Find the closest pairs in an array.
Closely compares distances of arrays/embeddings and sorts them.
pip install closely
or install from source:
git clone https://github.com/justinshenk/closely
cd closely
pip install .
import closely
# X is an n x m numpy array
pairs, distances = closely.solve(X, n=1)
You can specify how many pairs you want to identify with n
.
The distance metric can be changed from the default euclidean
to any supported by scipy.spatial.distance.cdist
, eg, cosine
, hamming
, etc:
closely.solve(X, metric='cosine`)
import closely
import numpy as np
import matplotlib.pyplot as plt
# Create dataset
X = np.random.random((100,2))
pairs, distances = closely.solve(X, n=1)
# Plot points
z, y = np.split(X, 2, axis=1)
fig, ax = plt.subplots()
ax.scatter(z, y)
for i, txt in enumerate(X):
if i in pairs:
ax.annotate(i, (z[i], y[i]), color='red')
else:
ax.annotate(i, (z[i], y[i]))
plt.show()
Check pairs
:
In [10]: pairs
Out[10]:
array([[ 7, 16],
[96, 50]])
Python code for ordering distance matrices modified from Andriy Lazorenko, packaged and made useful for >2 features by Justin Shenk.