Skip to main content

pyjags_arviz

Makes MCMC samples from PyJAGS usable in ArviZ

Table of Contents

  1. Installation
  2. Getting Started

Installation

  1. Install via PIP:

    pip install pyjags_arviz 
    

    or

    pip3 install pyjags_arviz 
    

    if not using Anaconda.

    To get the latest version, clone the repository from github, open a terminal/command prompt, navigate to the root folder and install via

    pip install .
    

    or

    pip3 install . 
    

    if not using Anaconda.

Usage

Import the function convert_pyjags_samples_dict_to_arviz_inference_data via

from pyjags_arviz import convert_pyjags_samples_dict_to_arviz_inference_data

Having sampled the from the posterior distribution using PyJAGS via

samples \
    = jags_model.sample(...)

one can write

idata = convert_pyjags_samples_dict_to_arviz_inference_data(samples)

to convert the dictionary returned from PyJAGS to an ArviZ InferenceData object.

This object can be used in ArviZ to generate trace plots and compute diagnostics.
Trace plot:

az.plot_trace(idata);

Effective sample size:

az.ess(idata)

Gelman and Rubin statistic:

az.rhat(idata)

Autocorrelation plot:

az.plot_autocorr(idata);

Metadata

Release files for pyjags-arviz 0.0.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyjags-arviz 0.0.3
File Size Uploaded
pyjags_arviz-0.0.3.tar.gz 4.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pyjags-arviz 0.0.3
File Interpreter ABI Platform
pyjags_arviz-0.0.3-py3-none-any.whl Python 3 none any Details

Total release size: 7.3 kB

Release files / pyjags_arviz-0.0.3.tar.gz

Download URL pyjags_arviz-0.0.3.tar.gz
Size 4.2 kB
Tags Source
SHA-256 checksum
How to use checksums
dee48febfd516fb4873c3c00759add8b752c0217ce87f75e028fbb53f2c9ffa4
BLAKE2b-256 checksum
How to use checksums
ad3a3d8d8b28a040d064dbf2bcc2067eec520c6f3a7f1154db4d07d0358932c7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3.post20200330 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.1

Release files / pyjags_arviz-0.0.3-py3-none-any.whl

Download URL pyjags_arviz-0.0.3-py3-none-any.whl
Size 3.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
1949213c80cc39605e96f49693342e6020d8af0631948f8bdc42c02f0a4a30a2
BLAKE2b-256 checksum
How to use checksums
c2ce71759492de9aeb2181b2041e9a6d7fa4d9891641ae9b850281c59bbc4fc9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3.post20200330 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.1

Release history Release notifications | RSS feed

This release

0.0.3 This release

2 release files

0.0.2

2 release files

0.0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page