#! /usr/bin/env python
#
def r8_normal_01 ( seed ):

#*****************************************************************************80
#
## R8_NORMAL_01 samples the standard normal probability distribution.
#
#  Discussion:
#
#    The standard normal probability distribution function (PDF) has
#    mean 0 and standard deviation 1.
#
#    The Box-Muller method is used.
#
#  Licensing:
#
#    This code is distributed under the GNU LGPL license. 
#
#  Modified:
#
#    21 January 2016
#
#  Author:
#
#    John Burkardt
#
#  Parameters:
#
#    Input, integer SEED, a seed for the random number generator.
#
#    Output, real X, a sample of the standard normal PDF.
#
#    Output, integer SEED, an updated seed for the random number generator.
#
  import numpy as np
  from r8_uniform_01 import r8_uniform_01

  r1, seed = r8_uniform_01 ( seed )
  r2, seed = r8_uniform_01 ( seed )

  x = np.sqrt ( - 2.0 * np.log ( r1 ) ) * np.cos ( 2.0 * np.pi * r2 )

  return x, seed

def r8_normal_01_test ( ):

#*****************************************************************************80
#
## R8_NORMAL_01_TEST tests R8_NORMAL_01.
#
#  Licensing:
#
#    This code is distributed under the GNU LGPL license.
#
#  Modified:
#
#    26 July 2014
#
#  Author:
#
#    John Burkardt
#
  import platform
  from r8_normal_01 import r8_normal_01

  seed = 123456789
  test_num = 20

  print ( '' )
  print ( 'R8_NORMAL_01_TEST' )
  print ( '  Python version: %s' % ( platform.python_version ( ) ) )
  print ( '  R8_NORMAL_01 generates normally distributed' )
  print ( '  random values.' )
  print ( '  Using initial random number seed = %d' % ( seed ) )
  print ( '' )

  for test in range ( 0, test_num ):

    x, seed = r8_normal_01 ( seed )
    print ( '  %f' % ( x ) )
#
#  Terminate.
#
  print ( '' )
  print ( 'R8_NORMAL_01_TEST' )
  print ( '  Normal end of execution.' )
  return

if ( __name__ == '__main__' ):
  from timestamp import timestamp
  timestamp ( )
  r8_normal_01_test ( )
  timestamp ( )