Constrained Lloyd Iteration
| from lloyd import Field | |
| from scipy.spatial import voronoi_plot_2d | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| import umap, os | |
| def plot(vor, name, e=0.3): | |
| '''Plot the Voronoi map of 2D numpy array X''' | |
| plot = voronoi_plot_2d(vor, show_vertices=False, line_colors='y', line_alpha=0.5, point_size=5) | |
| plot.set_figheight(14) | |
| plot.set_figwidth(20) | |
| plt.axis([field.bb[0]-e, field.bb[1]+e, field.bb[2]-e, field.bb[3]+e]) | |
| if not os.path.exists('plots'): os.makedirs('plots') | |
| if len(str(name)) < 2: name = '0' + str(name) | |
| plot.savefig( 'plots/' + str(name) + '.png' ) | |
| # get 1000 observations in two dimensions and plot their Voronoi map | |
| np.random.seed(1144392507) | |
| X = np.random.rand(1000, 4) | |
| X = umap.UMAP().fit_transform(X) | |
| # run 20 iterations of Lloyd's algorithm | |
| field = Field(X) | |
| for i in range(20): | |
| print(' * running iteration', i) | |
| plot(field.voronoi, i) | |
| field.relax() |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment