lshknn 0.1.2

k nearest neighbor (KNN) graphs via Pearson correlation distance and local sensitive hashing (LSH).

k nearest neighbor (KNN) graphs via Pearson correlation distance and local sensitive hashing (LSH).

• Development: https://github.com/iosonofabio/lshknn

• Authors: Fabio Zanini and Paolo Carnevali

• License: MIT

• Copyright: Fabio Zanini and Chan Zuckerberg Initiative

import numpy as np
import lshknn

# Make mock data
# 2 features (rows), 4 samples (columns)
data = np.array(
        [[1, 0, 1, 0],
         [0, 1, 0, 1]],
        dtype=np.float64)

# Instantiate class
c = lshknn.Lshknn(
        data=data,
        k=1,
        threshold=0.2,
        m=10,
        slice_length=4)

# Call subroutine
knn, similarity, n_neighbors = c()

# Check result
assert (knn == [[2], [3], [0], [1]]).all()