lazy-k 0.1.1

A C++ implementation of the Lazy-k algorithm (A* with partial expansion)

lazyk

A C++/Python library for efficiently iterating over high-probability label-assignments.

Installation

The library can be installed by cloning it and installing the Python package using pip.

git clone [e-mail]:ArthurDevNL/lazyk.git
cd lazyk
pip install -e .

Usage

The library can be used to iterate over the high-probability label-assignments of a given probability matrix. The following example shows how to use the library to iterate over the high-probability label-assignments of a 3x3 grid.

from lazyk import lazyk
import numpy as np

probs = np.arange(1, 10).reshape(3, -1)
probs = probs / probs.sum(axis=1, keepdims=True)

for seq in lazyk(probs, cache_assignments=True): # cache_assignments is true by default, but can be turned off
    print(seq)

The cache_assignments parameter indicates whether the algorithm should cache the intermediate label-assignments. This will improve the running speed of the algorithm but also require more memory. The default value is True but can be turned off if memory is a concern.