00001 /* 00002 * $Id$ 00003 * 00004 * Author: David Fournier 00005 * Copyright (c) 2008-2012 Regents of the University of California 00006 */ 00011 #include "fvar.hpp" 00012 00019 prevariable& cube(const prevariable& v1) 00020 { 00021 double x=value(v1); 00022 double x2=x*x; 00023 if (++gradient_structure::RETURN_PTR > gradient_structure::MAX_RETURN) 00024 gradient_structure::RETURN_PTR = gradient_structure::MIN_RETURN; 00025 gradient_structure::RETURN_PTR->v->x=x2*x; 00026 gradient_structure::GRAD_STACK1->set_gradient_stack(default_evaluation2, 00027 &(gradient_structure::RETURN_PTR->v->x), &(v1.v->x),3*x2 ); 00028 return(*gradient_structure::RETURN_PTR); 00029 } 00030 00037 prevariable& fourth(const prevariable& v1) 00038 { 00039 double x=value(v1); 00040 double x2=x*x; 00041 if (++gradient_structure::RETURN_PTR > gradient_structure::MAX_RETURN) 00042 gradient_structure::RETURN_PTR = gradient_structure::MIN_RETURN; 00043 gradient_structure::RETURN_PTR->v->x=x2*x2; 00044 gradient_structure::GRAD_STACK1->set_gradient_stack(default_evaluation2, 00045 &(gradient_structure::RETURN_PTR->v->x), &(v1.v->x),4*x2*x ); 00046 return(*gradient_structure::RETURN_PTR); 00047 }
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