exchangealgebra
exchangealgebra is a Haskell library for Exchange Algebra,
an algebraic description of bookkeeping systems developed by Hiroshi Deguchi. It treats bookkeeping entries
as elements of a scaled basis algebra, so journaling, closing, transfer, and simulation can be written as
function composition and projection.
The library is used in the preprint
Accounting State Space as the Minimal Unit for Economic Agent-Based Modeling
(Akagi, 2026) as the minimal unit for economic agent-based simulation and
ripple-effect analysis. See the Publications section for citation details.
Installation
The package is on Hackage. Pin a specific version in your Stack project:
# stack.yaml
extra-deps:
- exchangealgebra-0.4.0.0
# package.yaml (your project)
dependencies:
- exchangealgebra
If you need an unreleased revision, you can also point extra-deps at a
specific Git commit instead:
extra-deps:
- git: https://github.com/yakagika/ExchangeAlgebra.git
commit: <commit-sha>
Requirements:
- GHC 9.10 (tested with Stackage
lts-24.4)
- Cabal 3.0 or later
Chart / Chart-cairo transitively require the Cairo / Pango / Freetype system libraries
(on macOS: brew install cairo pango)
How to consume this package
Three common use cases:
1. Use it as a library dependency
Add exchangealgebra to your project's build-depends via the Hackage
extra-deps pin above (or the Git pin for unreleased revisions). The
examples/ directory is not needed for this; it is only shipped in
this Git repository.
2. Run the bundled examples
Clone the repository and build from the root:
git clone https://github.com/yakagika/ExchangeAlgebra.git
cd ExchangeAlgebra
stack build
stack exec -- sim1 # or ebex1, ripple, cge, ...
See the examples directory
for the full catalogue and runtime prerequisites (uv for Python plots,
output directories, etc.).
3. Copy or fork a single example
If you want to start from one example without pulling the whole repository,
degit (or its maintained successor tiged)
lets you grab just the subtree without git history:
npx degit yakagika/ExchangeAlgebra/examples my-examples
cd my-examples
# then edit freely as a starting point
A Git sparse-checkout with a standalone examples/stack.yaml is planned so that
cd examples && stack build works after a sparse-clone; this will land together
with the first Hackage release.
Module Overview
The public modules are organised into two parallel layers.
Foundation layer (Algebra)
| Module |
Role |
ExchangeAlgebra.Algebra |
Core algebra: the Alg type, HatVal / BaseClass, addition .+ / hat .^ / bar .- / projection proj |
ExchangeAlgebra.Algebra.Base |
Basis classes (BaseClass, HatBaseClass, ExBaseClass) and basis display helpers |
ExchangeAlgebra.Algebra.Base.Element |
The Element type class (wildcard-aware basis components) |
ExchangeAlgebra.Algebra.Transfer |
Transfer rewriting (TransTable, (.->), transfer, finalStockTransfer) |
| Module |
Role |
ExchangeAlgebra.Journal |
Journal n v b (journal entries carrying a Note), sigmaOn, filterByAxis, projWithNote, … |
ExchangeAlgebra.Journal.Transfer |
Transfer API specialised for Journal (thin wrappers over Algebra.Transfer) |
Simulation / IO layer
| Module |
Role |
ExchangeAlgebra.Simulate |
StateSpace, Updatable, runSimulation, spill-to-disk, ripple-effect utilities (rippleEffect, leontiefInverse) |
ExchangeAlgebra.Simulate.Visualize |
Chart/Cairo based PNG rendering (see the caveats below) |
ExchangeAlgebra.Write |
CSV output (writeBS, writePL, writeIOMatrix, writeCSV) and binary-spill restore helpers |
Umbrella entry modules
| Module |
Content |
ExchangeAlgebra (top level) |
Umbrella for the Algebra layer: re-exports Algebra, Algebra.Transfer, Write, and Simulate |
ExchangeAlgebra.Journal |
Umbrella for the Journal layer. Re-exports Algebra.Base, so user-defined Element instances are available through this import as well |
Importing both ExchangeAlgebra and ExchangeAlgebra.Journal unqualified causes name
collisions on sigma, fromList, map, filter, and friends. See the recommended import
patterns below.
Recommended import patterns
Simple single-period bookkeeping
import ExchangeAlgebra -- Algebra-layer umbrella
main = do
let e = 100 :@ Hat :< Cash .+ 100 :@ Not :< Sales
putStr (showBS e)
Journal-based work (multi-period, notes, simulation)
import ExchangeAlgebra.Journal -- pulls in the type classes and the Journal API
import qualified ExchangeAlgebra.Algebra as EA
import qualified ExchangeAlgebra.Journal as EJ
import qualified ExchangeAlgebra.Journal.Transfer as EJT
import qualified ExchangeAlgebra.Simulate as ES
import ExchangeAlgebra.Simulate -- unqualified, for StateSpace, Updatable, etc.
import ExchangeAlgebra.Write -- writeBS / writeIOMatrix and friends
Even in Journal-centric code you will frequently reach into the Algebra layer (for the Alg
type or EA.proj, for example). Using Journal as the unqualified umbrella and pulling the
Algebra layer in as EA qualified is the idiomatic style for this library.
A note on visualization
ExchangeAlgebra.Simulate.Visualize provides Chart-based PNG rendering, but we recommend
writing CSV output and visualising it from a separate Python script for production-quality
plotting.
Why
- Chart / Chart-cairo transitively pull in cairo / pango / freetype system libraries, which
makes the build environment heavier to set up.
- For academic work, matplotlib / seaborn / pandas are more flexible than Chart.
- Using CSV as an intermediate format cleanly separates "compute" from "plot".
- The same CSVs can be reused with R / Julia / Excel if you need them.
Recommended workflow
-- Haskell side: write the simulation outputs to CSV
import ExchangeAlgebra.Write (writeIOMatrix)
import qualified ExchangeAlgebra.Simulate.Visualize as ESV
-- qualified access to writeFuncResults etc.
main = do
-- ... run the simulation ...
writeIOMatrix "result/io.csv" matrix
ESV.writeFuncResults header range world "result/profit.csv"
# Plotting side: run a standalone script with uv + PEP 723 inline deps
uv run --script visualize.py
# visualize.py
# /// script
# requires-python = ">=3.10"
# dependencies = ["pandas>=2.0", "matplotlib>=3.7"]
# ///
import pandas as pd, matplotlib.pyplot as plt
df = pd.read_csv("result/profit.csv")
df.plot(); plt.savefig("result/profit.png")
Concrete runnable examples of this pattern live under the examples/ sub-package
(see the examples directory on GitHub).
If you still want to plot from Haskell
If keeping everything in Haskell is important to your workflow, plotLineVector,
plotMultiLines, and plotWldsDiffLine in ExchangeAlgebra.Simulate.Visualize write PNGs
directly and work without any Python setup.
Examples
Runnable usage examples are collected in the examples/ sub-package on GitHub.
See the examples directory
and its README for details.
stack build
stack exec -- ebex1 # Introductory bookkeeping example
stack exec -- sim1 # 100-term simulation (+ Python visualization)
stack exec -- ripple # 10-agent ripple-effect simulation
stack exec -- cge # CGE model
Documentation
License
Dual licensed under MIT and the Open World License (OWL). See LICENSE for details.
Publications using this library
-
Kaya Akagi.
Accounting State Space as the Minimal Unit for Economic Agent-Based
Modeling: Advancing Ripple Effect Analysis in Real-Time Economy.
Research Square, preprint (Version 1), posted 5 January 2026.
DOI: 10.21203/rs.3.rs-8485050/v1
The ripple-effect simulations reported in this preprint are driven by
ExchangeAlgebra.Simulate and the ripple example family under
examples/deterministic/ripple/.
If you use this library in academic work, please cite the preprint above.
A CITATION.cff file at the repository root provides BibTeX and
plain-text forms via GitHub's "Cite this repository" button.
References