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dmfad_example.cpp
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31 
32 // dmfad_example
33 //
34 // usage:
35 // dmfad_example
36 //
37 // output:
38 // prints the results of differentiating a simple function with forward
39 // mode AD using the Sacado::Fad::DMFad class (uses dynamic memory
40 // allocation for number of derivative components using a custom memory
41 // manager).
42 
43 #include <iostream>
44 #include <iomanip>
45 
46 #include "Sacado_No_Kokkos.hpp"
47 
48 template <>
50 
51 // The function to differentiate
52 template <typename ScalarT>
53 ScalarT func(const ScalarT& a, const ScalarT& b, const ScalarT& c) {
54  ScalarT r = c*std::log(b+1.)/std::sin(a);
55 
56  return r;
57 }
58 
59 // The analytic derivative of func(a,b,c) with respect to a and b
60 void func_deriv(double a, double b, double c, double& drda, double& drdb)
61 {
62  drda = -(c*std::log(b+1.)/std::pow(std::sin(a),2.))*std::cos(a);
63  drdb = c / ((b+1.)*std::sin(a));
64 }
65 
66 int main(int argc, char **argv)
67 {
68  double pi = std::atan(1.0)*4.0;
69 
70  // Values of function arguments
71  double a = pi/4;
72  double b = 2.0;
73  double c = 3.0;
74 
75  // Number of independent variables
76  int num_deriv = 2;
77 
78  // Memory pool & manager
80  Sacado::Fad::MemPool* pool = poolManager.getMemoryPool(num_deriv);
82 
83  // Fad objects
84  Sacado::Fad::DMFad<double> afad(num_deriv, 0, a); // First (0) indep. var
85  Sacado::Fad::DMFad<double> bfad(num_deriv, 1, b); // Second (1) indep. var
86  Sacado::Fad::DMFad<double> cfad(c); // Passive variable
87  Sacado::Fad::DMFad<double> rfad; // Result
88 
89  // Compute function
90  double r = func(a, b, c);
91 
92  // Compute derivative analytically
93  double drda, drdb;
94  func_deriv(a, b, c, drda, drdb);
95 
96  // Compute function and derivative with AD
97  rfad = func(afad, bfad, cfad);
98 
99  // Extract value and derivatives
100  double r_ad = rfad.val(); // r
101  double drda_ad = rfad.dx(0); // dr/da
102  double drdb_ad = rfad.dx(1); // dr/db
103 
104  // Print the results
105  int p = 4;
106  int w = p+7;
107  std::cout.setf(std::ios::scientific);
108  std::cout.precision(p);
109  std::cout << " r = " << r << " (original) == " << std::setw(w) << r_ad
110  << " (AD) Error = " << std::setw(w) << r - r_ad << std::endl
111  << "dr/da = " << std::setw(w) << drda << " (analytic) == "
112  << std::setw(w) << drda_ad << " (AD) Error = " << std::setw(w)
113  << drda - drda_ad << std::endl
114  << "dr/db = " << std::setw(w) << drdb << " (analytic) == "
115  << std::setw(w) << drdb_ad << " (AD) Error = " << std::setw(w)
116  << drdb - drdb_ad << std::endl;
117 
118  double tol = 1.0e-14;
119  if (std::fabs(r - r_ad) < tol &&
120  std::fabs(drda - drda_ad) < tol &&
121  std::fabs(drdb - drdb_ad) < tol) {
122  std::cout << "\nExample passed!" << std::endl;
123  return 0;
124  }
125  else {
126  std::cout <<"\nSomething is wrong, example failed!" << std::endl;
127  return 1;
128  }
129 }
MemPool * getMemoryPool(unsigned int dim)
Get memory pool for supplied dimension dim.
atan(expr.val())
KOKKOS_INLINE_FUNCTION mpl::enable_if_c< ExprLevel< Expr< T1 > >::value==ExprLevel< Expr< T2 > >::value, Expr< PowerOp< Expr< T1 >, Expr< T2 > > > >::type pow(const Expr< T1 > &expr1, const Expr< T2 > &expr2)
expr expr1 expr1 expr1 c expr2 expr1 expr2 expr1 expr2 expr1 expr1 expr1 expr1 c expr2 expr1 expr2 expr1 expr2 expr1 expr1 expr1 expr1 c *expr2 expr1 expr2 expr1 expr2 expr1 expr1 expr1 expr1 c expr2 expr1 expr2 expr1 expr2 expr1 expr1 expr1 expr2 expr1 expr2 expr1 expr1 expr1 expr2 expr1 expr2 expr1 expr1 expr1 c
Derivative array storage class using dynamic memory allocation.
int main()
Definition: ad_example.cpp:191
void func_deriv(double a, double b, double c, double &drda, double &drdb)
sin(expr.val())
log(expr.val())
const double tol
const T func(int n, T *x)
Definition: ad_example.cpp:49
Forward-mode AD class using dynamic memory allocation and expression templates.
fabs(expr.val())
cos(expr.val())