

Thomas

Very simple (almost naive ;-) bayesian network implementation.

Example (module thomas.core.examples) contains examples from the book "Probabilistic Graphical Models: Principles and Techniques" from Koller and Friedman (PGM Stanford) and from the lecture by Adnan Darwiche on YouTube:

Installation

Normal

To install from PyPI use pip:

    pip install thomas-core

Development

To do a development install:

    git clone https://github.com/mellesies/thomas-core
    cd thomas-core
    pip install -e .

Docker

A Docker image is available for easy desployment. The following command will start a JupyterLab server, listening on localhost, port 8888:

    docker run --rm -it -p 8888:8888 mellesies/thomas-core

Usage

To get started with querying a network, try the following:

from thomas.core import examples

# Load an example network
Gs = examples.get_student_network()

# This should output the prior probability of random variable 'S' (SAT score).
print(Gs.P('S'))
print()

# Expected output:
# P(S)
# S
# s0    0.725
# s1    0.275
# dtype: float64

# Query for the conditional probability of S given the student is intelligent.
print(Gs.P('S|I=i1'))

# Expected output:
# P(S)
# S
# s0    0.2
# s1    0.8
# dtype: float64

Alternatively, you can have a go at the example notebooks through Binder:

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

thomas-core-0.1.0a15.tar.gz (671.2 kB view details)

Uploaded Source

Built Distribution

thomas_core-0.1.0a15-py3-none-any.whl (74.7 kB view details)

Uploaded Python 3

File details

Details for the file thomas-core-0.1.0a15.tar.gz.

File metadata

  • Download URL: thomas-core-0.1.0a15.tar.gz
  • Upload date:
  • Size: 671.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.0.0 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.6.9

File hashes

Hashes for thomas-core-0.1.0a15.tar.gz
Algorithm Hash digest
SHA256 4bfcfbb74eba260890af1e9d2702b7ac244e7f4566a609a386e9c1e03c407e57
MD5 2ae238c18b08d390c9fd24a0d380dda7
BLAKE2b-256 404a0b1ee7c5044aaf5b17b76a3c81fc697279dcd21d844e314f46e89c8d7201

See more details on using hashes here.

File details

Details for the file thomas_core-0.1.0a15-py3-none-any.whl.

File metadata

  • Download URL: thomas_core-0.1.0a15-py3-none-any.whl
  • Upload date:
  • Size: 74.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.0.0 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.6.9

File hashes

Hashes for thomas_core-0.1.0a15-py3-none-any.whl
Algorithm Hash digest
SHA256 9053f35fde73f8da14efa828c98183b7444d5d2b3760590f679fa3dbfa81b9d5
MD5 7ae08f413f47857c1b938d0ece1d4182
BLAKE2b-256 54cc82dee0b15eade597d07732a3fff681e67d4fe543bf713e575470c7781583

See more details on using hashes here.

Supported by

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