Principal curves implementation in Python
Project description
pcurvepy
Principal Curves
This is an implementation of the Principal Curves (Hastie '89) algorithm in Python.
It is a fork of the zsteve/pcurvepy
package where
the projection indices are selected according to our
translation of the R/C++ princurve
package.
Installation:
pip install git+https://github.com/mossjacob/pcurvepy
Example:
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import pcurve
data = pd.read_csv('test_data.csv')
x = data.loc[:, ('X1', 'X2')].to_numpy()
# transform data to have zero mean
x = x - np.mean(x, 0)
index = np.arange(0, len(x))
curve = pcurve.PrincipalCurve(k=5)
curve.fit(x)
plt.scatter(x[:, 0], x[:, 1], alpha=0.25, c=index)
plt.plot(curve.points[:, 0], curve.points[:, 1], c='k')
# get interpolation indices
pseudotime_interp, point_interp, order = curve.unpack_params()
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pcurvepy2-0.1.3.tar.gz
(16.3 kB
view hashes)
Built Distribution
pcurvepy2-0.1.3-py3-none-any.whl
(16.9 kB
view hashes)
Close
Hashes for pcurvepy2-0.1.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | c858b75abc109d3cfb7c953782a69e8de413ae6e84ea16d419b282d001f36c9b |
|
MD5 | 1f2058683fd2c38840bc5808391ad210 |
|
BLAKE2b-256 | 8b3864352ead58ced95647dbb1b0a762e7e1ce6ae0edcb154bbbfef8e85763fa |