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VARTOOLS

VARTOOLS is a collection of tools for analyzing astronomical photometric time series (light curves). It is written in C and runs from the command line, or via the Python package, pyvartools, processing one or many light curves through a user-defined pipeline of statistical, filtering, period-finding, and model-fitting operations. The tool is designed to enable efficient batch processing of a large collection of light curves.

Quick Start

vartools -i EXAMPLES/2 -LS 1.0 2.0 0.01 1 0 -oneline

This command reads the light curve file EXAMPLES/2, searches for periods between 1.0 and 2.0 days with a step size of 0.01, and prints a single summary line to standard output.

import pyvartools as vt

# Pass a filename directly to the command
result = vt.LS("EXAMPLES/2", 1.0, 2.0, 0.01)
print(f"Best period: {result.varobjs.LS.Period_1:.5f} d")

Every vartools command is available as vt.CMD(lc_input, ...), where lc_input can be a filename, a LightCurve object, a pandas DataFrame, a 2-D numpy array, or a (t, mag, err) tuple. For chaining multiple commands use lc.LS(...).rms() — see the Python API docs.

Download

Current release: vartools 1.6

Format Link
Source tarball vartools-1.6.tar.gz
GitHub github.com/joeldhartman/vartools

See the Installation page for build instructions, optional dependencies, and platform-specific notes.

Citation

If you use VARTOOLS in published research, please cite:

Hartman, J. D. & Bakos, G. Á. 2016, Astronomy and Computing, 17, 1

@article{Hartman2016,
  author  = {Hartman, Joel D. and Bakos, G{\'a}sp{\'a}r {\'A}.},
  title   = {{VARTOOLS}: A program for characterizing and searching for variable stars},
  journal = {Astronomy and Computing},
  year    = {2016},
  volume  = {17},
  pages   = {1},
  doi     = {10.1016/j.ascom.2016.05.006}
}

AI Usage

This website and recent versions of VARTOOLS (1.6+) have been developed with the assistance of Claude Code using the Claude Opus 4.7 (1M context) model. The file python/llms.txt (a plain-text API overview) included in the distribution can be used to provide context to an LLM to understand the usage of this package.

Contact

Questions, bug reports, and feature requests are welcome.

Joel D. Hartman — jhartman AT astro DOT princeton DOT edu