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Created with Raphaël 2.2.013Feb121110965421Jan191323Oct2221191513824Sep19Aug526May17126530Apr2928272322212019181716865Feb211Jan30Dec282529Oct24Jul232111Jun96519May1218Apr9Mar87643Jan31Dec20Nov1523Oct22171612428Sep5429Aug282724222120171514138321Feb58Jan54221Dec1413630Nov151324Aug2321Jun20151429May21Mar28Feb85Jan30Nov28155Sep23Aug18Julvarious 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 implementationimplement the distance metricactivate evaluate() method againUnit vectors in R^n, or, equivalently, members of S^{n-1}added missing call-by-referenceTest RealTuples as wellA rudimentary class implementing tuples of real numbers as a Riemannian manifold. Mainly for testingfix a warningFactor out the actual test into a separate method. This paves the way for testing more target spacesremove code for interpolation via recursive geodesics. It is invariant under permutation of the vertices