closest_pairs finds the closest pairs of points in a dataset
Project description
Closest Pairs :triangular_ruler:
Find the closest pairs in an array.
Getting Started
pip install closest_pairs
or install from source:
git clone https://github.com/justinshenk/closest-pairs
cd closest_pairs
pip install .
How to use
import closest_pairs
# X is an n x m numpy array
pairs, distances = closest_pairs.solve(X, n=1)
You can specify how many pairs you want to identify with n
.
Example
import closest_pairs
import numpy as np
import matplotlib.pyplot as plt
# Create dataset
X = np.random.random((100,2))
pairs, distance = closest_pairs.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]))
Check pairs:
In [10]: pairs
Out[10]:
array([[[ 7],
[16]],
[[96],
[50]]])
Output:
Caveats
closest_pairs
will reduce the dimensionality with PCA of your data to two-dimensions for faster processing.
It also removes the first point in a pair if n
>1. In rare cases this leads to false negatives if the data is highly overlapping.
Credit and Explanation
Python code modified from Andriy Lazorenko, packaged and made useful for >2 features by Justin Shenk.
Project details
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