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Lazy.jl ​

Fast, scalable photometric redshift fitting in Julia

Lazy.jl is a multithreaded photometric redshift fitting package designed for modern astronomical surveys. Built from the ground up in Julia, it provides memory-efficient and multithreaded processing of large catalogs using NNLS template fitting of SED models with IGM attenuation.

Why Lazy.jl? ​

Lazy.jl is a Julia reimplementation of eazy-py focused on performance and ease of use.

  • Fast: Native multithreading scales near-linearly across cores, with shared memory instead of the per-process overhead of Python multiprocessing.

  • Scalable: Chunked processing fits arbitrarily large catalogs within a fixed memory budget, with automatic resume for interrupted jobs.

  • Simple: A single CLI (lazy fit -p params.toml) with human-readable TOML configuration, easy to integrate into existing pipelines.

Quick Start ​

bash
# Install
git clone https://github.com/hollisakins/Lazy.jl.git
cd Lazy.jl && bash install.sh

# Generate a parameter file and run
lazy params > my_params.toml
# Edit my_params.toml to point to your catalog...
lazy fit -p my_params.toml

See Installation for detailed setup instructions and Getting Started for a step-by-step tutorial.