Parallel coordinates plotting
Project description
Parallel Coordinates Plotting for Python parcoords
This package implements a parallel-coordinate plot, commonly used in machine learning, i.e. for hyperparameter visualization.
Installation
The parcoords
package can be installed with pip:
pip install <package name>
Usage
The following code produces the sample plot at the beginning of this page.
import matplotlib.pyplot as plt
from parcoords.parcoords import plot_parcoords
# let's define some data to plot
values = [
[0.1, 10, "smote", 0.78],
[0.15, 9, "none", 0.46],
[0.18, 8, "rand_over", 0.67],
[0.01, 16, "rand_over", 0.84],
[0.01, 15, "smote", 0.86],
[0.015, 12, "smote", 0.87],
[0.03, 12, "smote", 0.81],
[0.12, 13, "none", 0.51],
[0.07, 11, "rand_over", 0.7],
[0.2, 14, "none", 0.55],
]
# plot the values as parallel-coordinate plot
plot_parcoords(
values,
labels=["lr", "# epochs", "sampling method", "accuracy"],
color_field="accuracy",
scale=[("lr", "log")],
title="Parallel-Coordinates of the Hyperparameters",
)
plt.show()
License
This repository is licensed under the MIT-License.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
parcoords-0.1.1.tar.gz
(4.6 kB
view details)
Built Distribution
File details
Details for the file parcoords-0.1.1.tar.gz
.
File metadata
- Download URL: parcoords-0.1.1.tar.gz
- Upload date:
- Size: 4.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.17
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 531b689cd7b9a81da0d42e2a8bf66437a3fd447754706c515770cc905595bc90 |
|
MD5 | 216bfc1d9ffd5014d47fc502bd568d55 |
|
BLAKE2b-256 | dabcb14dbfd263b6ffb310a52bd3ef6979c60b4eee29450e0e857d1408026a83 |
File details
Details for the file parcoords-0.1.1-py3-none-any.whl
.
File metadata
- Download URL: parcoords-0.1.1-py3-none-any.whl
- Upload date:
- Size: 5.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.17
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | dfd801325c08523ba96eaba10eb869cab7171e434bd1507f54824ab485efe1f4 |
|
MD5 | d44b203f89fc70076cba3cadfbc322aa |
|
BLAKE2b-256 | 572242f31509dd635ef93021b2a01e04793e0488a18e50de46594bf9ffdbc667 |