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

#*****************************************************************************80
#
## faithful_wait() computes and displays wait statistics.
#
#  Licensing:
#
#    This code is distributed under the MIT license.
#
#  Modified:
#
#    27 September 2023
#
#  Author:
#
#    John Burkardt
#
  import matplotlib.pyplot as plt
  import numpy as np
  import platform

  print ( '' )
  print ( 'faithful_wait():' )
  print ( '  Python version ' + platform.python_version ( ) )
  print ( '  Compute and display Old Faithful wait-time statistics.' )
#
#  Read the data.
#
  data = np.loadtxt ( 'faithful_data.txt' )
  x = data[:,0]
  y = data[:,1]
#
#  Compute statistics.
#
  print ( '' )
  print ( '  Statistics for Old Faithful wait times y' )
  print ( '  y.shape = ', y.shape )
  print ( '  y min   = ', np.min ( y ) )
  print ( '  y mean  = ', np.mean ( y ) )
  print ( '  y max   = ', np.max ( y ) )
  print ( '  y var   = ', np.var ( y ) )
  print ( '  y std   = ', np.std ( y ) )
#
#  Histogram of wait times (y)
#
  y_mean = np.mean ( y )
  y_std = np.std ( y )

  plt.clf ( )
  plt.hist ( y, bins = 20 )
  bot, top = plt.ylim ( )
  plt.plot ( [y_mean-y_std,y_mean-y_std], [0.0,top], 'r-', linewidth = 3 )
  plt.plot ( [y_mean+y_std,y_mean+y_std], [0.0,top], 'r-', linewidth = 3 )
  plt.xlabel ( '<-- Wait -->', fontsize = 16 )
  plt.ylabel ( '<-- Frequency -->', fontsize = 16 )
  plt.title ( 'Wait mean $\pm 1 std$', fontsize = 16 )
  plt.grid ( True )
  plt.axis ( 'equal' )
  filename = 'faithful_wait.png'
  plt.savefig ( filename )
  print ( '  Graphics saved as "' + filename + '"' )
  plt.show ( )

  return

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