saturnscore 1.2.0

Saturn coefficient to assess the results of an UMAP dimensionality reduction

Saturn score

Summary

A Python package that computes the Saturn coefficient of a matrix to assess the quality of its UMAP dimensionality reduction.

Installation

You can execute the following command to install this package and its dependencies:

pip3 install numpy pandas scipy umap-learn scikit-learn saturnscore

Example

You can run the following Python code to test your package installation:

import numpy as np
import pandas as pd
import scipy
import umap.umap_ as umap
from saturnscore import Saturn_coefficient
from sklearn.preprocessing import StandardScaler

np.random.seed(0)  # Set random seed for reproducibility
input_data = np.random.randn(120, 200)  # Generate random matrix X1

these_n_neighbors = 20
this_min_dist = 0.01
these_n_components = 2
this_metric = 'euclidean'
this_random_state = 42
this_n_jobs = 1
this_n_epochs = 200

print("these_n_neighbors = ", these_n_neighbors)
print("this_min_dist = ", this_min_dist)
print("these_n_components = ", these_n_components)
print("this_metric = ", this_metric)

umap_verbose = False
fit = umap.UMAP(n_neighbors=these_n_neighbors,
min_dist=this_min_dist,
n_components=these_n_components,
metric=this_metric,
n_jobs=this_n_jobs,
random_state=this_random_state,
n_epochs = this_n_epochs,
verbose=umap_verbose)

umap_output_layout = fit.fit_transform(input_data)

result = Saturn_coefficient.SaturnCoefficient(input_data, umap_output_layout)
print(f" Saturn coefficient =  ", result)

The final command should print something like Saturn coefficient = 0.11817430122179944 (this value might be different because of the random component of UMAP).

Contact

The SaturnScore package was developed by Davide Chicco. Questions should be addressed to davidechicco(AT)davidechicco.it