Îõ³h&ÑàÛ      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ(c) Masahiro Sakai 2023 BSD-stylemasahiro.sakai@gmail.com provisional non-portable Safe-Inferred /ÁÂÃÜï8,numeric-optimization0Wrapper type for adding constraints to a problemnumeric-optimization+Wrapper type for adding bounds to a problemnumeric-optimization,Wrapper type for adding hessian to a problemnumeric-optimization6Wrapper type for adding gradient function to a problem numeric-optimizationType of constraint(Currently, no constraints are supported. numeric-optimizationOptional constraint numeric-optimization6Optimization problem equipped with hessian informationnumeric-optimization"Hessian of a function computed by  It is called hess in scipy.optimize.minimize.numeric-optimizationThe product of the hessian H of a function f at x with a vector x. It is called hessp in scipy.optimize.minimize. See also  Òhttps://hackage.haskell.org/package/ad-4.5.4/docs/Numeric-AD.html#v:hessianProduct.numeric-optimization7Optimization problem equipped with gradient informationnumeric-optimization#Gradient of a function computed by  It is called jac in scipy.optimize.minimize.numeric-optimizationPair of  and numeric-optimization Similar to : but destination passing style is used for gradient vectornumeric-optimizationOptimization problemsnumeric-optimizationObjective function It is called fun in scipy.optimize.minimize.numeric-optimizationBoundsnumeric-optimization Constraintsnumeric-optimization8The bad things that can happen when you use the library.numeric-optimization!Statistics of optimizaion processnumeric-optimizationTotal number of iterations. numeric-optimization%Total number of function evaluations.!numeric-optimization%Total number of gradient evaluations."numeric-optimization$Total number of hessian evaluations.#numeric-optimizationOptimization result%numeric-optimization1Whether or not the optimizer exited successfully.&numeric-optimization,Description of the cause of the termination.'numeric-optimizationSolution(numeric-optimization&Value of the function at the solution.)numeric-optimizationGradient at the solution*numeric-optimization1Hessian at the solution; may be an approximation.+numeric-optimization Double rosenbrock [x,y] = sq (1 - x) + 100 * sq (y - sq x) rosenbrock' :: Vector Double -> Vector Double rosenbrock' [x,y] = [ 2 * (1 - x) * (-1) + 100 * 2 * (y - sq x) * (-2) * x , 100 * 2 * (y - sq x) ] sq :: Floating a => a -> a sq x = x ** 29numeric-optimization'Numerical optimization algorithm to usenumeric-optimization,Parameters for optimization algorithms. Use  as a default.numeric-optimizationOptimization problem to solvenumeric-optimization Initial value:  !"#$%&'()*+,-./0132456789:9  78 13245-./0#$%&'()*+, !" 6 Safe-InferredÓ[\]^_`abã        !"##$%&'()*+,,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`á3numeric-optimization-0.1.0.0-96ugwwsWHbi3pCCtm3ozJONumeric.OptimizationPaths_numeric_optimization1data-default-class-0.1.2.0-CQYBH38PFES4dDyailJWvdData.Default.ClassdefDefaultWithConstraints WithBounds WithHessianWithGrad Constraint Optionally optionalDict HasHessianhessianhessianProductHasGradgradgrad'grad'M IsProblemfuncbounds constraintsOptimizationExceptionUnsupportedProblemUnsupportedMethodGradUnavailableHessianUnavailable Statistics totalIters funcEvals gradEvals hessEvalsResult resultSuccess resultMessageresultSolution resultValue resultGrad resultHessianresultHessianInvresultStatisticsParamsparamsCallback paramsTolMethod CGDescentLBFGSNewtonisSupportedMethodhasOptionalDictboundsUnconstrainedisUnconstainedBoundsminimize$fContravariantParams$fDefaultParams$fFunctorResult $fExceptionOptimizationException$fIsProblemFUN$fOptionallyHasHessian$fOptionallyHasGrad$fOptionallyHasHessian0$fOptionallyHasGrad0$fHasHessianWithGrad$fHasGradWithGrad$fIsProblemWithGrad$fOptionallyHasHessian1$fOptionallyHasGrad1$fHasHessianWithHessian$fHasGradWithHessian$fIsProblemWithHessian$fOptionallyHasHessian2$fOptionallyHasGrad2$fHasHessianWithBounds$fHasGradWithBounds$fIsProblemWithBounds$fOptionallyHasHessian3$fOptionallyHasGrad3$fHasHessianWithConstraints$fHasGradWithConstraints$fIsProblemWithConstraints$fShowOptimizationException $fEqMethod $fOrdMethod $fEnumMethod $fShowMethod$fBoundedMethodversiongetDataFileName getBinDir getLibDir getDynLibDir getDataDir getLibexecDir getSysconfDir