# achael/eht-imaging

Imaging, analysis, and simulation software for radio interferometry

Repository: https://github.com/achael/eht-imaging
Canonical: https://ross.abutalabs.com/products/eht-imaging
Homepage: https://achael.github.io/eht-imaging/
Language: Python
License: GPL-3.0
License Family: copyleft
Last push: 2026-08-20T18:29:28+00:00

## Health v2 (maintenance only)
Score: 95/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 89, longevity 100
- inputs: {"age_days": 3998, "days_push": 13, "days_rel": 78, "gap_med": 27, "n_releases_24m": 6}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5313, forks 503 (observed 2026-08-28T04:09:15.487343+00:00)

## What it is
eht-imaging (ehtim) is a Python library for simulating, calibrating, and manipulating very long baseline interferometry (VLBI) data and reconstructing images using regularized maximum likelihood methods. It was developed for Event Horizon Telescope analysis and provides classes for images, movies, arrays, observation data, calibration tables, and imaging.

## Use cases
- reconstruct images from radio interferometry data
- simulate VLBI observations from an image
- calibrate and plot interferometric visibility data
- produce polarimetric images with regularized maximum likelihood
- generate time-variable movie simulations with real u-v tracks
- analyze Event Horizon Telescope data

## When to choose
- you work with VLBI or radio interferometric data in Python
- you need RML-based image reconstruction for sparse interferometric arrays
- you want to simulate observations with realistic u-v coverage
- you are doing EHT-style black hole imaging research

## When to avoid
- you need a general-purpose radio astronomy pipeline like CASA
- you require fast Fourier transforms on Python >3.11 with the stable release (pyNFFT limitation)
- you need a GUI-based imaging tool
- your data is not interferometric in nature

## Facets
- artifact type: library
- maturity: active
- function: simulation, data-visualization, image-processing, math
- domain: astronomy, data-science
- platform: python
- tags: radio-interferometry, vlbi, black-hole-imaging, scientific-computing, regularized-maximum-likelihood, algorithms, linux, macos

## Member repositories
- achael/eht-imaging (main) score 95

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:15.487343+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:58:58.043513+00:00, confidence not recorded.
  - readme: https://github.com/achael/eht-imaging (fetched 2026-08-28T04:09:15.487343+00:00, sha e094383172cc)
  - homepage: https://achael.github.io/eht-imaging/ (fetched 2026-08-29T08:53:40.209719+00:00, sha b2a23fc34592)
- Data as of 2026-08-30T08:39:29.467469+00:00.