úÎVÁPÃM      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLSafe+MNOPQRSTUVWXYZ[\]^_`abcdef,(c) 2009 - 2014 Roel van Dijk & Bas van Dijk BSD-style (see the file LICENSE)WRoel van Dijk <vandijk.roel@gmail.com> Bas van Dijk <v.dijk.bas@gmail.com> ExperimentalNone01<VNƒ/%Generic error (not one of the others)KA call to a lapack subroutine failed in the underlying C levmar library.2At least one lower bound exceeds the upper one. A call to malloc. failed in the underlying C levmar library.@The matrix of constraints cannot have more rows than columns..Constraints matrix is not of full row rank.ÿCannot solve a problem with fewer measurements than unknowns. In case linear constraints are provided, this error is also returned when the number of measurements is smaller than the number of unknowns minus the number of equality constraints.Reason for terminating. "Stopped because of small gradient J^T e. Stopped because of small Dp. /Stopped because maximum iterations was reached. `Stopped because of singular matrix. Restart from current estimated parameters with increased %. RStopped because no further error reduction is possible. Restart with increased %.Stopped because of small ||e||_2.bStopped because model function returned invalid values (i.e. NaN or Inf). This is a user error.'Information regarding the minimization.||e||_2# at initial parameters.||e||_2% at estimated parameters. ||J^T e||_inf at estimated parameters.||Dp||_2$ at estimated parameters.mu/max[J^T J]_ii ] at estimated parameters.Number of iterations.Reason for terminating.Number of function evaluations.Number of jacobian evaluations.ENumber of linear systems solved, i.e. attempts for reducing error.7Linear constraints consisting of a constraints matrix, k><m3 and a right hand constraints vector, of length k where m$ is the number of parameters and k is the number of constraints.KEnsure that these vectors have the same length as the number of parameters.Optional lower bounds Optional upper bounds!Optional weights"Optional linear constraints#Minimization options%Scale factor for initial mu.&Stopping thresholds for  ||J^T e||_inf.'Stopping thresholds for ||Dp||_2.(Stopping thresholds for ||e||_2.)@Step used in the difference approximation to the Jacobian. If  optDelta<0š, the Jacobian is approximated with central differences which are more accurate (but slower!) compared to the forward differences employed by default.*;The Levenberg-Marquardt algorithm is overloaded to work on g and h.+"The Levenberg-Marquardt algorithm.Returns a triple of the found parameters, a structure containing information about the minimization and the covariance matrix corresponding to LS solution. Ensure that n >= m.,The  <http://en.wikipedia.org/wiki/Jacobian_matrix_and_determinantjacobian of the -ž function. Expressed as a function from a vector of parameters to a matrix which for each expected sample describes the partial derivatives of the parameters.Ensure that the length mQ of the parameter vector equals the length of the initial parameter vector in +.0Ensure that the output matrix has the dimension n><m where n! is the number of samples and m is the number of parameters.-„A functional relation describing measurements represented as a function from a vector of parameters to a vector of expected samples.Ensure that the length mQ of the parameter vector equals the length of the initial parameter vector in +.Ensure that the length nJ of the output sample vector equals the length of the sample vector in +.Ensure that the length nM of the output sample vector vector is bigger than or equal to the length m of the parameter vector..Sample vector of length n. Ensure that n >= m where m is the length of the / vector./Parameter vector of length m. Ensure that m <= n where n is the length of the . vector.i gen_levmarz takes the low-level C functions as arguments and executes one of them depending on the optional jacobian and constraints.Preconditions: ß length ys >= length ps isJust mLowBs && length (fromJust mLowBs) == length ps && isJust mUpBs && length (fromJust mUpBs) == length ps boxConstrained && (all $ zipWith (<=) (fromJust mLowBs) (fromJust mUpBs)) 0Default minimization options1j is defined as a  where all fields are k.l merges two  by taking the first non-k value for each field.+ModelOptional jacobianInitial parameters of length mSample vector of length nMaximum iterationsMinimization options ConstraintsiModel Optional jacobian Initial parameters Samples Maximum iterations Options Constraints1  !"#$%&'()*+,-./01/.-,*+#$%&'()0 !"    !"#$%&'()*+m      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghfgijklmklnklop%levmar-1.2.1.8-DwFFxZ1qRki5ylBQlJWz08Numeric.LevMarBindings.LevMar.CurryFriendly LevMarError LapackErrorFailedBoxCheckMemoryAllocationFailureConstraintMatrixRowsGtColsConstraintMatrixNotFullRowRankTooFewMeasurements StopReason SmallGradientSmallDp MaxIterationsSingularMatrix SmallestError SmallNorm2E InvalidValuesInfo infNorm2initE infNorm2EinfNormInfJacTe infNorm2Dp infMuDivMax infNumIter infStopReasoninfNumFuncEvalsinfNumJacobEvalsinfNumLinSysSolvedLinearConstraints Constraints lowerBounds upperBoundsweightslinearConstraintsOptionsOptsoptScaleInitMuoptStopNormInfJacTeoptStopNorm2Dp optStopNorm2EoptDelta LevMarablelevmarJacobianModelSamplesParams defaultOpts$fMonoidConstraints$fExceptionLevMarError$fLevMarableDouble$fLevMarableFloat $fEqOptions $fOrdOptions $fReadOptions $fShowOptions $fDataOptions$fReadConstraints$fShowConstraints$fEqStopReason$fOrdStopReason$fReadStopReason$fShowStopReason$fDataStopReason$fEnumStopReason$fEqInfo $fOrdInfo $fReadInfo $fShowInfo $fDataInfo$fEqLevMarError$fOrdLevMarError$fReadLevMarError$fShowLevMarError$fDataLevMarError$fEqConstraints LevMarBLecDer LevMarBLecDif LevMarLecDer LevMarLecDif LevMarBCDer LevMarBCDif LevMarDer LevMarDifBoxConstraints slevmar_dif dlevmar_dif slevmar_der dlevmar_derslevmar_bc_difdlevmar_bc_difslevmar_bc_derdlevmar_bc_derslevmar_lec_difdlevmar_lec_difslevmar_lec_derdlevmar_lec_derslevmar_blec_difdlevmar_blec_difslevmar_blec_derdlevmar_blec_derghc-prim GHC.TypesDoubleFloat gen_levmarbaseGHC.BasememptyNothingmappend