You'll first need to install annoy via;
pip install annoy
Once installed you can run the code from the video below.
This code generates the random data.
import numpy as np
import matplotlib.pylab as plt
from annoy import AnnoyIndex
columns = 2
vecs = np.concatenate([
np.random.normal(-1, 1, (5000, columns)),
np.random.normal(0, 0.5, (5000, columns)),
])
plt.scatter(vecs[:, 0], vecs[:, 1], s=1);
This code generates the annoy index.
annoy = AnnoyIndex(columns, 'euclidean')
for i in range(vecs.shape[0]):
annoy.add_item(i, vecs[i, :])
annoy.build(n_trees=1)
This code fetches the indices of the neighbors;
indices = annoy.get_nns_by_vector(np.array([0., 0.]), 20)