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

#*****************************************************************************80
#
## STUDENT_CDF_VALUES returns some values of the Student CDF.
#
#  Discussion:
#
#    In Mathematica, the function can be evaluated by:
#
#      Needs["Statistics`ContinuousDistributions`"]
#      dist = StudentTDistribution [ df ]
#      CDF [ dist, x ]
#
#  Licensing:
#
#    This code is distributed under the GNU LGPL license.
#
#  Modified:
#
#    22 February 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 C, is usually called the number of 
#    degrees of freedom of the distribution.  C is typically an 
#    integer, but that is not essential.  It is required that
#    C be strictly positive.
#
#    Output, real X, the argument of the function.
#
#    Output, real F, the value of the function.
#
  import numpy as np

  n_max = 13

  c_vec = np.array ( ( \
    1.0, 2.0, 3.0, 4.0, \
    5.0, 2.0, 5.0, 2.0, \
    5.0, 2.0, 3.0, 4.0, \
    5.0 ))

  f_vec = np.array ( ( \
     0.6000231200328521, \
     0.6001080279134390, \
     0.6001150934648930, \
     0.6000995134721354, \
     0.5999341989834830, \
     0.7498859393137811, \
     0.7500879487671045, \
     0.9500004222186464, \
     0.9499969138365968, \
     0.9900012348724744, \
     0.9900017619355059, \
     0.9900004567580596, \
     0.9900007637471291 ))

  x_vec = np.array ( ( \
     0.325, \
     0.289, \
     0.277, \
     0.271, \
     0.267, \
     0.816, \
     0.727, \
     2.920, \
     2.015, \
     6.965, \
     4.541, \
     3.747, \
     3.365 ))

  if ( n_data < 0 ):
    n_data = 0

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

  return n_data, c, x, f

def student_cdf_values_test ( ):

#*****************************************************************************80
#
## STUDENT_CDF_VALUES_TEST demonstrates the use of STUDENT_CDF_VALUES.
#
#  Licensing:
#
#    This code is distributed under the GNU LGPL license.
#
#  Modified:
#
#    22 February 2015
#
#  Author:
#
#    John Burkardt
#
  import platform

  print ( '' )
  print ( 'STUDENT_CDF_VALUES_TEST:' )
  print ( '  Python version: %s' % ( platform.python_version ( ) ) )
  print ( '  STUDENT_CDF_VALUES stores values of the STUDENT_CDF function.' )
  print ( '' )
  print ( '      C             X         STUDENT_CDF(C,X)' )
  print ( '' )

  n_data = 0

  while ( True ):

    n_data, c, x, f = student_cdf_values ( n_data )

    if ( n_data == 0 ):
      break

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

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