Atlas Format

Atlas files contain a collection of map assignments or redistrictings. The format is a specialization of the JSONL format. Each line in an Atlas file is a JSON object. The first three lines describe the particular Atlas. Starting with the fourth line, each line is a JSON object that describes a map assignment. In addition to the map assignment, each line can also contain statistics and other information about the map assignment. These can be specified by the user.

AtlasIO code

The primary code is written in the Julia programming language, but it can be used in Python as well. The Julia AtlasIO library is an official Julia package and can be loaded using the Julia Package Manager.

The Python libraries, as well as the Julia source code, can be found in the AtlasIO Git repository. This repository contains a number of tools to read in and manipulate Atlas files. The Python library can only read Atlas files, it cannot write them. The Julia library can read and write Atlas files.

The Atlas File Format

The Atlas format is a JSONL (JSON Lines) format adapted to hold district maps from redistricting efforts. The Atlas format is a simple extension of the JSONL format that allows for the storage of maps and their associated data in a single file. The AtlasIO.jl Julia library provides the ability to read and write Atlas files. The AtlasIO.py Python library, from the same git repository, provides the ability to read but not the ability to write files. This format was developed by the Duke Quantifying Gerrymandering Group.

Structure of an Atlas File

Each individual line of an Atlas file is JSON object. As such they can be read line by line unlike a single JSON.

• This first line is a comment that identifies the file as an Atlas of maps and describes the Atlas format.
• The second line is a JSON object that describes the basic information of the collection of maps saved in this Atlas.
• The third line is a JSON object that describes the extra data assigned to each map. It can be adapted to the particular setting. In particular, it gives that data times and key names associated to the additional data.
• Each of the following lines, starting with the 4th line, is a JSON object that describes a map and its associated data.

Example Atlas file

This is a simple example of Atlas file. It is for splitting a 4x4 rectangular grid into two districts. It was generated using the cycle walk algorithm. The file can be down loaded here cycleWalk_grid4x4__gamma0.0_kappa0.1.jsonl.

"This is an Atlas for Redistricting Maps. See 'https://git.math.duke.edu/gitlab/jonm/atlasio.jl' for more information."
{"description":"","date":"2025-09-07T15:39:21.934","atlasParamType":"Dict{String, Any}","mapParamType":"Dict{String, Any}"}
{"energy weights":[],"population bounds":[8,8],"energies":[],"package.version":"CycleWalk v0.1.3","districts":2,"popdev":0.05}
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File Extension and Compression

Atlas files use the file extension .jsonl if the file in Atlas is plain, uncompressed text. If the Atlas is compressed it will either use the file extension .jsonl.gz or .jsonl.bz2.

The .gz extension signifies the use of the standard Gnu Zip tools (gzip, gunzip, zcat) and can be read by a number of libraries and command line tools. These tools use the standard Deflate algorithm to compress data.

The .bz2 extension signifies the use of the standard BZip2 tools (bzip2, bzcat) and also can be read by a number of libraries and command line tools. These tools use the standard Burrows–Wheeler algorithm to compress data.

The Bzip2 compression format typically results in a smaller file than the Gzip compression format. However, the Bzip2 compression is slower to compress and uncompress. We also explored saving files by saving the incremental changes in the maps. However, it was decided that the advantage of using standard compression tools was significant in light of the very high compression ratios they delivered out of the box.

Work Directly with Compressed Files

One nice feature of the AtlasIO libraries, both in Julia and Python, is that they can read and write compressed files directly. This both increase the speed of writing and decreases the size of the Atlas files significantly.

Corrupted Compressed Files

One downside of directly writing compressed files is that the files can not be directly examined during the run and might be left in a corrupted state if the run is interrupted. A corrupted file can typically easily be largely recovered using

zcat atlas-corrupted.jsonl.gz > atlas-fixed.jsonl

You can also use the zcat command to examine a file during a run.