Constrained Lloyd Iteration

lloyd.py

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()