#! /usr/bin/env python
#
def sqrt_values ( n_data ):

#*****************************************************************************80
#
## SQRT_VALUES returns some values of the square root function.
#
#  Discussion:
#
#    SQRT(X) = positive real number Y such that Y * Y = X.
#
#    In Mathematica, the function can be evaluated by:
#
#      Sqrt[x]
#
#  Licensing:
#
#    This code is distributed under the GNU LGPL license.
#
#  Modified:
#
#    19 January 2015
#
#  Author:
#
#    John Burkardt
#
#  Reference:
#
#    Milton Abramowitz and Irene Stegun,
#    Handbook of Mathematical Functions,
#    US Department of Commerce, 1964.
#
#    Stephen Wolfram,
#    The Mathematica Book,
#    Fourth Edition,
#    Wolfram Media / Cambridge University Press, 1999.
#
#  Parameters:
#
#    Input/output, integer N_DATA.  The user sets N_DATA to 0 before the
#    first call.  On each call, the routine increments N_DATA by 1, and
#    returns the corresponding data; when there is no more data, the
#    output value of N_DATA will be 0 again.
#
#    Output, real X, the argument of the function.
#
#    Output real F, the value of the function.
#
  import numpy as np

  n_max = 14

  f_vec = np.array ( ( \
     0.0000000000000000E+00, \
     0.9000000040950000E-04, \
     0.3000000000000000E+00, \
     0.3162277660168379E+00, \
     0.6324555320336759E+00, \
     0.1000000000000000E+01, \
     0.1414213562373095E+01, \
     0.1732050807568877E+01, \
     0.1772453850905516E+01, \
     0.4358898943540674E+01, \
     0.5385164807134504E+01, \
     0.8426149773176359E+01, \
     0.9848857801796105E+01, \
     0.1111111106055556E+05 ) )

  x_vec = np.array ( ( \
     0.0000000000000000E+00, \
     0.8100000073710001E-08, \
     0.9000000000000000E-01, \
     0.1000000000000000E+00, \
     0.4000000000000000E+00, \
     0.1000000000000000E+01, \
     0.2000000000000000E+01, \
     0.3000000000000000E+01, \
     0.3141592653589793E+01, \
     0.1900000000000000E+02, \
     0.2900000000000000E+02, \
     0.7100000000000000E+02, \
     0.9700000000000000E+02, \
     0.1234567890000000E+09 ) )

  if ( n_data < 0 ):
    n_data = 0

  if ( n_max <= n_data ):
    n_data = 0
    x = 0.0
    f = 0.0
  else:
    x = x_vec[n_data]
    f = f_vec[n_data]
    n_data = n_data + 1

  return n_data, x, f

def sqrt_values_test ( ):

#*****************************************************************************80
#
## SQRT_VALUES_TEST demonstrates the use of SQRT_VALUES.
#
#  Licensing:
#
#    This code is distributed under the GNU LGPL license.
#
#  Modified:
#
#    19 January 2015
#
#  Author:
#
#    John Burkardt
#
  import platform

  print ( '' )
  print ( 'SQRT_VALUES_TEST:' )
  print ( '  Python version: %s' % ( platform.python_version ( ) ) )
  print ( '  SQRT_VALUES stores values of the SQRT function.' )
  print ( '' )
  print ( '      X         SQRT(X)' )
  print ( '' )

  n_data = 0

  while ( True ):

    n_data, x, f = sqrt_values ( n_data )

    if ( n_data == 0 ):
      break

    print ( '  %12f  %24.16f' % ( x, f ) )
#
#  Terminate.
#
  print ( '' )
  print ( 'SQRT_VALUES_TEST:' )
  print ( '  Normal end of execution.' )
  return

if ( __name__ == '__main__' ):
  from timestamp import timestamp
  timestamp ( )
  sqrt_values_test ( )
  timestamp ( )