Skip to main content

Tools for the statistical analysis and treatment of macroeconomic simulation models, with a focus on Agent-based and Stock-Flow Consistent Models

Project description

Build Status PyPI-Server Documentation Status Coveralls Project generated with PyScaffold

MacroStat

A Package providing multiple tools for the statistical analysis and treatment of macroeconomic simulation models, with a particular focus on Agent-based and Stock-Flow Consistent Models

The purpose of this project is to provide a statistical toolbox for the analysis of Agent-based Models. The toolbox is developed in python and aims to provide a simple interface for researchers to attach their model, such that simulations can be steered from within the toolbox and the relevant analysis can be run (such as sensitivities, confidence intervals, and simulation studies). Only the analysis itself requires python, while the models can be written in any language.

The code was developed using Python 3.10. Backwards compatibility is not guaranteed

Installation

This project requires Python v3.10 or later.

To install the latest version of the package from PyPI:

pip install macrostat

Or, directly from GitHub:

pip install git+https://github.com/KarlNaumann/MacroStat.git#egg=macrostat

Continuous Integration

MacroStat runs on GitHub Actions across Linux (ubuntu-latest) and Windows (windows-latest) for Python 3.11, 3.12, and 3.13. The full test suite including slow-marked tests runs nightly on master. macOS is not currently covered; it is tracked as a follow-up before the planned JOSS submission.

Development Installation

For development, install the package in editable mode. This project uses uv for dependency management:

uv sync                    # Install all dependencies
uv pip install -e .        # Install package in editable mode

After this, you can run tests with:

uv run pytest

If you’d like to contribute to the package, please read the CONTRIBUTING.md guide.

Making Changes & Contributing

This project uses pre-commit, please make sure to install it before making any changes:

pip install pre-commit
cd MacroStat
pre-commit install

It is a good idea to update the hooks to the latest version:

pre-commit autoupdate

Don’t forget to tell your contributors to also install and use pre-commit.

Contact

Karl Naumann-Woleske - karlnaumann.com

Project Link: [https://github.com/KarlNaumann/MacroStat](https://github.com/KarlNaumann/MacroStat)

Note

This project has been set up using PyScaffold 4.5. For details and usage information on PyScaffold see https://pyscaffold.org/.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

macrostat-0.6.0.tar.gz (5.5 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

macrostat-0.6.0-py3-none-any.whl (246.2 kB view details)

Uploaded Python 3

File details

Details for the file macrostat-0.6.0.tar.gz.

File metadata

  • Download URL: macrostat-0.6.0.tar.gz
  • Upload date:
  • Size: 5.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for macrostat-0.6.0.tar.gz
Algorithm Hash digest
SHA256 34822ee086e5fb1df35ed8cc9d188351c0f0a22a143e9fd32b77ed2de77f4340
MD5 7d66aae53f6c5c6247188c450ec11fc6
BLAKE2b-256 b0f81e299f46c1858fe2f66fc20970f2e164166cbfae472ada419dbc89861053

See more details on using hashes here.

File details

Details for the file macrostat-0.6.0-py3-none-any.whl.

File metadata

  • Download URL: macrostat-0.6.0-py3-none-any.whl
  • Upload date:
  • Size: 246.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for macrostat-0.6.0-py3-none-any.whl
Algorithm Hash digest
SHA256 922da689e39e773892bf7afdbdd6c9cbf45be54b3b5fdc4c27a2500bd86b597a
MD5 800d1c7999d44597962204816fbf7466
BLAKE2b-256 54992059db40b2fa459722a12c66085939006895c5b84b500090e6648616ff9c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page