text: /// @file
  /// @author David Pilger <dpilger26@gmail.com>
  /// [GitHub Repository](https://github.com/dpilger26/NumCpp)
  ///
  /// License
  /// Copyright 2020 David Pilger
  ///
  /// Permission is hereby granted, free of charge, to any person obtaining a copy of this
  /// software and associated documentation files(the "Software"), to deal in the Software
  /// without restriction, including without limitation the rights to use, copy, modify,
  /// merge, publish, distribute, sublicense, and/or sell copies of the Software, and to
  /// permit persons to whom the Software is furnished to do so, subject to the following
  /// conditions :
  ///
  /// The above copyright notice and this permission notice shall be included in all copies
  /// or substantial portions of the Software.
  ///
  /// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
  /// INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR
  /// PURPOSE AND NONINFRINGEMENT.IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE
  /// FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR
  /// OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
  /// DEALINGS IN THE SOFTWARE.
  ///
  /// Description
  /// "student-T" distribution
  ///
  #pragma once
  
  #include "NumCpp/Core/Internal/Error.hpp"
  #include "NumCpp/Core/Internal/StaticAsserts.hpp"
  #include "NumCpp/Core/Internal/StlAlgorithms.hpp"
  #include "NumCpp/Core/Shape.hpp"
  #include "NumCpp/NdArray.hpp"
  #include "NumCpp/Random/generator.hpp"
  
  #include "boost/random/student_t_distribution.hpp"
  
  #include <string>
  
  namespace nc
  {
      namespace random
      {
          //============================================================================
          // Method Description:
          ///						Single random value sampled from the "student-T" distribution.
          ///
          ///                     NumPy Reference: https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.standard_t.html#numpy.random.standard_t
          ///
          /// @param				inDof independent random variables
          /// @return
          ///				NdArray
          ///
          template<typename dtype>
          dtype studentT(dtype inDof)
          {
              STATIC_ASSERT_ARITHMETIC(dtype);
  
              if (inDof <= 0)
              {
                  THROW_INVALID_ARGUMENT_ERROR("degrees of freedom must be greater than zero.");
              }
  
              boost::random::student_t_distribution<dtype> dist(inDof);
              return dist(generator_);
          }
  
          //============================================================================
          // Method Description:
          ///						Create an array of the given shape and populate it with
          ///						random samples from the "student-T" distribution.
          ///
          ///                     NumPy Reference: https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.standard_t.html#numpy.random.standard_t
          ///
          /// @param				inShape
          /// @param				inDof independent random variables
          /// @return
          ///				NdArray
          ///
          template<typename dtype>
          NdArray<dtype> studentT(const Shape& inShape, dtype inDof)
          {
              STATIC_ASSERT_ARITHMETIC(dtype);
  
              if (inDof <= 0)
              {
                  THROW_INVALID_ARGUMENT_ERROR("degrees of freedom must be greater than zero.");
              }
  
              NdArray<dtype> returnArray(inShape);
  
              boost::random::student_t_distribution<dtype> dist(inDof);
  
              stl_algorithms::for_each(returnArray.begin(), returnArray.end(),
                  [&dist](dtype& value)  -> void
                  { 
                      value = dist(generator_);
                  });
  
              return returnArray;
          }
      }  // namespace random
  } // namespace nc
  