ProdNet 0.0.2

A collection of models of economic Production Networks and their associated measures and functions.

ProdNet

ProdNet is a collection of models of economic Production Networks and their associated measures and functions. It can be used to perform and compare economic shock propagation simulations.

It is currently in development and functions may be broken, change, or be deleted. Before use contact the authors.

• Free software: GNU General Public License v3

Installation

Install using:

pip install ProdNet

Usage

Currently only the Per Bak models are fully implemented. An example of how it can be used is the following. For more see the example notebooks in the examples folder.

import numpy as np
import matplotlib.pyplot as plt
from ProdNet import PerBak
from ProdNet.lib import icdf
import time

# Select economy depth and width, and total number of iterations
L = 1600
T = 1000

# Time performance for reference
start = time.time()

# Initialize simulation object
model = PerBak(L, T)

# Compute p, probability of demand "shock"
model.set_final_demand()

# Simulate
model.simulate()

# Print elapsed time
print(time.time() - start)  # current best=37s

# Plot Y distribution
Y = np.sum(model.P, axis=(1, 2))
x, p = icdf(Y)
plt.scatter(x, p)
plt.yscale('log')
plt.xscale('log')
plt.show()

Development

Please work on a feature branch and create a pull request to the development branch. If necessary to merge manually do so without fast forward:

git merge --no-ff myfeature

To build a development environment run:

python3 -m venv env
source env/bin/activate
pip install -e '.[dev]'

For testing:

pytest --cov

Credits

This is a project by Leonardo Niccolò Ialongo and Davide Luzzati, under the supervision of Diego Garlaschelli and Giorgio Fagiolo .

History

0.0.2 (2023-12-02)

• First release with working ARIO model.

0.0.1 (2022-07-27)

• First release on PyPI. Per Bak models available but not thoroughly tested.