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

#*****************************************************************************80
#
## ford_data returns a normalized copy of the Ford data.
#
#  Discussion:
#
#    Here, the data is read from a file:
#
#      data = np.loadtxt ( 'ford_data.txt' )
#
#    It might be more efficient for it to be stored internally as an array:
#
#      data = np.array ( [
#      [ 27,     9991 ], 
#      [ 17,     9925 ],
#      [ 28,    10491 ],
#        ...    .....
#      [  7,    11000 ] ] )
#
#  Output:
#
#    real x[23], y[23]: the mileage and asking price for used Ford Escorts.
#
  import numpy as np

  data = np.loadtxt ( 'ford_data.txt' )

  x = data[:,0]
  y = data[:,1]

  x = ( x - np.min ( x ) ) / ( np.max ( x ) - np.min ( x ) )
  y = ( y - np.min ( y ) ) / ( np.max ( y ) - np.min ( y ) )

  return x, y