#! /usr/bin/env python3
#
def voronoi_test ( ):

  from scipy.spatial import Delaunay
  from scipy.spatial import Voronoi
  from scipy.spatial import voronoi_plot_2d
  import matplotlib.pyplot as plt
  import numpy as np

  points = np.loadtxt ( 'i18.txt' )
#
#  Display just the points.
#
  plt.clf ( )
  plt.plot ( points[:,0], points[:,1], 'o' )
  for i in range ( 0, 18 ):
    s = str(i)
    plt.text ( points[i,0]+0.15, points[i,1]+0.15, s )
  plt.grid ( 'True' )
  plt.axis ( 'equal' )
  filename = 'i18_points_labeled.png'
  plt.savefig ( filename )
  print ( '  Graphics saved as "' + filename + '"' )
  plt.show ( )
  plt.close ( )
#
#  Compute the diagram.
#
  diagram = Voronoi ( points )
#
#  Plot the diagram.
#
  voronoi_plot_2d ( diagram, line_width = 2, point_size = 20 )
  plt.grid ( True )
  filename = 'i18_voronoi.png'
  plt.savefig ( filename )
  print ( '  Graphics saved as "%s"' % ( filename ) )
  plt.show ( )
  plt.close ( )
#
#  Plot the diagram on a larger scale.
#
  voronoi_plot_2d ( diagram, line_width = 2, point_size = 10 )
  plt.grid ( True )
  plt.axis ( 'equal' )
  filename = 'i18_voronoi_infinity.png'
  plt.savefig ( filename )
  print ( '  Graphics saved as "%s"' % ( filename ) )
  plt.show ( )
  plt.close ( )
#
#  Plot the diagram and the Delaunay triangulation.
#
  tri = Delaunay ( points )
  voronoi_plot_2d ( diagram, line_width = 2, point_size = 20 )
  plt.triplot ( points[:,0], points[:,1], tri.simplices )
  plt.grid ( True )
  filename = 'i18_voronoi_delaunay.png'
  plt.savefig ( filename )
  print ( '  Graphics saved as "%s"' % ( filename ) )
  plt.show ( )
  plt.close ( )
  return

if ( __name__ == "__main__" ):
  voronoi_test ( )