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

#*****************************************************************************80
#
## comfort does an exercise in logistic regression.
#
#  Licensing:
#
#    This code is distributed under the GNU LGPL license.
#
#  Modified:
#
#    11 October 2019
#
#  Author:
#
#    John Burkardt
#
  import matplotlib.pyplot as plt
  import numpy as np
  from logistic_regression import logistic_regression

  print ( '' )
  print ( 'comfort:' )
  print ( '  Seek parameters for logistic regression example.' )
  print ( '  We have M examples of N-dimensional data X.' )
  print ( '  For a model' )
  print ( '    h(x) = 1 / ( 1 + exp ( - ( w(0) + w(1)*h + w(2)*t ) ) )' )
  print ( '  determine the weights w.' )
  print ( '' )
  print ( '  Use gradient descent' )
#
#  Read the data file.
#
  data = np.loadtxt ( 'comfort_data.txt' )
#
#  First two columns are humidity and temperature.  
#  Third column is Y (comfortable = 1, no = 0).
#
  h = data[:,0]
  t = data[:,1]
  y = data[:,2]
  m = len ( h )
#
#  Normalize the X data.
#
  h = ( h - np.min ( h ) ) / ( np.max ( h ) - np.min ( h ) )
  t = ( t - np.min ( t ) ) / ( np.max ( t ) - np.min ( t ) )
#
#  Create a data array x = [ 1 | h | t ].
#
  x = np.zeros ( [ m, 3 ] )
  x[:,0] = 1
  x[:,1] = h
  x[:,2] = t
#
#  Request logistic regression weights.
#
  alpha = 1.0
  kmax = 10000

  w = logistic_regression ( x, y, alpha, kmax )

  print ( '' )
  print ( '  Estimated weights W = (%g,%g,%g)' % ( w[0], w[1], w[2] ) )
#
#  Display the data.
#
  plt.plot ( x[y==0,1], x[y==0,2], 'r.', markersize = 15 )
  plt.plot ( x[y==1,1], x[y==1,2], 'b.', markersize = 15 )

  plt.xlabel ( '<-- Humidity -->' )
  plt.ylabel ( '<-- Temperature -->' )
  plt.title ( 'Blue = Comfortable, Red = Not' )
  plt.plot ( [-w[0]/w[1], (-w[0]-w[2])/w[1]], [0,1], 'k-', linewidth = 3 )
  plt.grid ( True )
  filename = 'comfort.png'
  plt.savefig ( filename )
  plt.show ( )
  print ( '' )
  print ( '  Graphics saved as "%s"' % ( filename ) )
#
#  Terminate.
#
  print ( '' )
  print ( 'comfort:' )
  print ( '  Normal end of execution.' )

  return

if ( __name__ == '__main__' ):
  comfort ( )