import numpy as np from dyneusr import DyNeuGraph from dyneusr.datasets import make_trefoil from kmapper import KeplerMapper from sklearn.decomposition import PCA # Generate synthetic dataset import tadasets X = tadasets.sphere(n=500, r=1) # Sort by first column inds = np.argsort(X[:, 0]) X = X[inds].copy() y = np.arange(X.shape[0]) # Generate shape graph using KeplerMapper mapper = KeplerMapper(verbose=1) lens = mapper.fit_transform(X, projection=PCA(2)) graph = mapper.map(lens, X, nr_cubes=6, overlap_perc=0.5) # Visualize the shape graph using DyNeuSR's DyNeuGraph dG = DyNeuGraph(G=graph, y=y) dG.visualize('dyneusr2D_sphere.html', template='2D', static=True, show=True)
def test_r(self): r = 23 s = tadasets.sphere(r=r) rs = np.fromiter((norm(p) for p in s), np.float64) assert np.all(rs <= r + 1e-5) assert np.all([r - 1e-5 <= rx <= r + 1e-5 for rx in rs])
def test_ambient(self): s = tadasets.sphere(n=200, r=3, ambient=15) assert s.shape == (200, 15)
def test_n(self): s = tadasets.sphere(n=543) assert s.shape[0] == 543