20 …return x*2 - 1 + static_cast<Scalar>(pow(1+x,2)) + 2*sqrt(y*y+0) - 4 * sin(0+x) + 2 * cos(y+0) - e…  in foo()
21   //return x+2*y*x;//x*2 -std::pow(x,2);//(2*y/x);// - y*2;  in foo()
29   return (p-Vector(Scalar(-1),Scalar(1.))).norm() + (p.array() * p.array()).sum() + p.dot(p);  in foo()
57     v[0] = 2 * x[0] * x[0] + x[0] * x[1];  in operator ()()
58     v[1] = 3 * x[1] * x[0] + 0.5 * x[1] * x[1];  in operator ()()
61       v[0] += 0.5 * x[2];  in operator ()()
66       v[2] = 3 * x[1] * x[0] * x[0];  in operator ()()
80       j(0,0) = 4 * x[0] + x[1];  in operator ()()
81       j(1,0) = 3 * x[1];  in operator ()()
83       j(0,1) = x[0];  in operator ()()
84       j(1,1) = 3 * x[0] + 2 * 0.5 * x[1];  in operator ()()
88         j(0,2) = 0.5;  in operator ()()
93         j(2,0) = 3 * x[1] * 2 * x[0];  in operator ()()
94         j(2,1) = 3 * x[0] * x[0];  in operator ()()
98         j(2,0) *= x[2];  in operator ()()
101         j(2,2) = 3 * x[1] * x[0] * x[0];  in operator ()()
102         j(2,2) = 3 * x[1] * x[0] * x[0];  in operator ()()
129         /* Integrator to test the AD. */  in operator ()()
130         o[0] = input[0] + input[1] * dt * _gain;  in operator ()()
140         /* Integrator to test the AD. */  in operator ()()
141         o[0] = input[0] + input[1] * dt * _gain;  in operator ()()
148             j(0, 0) = 1;  in operator ()()
149             j(0, 1) = dt * _gain;  in operator ()()
150             j(1, 0) = 0;  in operator ()()
219   typedef AutoDiffScalar<Vector2f> AD;  in test_autodiff_scalar()  typedef
220   AD ax(p.x(),Vector2f::UnitX());  in test_autodiff_scalar()
221   AD ay(p.y(),Vector2f::UnitY());  in test_autodiff_scalar()
222   AD res = foo<AD>(ax,ay);  in test_autodiff_scalar()
232   typedef AutoDiffScalar<Vector2f> AD;  in test_autodiff_vector()  typedef
233   typedef Matrix<AD,2,1> VectorAD;  in test_autodiff_vector()
234   VectorAD ap = p.cast<AD>();  in test_autodiff_vector()
238   AD res = foo<VectorAD>(ap);  in test_autodiff_vector()
259   typedef AutoDiffScalar<VectorXd> AD;  in test_autodiff_hessian()  typedef
260   typedef Matrix<AD,Eigen::Dynamic,1> VectorAD;  in test_autodiff_hessian()
265   x(0).value()=s1;  in test_autodiff_hessian()
269   x(0).derivatives().resize(2);  in test_autodiff_hessian()
270   x(0).derivatives().setZero();  in test_autodiff_hessian()
271   x(0).derivatives()(0)= 1;  in test_autodiff_hessian()
277   x(0).value().derivatives() = VectorXd::Unit(2,0);  in test_autodiff_hessian()
281   for(int idx=0; idx<2; idx++) {  in test_autodiff_hessian()
282       x(0).derivatives()(idx).derivatives()  = VectorXd::Zero(2);  in test_autodiff_hessian()
286   ADD y = sin(AD(s3)*x(0) + AD(s4)*x(1));  in test_autodiff_hessian()
288   VERIFY_IS_APPROX(y.value().derivatives()(0), y.derivatives()(0).value());  in test_autodiff_hessian()
290   VERIFY_IS_APPROX(y.value().derivatives()(0), s3*std::cos(s1*s3+s2*s4));  in test_autodiff_hessian()
292   VERIFY_IS_APPROX(y.derivatives()(0).derivatives(), -std::sin(s1*s3+s2*s4)*Vector2d(s3*s3,s4*s3));  in test_autodiff_hessian()
293   VERIFY_IS_APPROX(y.derivatives()(1).derivatives(),  -std::sin(s1*s3+s2*s4)*Vector2d(s3*s4,s4*s4));  in test_autodiff_hessian()
295   ADD z = x(0)*x(1);  in test_autodiff_hessian()
296   VERIFY_IS_APPROX(z.derivatives()(0).derivatives(), Vector2d(0,1));  in test_autodiff_hessian()
297   VERIFY_IS_APPROX(z.derivatives()(1).derivatives(), Vector2d(1,0));  in test_autodiff_hessian()
301   typedef Eigen::AutoDiffScalar<Eigen::Vector3d> AD;  in bug_1222()  typedef
303   const AD chi_3 = 1.0;  in bug_1222()
305   const AD denom = chi_3 + _cv1_3;  in bug_1222()
313   typedef Eigen::AutoDiffScalar<Eigen::Vector3d> AD;  in bug_1223()  typedef
316   const AD chi_3 = 1.0;  in bug_1223()
317   const AD denom = 1.0;  in bug_1223()
322   const AD t = min EIGEN_TEST_SPACE (denom / chi_3, 1.0);  in bug_1223()
324   const AD t2 = min EIGEN_TEST_SPACE (denom / (chi_3 * _cv1_3), 1.0);  in bug_1223()
338   typedef AutoDiffScalar<Matrix2d> AD;  in bug_1261()  typedef
339   typedef Matrix<AD,2,1> VectorAD;  in bug_1261()
341   VectorAD v(0.,0.);  in bug_1261()
342   const AD maxVal = v.maxCoeff();  in bug_1261()
343   const AD minVal = v.minCoeff();  in bug_1261()
348   typedef AutoDiffScalar<Vector2d> AD;  in bug_1264()  typedef
349   const AD s = 0.;  in bug_1264()
350   const Matrix<AD, 3, 1> v1(0.,0.,0.);  in bug_1264()
351   const Matrix<AD, 3, 1> v2 = (s + 3.0) * v1;  in bug_1264()  local
352   return v2(0).value();  in bug_1264()
358   typedef AutoDiffScalar<VectorXd> AD;  in bug_1281()  typedef
359   const AD c = 1.;  in bug_1281()
360   AD x0(2,n,0);  in bug_1281()
361   AD y1 = (AD(c)+AD(c))*x0;  in bug_1281()
362   y1 = x0 * (AD(c)+AD(c));  in bug_1281()
363   AD y2 = (-AD(c))+x0;  in bug_1281()
364   y2 = x0+(-AD(c));  in bug_1281()
365   AD y3 = (AD(c)*(-AD(c))+AD(c))*x0;  in bug_1281()
366   y3 = x0 * (AD(c)*(-AD(c))+AD(c));  in bug_1281()
374   for(int i = 0; i < g_repeat; i++) {  in EIGEN_DECLARE_TEST()