achael/eht-imaging

Health v2 · maintenance only

Adoption not part of the score

5313 stars · 503 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

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

library · maturity active

simulation data-visualization image-processing math astronomy data-science python radio-interferometry vlbi black-hole-imaging scientific-computing regularized-maximum-likelihood algorithms linux macos

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