Running t-SNE, UMAP, TriMAP and PaCMAP

dimensionality_reduction.py

import time
import trimap
import umap
import pacmap
from sklearn.manifold import TSNE

# Read data
df = pd.read_csv('your_dataset.csv')

# Algorithms to test
algorithms = {
    't-SNE': TSNE(),
    'UMAP': umap.UMAP(),
    'TriMAP': trimap.TRIMAP(),
    'PaCMAP': pacmap.PaCMAP()
}

# Create embeddings for each algorithm & save fitting time
results = {}
for name, algorithm in algorithms.items():

    # Calculate embeddings
    t0 = time.time()
    embedding = algorithm.fit_transform(df.values)

    # Store results & runtime
    results[name] = {
        'embedding': pd.DataFrame(embedding, columns=['x', 'y']), 
        'time': time.time() - t0
    }