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VCAT — VLBI Comprehensive Analysis Toolkit

VCAT (VLBI Comprehensive Analysis Toolkit) is a Python package that provides a unified framework for the analysis of Very Long Baseline Interferometry (VLBI) data. It was developed in collaboration with several colleagues from the VLBI community (A. Baczko, V. Bartolini, F. Eppel, F. Pötzl, L. Ricci, J. Röder, F. Rösch) to combine existing analysis scripts into a single, coherent package that supports a wide range of VLBI analysis methods.

Many of the implemented analysis techniques have been used for a long time, while others were specifically developed for recent scientific projects. VCAT is still evolving — we’d love your help! Contributions, feedback, and ideas are always welcome. All included methods are applicable to any source with standard VLBI data available in .fits, .uvf format.


Installation

The package can be installed directly from PyPI:

pip install vcat-vlbi

Important Note

Many tasks run DIFMAP in the background.
If DIFMAP is already in your PATH, VCAT will automatically find it.
If you don't have DIFMAP yet, see here for a quick installation instruction for Ubuntu-based systems. It is also possible to use many functions without DIFMAP by specifying use_difmap=False, but this mode is not yet fully supported and may have limited functionality.


Documentation

Please find the online documentation of VCAT at this link: https://mpifr-vlbi.github.io/VCAT/


Overview

VCAT consists of the two core classes: ImageData and ImageCube.

ImageData

ImageData represents a single observation of a radio source at a given frequency and epoch.
It accepts as input:

  • FITS files (full polarization images)
  • UVFITS (.uvf) visibility data
  • Modelfit files (.mod or .fits)

For example, loading and plotting an image can quickly be done with

from vcat import ImageData

image=ImageData("image.fits", uvf_file="data.uvf", model="model.mod")
image.plot()

Upon loading, key parameters such as image noise, integrated flux density, and fractional polarization are automatically calculated and stored as attributes.
If a modelfit file is provided, VCAT also calculates the signal-to-noise ratio (SNR), brightness temperature, and component errors automatically.

ImageData objects can be modified or analyzed using various tasks:

  • restore(), regrid(), shift(), center() – runs DIFMAP in the background to modify full-polarization images
  • get_ridgeline() – perform a ridgeline fit
  • align() – align one image to another
  • plot() – generate customizable plots of total intensity or polarization

ImageCube

ImageCube is designed to handle multi-frequency, multi-epoch data sets.
It manages a collection of ImageData objects representing different observations of the same source and provides high-level analysis methods, including:

  • Spectral analysis

    • get_turnover_map() — pixel-based turnover frequency fitting
    • fit_comp_spectrum() — component-based spectral fitting
  • Kinematic analysis

    • get_speed() and get_speed2d() — estimate apparent jet speeds and perform kinematic analysis
  • Structural analysis

    • stack() — stack multiple images
    • fit_collimation_profile() — fit collimation profiles (ridgeline or component-based)
  • Spectral & polarization mapping

    • get_spectral_index_map() and get_rm_map() — compute spectral index and rotation measure maps
  • Temporal evolution & visualization

    • plot_evolution() and plot_component_evolution() — track flux density, polarization, and EVPA evolution
    • movie() — generate interpolated movies of jet evolution in total intensity or full polarization

Configuration

Usually, the standard settings are sufficient, but some parameters can be customized via a config.yml file.
An example configuration file is provided in the repository.

To use a custom configuration file, define the environment variable VCAT_CONFIG to point to it:

export VCAT_CONFIG=/path/to/config.yml

Example config.yml

# General settings:
difmap_path: "/usr/local/difmap/uvf_difmap_2.5g/"
uvw: [0, -1]

# Method selection
noise_method: "Histogram Fit"
mfit_err_method: "Schinzel12"
res_lim_method: "Kovalev05"

# Plot settings
font: "Quicksand"
plot_colors: ["#023743FF", "#FED789FF", "#72874EFF", "#476F84FF", "#A4BED5FF", "#453947FF"]
plot_markers: [".", ".", ".", ".", ".", "."]

# Cosmology
# Values from Planck Collaboration et al. 2020
H0: 67.4
Om0: 0.315

logging:
  level: "INFO"       # Options: DEBUG, INFO, WARNING, ERROR, CRITICAL
  log_file: ""         # Optional: specify path to redirect log output to a file

Example Scripts

Example scripts demonstrating the different functionalities of VCAT are available on the [VCAT website](INSERT LINK).
These examples showcase how to load data, perform analysis, and generate publication-quality plots.


Citation

If you use VCAT in your research, please cite the Zenodo release( DOI: 10.5281/zenodo.17404907) image


License

VCAT is released under the GNU General Public License v3.0 (GPL-3.0).
You are free to use, modify, and distribute this software under the terms of the GPL-3.0 license.
For more details, see the LICENSE file included with this repository.


VCAT – VLBI Comprehensive Analysis Toolkit
A unified framework for the analysis and visualization of VLBI data.

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VLBI Comprehensive Analysis Toolkit to analyze, modify and plot VLBI images

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