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Created with Raphaël 2.2.018Feb17161513121110965421Jan191323Oct2221191513824Sep19Aug526May17126530Apr2928272322212019181716865Feb211Jan30Dec282529Oct24Jul232111Jun96519May1218Apr9Mar87643Jan31Dec20Nov1523Oct22171612428Sep5429Aug282724222120171514138321Feb58Jan54221Dec1413630Nov151324Aug2321Jun20151429May21Mar28Feb85Jan30Nov28155Sep23Aug18Julbarf if derivative of distance is requested for two conjugate points. The derivative doesn't exist in that casestable implementation of sincuse absolute error for the termination criterion. This avoids a floating point exceptionchanged include <cmath.h> to <cmath>make sure arccos _never_ gets a value >1, because that leads to NaNfix spelling in a commenta few screen output fixesimplement fd gradientnew method projectOntoTangentSpacevarious fixes computing the energyremoved some dead codeuse method globalCoordinates() in the fd approximation of the tangentmake a specialization for TargetSpace==UnitVector. I hope this doesn't have to stay foreverintroduce method globalCoordinates()remove some old codeNew local copy of LocalStiffness needs less initializationlocalstiffness.hh copied here from dune-disc and stripped of everything we don't needheadercheck fixesexport ctype, the type used for coordinatesdecrease tr solver tolerancevarious fixes in derivativeOfDistanceSquaredWRTSecondArgument()Test UnitVectorsimplement derivativeOfDistanceSquaredWRTSecondArgument(). Not tested yetfix memory leak by using an auto_ptr for the inner solverimplement derivativeOfDistanceSquaredWRTSecondArgument()rewrite the gradient assembler such as to demand the derivative of the _squared_ distance from the target space. Unlike the distance itself, the squared distance is differentiable at zeroimplement matrix assembly by simply returning the identity matrix. This should a sort of projected gradient descent. It is too late at night for me to compute the actual matriximplement gradient of distance functionassemble gradient of functionalbugfix: properly set matrix and rhs sizesbugfix: set member 'assembler_'activate the solve()-method and make it compileinherit at least from NumProcimplement the exponential mapimplement the exponential map. Use a FieldVector to store the data instead of Dune::arrayadd more constsimplement the Riemannian distancemethod value() is construn and don't crashstart a generic implementation