kleinberg-grid-simulator 0.1.0

A Python+Julia package to compute Expected Delivery Time in Kleinberg's augmented grid model.

Kleinberg's Grid Ultimate

Great Trilogies Come in Threes.

• Kleinberg's Grid Reloaded proposed a new dynamic rejection sampling approach to simulate Kleinberg's small world model on very large graphs.

• Kleinberg's Grid Unchained introduced double rejection sampling, enabling computations on virtual grids the size of the universe (yes, that's big).

• Kleinberg's Grid Ultimate proposes an improved version of the simulator that isn't afraid with universe to the square! And it is nicely packaged for everyone to use.

• Free software: MIT license

• Documentation: https://balouf.github.io/kleinberg-grid-simulator/.

Features

• Provides a Python frontend with possibility to use Julia or Python backend.
• Julia backend improved with fixed-size big ints (int256, int512, int1024) to speed up computation.
• Provides tools to parallelize, estimate complexity bounds, estimate reasonable shortcut distributions.
• Provides notebooks to benchmark the performance and reproduce the results from previous papers.

Installation

Pip installation preferred.

pip install kleinberg-grid-simulator

Usage

from kleinberg_grid_simulator import compute_edt
compute_edt(n=1000, r=2, p=1, q=1)

Credits

Céline Comte, co-author of Kleinberg's Grid Unchained.

This package was created with Cookiecutter and the Package Helper 3 project template.