Skip to main content

A fast elliptical accretion disk modeling engine built on JAX and NumPyro.

feadme implements the elliptical accretion disk model described in Eracleous et al. (1995) and fits it to double-peaked emission line profiles via Bayesian inference.

Features

  • Fast: JAX-accelerated disk integration with JIT compilation and GPU support.
  • Bayesian: NUTS-based posterior sampling via NumPyro with full uncertainty quantification.
  • Flexible: JSON-driven model templates supporting multiple disk and line components with shared parameters.
  • Robust initialization: SVI, Pathfinder, MAP, AutoDelta-style MAP, and JAX-LSQ initializers for difficult multimodal line-profile fits.

Installation

pip install feadme         # CPU
pip install feadme[gpu]    # GPU (CUDA 12)

From source with uv:

git clone https://github.com/nmearl/feadme.git
cd feadme
uv sync --group dev

From source without uv:

git clone https://github.com/nmearl/feadme.git
cd feadme
pip install -e ".[dev]"

Quickstart

feadme run \
  --template-path my_template.json \
  --data-path my_data.csv \
  --output-path results \
  --init-method jax-lsq \
  --integrator mixed

See the documentation for the full CLI reference, data format, and template specification.

Contributing

Bug reports, feature requests, and pull requests are welcome on the GitHub repository.

Download files

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

Source Distribution

feadme-0.2.1.tar.gz (58.8 kB view details)

Uploaded Source

Built Distribution

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

feadme-0.2.1-py3-none-any.whl (71.6 kB view details)

Uploaded Python 3

File details

Details for the file feadme-0.2.1.tar.gz.

File metadata

  • Download URL: feadme-0.2.1.tar.gz
  • Upload date:
  • Size: 58.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.14

File hashes

Hashes for feadme-0.2.1.tar.gz
Algorithm Hash digest
SHA256 58a26759f587a1e0f14435ad95f972493936a03942d465101bc913d722b0fe54
MD5 3bcdc268129eacc6a95134a8fbfb537c
BLAKE2b-256 9745dac802d07042ba62f6ce7ae03a033c91f74ec8606bc7ec4a8b56ba83200d

See more details on using hashes here.

File details

Details for the file feadme-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: feadme-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 71.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.14

File hashes

Hashes for feadme-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 10e0cb165fe51a3d2387f6914bd411bb7a00b6ccdc7b6bbde9780d57a9aedaa7
MD5 794ca835b0bdd3f5927cf17f3522699d
BLAKE2b-256 937044c7391a2809d141909536c13d234ccd12560276c93ee410d6f0a3e28b0b

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

0.2.1 This release

2 files

0.2.0

2 files

0.1.4

2 files

0.1.3

2 files

0.1.2

2 files

Supported by

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