% Starting Algorithm: 
%	className: org.openda.algorithms.Dud
%	dir.: /home/verlaanm/tudelft/svn_costa/trunk/openda/tests/l21triad/./algorithm
%	config.: dudWithConstr.xml
% configstring = dudWithConstr.xml
% opening :/home/verlaanm/tudelft/svn_costa/trunk/openda/tests/l21triad/./algorithm/dudWithConstr.xml
% Dud initialized
% Application initializing finished
% Initializing application
% Dud preparation
% Retrieving initial parameters from model
% Starting optimizer
% costFunction@class=org.openda.algorithms.SimulationKwadraticCostFunction
% costFunction@weakParameterConstraint=true
% costFunction@factor=0.5
% ========================================================================
% no1
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{1}	=[0.05,2.5];
costWeakConstraintPenalty{1}	=0.0;
predicted{1}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3366,1.6621,0.02581,2.0081,1.2385,1.5915,0.02517,2.0081,1.1647,1.5353,0.02315,2.0081,1.0781,1.4673,0.02161,2.0081,1.0196,1.3941,0.02115,2.0081,0.9919,1.3446];
observed{1}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{1}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024599999999999955,0.005900000000000016,0.00119,-0.008100000000000218,-0.25149999999999995,-0.0044999999999999485,0.0018299999999999983,-0.008100000000000218,-0.22570000000000012,-0.02430000000000021,0.001850000000000001,-0.008100000000000218,-0.09310000000000007,-0.03930000000000011,0.0023899999999999998,-0.008100000000000218,0.019399999999999862,0.027900000000000036,0.002850000000000002,-0.008100000000000218,0.0250999999999999,0.04339999999999988];
obs_stdev{1}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{1}	=8.640480586480448;
costTotal{1}	=8.640480586480448;
% SimulationKwadraticCostFunction: evaluation 1 : cost = 8.640480586480448
% ========================================================================
% no2
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{2}	=[0.05500000007450581,2.5];
costWeakConstraintPenalty{2}	=0.5000000000000004;
predicted{2}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.6619,0.02584,2.0081,1.2283,1.5843,0.02523,2.0081,1.1457,1.5239,0.02323,2.0081,1.0604,1.454,0.02173,2.0081,1.0023,1.3794,0.02128,2.0081,0.9756,1.3298];
observed{2}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{2}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006099999999999994,0.0011600000000000013,-0.008100000000000218,-0.24129999999999996,0.0026999999999999247,0.0017700000000000007,-0.008100000000000218,-0.2067,-0.012900000000000134,0.0017700000000000007,-0.008100000000000218,-0.07540000000000002,-0.026000000000000023,0.002270000000000001,-0.008100000000000218,0.036699999999999955,0.04259999999999997,0.00272,-0.008100000000000218,0.04139999999999988,0.05819999999999981];
obs_stdev{2}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{2}	=7.739612005289244;
costTotal{2}	=8.239612005289244;
% SimulationKwadraticCostFunction: evaluation 2 : cost = 8.239612005289244
% ========================================================================
% no3
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{3}	=[0.05,2.7500000037252903];
costWeakConstraintPenalty{3}	=0.5;
predicted{3}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3365,1.6621,0.02588,2.0081,1.2123,1.5821,0.02534,2.0081,1.1048,1.5117,0.02339,2.0081,1.0134,1.4366,0.02192,2.0081,0.9562,1.3599,0.02146,2.0081,0.9316,1.3109];
observed{3}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{3}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024499999999999966,0.005900000000000016,0.0011199999999999995,-0.008100000000000218,-0.22529999999999994,0.004899999999999904,0.0016599999999999983,-0.008100000000000218,-0.16580000000000006,-7.00000000000145E-4,0.0016100000000000003,-0.008100000000000218,-0.028400000000000092,-0.008600000000000163,0.002080000000000002,-0.008100000000000218,0.08279999999999987,0.06209999999999982,0.0025400000000000006,-0.008100000000000218,0.08539999999999992,0.07709999999999995];
obs_stdev{3}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{3}	=6.635494326667225;
costTotal{3}	=7.135494326667225;
% SimulationKwadraticCostFunction: evaluation 3 : cost = 7.135494326667225
% outerLoop@maxIterations=20
% outerLoop@absTolerance=0.0010
% outerLoop@relTolerance=0.0
% lineSearch@maxIterations=5
% lineSearch@maxRelStepSize=10.0
% lineSearch/backtracking@startIterationNegativeLook=3
% lineSearch/backtracking@shorteningFactor=0.5
% Application initialized
% Application starting next step
% ======================================================
% DUD outer iteration no.1
% ======================================================
% -----------------------------------------------------
costs{1}	=[7.135494326667225,8.239612005289244,8.640480586480448];
% -----------------------------------------------------
% Start search until improvement,
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05189047522511055]
%	TreeVector TRIAD.cutfr [2.737135882726282] , delta_p= TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.001890475225110545]
%	TreeVector TRIAD.cutfr [-0.012864120999008022]
% ========================================================================
% no4
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{4}	=[0.05189047522511055,2.737135882726282];
costWeakConstraintPenalty{4}	=0.521345331008818;
predicted{4}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0077,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{4}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{4}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022700000000000053,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{4}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{4}	=6.503431999769555;
costTotal{4}	=7.024777330778373;
% SimulationKwadraticCostFunction: evaluation 4 : cost = 7.024777330778373
%      cost =7.024777330778373
% Error estimate for this outer iteration
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
parameterErrorEstimateStd{1}	=[0.004838508955058822,0.15529043620626262];
parameterErrorCorrelations{1}	=[1.0,-0.31182718303972345;-0.3118271830397231,1.0];
% Application starting next step
% ======================================================
% DUD outer iteration no.2
% ======================================================
% -----------------------------------------------------
costs{2}	=[7.024777330778373,7.135494326667225,8.239612005289244];
% -----------------------------------------------------
% Start search until improvement,
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05220914104520144]
%	TreeVector TRIAD.cutfr [2.735732781942702] , delta_p= TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [3.186658200908964E-4]
%	TreeVector TRIAD.cutfr [-0.0014031007835799167]
% ========================================================================
% no5
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{5}	=[0.05220914104520144,2.735732781942702];
costWeakConstraintPenalty{5}	=0.5421656228536438;
predicted{5}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2075,1.5788,0.02536,2.0081,1.0985,1.5072,0.02343,2.0081,1.0068,1.4312,0.02196,2.0081,0.9499,1.354,0.02151,2.0081,0.9256,1.3051];
observed{5}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{5}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22050000000000003,0.008199999999999985,0.001639999999999999,-0.008100000000000218,-0.1595000000000001,0.0037999999999998035,0.001570000000000002,-0.008100000000000218,-0.02179999999999993,-0.0032000000000000917,0.00204,-0.008100000000000218,0.08909999999999996,0.06799999999999984,0.002489999999999999,-0.008100000000000218,0.09139999999999993,0.08289999999999997];
obs_stdev{5}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{5}	=6.483993006294035;
costTotal{5}	=7.026158629147679;
% SimulationKwadraticCostFunction: evaluation 5 : cost = 7.026158629147679
%      cost =7.026158629147679
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05220914104520144]
%	TreeVector TRIAD.cutfr [2.735732781942702]
% ========================================================================
% no6
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{6}	=[0.052049808135155994,2.7364343323344924];
costWeakConstraintPenalty{6}	=0.531243800038392;
predicted{6}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2079,1.579,0.02536,2.0081,1.0989,1.5076,0.02342,2.0081,1.0072,1.4316,0.02196,2.0081,0.9503,1.3544,0.02151,2.0081,0.926,1.3055];
observed{6}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{6}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22089999999999999,0.008000000000000007,0.001639999999999999,-0.008100000000000218,-0.15990000000000004,0.0033999999999998476,0.0015800000000000015,-0.008100000000000218,-0.02220000000000011,-0.0036000000000000476,0.00204,-0.008100000000000218,0.08869999999999989,0.06759999999999988,0.002489999999999999,-0.008100000000000218,0.09099999999999986,0.0824999999999998];
obs_stdev{6}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{6}	=6.4937869473603875;
costTotal{6}	=7.025030747398779;
% SimulationKwadraticCostFunction: evaluation 6 : cost = 7.025030747398779
%      cost =7.025030747398779
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.052049808135155994]
%	TreeVector TRIAD.cutfr [2.7364343323344924]
% ========================================================================
% no7
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{7}	=[0.051970141680133274,2.736785107530387];
costWeakConstraintPenalty{7}	=0.5261666463003946;
predicted{7}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.208,1.5792,0.02536,2.0081,1.0991,1.5077,0.02342,2.0081,1.0074,1.4318,0.02196,2.0081,0.9505,1.3546,0.0215,2.0081,0.9262,1.3057];
observed{7}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{7}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22099999999999997,0.007800000000000029,0.001639999999999999,-0.008100000000000218,-0.16010000000000002,0.0032999999999998586,0.0015800000000000015,-0.008100000000000218,-0.022400000000000087,-0.0038000000000000256,0.00204,-0.008100000000000218,0.08849999999999991,0.0673999999999999,0.0025000000000000022,-0.008100000000000218,0.09079999999999988,0.08229999999999982];
obs_stdev{7}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{7}	=6.49951222276976;
costTotal{7}	=7.025678869070155;
% SimulationKwadraticCostFunction: evaluation 7 : cost = 7.025678869070155
%      cost =7.025678869070155
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.051970141680133274]
%	TreeVector TRIAD.cutfr [2.736785107530387]
% ========================================================================
% no8
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{8}	=[0.05193030845262191,2.7369604951283346];
costWeakConstraintPenalty{8}	=0.5237240088488033;
predicted{8}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2081,1.5792,0.02536,2.0081,1.0992,1.5078,0.02342,2.0081,1.0075,1.4318,0.02196,2.0081,0.9506,1.3547,0.0215,2.0081,0.9263,1.3058];
observed{8}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{8}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22109999999999996,0.007800000000000029,0.001639999999999999,-0.008100000000000218,-0.1602,0.0031999999999998696,0.0015800000000000015,-0.008100000000000218,-0.022500000000000075,-0.0038000000000000256,0.00204,-0.008100000000000218,0.08839999999999992,0.06729999999999992,0.0025000000000000022,-0.008100000000000218,0.09069999999999989,0.08219999999999983];
obs_stdev{8}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{8}	=6.501358063374103;
costTotal{8}	=7.025082072222906;
% SimulationKwadraticCostFunction: evaluation 8 : cost = 7.025082072222906
%      cost =7.025082072222906
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05193030845262191]
%	TreeVector TRIAD.cutfr [2.7369604951283346]
% ========================================================================
% no9
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{9}	=[0.05191039183886623,2.7370481889273086];
costWeakConstraintPenalty{9}	=0.5225266749773608;
predicted{9}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5078,0.02342,2.0081,1.0076,1.4319,0.02196,2.0081,0.9506,1.3548,0.0215,2.0081,0.9264,1.3058];
observed{9}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{9}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0031999999999998696,0.0015800000000000015,-0.008100000000000218,-0.022600000000000064,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08839999999999992,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08219999999999983];
obs_stdev{9}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{9}	=6.504457175409871;
costTotal{9}	=7.026983850387232;
% SimulationKwadraticCostFunction: evaluation 9 : cost = 7.026983850387232
%      cost =7.026983850387232
% Cost is worse! Reducing stepsize.
% Start looking in negative direction
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05191039183886623]
%	TreeVector TRIAD.cutfr [2.7370481889273086]
% ========================================================================
% no10
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{10}	=[0.05188051691823271,2.737179729625769];
costWeakConstraintPenalty{10}	=0.5207606552381342;
predicted{10}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0994,1.5079,0.02342,2.0081,1.0077,1.432,0.02196,2.0081,0.9507,1.3549,0.0215,2.0081,0.9265,1.3059];
observed{10}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{10}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1604,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022700000000000053,-0.0040000000000000036,0.00204,-0.008100000000000218,0.08829999999999993,0.06709999999999994,0.0025000000000000022,-0.008100000000000218,0.09049999999999991,0.08209999999999984];
obs_stdev{10}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{10}	=6.504062408944981;
costTotal{10}	=7.024823064183115;
% SimulationKwadraticCostFunction: evaluation 10 : cost = 7.024823064183115
%      cost =7.024823064183115
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05188051691823271]
%	TreeVector TRIAD.cutfr [2.737179729625769]
% ========================================================================
% no11
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{11}	=[0.05189545437854947,2.7371139592765386];
costWeakConstraintPenalty{11}	=0.5216391679475559;
predicted{11}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0076,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{11}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{11}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022600000000000064,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{11}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{11}	=6.503198548772881;
costTotal{11}	=7.0248377167204366;
% SimulationKwadraticCostFunction: evaluation 11 : cost = 7.0248377167204366
%      cost =7.0248377167204366
% Error estimate for this outer iteration
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
parameterErrorEstimateStd{2}	=[0.004758965721061722,0.1511732248281967];
parameterErrorCorrelations{2}	=[1.0000000000000002,-0.40790309394169255;-0.40790309394169216,1.0000000000000002];
% Application starting next step
% ======================================================
% DUD outer iteration no.3
% ======================================================
% -----------------------------------------------------
costs{3}	=[7.024777330778373,7.0248377167204366,7.135494326667225];
% -----------------------------------------------------
% Start search until improvement,
% % Reducing stepsize! Relative step was:[-157.19154452083498,-0.5906062186323136]
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05191171336521965]
%	TreeVector TRIAD.cutfr [2.7368717814385515] , delta_p= TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [2.1238140109104503E-5]
%	TreeVector TRIAD.cutfr [-2.641012877304887E-4]
% ========================================================================
% no12
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{12}	=[0.05191171336521965,2.7368717814385515];
costWeakConstraintPenalty{12}	=0.5219588709945853;
predicted{12}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5078,0.02342,2.0081,1.0076,1.4319,0.02196,2.0081,0.9506,1.3548,0.0215,2.0081,0.9264,1.3058];
observed{12}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{12}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0031999999999998696,0.0015800000000000015,-0.008100000000000218,-0.022600000000000064,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08839999999999992,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08219999999999983];
obs_stdev{12}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{12}	=6.504457175409871;
costTotal{12}	=7.0264160464044565;
% SimulationKwadraticCostFunction: evaluation 12 : cost = 7.0264160464044565
%      cost =7.0264160464044565
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05191171336521965]
%	TreeVector TRIAD.cutfr [2.7368717814385515]
% ========================================================================
% no13
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{13}	=[0.051879856155056,2.7372679333701475];
costWeakConstraintPenalty{13}	=0.5210457453915908;
predicted{13}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0994,1.5079,0.02342,2.0081,1.0077,1.432,0.02196,2.0081,0.9507,1.3549,0.0215,2.0081,0.9265,1.3059];
observed{13}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{13}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1604,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022700000000000053,-0.0040000000000000036,0.00204,-0.008100000000000218,0.08829999999999993,0.06709999999999994,0.0025000000000000022,-0.008100000000000218,0.09049999999999991,0.08209999999999984];
obs_stdev{13}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{13}	=6.504062408944981;
costTotal{13}	=7.025108154336572;
% SimulationKwadraticCostFunction: evaluation 13 : cost = 7.025108154336572
%      cost =7.025108154336572
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.051879856155056]
%	TreeVector TRIAD.cutfr [2.7372679333701475]
% ========================================================================
% no14
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{14}	=[0.05189578476013782,2.7370698574043497];
costWeakConstraintPenalty{14}	=0.5214969199113464;
predicted{14}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0076,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{14}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{14}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022600000000000064,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{14}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{14}	=6.503198548772881;
costTotal{14}	=7.024695468684227;
% SimulationKwadraticCostFunction: evaluation 14 : cost = 7.024695468684227
%      cost =7.024695468684227
% Error estimate for this outer iteration
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
parameterErrorEstimateStd{3}	=[0.004655853716222958,0.03438619136554154];
parameterErrorCorrelations{3}	=[0.9999999999999998,-0.9267945013788268;-0.926794501378823,0.9999999999999998];
% Application starting next step
% ======================================================
% DUD outer iteration no.4
% ======================================================
% -----------------------------------------------------
costs{4}	=[7.024695468684227,7.024777330778373,7.0248377167204366];
% -----------------------------------------------------
% Start search until improvement,
% % Reducing stepsize! Relative step was:[209.99920216600515,-4699.0512565318895]
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05189671576061939]
%	TreeVector TRIAD.cutfr [2.7366583452023345] , delta_p= TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [9.310004815704373E-7]
%	TreeVector TRIAD.cutfr [-4.1151220201527457E-4]
% ========================================================================
% no15
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{15}	=[0.05189671576061939,2.7366583452023345];
costWeakConstraintPenalty{15}	=0.5200079768654527;
predicted{15}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0076,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{15}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{15}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022600000000000064,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{15}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{15}	=6.503198548772881;
costTotal{15}	=7.023206525638334;
% SimulationKwadraticCostFunction: evaluation 15 : cost = 7.023206525638334
%      cost =7.023206525638334
% Error estimate for this outer iteration
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
parameterErrorEstimateStd{4}	=[0.0035588398124197004,0.045673756642084194];
parameterErrorCorrelations{4}	=[1.0,-1.0;-0.9999999999999999,1.0];
% Application starting next step
% ======================================================
% DUD outer iteration no.5
% ======================================================
% -----------------------------------------------------
costs{5}	=[7.023206525638334,7.024695468684227,7.024777330778373];
% -----------------------------------------------------
% Start search until improvement,
% % Reducing stepsize! Relative step was:[-697.3386824314414,126.17106049794393]
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05189473462379813]
%	TreeVector TRIAD.cutfr [2.733407242594012] , delta_p= TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [-1.9811368212631054E-6]
%	TreeVector TRIAD.cutfr [-0.003251102608322377]
% ========================================================================
% no16
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{16}	=[0.05189473462379813,2.733407242594012];
costWeakConstraintPenalty{16}	=0.5076318979264992;
predicted{16}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2092,1.5796,0.02536,2.0081,1.0996,1.508,0.02342,2.0081,1.0075,1.4319,0.02196,2.0081,0.9505,1.3548,0.0215,2.0081,0.9263,1.3059];
observed{16}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{16}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22220000000000006,0.007400000000000073,0.001639999999999999,-0.008100000000000218,-0.16059999999999997,0.0029999999999998916,0.0015800000000000015,-0.008100000000000218,-0.022500000000000075,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08849999999999991,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.09069999999999989,0.08209999999999984];
obs_stdev{16}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{16}	=6.53359411565432;
costTotal{16}	=7.041226013580819;
% SimulationKwadraticCostFunction: evaluation 16 : cost = 7.041226013580819
%      cost =7.041226013580819
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05189473462379813]
%	TreeVector TRIAD.cutfr [2.733407242594012]
% ========================================================================
% no17
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{17}	=[0.05189770632903002,2.7382838965064957];
costWeakConstraintPenalty{17}	=0.5262594932156035;
predicted{17}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0076,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{17}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{17}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022600000000000064,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{17}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{17}	=6.503198548772881;
costTotal{17}	=7.029458041988484;
% SimulationKwadraticCostFunction: evaluation 17 : cost = 7.029458041988484
%      cost =7.029458041988484
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05189770632903002]
%	TreeVector TRIAD.cutfr [2.7382838965064957]
% ========================================================================
% no18
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{18}	=[0.051896220476414075,2.735845569550254];
costWeakConstraintPenalty{18}	=0.5168980879105459;
predicted{18}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0076,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{18}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{18}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022600000000000064,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{18}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{18}	=6.503198548772881;
costTotal{18}	=7.0200966366834265;
% SimulationKwadraticCostFunction: evaluation 18 : cost = 7.0200966366834265
%      cost =7.0200966366834265
% Error estimate for this outer iteration
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
parameterErrorEstimateStd{5}	=[0.0035752020719090082,0.2492170742845169];
parameterErrorCorrelations{5}	=[1.0,-0.0775579773783975;-0.07755797737839738,1.0];
% Application starting next step
% ======================================================
% DUD outer iteration no.6
% ======================================================
% -----------------------------------------------------
costs{6}	=[7.0200966366834265,7.023206525638334,7.024695468684227];
% -----------------------------------------------------
% Start search until improvement,
% % Reducing stepsize! Relative step was:[-2523.9522829136026,1482.9530383245335]
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.051888707574964825]
%	TreeVector TRIAD.cutfr [2.7349111399608086] , delta_p= TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [-7.512901449250497E-6]
%	TreeVector TRIAD.cutfr [-9.344295894453238E-4]
% ========================================================================
% no19
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{19}	=[0.051888707574964825,2.7349111399608086];
costWeakConstraintPenalty{19}	=0.5128102602131459;
predicted{19}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.208,1.5792,0.02536,2.0081,1.0987,1.5077,0.02343,2.0081,1.0067,1.4315,0.02196,2.0081,0.9498,1.3543,0.02151,2.0081,0.9256,1.3054];
observed{19}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{19}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22099999999999997,0.007800000000000029,0.001639999999999999,-0.008100000000000218,-0.15970000000000006,0.0032999999999998586,0.001570000000000002,-0.008100000000000218,-0.02169999999999994,-0.0035000000000000586,0.00204,-0.008100000000000218,0.08919999999999995,0.06769999999999987,0.002489999999999999,-0.008100000000000218,0.09139999999999993,0.0826];
obs_stdev{19}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{19}	=6.497094294822723;
costTotal{19}	=7.009904555035869;
% SimulationKwadraticCostFunction: evaluation 19 : cost = 7.009904555035869
%      cost =7.009904555035869
% Error estimate for this outer iteration
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
parameterErrorEstimateStd{6}	=[1.5160022871628638E-5,0.24999885459119905];
parameterErrorCorrelations{6}	=[0.9999999999999999,-0.9999999999999983;-1.0000000000000013,1.0000000000000002];
% Application starting next step
% ======================================================
% DUD outer iteration no.7
% ======================================================
% -----------------------------------------------------
costs{7}	=[7.009904555035869,7.0200966366834265,7.023206525638334];
% -----------------------------------------------------
% Start search until improvement,
% % Reducing stepsize! Relative step was:[250.95375589100175,-270.06817425968694]
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.051878437381400064]
%	TreeVector TRIAD.cutfr [2.726122029018746] , delta_p= TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [-1.0270193564758658E-5]
%	TreeVector TRIAD.cutfr [-0.008789110942062698]
% ========================================================================
% no20
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{20}	=[0.051878437381400064,2.726122029018746];
costWeakConstraintPenalty{20}	=0.47961990168347146;
predicted{20}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02588,2.0081,1.2092,1.5796,0.02535,2.0081,1.1015,1.5086,0.02341,2.0081,1.0096,1.4328,0.02195,2.0081,0.9526,1.3558,0.02149,2.0081,0.9282,1.3069];
observed{20}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{20}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011199999999999995,-0.008100000000000218,-0.22220000000000006,0.007400000000000073,0.0016499999999999987,-0.008100000000000218,-0.16249999999999998,0.0023999999999999577,0.0015900000000000011,-0.008100000000000218,-0.024600000000000066,-0.0048000000000001375,0.0020499999999999997,-0.008100000000000218,0.08639999999999992,0.06620000000000004,0.002510000000000002,-0.008100000000000218,0.08879999999999988,0.08109999999999995];
obs_stdev{20}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{20}	=6.546812741777504;
costTotal{20}	=7.026432643460976;
% SimulationKwadraticCostFunction: evaluation 20 : cost = 7.026432643460976
%      cost =7.026432643460976
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.051878437381400064]
%	TreeVector TRIAD.cutfr [2.726122029018746]
% ========================================================================
% no21
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{21}	=[0.0518938426717472,2.73930569543184];
costWeakConstraintPenalty{21}	=0.529870512444172;
predicted{21}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0076,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{21}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{21}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022600000000000064,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{21}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{21}	=6.503198548772881;
costTotal{21}	=7.033069061217053;
% SimulationKwadraticCostFunction: evaluation 21 : cost = 7.033069061217053
%      cost =7.033069061217053
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.0518938426717472]
%	TreeVector TRIAD.cutfr [2.73930569543184]
% ========================================================================
% no22
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{22}	=[0.051886140026573636,2.732713862225293];
costWeakConstraintPenalty{22}	=0.5043964023391801;
predicted{22}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2092,1.5796,0.02536,2.0081,1.0996,1.508,0.02342,2.0081,1.0075,1.4319,0.02196,2.0081,0.9506,1.3548,0.0215,2.0081,0.9263,1.3059];
observed{22}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{22}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22220000000000006,0.007400000000000073,0.001639999999999999,-0.008100000000000218,-0.16059999999999997,0.0029999999999998916,0.0015800000000000015,-0.008100000000000218,-0.022500000000000075,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08839999999999992,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.09069999999999989,0.08209999999999984];
obs_stdev{22}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{22}	=6.5327747708026305;
costTotal{22}	=7.037171173141811;
% SimulationKwadraticCostFunction: evaluation 22 : cost = 7.037171173141811
%      cost =7.037171173141811
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.051886140026573636]
%	TreeVector TRIAD.cutfr [2.732713862225293]
% ========================================================================
% no23
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{23}	=[0.05188999134916042,2.736009778828566];
costWeakConstraintPenalty{23}	=0.517046256210515;
predicted{23}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0077,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{23}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{23}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022700000000000053,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{23}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{23}	=6.503431999769555;
costTotal{23}	=7.02047825598007;
% SimulationKwadraticCostFunction: evaluation 23 : cost = 7.02047825598007
%      cost =7.02047825598007
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05188999134916042]
%	TreeVector TRIAD.cutfr [2.736009778828566]
% ========================================================================
% no24
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{24}	=[0.051888065687867024,2.7343618205269298];
costWeakConstraintPenalty{24}	=0.5106995289795582;
predicted{24}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2092,1.5796,0.02536,2.0081,1.0997,1.5081,0.02342,2.0081,1.0079,1.4321,0.02195,2.0081,0.951,1.355,0.0215,2.0081,0.9267,1.3061];
observed{24}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{24}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22220000000000006,0.007400000000000073,0.001639999999999999,-0.008100000000000218,-0.16069999999999995,0.0028999999999999027,0.0015800000000000015,-0.008100000000000218,-0.02290000000000003,-0.0040999999999999925,0.0020499999999999997,-0.008100000000000218,0.08799999999999997,0.06699999999999995,0.0025000000000000022,-0.008100000000000218,0.09029999999999994,0.08189999999999986];
obs_stdev{24}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{24}	=6.530826256838644;
costTotal{24}	=7.041525785818202;
% SimulationKwadraticCostFunction: evaluation 24 : cost = 7.041525785818202
%      cost =7.041525785818202
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.051888065687867024]
%	TreeVector TRIAD.cutfr [2.7343618205269298]
% ========================================================================
% no25
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{25}	=[0.05188902851851372,2.735185799677748];
costWeakConstraintPenalty{25}	=0.5138674425212137;
predicted{25}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0077,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{25}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{25}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022700000000000053,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{25}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{25}	=6.503431999769555;
costTotal{25}	=7.017299442290769;
% SimulationKwadraticCostFunction: evaluation 25 : cost = 7.017299442290769
%      cost =7.017299442290769
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05188902851851372]
%	TreeVector TRIAD.cutfr [2.735185799677748]
% ========================================================================
% no26
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{26}	=[0.05188854710319037,2.7347738101023387];
costWeakConstraintPenalty{26}	=0.5122821232319296;
predicted{26}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.208,1.5792,0.02536,2.0081,1.0987,1.5077,0.02343,2.0081,1.0067,1.4315,0.02196,2.0081,0.9498,1.3543,0.02151,2.0081,0.9256,1.3054];
observed{26}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{26}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22099999999999997,0.007800000000000029,0.001639999999999999,-0.008100000000000218,-0.15970000000000006,0.0032999999999998586,0.001570000000000002,-0.008100000000000218,-0.02169999999999994,-0.0035000000000000586,0.00204,-0.008100000000000218,0.08919999999999995,0.06769999999999987,0.002489999999999999,-0.008100000000000218,0.09139999999999993,0.0826];
obs_stdev{26}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{26}	=6.497094294822723;
costTotal{26}	=7.009376418054653;
% SimulationKwadraticCostFunction: evaluation 26 : cost = 7.009376418054653
%      cost =7.009376418054653
% Error estimate for this outer iteration
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
parameterErrorEstimateStd{7}	=[4.0795566324317343E-4,0.24988470700378854];
parameterErrorCorrelations{7}	=[1.0,0.3711165870613376;0.3711165870613364,0.9999999999999999];
% Application starting next step
% ======================================================
% DUD outer iteration no.8
% ======================================================
% -----------------------------------------------------
costs{8}	=[7.009376418054653,7.009904555035869,7.0200966366834265];
% -----------------------------------------------------
% Start search until improvement,
% % Reducing stepsize! Relative step was:[-1593.5616631876314,-18.918498367720495]
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.0518860314153707]
%	TreeVector TRIAD.cutfr [2.7332732740229484] , delta_p= TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [-2.5156878196719456E-6]
%	TreeVector TRIAD.cutfr [-0.001500536079390333]
% ========================================================================
% no27
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{27}	=[0.0518860314153707,2.7332732740229484];
costWeakConstraintPenalty{27}	=0.5064736378882979;
predicted{27}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2092,1.5796,0.02536,2.0081,1.0996,1.508,0.02342,2.0081,1.0075,1.4319,0.02196,2.0081,0.9506,1.3548,0.0215,2.0081,0.9263,1.3059];
observed{27}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{27}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22220000000000006,0.007400000000000073,0.001639999999999999,-0.008100000000000218,-0.16059999999999997,0.0029999999999998916,0.0015800000000000015,-0.008100000000000218,-0.022500000000000075,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08839999999999992,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.09069999999999989,0.08209999999999984];
obs_stdev{27}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{27}	=6.5327747708026305;
costTotal{27}	=7.039248408690929;
% SimulationKwadraticCostFunction: evaluation 27 : cost = 7.039248408690929
%      cost =7.039248408690929
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.0518860314153707]
%	TreeVector TRIAD.cutfr [2.7332732740229484]
% ========================================================================
% no28
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{28}	=[0.05188980494710021,2.735524078142034];
costWeakConstraintPenalty{28}	=0.5151999704847721;
predicted{28}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2082,1.5793,0.02536,2.0081,1.0993,1.5079,0.02342,2.0081,1.0077,1.4319,0.02196,2.0081,0.9507,1.3548,0.0215,2.0081,0.9264,1.3059];
observed{28}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{28}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22119999999999995,0.00770000000000004,0.001639999999999999,-0.008100000000000218,-0.1603,0.0030999999999998806,0.0015800000000000015,-0.008100000000000218,-0.022700000000000053,-0.0039000000000000146,0.00204,-0.008100000000000218,0.08829999999999993,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.0905999999999999,0.08209999999999984];
obs_stdev{28}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{28}	=6.503431999769555;
costTotal{28}	=7.018631970254328;
% SimulationKwadraticCostFunction: evaluation 28 : cost = 7.018631970254328
%      cost =7.018631970254328
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05188980494710021]
%	TreeVector TRIAD.cutfr [2.735524078142034]
% ========================================================================
% no29
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{29}	=[0.051887918181235455,2.734398676082491];
costWeakConstraintPenalty{29}	=0.5108266007507647;
predicted{29}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2092,1.5796,0.02536,2.0081,1.0998,1.5081,0.02342,2.0081,1.0079,1.4321,0.02195,2.0081,0.951,1.355,0.0215,2.0081,0.9267,1.3061];
observed{29}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{29}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22220000000000006,0.007400000000000073,0.001639999999999999,-0.008100000000000218,-0.16080000000000017,0.0028999999999999027,0.0015800000000000015,-0.008100000000000218,-0.02290000000000003,-0.0040999999999999925,0.0020499999999999997,-0.008100000000000218,0.08799999999999997,0.06699999999999995,0.0025000000000000022,-0.008100000000000218,0.09029999999999994,0.08189999999999986];
obs_stdev{29}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{29}	=6.532649395849847;
costTotal{29}	=7.043475996600612;
% SimulationKwadraticCostFunction: evaluation 29 : cost = 7.043475996600612
%      cost =7.043475996600612
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.051887918181235455]
%	TreeVector TRIAD.cutfr [2.734398676082491]
% ========================================================================
% no30
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{30}	=[0.05188886156416783,2.7349613771122625];
costWeakConstraintPenalty{30}	=0.5130107347588259;
predicted{30}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.208,1.5792,0.02536,2.0081,1.0987,1.5077,0.02343,2.0081,1.0067,1.4315,0.02196,2.0081,0.9498,1.3543,0.02151,2.0081,0.9256,1.3054];
observed{30}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{30}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22099999999999997,0.007800000000000029,0.001639999999999999,-0.008100000000000218,-0.15970000000000006,0.0032999999999998586,0.001570000000000002,-0.008100000000000218,-0.02169999999999994,-0.0035000000000000586,0.00204,-0.008100000000000218,0.08919999999999995,0.06769999999999987,0.002489999999999999,-0.008100000000000218,0.09139999999999993,0.0826];
obs_stdev{30}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{30}	=6.497094294822723;
costTotal{30}	=7.010105029581549;
% SimulationKwadraticCostFunction: evaluation 30 : cost = 7.010105029581549
%      cost =7.010105029581549
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05188886156416783]
%	TreeVector TRIAD.cutfr [2.7349613771122625]
% ========================================================================
% no31
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{31}	=[0.05188838987270164,2.7346800265973767];
costWeakConstraintPenalty{31}	=0.5119180300400594;
predicted{31}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.2092,1.5796,0.02536,2.0081,1.0996,1.508,0.02342,2.0081,1.0076,1.432,0.02196,2.0081,0.9506,1.3548,0.0215,2.0081,0.9263,1.3059];
observed{31}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{31}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22220000000000006,0.007400000000000073,0.001639999999999999,-0.008100000000000218,-0.16059999999999997,0.0029999999999998916,0.0015800000000000015,-0.008100000000000218,-0.022600000000000064,-0.0040000000000000036,0.00204,-0.008100000000000218,0.08839999999999992,0.06719999999999993,0.0025000000000000022,-0.008100000000000218,0.09069999999999989,0.08209999999999984];
obs_stdev{31}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{31}	=6.533026561603297;
costTotal{31}	=7.044944591643356;
% SimulationKwadraticCostFunction: evaluation 31 : cost = 7.044944591643356
%      cost =7.044944591643356
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05188838987270164]
%	TreeVector TRIAD.cutfr [2.7346800265973767]
% ========================================================================
% no32
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{32}	=[0.051888625718434736,2.7348207018548196];
costWeakConstraintPenalty{32}	=0.512464222970759;
predicted{32}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.208,1.5792,0.02536,2.0081,1.0987,1.5077,0.02343,2.0081,1.0067,1.4315,0.02196,2.0081,0.9498,1.3543,0.02151,2.0081,0.9256,1.3054];
observed{32}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{32}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22099999999999997,0.007800000000000029,0.001639999999999999,-0.008100000000000218,-0.15970000000000006,0.0032999999999998586,0.001570000000000002,-0.008100000000000218,-0.02169999999999994,-0.0035000000000000586,0.00204,-0.008100000000000218,0.08919999999999995,0.06769999999999987,0.002489999999999999,-0.008100000000000218,0.09139999999999993,0.0826];
obs_stdev{32}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{32}	=6.497094294822723;
costTotal{32}	=7.009558517793482;
% SimulationKwadraticCostFunction: evaluation 32 : cost = 7.009558517793482
%      cost =7.009558517793482
% Cost is worse! Reducing stepsize.
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.051888625718434736]
%	TreeVector TRIAD.cutfr [2.7348207018548196]
% ========================================================================
% no33
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{33}	=[0.05188850779556819,2.734750364226098];
costWeakConstraintPenalty{33}	=0.5121910866482381;
predicted{33}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.208,1.5792,0.02536,2.0081,1.0987,1.5077,0.02343,2.0081,1.0067,1.4315,0.02196,2.0081,0.9498,1.3543,0.02151,2.0081,0.9256,1.3054];
observed{33}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{33}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22099999999999997,0.007800000000000029,0.001639999999999999,-0.008100000000000218,-0.15970000000000006,0.0032999999999998586,0.001570000000000002,-0.008100000000000218,-0.02169999999999994,-0.0035000000000000586,0.00204,-0.008100000000000218,0.08919999999999995,0.06769999999999987,0.002489999999999999,-0.008100000000000218,0.09139999999999993,0.0826];
obs_stdev{33}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{33}	=6.497094294822723;
costTotal{33}	=7.009285381470962;
% SimulationKwadraticCostFunction: evaluation 33 : cost = 7.009285381470962
%      cost =7.009285381470962
% Error estimate for this outer iteration
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
parameterErrorEstimateStd{8}	=[4.550169277045319E-4,0.24957648386789816];
parameterErrorCorrelations{8}	=[0.9999999999999999,0.637779948615387;0.6377799486153863,1.0000000000000002];
% Application starting next step
% ======================================================
% DUD outer iteration no.9
% ======================================================
% -----------------------------------------------------
costs{9}	=[7.009285381470962,7.009376418054653,7.009904555035869];
% -----------------------------------------------------
% Start search until improvement,
% % Reducing stepsize! Relative step was:[-156952.1041200909,21428.16669979426]
% Next try p=TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [0.05188838747174034]
%	TreeVector TRIAD.cutfr [2.7347354074107346] , delta_p= TreeVector swan-parameters, SubTreeVectors:
%	TreeVector TRIAD.trfac [-1.2032382784261384E-7]
%	TreeVector TRIAD.cutfr [-1.4956815363652596E-5]
% ========================================================================
% no34
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
evaluatedParameters{34}	=[0.05188838747174034,2.7347354074107346];
costWeakConstraintPenalty{34}	=0.5121258215442471;
predicted{34}	=[0.02321,2.0081,1.2787,1.6019,0.02279,2.0081,1.2716,1.5964,0.02422,2.0081,1.3364,1.662,0.02589,2.0081,1.208,1.5792,0.02536,2.0081,1.0987,1.5077,0.02343,2.0081,1.0067,1.4315,0.02196,2.0081,0.9498,1.3543,0.02151,2.0081,0.9256,1.3054];
observed{34}	=[0.023,2.0,1.265,1.603,0.023,2.0,1.265,1.603,0.025,2.0,1.312,1.668,0.027,2.0,0.987,1.587,0.027,2.0,0.939,1.511,0.025,2.0,0.985,1.428,0.024,2.0,1.039,1.422,0.024,2.0,1.017,1.388];
residuals{34}	=[-2.1000000000000185E-4,-0.008100000000000218,-0.013700000000000045,0.0010999999999998789,2.0999999999999838E-4,-0.008100000000000218,-0.006600000000000161,0.006599999999999939,7.800000000000029E-4,-0.008100000000000218,-0.024399999999999977,0.006000000000000005,0.0011099999999999999,-0.008100000000000218,-0.22099999999999997,0.007800000000000029,0.001639999999999999,-0.008100000000000218,-0.15970000000000006,0.0032999999999998586,0.001570000000000002,-0.008100000000000218,-0.02169999999999994,-0.0035000000000000586,0.00204,-0.008100000000000218,0.08919999999999995,0.06769999999999987,0.002489999999999999,-0.008100000000000218,0.09139999999999993,0.0826];
obs_stdev{34}	=[0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.0023000000342726706,0.20000000298023224,0.12650000188499688,0.16030000238865613,0.002500000037252903,0.20000000298023224,0.13120000195503234,0.1668000024855137,0.002700000040233135,0.20000000298023224,0.0987000014707446,0.15870000236481427,0.002700000040233135,0.20000000298023224,0.09390000139921903,0.15110000225156545,0.002500000037252903,0.20000000298023224,0.09850000146776437,0.14280000212788582,0.002400000035762787,0.20000000298023224,0.10390000154823065,0.14220000211894512,0.002400000035762787,0.20000000298023224,0.10170000151544809,0.13880000206828116];
costObserved{34}	=6.497094294822723;
costTotal{34}	=7.00922011636697;
% SimulationKwadraticCostFunction: evaluation 34 : cost = 7.00922011636697
%      cost =7.00922011636697
% Error estimate for this outer iteration
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
parameterErrorEstimateStd{9}	=[3.123001782738865E-4,0.24951187017709284];
parameterErrorCorrelations{9}	=[1.0,1.0;1.0,0.9999999999999999];
% ===================================================================
% SimulationKwadraticCostfunction:
% number of evaluations
% n = 34
% all cost values
% costs = [8.640480586480448,8.239612005289244,7.135494326667225,7.024777330778373,7.026158629147679,7.025030747398779,7.025678869070155,7.025082072222906,7.026983850387232,7.024823064183115,...,7.017299442290769,7.009376418054653,7.039248408690929,7.018631970254328,7.043475996600612,7.010105029581549,7.044944591643356,7.009558517793482,7.009285381470962,7.00922011636697]
% all parameter values
% parameters=[0.05,0.05500000007450581,0.05,0.05189047522511055,0.05220914104520144,0.052049808135155994,0.051970141680133274,0.05193030845262191,0.05191039183886623,0.05188051691823271,0.05189545437854947,0.05191171336521965,0.051879856155056,0.05189578476013782,0.05189671576061939,0.05189473462379813,0.05189770632903002,0.051896220476414075,0.051888707574964825,0.051878437381400064,0.0518938426717472,0.051886140026573636,0.05188999134916042,0.051888065687867024,0.05188902851851372,0.05188854710319037,0.0518860314153707,0.05188980494710021,0.051887918181235455,0.05188886156416783,0.05188838987270164,0.051888625718434736,0.05188850779556819,0.05188838747174034;2.5,2.5,2.7500000037252903,2.737135882726282,2.735732781942702,2.7364343323344924,2.736785107530387,2.7369604951283346,2.7370481889273086,2.737179729625769,2.7371139592765386,2.7368717814385515,2.7372679333701475,2.7370698574043497,2.7366583452023345,2.733407242594012,2.7382838965064957,2.735845569550254,2.7349111399608086,2.726122029018746,2.73930569543184,2.732713862225293,2.736009778828566,2.7343618205269298,2.735185799677748,2.7347738101023387,2.7332732740229484,2.735524078142034,2.734398676082491,2.7349613771122625,2.7346800265973767,2.7348207018548196,2.734750364226098,2.7347354074107346]
% number of observations
% nobs=32
% best cost
costOpt{1}	=7.00922011636697;
% best parameters
%  swan-parameters: TRIAD.trfac, TRIAD.cutfr
pOpt{1}	=[0.05188838747174034,2.7347354074107346];
% ===================================================================
% Application Done
