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 QUESO library, version 0.42.0, released on MMM/DD/20YY
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Beginning run at Wed Sep 22 20:35:05 2010

In uqFullEnvironment::commonConstructor():
  m_seed = -1
  internal seed = 1
Entering uqStatisticalInverseProblem<P_V,P_M>::constructor(): prefix = , alternativeOptionsValues = 0, m_env.optionsInputFileName() = example_1chain.inp
In uqStatisticalInverseProblemOptions::scanOptionsValues(): after reading values of options with prefix 'ip_', state of  object is:

ip_computeSolution = 1
ip_dataOutputFileName = outputData/sipOutput
ip_dataOutputAllowedSet = 0 

Leaving uqStatisticalInverseProblem<P_V,P_M>::constructor(): prefix = ip_
In uqStatisticalInverseProblem<P_V,P_M>::solveWithBayesMLSampling(): computing solution, as requested by user
Entering uqMLSampling<P_V,P_M>::constructor()
In uqMLSamplingOptions::scanOptionsValues(): after getting values of options with prefix 'ip_ml_', state of object is:
ip_ml_restartInputFileName = .
ip_ml_restartInputFileType = m
ip_ml_restartChainSize = 100
ip_ml_dataOutputFileName = outputData/sipOutput_ml
ip_ml_dataOutputAllowedSet = 0 1 

Leaving uqMLSampling<P_V,P_M>::constructor()
Entering uqMLSampling<P_V,P_M>::generateSequence()...
In uqMLSamplingLevelOptions::scanOptionsValues(): after getting values of options with prefix 'ip_ml_default_', state of object is:
m_prefix = ip_ml_default_
ip_ml_default_checkpointOutputFileName = .
ip_ml_default_stopAtEnd = 0
ip_ml_default_dataOutputFileName = .
ip_ml_default_dataOutputAllowedSet = 
ip_ml_default_loadBalanceAlgorithmId = 2
ip_ml_default_loadBalanceTreshold = 1
ip_ml_default_minEffectiveSizeRatio = 0.49
ip_ml_default_maxEffectiveSizeRatio = 0.51
ip_ml_default_scaleCovMatrix = 1
ip_ml_default_minRejectionRate = 0.24
ip_ml_default_maxRejectionRate = 0.4
ip_ml_default_covRejectionRate = 0.25
ip_ml_default_totallyMute = 1
ip_ml_default_rawChain_dataInputFileName = .
ip_ml_default_rawChain_dataInputFileType = m
ip_ml_default_rawChain_size = 5000
ip_ml_default_rawChain_generateExtra = 0
ip_ml_default_rawChain_displayPeriod = 500
ip_ml_default_rawChain_measureRunTimes = 1
ip_ml_default_rawChain_dataOutputFileName = .
ip_ml_default_rawChain_dataOutputFileType = m
ip_ml_default_rawChain_dataOutputAllowedSet = 
ip_ml_default_rawChain_computeStats = 0
ip_ml_default_filteredChain_generate = 0
ip_ml_default_filteredChain_discardedPortion = 0
ip_ml_default_filteredChain_lag = 1
ip_ml_default_filteredChain_dataOutputFileName = .
ip_ml_default_filteredChain_dataOutputFileType = m
ip_ml_default_filteredChain_dataOutputAllowedSet = 
ip_ml_default_filteredChain_computeStats = 0
ip_ml_default_displayCandidates = 0
ip_ml_default_putOutOfBoundsInChain = 0
ip_ml_default_tk_useLocalHessian = 0
ip_ml_default_tk_useNewtonComponent = 1
ip_ml_default_dr_maxNumExtraStages = 0
ip_ml_default_dr_listOfScalesForExtraStages = 
ip_ml_default_dr_duringAmNonAdaptiveInt = 1
ip_ml_default_am_keepInitialMatrix = 0
ip_ml_default_am_initialNonAdaptInterval = 0
ip_ml_default_am_adaptInterval = 0
ip_ml_default_am_eta = 1
ip_ml_default_am_epsilon = 1e-05

In uqMLSamplingLevelOptions::scanOptionsValues(): after getting values of options with prefix 'ip_ml_last_', state of object is:
m_prefix = ip_ml_last_
ip_ml_last_checkpointOutputFileName = .
ip_ml_last_stopAtEnd = 0
ip_ml_last_dataOutputFileName = outputData/sipOutput_ml
ip_ml_last_dataOutputAllowedSet = 0 1 
ip_ml_last_loadBalanceAlgorithmId = 2
ip_ml_last_loadBalanceTreshold = 1
ip_ml_last_minEffectiveSizeRatio = 0.49
ip_ml_last_maxEffectiveSizeRatio = 0.51
ip_ml_last_scaleCovMatrix = 1
ip_ml_last_minRejectionRate = 0.24
ip_ml_last_maxRejectionRate = 0.4
ip_ml_last_covRejectionRate = 0.25
ip_ml_last_totallyMute = 1
ip_ml_last_rawChain_dataInputFileName = .
ip_ml_last_rawChain_dataInputFileType = m
ip_ml_last_rawChain_size = 10000
ip_ml_last_rawChain_generateExtra = 0
ip_ml_last_rawChain_displayPeriod = 500
ip_ml_last_rawChain_measureRunTimes = 1
ip_ml_last_rawChain_dataOutputFileName = outputData/rawChain_ml
ip_ml_last_rawChain_dataOutputFileType = m
ip_ml_last_rawChain_dataOutputAllowedSet = 0 
ip_ml_last_rawChain_computeStats = 1
ip_ml_last_filteredChain_generate = 1
ip_ml_last_filteredChain_discardedPortion = 0
ip_ml_last_filteredChain_lag = 2
ip_ml_last_filteredChain_dataOutputFileName = outputData/filtChain_ml
ip_ml_last_filteredChain_dataOutputFileType = m
ip_ml_last_filteredChain_dataOutputAllowedSet = 0 
ip_ml_last_filteredChain_computeStats = 1
ip_ml_last_displayCandidates = 0
ip_ml_last_putOutOfBoundsInChain = 0
ip_ml_last_tk_useLocalHessian = 0
ip_ml_last_tk_useNewtonComponent = 1
ip_ml_last_dr_maxNumExtraStages = 1
ip_ml_last_dr_listOfScalesForExtraStages = 5 
ip_ml_last_dr_duringAmNonAdaptiveInt = 1
ip_ml_last_am_keepInitialMatrix = 0
ip_ml_last_am_initialNonAdaptInterval = 0
ip_ml_last_am_adaptInterval = 0
ip_ml_last_am_eta = 1
ip_ml_last_am_epsilon = 1e-05

Entering uqSequenceStatisticalOptions::constructor(1), prefix = ip_ml_last_rawChain_stats_
After reading values of options with prefix 'ip_ml_last_rawChain_stats_', state of uqSequenceStatisticalOptions object is:

ip_ml_last_rawChain_stats_initialDiscardedPortions = 0 
ip_ml_last_rawChain_stats_mean_monitorPeriod = 0
ip_ml_last_rawChain_stats_bmm_run = 0
ip_ml_last_rawChain_stats_bmm_lengths = 0 
ip_ml_last_rawChain_stats_fft_compute = 0
ip_ml_last_rawChain_stats_fft_paramId = 0
ip_ml_last_rawChain_stats_fft_size = 2048
ip_ml_last_rawChain_stats_fft_testInversion = 0
ip_ml_last_rawChain_stats_fft_write = 0
ip_ml_last_rawChain_stats_psd_compute = 0
ip_ml_last_rawChain_stats_psd_paramId = 0
ip_ml_last_rawChain_stats_psd_numBlocks = 8
ip_ml_last_rawChain_stats_psd_hopSizeRatio = 0
ip_ml_last_rawChain_stats_psd_write = 0
ip_ml_last_rawChain_stats_psdAtZero_compute = 0
ip_ml_last_rawChain_stats_psdAtZero_numBlocks = 8 
ip_ml_last_rawChain_stats_psdAtZero_hopSizeRatio = 0.5
ip_ml_last_rawChain_stats_psdAtZero_display = 0
ip_ml_last_rawChain_stats_psdAtZero_write = 0
ip_ml_last_rawChain_stats_geweke_compute = 0
ip_ml_last_rawChain_stats_geweke_naRatio = 0.1
ip_ml_last_rawChain_stats_geweke_nbRatio = 0.5
ip_ml_last_rawChain_stats_geweke_display = 0
ip_ml_last_rawChain_stats_geweke_write = 0
ip_ml_last_rawChain_stats_autoCorr_computeViaDef = 0
ip_ml_last_rawChain_stats_autoCorr_computeViaFft = 0
ip_ml_last_rawChain_stats_autoCorr_secondLag = 0
ip_ml_last_rawChain_stats_autoCorr_lagSpacing = 0
ip_ml_last_rawChain_stats_autoCorr_numLags = 0
ip_ml_last_rawChain_stats_autoCorr_display = 0
ip_ml_last_rawChain_stats_autoCorr_write = 0
ip_ml_last_rawChain_stats_meanStacc_compute = 0
ip_ml_last_rawChain_stats_hist_compute = 0
ip_ml_last_rawChain_stats_hist_numInternalBins = 100
ip_ml_last_rawChain_stats_cdfStacc_compute = 0
ip_ml_last_rawChain_stats_cdfStacc_numEvalPositions = 50
ip_ml_last_rawChain_stats_kde_compute = 1
ip_ml_last_rawChain_stats_kde_numEvalPositions = 200
ip_ml_last_rawChain_stats_covMatrix_compute = 1
ip_ml_last_rawChain_stats_corrMatrix_compute = 1

Leaving uqSequenceStatisticalOptions::constructor(1), prefix = ip_ml_last_rawChain_stats_
Entering uqSequenceStatisticalOptions::constructor(1), prefix = ip_ml_last_filteredChain_stats_
After reading values of options with prefix 'ip_ml_last_filteredChain_stats_', state of uqSequenceStatisticalOptions object is:

ip_ml_last_filteredChain_stats_initialDiscardedPortions = 0 
ip_ml_last_filteredChain_stats_mean_monitorPeriod = 0
ip_ml_last_filteredChain_stats_bmm_run = 0
ip_ml_last_filteredChain_stats_bmm_lengths = 0 
ip_ml_last_filteredChain_stats_fft_compute = 0
ip_ml_last_filteredChain_stats_fft_paramId = 0
ip_ml_last_filteredChain_stats_fft_size = 2048
ip_ml_last_filteredChain_stats_fft_testInversion = 0
ip_ml_last_filteredChain_stats_fft_write = 0
ip_ml_last_filteredChain_stats_psd_compute = 0
ip_ml_last_filteredChain_stats_psd_paramId = 0
ip_ml_last_filteredChain_stats_psd_numBlocks = 8
ip_ml_last_filteredChain_stats_psd_hopSizeRatio = 0
ip_ml_last_filteredChain_stats_psd_write = 0
ip_ml_last_filteredChain_stats_psdAtZero_compute = 0
ip_ml_last_filteredChain_stats_psdAtZero_numBlocks = 8 
ip_ml_last_filteredChain_stats_psdAtZero_hopSizeRatio = 0.5
ip_ml_last_filteredChain_stats_psdAtZero_display = 0
ip_ml_last_filteredChain_stats_psdAtZero_write = 0
ip_ml_last_filteredChain_stats_geweke_compute = 0
ip_ml_last_filteredChain_stats_geweke_naRatio = 0.1
ip_ml_last_filteredChain_stats_geweke_nbRatio = 0.5
ip_ml_last_filteredChain_stats_geweke_display = 0
ip_ml_last_filteredChain_stats_geweke_write = 0
ip_ml_last_filteredChain_stats_autoCorr_computeViaDef = 0
ip_ml_last_filteredChain_stats_autoCorr_computeViaFft = 0
ip_ml_last_filteredChain_stats_autoCorr_secondLag = 0
ip_ml_last_filteredChain_stats_autoCorr_lagSpacing = 0
ip_ml_last_filteredChain_stats_autoCorr_numLags = 0
ip_ml_last_filteredChain_stats_autoCorr_display = 0
ip_ml_last_filteredChain_stats_autoCorr_write = 0
ip_ml_last_filteredChain_stats_meanStacc_compute = 0
ip_ml_last_filteredChain_stats_hist_compute = 0
ip_ml_last_filteredChain_stats_hist_numInternalBins = 100
ip_ml_last_filteredChain_stats_cdfStacc_compute = 0
ip_ml_last_filteredChain_stats_cdfStacc_numEvalPositions = 50
ip_ml_last_filteredChain_stats_kde_compute = 1
ip_ml_last_filteredChain_stats_kde_numEvalPositions = 200
ip_ml_last_filteredChain_stats_covMatrix_compute = 1
ip_ml_last_filteredChain_stats_corrMatrix_compute = 1

Leaving uqSequenceStatisticalOptions::constructor(1), prefix = ip_ml_last_filteredChain_stats_
In uqMLSamplingLevelOptions::scanOptionsValues(): after getting values of options with prefix 'ip_ml_0_', state of object is:
m_prefix = ip_ml_0_
ip_ml_0_checkpointOutputFileName = .
ip_ml_0_stopAtEnd = 0
ip_ml_0_dataOutputFileName = .
ip_ml_0_dataOutputAllowedSet = 
ip_ml_0_loadBalanceAlgorithmId = 2
ip_ml_0_loadBalanceTreshold = 1
ip_ml_0_minEffectiveSizeRatio = 0.49
ip_ml_0_maxEffectiveSizeRatio = 0.51
ip_ml_0_scaleCovMatrix = 1
ip_ml_0_minRejectionRate = 0.24
ip_ml_0_maxRejectionRate = 0.4
ip_ml_0_covRejectionRate = 0.25
ip_ml_0_totallyMute = 1
ip_ml_0_rawChain_dataInputFileName = .
ip_ml_0_rawChain_dataInputFileType = m
ip_ml_0_rawChain_size = 5000
ip_ml_0_rawChain_generateExtra = 0
ip_ml_0_rawChain_displayPeriod = 500
ip_ml_0_rawChain_measureRunTimes = 1
ip_ml_0_rawChain_dataOutputFileName = .
ip_ml_0_rawChain_dataOutputFileType = m
ip_ml_0_rawChain_dataOutputAllowedSet = 
ip_ml_0_rawChain_computeStats = 0
ip_ml_0_filteredChain_generate = 0
ip_ml_0_filteredChain_discardedPortion = 0
ip_ml_0_filteredChain_lag = 1
ip_ml_0_filteredChain_dataOutputFileName = .
ip_ml_0_filteredChain_dataOutputFileType = m
ip_ml_0_filteredChain_dataOutputAllowedSet = 
ip_ml_0_filteredChain_computeStats = 0
ip_ml_0_displayCandidates = 0
ip_ml_0_putOutOfBoundsInChain = 0
ip_ml_0_tk_useLocalHessian = 0
ip_ml_0_tk_useNewtonComponent = 1
ip_ml_0_dr_maxNumExtraStages = 0
ip_ml_0_dr_listOfScalesForExtraStages = 
ip_ml_0_dr_duringAmNonAdaptiveInt = 1
ip_ml_0_am_keepInitialMatrix = 0
ip_ml_0_am_initialNonAdaptInterval = 0
ip_ml_0_am_adaptInterval = 0
ip_ml_0_am_eta = 1
ip_ml_0_am_epsilon = 1e-05

KEY In uqMLSampling<P_V,P_M>::generateSequence(): beginning level 0, currOptions.m_rawChainSize = 5000
In uqMLSampling<P_V,P_M>::generateSequence(), level 0: finished generating 5000 chain positions
In uqMLSampling<P_V,P_M>::generateSequence(): ending level 0, total level time = 0.012536 seconds
In uqMLSampling<P_V,P_M>::generateSequence(): beginning level 1
In uqMLSamplingLevelOptions::scanOptionsValues(): after getting values of options with prefix 'ip_ml_1_', state of object is:
m_prefix = ip_ml_1_
ip_ml_1_checkpointOutputFileName = .
ip_ml_1_stopAtEnd = 0
ip_ml_1_dataOutputFileName = .
ip_ml_1_dataOutputAllowedSet = 
ip_ml_1_loadBalanceAlgorithmId = 2
ip_ml_1_loadBalanceTreshold = 1
ip_ml_1_minEffectiveSizeRatio = 0.49
ip_ml_1_maxEffectiveSizeRatio = 0.51
ip_ml_1_scaleCovMatrix = 1
ip_ml_1_minRejectionRate = 0.24
ip_ml_1_maxRejectionRate = 0.4
ip_ml_1_covRejectionRate = 0.25
ip_ml_1_totallyMute = 1
ip_ml_1_rawChain_dataInputFileName = .
ip_ml_1_rawChain_dataInputFileType = m
ip_ml_1_rawChain_size = 5000
ip_ml_1_rawChain_generateExtra = 0
ip_ml_1_rawChain_displayPeriod = 500
ip_ml_1_rawChain_measureRunTimes = 1
ip_ml_1_rawChain_dataOutputFileName = .
ip_ml_1_rawChain_dataOutputFileType = m
ip_ml_1_rawChain_dataOutputAllowedSet = 
ip_ml_1_rawChain_computeStats = 0
ip_ml_1_filteredChain_generate = 0
ip_ml_1_filteredChain_discardedPortion = 0
ip_ml_1_filteredChain_lag = 1
ip_ml_1_filteredChain_dataOutputFileName = .
ip_ml_1_filteredChain_dataOutputFileType = m
ip_ml_1_filteredChain_dataOutputAllowedSet = 
ip_ml_1_filteredChain_computeStats = 0
ip_ml_1_displayCandidates = 0
ip_ml_1_putOutOfBoundsInChain = 0
ip_ml_1_tk_useLocalHessian = 0
ip_ml_1_tk_useNewtonComponent = 1
ip_ml_1_dr_maxNumExtraStages = 0
ip_ml_1_dr_listOfScalesForExtraStages = 
ip_ml_1_dr_duringAmNonAdaptiveInt = 1
ip_ml_1_am_keepInitialMatrix = 0
ip_ml_1_am_initialNonAdaptInterval = 0
ip_ml_1_am_adaptInterval = 0
ip_ml_1_am_eta = 1
ip_ml_1_am_epsilon = 1e-05

In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 1: beginning step 1 of 11
KEY In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 1, currOptions->m_rawChainSize = 5000
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 1, after 8e-06 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 2: beginning step 2 of 11
In uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 2, prevLogLikelihoodValues[0] = -520
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 2: prevChain.unifiedSequenceSize() = 5000, currChain.unifiedSequenceSize() = 0, prevLogLikelihoodValues.unifiedSequenceSize() = 5000, currLogLikelihoodValues.unifiedSequenceSize() = 0, prevLogTargetValues.unifiedSequenceSize() = 5000, currLogTargetValues.unifiedSequenceSize() = 0
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 2, after 0.003326 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: beginning step 3 of 11
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 0
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 0, prevExponent = 0, exponents[0] = 0, nowExponent = 1, exponents[1] = 1, effectiveSampleSize = 201.155, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.0402309, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 1
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 1, prevExponent = 0, exponents[0] = 0, nowExponent = 0.5, exponents[1] = 1, effectiveSampleSize = 303.729, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.0607458, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 2
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 2, prevExponent = 0, exponents[0] = 0, nowExponent = 0.25, exponents[1] = 0.5, effectiveSampleSize = 429.875, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.085975, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 3
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 3, prevExponent = 0, exponents[0] = 0, nowExponent = 0.125, exponents[1] = 0.25, effectiveSampleSize = 611.653, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.122331, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 4
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 4, prevExponent = 0, exponents[0] = 0, nowExponent = 0.0625, exponents[1] = 0.125, effectiveSampleSize = 872.178, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.174436, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 5
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 5, prevExponent = 0, exponents[0] = 0, nowExponent = 0.03125, exponents[1] = 0.0625, effectiveSampleSize = 1229.01, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.245802, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 6
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 6, prevExponent = 0, exponents[0] = 0, nowExponent = 0.015625, exponents[1] = 0.03125, effectiveSampleSize = 1656.48, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.331295, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 7
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 7, prevExponent = 0, exponents[0] = 0, nowExponent = 0.0078125, exponents[1] = 0.015625, effectiveSampleSize = 2209.35, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.441871, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 8
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 8, prevExponent = 0, exponents[0] = 0, nowExponent = 0.00390625, exponents[1] = 0.0078125, effectiveSampleSize = 3189.83, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.637966, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 9
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 9, prevExponent = 0, exponents[0] = 0.00390625, nowExponent = 0.00585938, exponents[1] = 0.0078125, effectiveSampleSize = 2557.03, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.511406, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 10
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 10, prevExponent = 0, exponents[0] = 0.00585938, nowExponent = 0.00683594, exponents[1] = 0.0078125, effectiveSampleSize = 2358.99, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.471797, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: entering loop for computing next exponent, with nowAttempt = 11
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: nowAttempt = 11, prevExponent = 0, exponents[0] = 0.00585938, nowExponent = 0.00634766, exponents[1] = 0.00683594, effectiveSampleSize = 2450.76, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.490153, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 3: weightSequence.subSequenceSize() = 5000, weightSequence.unifiedSequenceSize() = 5000, currExponent = 0.00634766, effective ratio = 0.490153, log(evidence factor) = -1.04224, evidence factor = 0.352663
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 3, after 0.021929 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 4: beginning step 4 of 11
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 4: unifiedCovMatrix = 6024.78 
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 4, after 0.006177 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 5: beginning step 5 of 11
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 1, step 5: unifiedRequestedNumSamples = 5000, unifiedWeightStdVectorAtProc0Only.size() = 5000
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 5, after 0.006296 seconds
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 1, step 6: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 1, step 6: result = 0
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 6, after 2.1e-05 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 7: beginning step 7 of 11
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 7: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 7: subNumSamples = 5000, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 7: minModifiedSubNumSamples = 5000, avgModifiedSubNumSamples = 5000, maxModifiedSubNumSamples = 5000
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 7: numberOfPositionsToGuaranteeForNode = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 7: unbalancedLinkControl.unbLinkedChains.size() = 2261
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 7: balancedLinkControl.balLinkedChains.size() = 0, unbalancedLinkControl.unbLinkedChains.size() = 2261
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 7, after 0.000356 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 8: beginning step 8 of 11
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 8, after 4e-06 seconds
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 1, step 9: beginning step 9 of 11
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 1, step 9: entering loop for assessing rejection rate, with nowAttempt = 0, nowRejectionRate = 0
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 1, step 9: in loop for assessing rejection rate, about to sample 34 indexes, meanRejectionRate = 0.32, covRejectionRate = 0.25
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 1, step 9: unifiedRequestedNumSamples = 34, unifiedWeightStdVectorAtProc0Only.size() = 5000
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 1, step 9: in loop for assessing rejection rate, about to distribute sampled assessment indexes
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 1, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 1, step 9: result = 0
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 9: subNumSamples = 34, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 9: minModifiedSubNumSamples = 34, avgModifiedSubNumSamples = 34, maxModifiedSubNumSamples = 34
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 9: numberOfPositionsToGuaranteeForNode = 34
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 1, step 9: unbalancedLinkControl.unbLinkedChains.size() = 32
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 1, step 9: in loop for assessing rejection rate, about to generate assessment chain
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 32, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 1, step 9: chainIdMax = 32, numberOfPositions = 34
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 1, step 9: minNumberOfPositions = 34, avgNumberOfPositions = 34, maxNumberOfPositions = 34
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 1, step 9: in loop for assessing rejection rate, nowAttempt = 0, beforeEta = 1, etas[0] = 1, nowEta = 1, etas[1] = 1, minRejectionRate = 0.24, nowRejectionRate = 0.294118, maxRejectionRate = 0.4
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 1, step 9: weightSequence.subSequenceSize() = 5000, weightSequence.unifiedSequenceSize() = 5000, currEta = 1, assessed rejection rate = 0.294118
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 9, after 0.005613 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 1, step 10: beginning step 10 of 11, currLogLikelihoodValues = 0x7fff29858710
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 2261, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 1, step 10: chainIdMax = 2261, numberOfPositions = 5000
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 1, step 10: minNumberOfPositions = 5000, avgNumberOfPositions = 5000, maxNumberOfPositions = 5000
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 10, after chain generatrion, currLogLikelihoodValues[0] = -0.0189179
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 10, after 0.147922 seconds
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 1, step 11, after 3e-06 seconds
In uqMLSampling<P_V,P_M>::generateSequence(): ending level 1, having generated 5000 chain positions, cumulativeRawChainRunTime = 0.079255 seconds, total level time = 0.193156 seconds, cumulativeRawChainRejections = 1422 (28.44% at this processor) (28.44% over all processors), stopAtEndOfLevel = 0
In uqMLSampling<P_V,P_M>::generateSequence(), level 1: min cumul seconds = 0.079255, avg cumul seconds = 0.079255, max cumul seconds = 0.079255, min level seconds = 0.193156, avg level seconds = 0.193156, max level seconds = 0.193156
In uqMLSampling<P_V,P_M>::generateSequence(): beginning level 2
In uqMLSamplingLevelOptions::scanOptionsValues(): after getting values of options with prefix 'ip_ml_2_', state of object is:
m_prefix = ip_ml_2_
ip_ml_2_checkpointOutputFileName = .
ip_ml_2_stopAtEnd = 0
ip_ml_2_dataOutputFileName = .
ip_ml_2_dataOutputAllowedSet = 
ip_ml_2_loadBalanceAlgorithmId = 2
ip_ml_2_loadBalanceTreshold = 1
ip_ml_2_minEffectiveSizeRatio = 0.49
ip_ml_2_maxEffectiveSizeRatio = 0.51
ip_ml_2_scaleCovMatrix = 1
ip_ml_2_minRejectionRate = 0.24
ip_ml_2_maxRejectionRate = 0.4
ip_ml_2_covRejectionRate = 0.25
ip_ml_2_totallyMute = 1
ip_ml_2_rawChain_dataInputFileName = .
ip_ml_2_rawChain_dataInputFileType = m
ip_ml_2_rawChain_size = 5000
ip_ml_2_rawChain_generateExtra = 0
ip_ml_2_rawChain_displayPeriod = 500
ip_ml_2_rawChain_measureRunTimes = 1
ip_ml_2_rawChain_dataOutputFileName = .
ip_ml_2_rawChain_dataOutputFileType = m
ip_ml_2_rawChain_dataOutputAllowedSet = 
ip_ml_2_rawChain_computeStats = 0
ip_ml_2_filteredChain_generate = 0
ip_ml_2_filteredChain_discardedPortion = 0
ip_ml_2_filteredChain_lag = 1
ip_ml_2_filteredChain_dataOutputFileName = .
ip_ml_2_filteredChain_dataOutputFileType = m
ip_ml_2_filteredChain_dataOutputAllowedSet = 
ip_ml_2_filteredChain_computeStats = 0
ip_ml_2_displayCandidates = 0
ip_ml_2_putOutOfBoundsInChain = 0
ip_ml_2_tk_useLocalHessian = 0
ip_ml_2_tk_useNewtonComponent = 1
ip_ml_2_dr_maxNumExtraStages = 0
ip_ml_2_dr_listOfScalesForExtraStages = 
ip_ml_2_dr_duringAmNonAdaptiveInt = 1
ip_ml_2_am_keepInitialMatrix = 0
ip_ml_2_am_initialNonAdaptInterval = 0
ip_ml_2_am_adaptInterval = 0
ip_ml_2_am_eta = 1
ip_ml_2_am_epsilon = 1e-05

In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 1: beginning step 1 of 11
KEY In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 1, currOptions->m_rawChainSize = 5000
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 1, after 1.1e-05 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 2: beginning step 2 of 11
In uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 2, prevLogLikelihoodValues[0] = -0.0189179
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 2: prevChain.unifiedSequenceSize() = 5000, currChain.unifiedSequenceSize() = 0, prevLogLikelihoodValues.unifiedSequenceSize() = 5000, currLogLikelihoodValues.unifiedSequenceSize() = 0, prevLogTargetValues.unifiedSequenceSize() = 5000, currLogTargetValues.unifiedSequenceSize() = 0
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 2, after 0.003181 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: beginning step 3 of 11
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: entering loop for computing next exponent, with nowAttempt = 0
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: nowAttempt = 0, prevExponent = 0.00634766, exponents[0] = 0.00634766, nowExponent = 1, exponents[1] = 1, effectiveSampleSize = 516.628, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.103326, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: entering loop for computing next exponent, with nowAttempt = 1
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: nowAttempt = 1, prevExponent = 0.00634766, exponents[0] = 0.00634766, nowExponent = 0.503174, exponents[1] = 1, effectiveSampleSize = 817.803, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.163561, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: entering loop for computing next exponent, with nowAttempt = 2
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: nowAttempt = 2, prevExponent = 0.00634766, exponents[0] = 0.00634766, nowExponent = 0.254761, exponents[1] = 0.503174, effectiveSampleSize = 1179.39, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.235878, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: entering loop for computing next exponent, with nowAttempt = 3
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: nowAttempt = 3, prevExponent = 0.00634766, exponents[0] = 0.00634766, nowExponent = 0.130554, exponents[1] = 0.254761, effectiveSampleSize = 1666.09, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.333218, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: entering loop for computing next exponent, with nowAttempt = 4
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: nowAttempt = 4, prevExponent = 0.00634766, exponents[0] = 0.00634766, nowExponent = 0.0684509, exponents[1] = 0.130554, effectiveSampleSize = 2293.03, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.458606, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: entering loop for computing next exponent, with nowAttempt = 5
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: nowAttempt = 5, prevExponent = 0.00634766, exponents[0] = 0.00634766, nowExponent = 0.0373993, exponents[1] = 0.0684509, effectiveSampleSize = 3026.67, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.605334, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: entering loop for computing next exponent, with nowAttempt = 6
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: nowAttempt = 6, prevExponent = 0.00634766, exponents[0] = 0.0373993, nowExponent = 0.0529251, exponents[1] = 0.0684509, effectiveSampleSize = 2588.73, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.517747, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: entering loop for computing next exponent, with nowAttempt = 7
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: nowAttempt = 7, prevExponent = 0.00634766, exponents[0] = 0.0529251, nowExponent = 0.060688, exponents[1] = 0.0684509, effectiveSampleSize = 2428.09, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.485619, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: entering loop for computing next exponent, with nowAttempt = 8
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: nowAttempt = 8, prevExponent = 0.00634766, exponents[0] = 0.0529251, nowExponent = 0.0568066, exponents[1] = 0.060688, effectiveSampleSize = 2504.74, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.500948, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 3: weightSequence.subSequenceSize() = 5000, weightSequence.unifiedSequenceSize() = 5000, currExponent = 0.0568066, effective ratio = 0.500948, log(evidence factor) = -1.15317, evidence factor = 0.315636
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 3, after 0.01625 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 4: beginning step 4 of 11
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 4: unifiedCovMatrix = 1512.44 
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 4, after 0.00603 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 5: beginning step 5 of 11
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 2, step 5: unifiedRequestedNumSamples = 5000, unifiedWeightStdVectorAtProc0Only.size() = 5000
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 5, after 0.006129 seconds
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 2, step 6: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 2, step 6: result = 0
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 6, after 1.1e-05 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 7: beginning step 7 of 11
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 7: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 7: subNumSamples = 5000, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 7: minModifiedSubNumSamples = 5000, avgModifiedSubNumSamples = 5000, maxModifiedSubNumSamples = 5000
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 7: numberOfPositionsToGuaranteeForNode = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 7: unbalancedLinkControl.unbLinkedChains.size() = 2279
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 7: balancedLinkControl.balLinkedChains.size() = 0, unbalancedLinkControl.unbLinkedChains.size() = 2279
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 7, after 0.000337 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 8: beginning step 8 of 11
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 8, after 4e-06 seconds
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: beginning step 9 of 11
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: entering loop for assessing rejection rate, with nowAttempt = 0, nowRejectionRate = 0
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: in loop for assessing rejection rate, about to sample 34 indexes, meanRejectionRate = 0.32, covRejectionRate = 0.25
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 2, step 9: unifiedRequestedNumSamples = 34, unifiedWeightStdVectorAtProc0Only.size() = 5000
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: in loop for assessing rejection rate, about to distribute sampled assessment indexes
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 2, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 2, step 9: result = 0
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: subNumSamples = 34, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: minModifiedSubNumSamples = 34, avgModifiedSubNumSamples = 34, maxModifiedSubNumSamples = 34
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: numberOfPositionsToGuaranteeForNode = 34
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: unbalancedLinkControl.unbLinkedChains.size() = 33
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: in loop for assessing rejection rate, about to generate assessment chain
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 33, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 2, step 9: chainIdMax = 33, numberOfPositions = 34
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 2, step 9: minNumberOfPositions = 34, avgNumberOfPositions = 34, maxNumberOfPositions = 34
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: in loop for assessing rejection rate, nowAttempt = 0, beforeEta = 1, etas[0] = 1, nowEta = 1, etas[1] = 1, minRejectionRate = 0.24, nowRejectionRate = 0.529412, maxRejectionRate = 0.4
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: entering loop for assessing rejection rate, with nowAttempt = 1, nowRejectionRate = 0.529412
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: in loop for assessing rejection rate, with nowAttempt = 1, useMiddlePointLogicForEta = false, nowEta just updated to value (to be tested) 0.25
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: in loop for assessing rejection rate, about to sample 34 indexes, meanRejectionRate = 0.32, covRejectionRate = 0.25
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 2, step 9: unifiedRequestedNumSamples = 34, unifiedWeightStdVectorAtProc0Only.size() = 5000
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: in loop for assessing rejection rate, about to distribute sampled assessment indexes
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 2, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 2, step 9: result = 0
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: subNumSamples = 34, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: minModifiedSubNumSamples = 34, avgModifiedSubNumSamples = 34, maxModifiedSubNumSamples = 34
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: numberOfPositionsToGuaranteeForNode = 34
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 2, step 9: unbalancedLinkControl.unbLinkedChains.size() = 34
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: in loop for assessing rejection rate, about to generate assessment chain
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 34, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 2, step 9: chainIdMax = 34, numberOfPositions = 34
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 2, step 9: minNumberOfPositions = 34, avgNumberOfPositions = 34, maxNumberOfPositions = 34
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: in loop for assessing rejection rate, nowAttempt = 1, beforeEta = 1, etas[0] = 1, nowEta = 0.25, etas[1] = 1, minRejectionRate = 0.24, nowRejectionRate = 0.294118, maxRejectionRate = 0.4
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 2, step 9: weightSequence.subSequenceSize() = 5000, weightSequence.unifiedSequenceSize() = 5000, currEta = 0.25, assessed rejection rate = 0.294118
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 9, after 0.011107 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 2, step 10: beginning step 10 of 11, currLogLikelihoodValues = 0x7fff29858710
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 2279, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 2, step 10: chainIdMax = 2279, numberOfPositions = 5000
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 2, step 10: minNumberOfPositions = 5000, avgNumberOfPositions = 5000, maxNumberOfPositions = 5000
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 10, after chain generatrion, currLogLikelihoodValues[0] = -0.19709
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 10, after 0.146569 seconds
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 2, step 11, after 3e-06 seconds
In uqMLSampling<P_V,P_M>::generateSequence(): ending level 2, having generated 5000 chain positions, cumulativeRawChainRunTime = 0.077431 seconds, total level time = 0.191834 seconds, cumulativeRawChainRejections = 1782 (35.64% at this processor) (35.64% over all processors), stopAtEndOfLevel = 0
In uqMLSampling<P_V,P_M>::generateSequence(), level 2: min cumul seconds = 0.077431, avg cumul seconds = 0.077431, max cumul seconds = 0.077431, min level seconds = 0.191834, avg level seconds = 0.191834, max level seconds = 0.191834
In uqMLSampling<P_V,P_M>::generateSequence(): beginning level 3
In uqMLSamplingLevelOptions::scanOptionsValues(): after getting values of options with prefix 'ip_ml_3_', state of object is:
m_prefix = ip_ml_3_
ip_ml_3_checkpointOutputFileName = .
ip_ml_3_stopAtEnd = 0
ip_ml_3_dataOutputFileName = .
ip_ml_3_dataOutputAllowedSet = 
ip_ml_3_loadBalanceAlgorithmId = 2
ip_ml_3_loadBalanceTreshold = 1
ip_ml_3_minEffectiveSizeRatio = 0.49
ip_ml_3_maxEffectiveSizeRatio = 0.51
ip_ml_3_scaleCovMatrix = 1
ip_ml_3_minRejectionRate = 0.24
ip_ml_3_maxRejectionRate = 0.4
ip_ml_3_covRejectionRate = 0.25
ip_ml_3_totallyMute = 1
ip_ml_3_rawChain_dataInputFileName = .
ip_ml_3_rawChain_dataInputFileType = m
ip_ml_3_rawChain_size = 5000
ip_ml_3_rawChain_generateExtra = 0
ip_ml_3_rawChain_displayPeriod = 500
ip_ml_3_rawChain_measureRunTimes = 1
ip_ml_3_rawChain_dataOutputFileName = .
ip_ml_3_rawChain_dataOutputFileType = m
ip_ml_3_rawChain_dataOutputAllowedSet = 
ip_ml_3_rawChain_computeStats = 0
ip_ml_3_filteredChain_generate = 0
ip_ml_3_filteredChain_discardedPortion = 0
ip_ml_3_filteredChain_lag = 1
ip_ml_3_filteredChain_dataOutputFileName = .
ip_ml_3_filteredChain_dataOutputFileType = m
ip_ml_3_filteredChain_dataOutputAllowedSet = 
ip_ml_3_filteredChain_computeStats = 0
ip_ml_3_displayCandidates = 0
ip_ml_3_putOutOfBoundsInChain = 0
ip_ml_3_tk_useLocalHessian = 0
ip_ml_3_tk_useNewtonComponent = 1
ip_ml_3_dr_maxNumExtraStages = 0
ip_ml_3_dr_listOfScalesForExtraStages = 
ip_ml_3_dr_duringAmNonAdaptiveInt = 1
ip_ml_3_am_keepInitialMatrix = 0
ip_ml_3_am_initialNonAdaptInterval = 0
ip_ml_3_am_adaptInterval = 0
ip_ml_3_am_eta = 1
ip_ml_3_am_epsilon = 1e-05

In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 1: beginning step 1 of 11
KEY In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 1, currOptions->m_rawChainSize = 5000
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 1, after 1.1e-05 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 2: beginning step 2 of 11
In uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 2, prevLogLikelihoodValues[0] = -0.19709
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 2: prevChain.unifiedSequenceSize() = 5000, currChain.unifiedSequenceSize() = 0, prevLogLikelihoodValues.unifiedSequenceSize() = 5000, currLogLikelihoodValues.unifiedSequenceSize() = 0, prevLogTargetValues.unifiedSequenceSize() = 5000, currLogTargetValues.unifiedSequenceSize() = 0
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 2, after 0.003333 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: beginning step 3 of 11
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: entering loop for computing next exponent, with nowAttempt = 0
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: nowAttempt = 0, prevExponent = 0.0568066, exponents[0] = 0.0568066, nowExponent = 1, exponents[1] = 1, effectiveSampleSize = 1365.35, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.273071, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: entering loop for computing next exponent, with nowAttempt = 1
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: nowAttempt = 1, prevExponent = 0.0568066, exponents[0] = 0.0568066, nowExponent = 0.528403, exponents[1] = 1, effectiveSampleSize = 2099.23, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.419846, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: entering loop for computing next exponent, with nowAttempt = 2
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: nowAttempt = 2, prevExponent = 0.0568066, exponents[0] = 0.0568066, nowExponent = 0.292605, exponents[1] = 0.528403, effectiveSampleSize = 2835.05, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.56701, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: entering loop for computing next exponent, with nowAttempt = 3
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: nowAttempt = 3, prevExponent = 0.0568066, exponents[0] = 0.292605, nowExponent = 0.410504, exponents[1] = 0.528403, effectiveSampleSize = 2401.37, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.480273, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: entering loop for computing next exponent, with nowAttempt = 4
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: nowAttempt = 4, prevExponent = 0.0568066, exponents[0] = 0.292605, nowExponent = 0.351555, exponents[1] = 0.410504, effectiveSampleSize = 2595.17, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.519033, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: entering loop for computing next exponent, with nowAttempt = 5
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: nowAttempt = 5, prevExponent = 0.0568066, exponents[0] = 0.351555, nowExponent = 0.381029, exponents[1] = 0.410504, effectiveSampleSize = 2493.6, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.49872, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 3: weightSequence.subSequenceSize() = 5000, weightSequence.unifiedSequenceSize() = 5000, currExponent = 0.381029, effective ratio = 0.49872, log(evidence factor) = -1.89283, evidence factor = 0.150645
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 3, after 0.010633 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 4: beginning step 4 of 11
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 4: unifiedCovMatrix = 1403.52 
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 4, after 0.005997 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 5: beginning step 5 of 11
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 3, step 5: unifiedRequestedNumSamples = 5000, unifiedWeightStdVectorAtProc0Only.size() = 5000
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 5, after 0.006093 seconds
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 3, step 6: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 3, step 6: result = 0
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 6, after 1e-05 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 7: beginning step 7 of 11
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 7: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 7: subNumSamples = 5000, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 7: minModifiedSubNumSamples = 5000, avgModifiedSubNumSamples = 5000, maxModifiedSubNumSamples = 5000
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 7: numberOfPositionsToGuaranteeForNode = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 7: unbalancedLinkControl.unbLinkedChains.size() = 2285
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 7: balancedLinkControl.balLinkedChains.size() = 0, unbalancedLinkControl.unbLinkedChains.size() = 2285
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 7, after 0.000341 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 8: beginning step 8 of 11
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 8, after 3e-06 seconds
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: beginning step 9 of 11
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: entering loop for assessing rejection rate, with nowAttempt = 0, nowRejectionRate = 0
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, about to sample 34 indexes, meanRejectionRate = 0.32, covRejectionRate = 0.25
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 3, step 9: unifiedRequestedNumSamples = 34, unifiedWeightStdVectorAtProc0Only.size() = 5000
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, about to distribute sampled assessment indexes
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 3, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 3, step 9: result = 0
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: subNumSamples = 34, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: minModifiedSubNumSamples = 34, avgModifiedSubNumSamples = 34, maxModifiedSubNumSamples = 34
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: numberOfPositionsToGuaranteeForNode = 34
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: unbalancedLinkControl.unbLinkedChains.size() = 34
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, about to generate assessment chain
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 34, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 3, step 9: chainIdMax = 34, numberOfPositions = 34
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 3, step 9: minNumberOfPositions = 34, avgNumberOfPositions = 34, maxNumberOfPositions = 34
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, nowAttempt = 0, beforeEta = 0.25, etas[0] = 0.25, nowEta = 0.25, etas[1] = 1, minRejectionRate = 0.24, nowRejectionRate = 0.647059, maxRejectionRate = 0.4
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: entering loop for assessing rejection rate, with nowAttempt = 1, nowRejectionRate = 0.647059
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, with nowAttempt = 1, useMiddlePointLogicForEta = false, nowEta just updated to value (to be tested) 0.0625
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, about to sample 34 indexes, meanRejectionRate = 0.32, covRejectionRate = 0.25
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 3, step 9: unifiedRequestedNumSamples = 34, unifiedWeightStdVectorAtProc0Only.size() = 5000
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, about to distribute sampled assessment indexes
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 3, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 3, step 9: result = 0
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: subNumSamples = 34, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: minModifiedSubNumSamples = 34, avgModifiedSubNumSamples = 34, maxModifiedSubNumSamples = 34
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: numberOfPositionsToGuaranteeForNode = 34
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: unbalancedLinkControl.unbLinkedChains.size() = 33
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, about to generate assessment chain
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 33, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 3, step 9: chainIdMax = 33, numberOfPositions = 34
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 3, step 9: minNumberOfPositions = 34, avgNumberOfPositions = 34, maxNumberOfPositions = 34
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, nowAttempt = 1, beforeEta = 0.25, etas[0] = 0.25, nowEta = 0.0625, etas[1] = 1, minRejectionRate = 0.24, nowRejectionRate = 0.5, maxRejectionRate = 0.4
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: entering loop for assessing rejection rate, with nowAttempt = 2, nowRejectionRate = 0.5
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, with nowAttempt = 2, useMiddlePointLogicForEta = false, nowEta just updated to value (to be tested) 0.015625
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, about to sample 34 indexes, meanRejectionRate = 0.32, covRejectionRate = 0.25
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 3, step 9: unifiedRequestedNumSamples = 34, unifiedWeightStdVectorAtProc0Only.size() = 5000
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, about to distribute sampled assessment indexes
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 3, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 3, step 9: result = 0
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: subNumSamples = 34, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: minModifiedSubNumSamples = 34, avgModifiedSubNumSamples = 34, maxModifiedSubNumSamples = 34
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: numberOfPositionsToGuaranteeForNode = 34
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 3, step 9: unbalancedLinkControl.unbLinkedChains.size() = 34
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, about to generate assessment chain
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 34, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 3, step 9: chainIdMax = 34, numberOfPositions = 34
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 3, step 9: minNumberOfPositions = 34, avgNumberOfPositions = 34, maxNumberOfPositions = 34
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: in loop for assessing rejection rate, nowAttempt = 2, beforeEta = 0.0625, etas[0] = 0.25, nowEta = 0.015625, etas[1] = 1, minRejectionRate = 0.24, nowRejectionRate = 0.294118, maxRejectionRate = 0.4
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 3, step 9: weightSequence.subSequenceSize() = 5000, weightSequence.unifiedSequenceSize() = 5000, currEta = 0.015625, assessed rejection rate = 0.294118
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 9, after 0.016676 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 3, step 10: beginning step 10 of 11, currLogLikelihoodValues = 0x7fff29858710
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 2285, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 3, step 10: chainIdMax = 2285, numberOfPositions = 5000
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 3, step 10: minNumberOfPositions = 5000, avgNumberOfPositions = 5000, maxNumberOfPositions = 5000
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 10, after chain generatrion, currLogLikelihoodValues[0] = -1.12006
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 10, after 0.146687 seconds
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 3, step 11, after 3e-06 seconds
In uqMLSampling<P_V,P_M>::generateSequence(): ending level 3, having generated 5000 chain positions, cumulativeRawChainRunTime = 0.077353 seconds, total level time = 0.191848 seconds, cumulativeRawChainRejections = 1418 (28.36% at this processor) (28.36% over all processors), stopAtEndOfLevel = 0
In uqMLSampling<P_V,P_M>::generateSequence(), level 3: min cumul seconds = 0.077353, avg cumul seconds = 0.077353, max cumul seconds = 0.077353, min level seconds = 0.191848, avg level seconds = 0.191848, max level seconds = 0.191848
In uqMLSampling<P_V,P_M>::generateSequence(): beginning level 4
In uqMLSamplingLevelOptions::scanOptionsValues(): after getting values of options with prefix 'ip_ml_4_', state of object is:
m_prefix = ip_ml_4_
ip_ml_4_checkpointOutputFileName = .
ip_ml_4_stopAtEnd = 0
ip_ml_4_dataOutputFileName = .
ip_ml_4_dataOutputAllowedSet = 
ip_ml_4_loadBalanceAlgorithmId = 2
ip_ml_4_loadBalanceTreshold = 1
ip_ml_4_minEffectiveSizeRatio = 0.49
ip_ml_4_maxEffectiveSizeRatio = 0.51
ip_ml_4_scaleCovMatrix = 1
ip_ml_4_minRejectionRate = 0.24
ip_ml_4_maxRejectionRate = 0.4
ip_ml_4_covRejectionRate = 0.25
ip_ml_4_totallyMute = 1
ip_ml_4_rawChain_dataInputFileName = .
ip_ml_4_rawChain_dataInputFileType = m
ip_ml_4_rawChain_size = 5000
ip_ml_4_rawChain_generateExtra = 0
ip_ml_4_rawChain_displayPeriod = 500
ip_ml_4_rawChain_measureRunTimes = 1
ip_ml_4_rawChain_dataOutputFileName = .
ip_ml_4_rawChain_dataOutputFileType = m
ip_ml_4_rawChain_dataOutputAllowedSet = 
ip_ml_4_rawChain_computeStats = 0
ip_ml_4_filteredChain_generate = 0
ip_ml_4_filteredChain_discardedPortion = 0
ip_ml_4_filteredChain_lag = 1
ip_ml_4_filteredChain_dataOutputFileName = .
ip_ml_4_filteredChain_dataOutputFileType = m
ip_ml_4_filteredChain_dataOutputAllowedSet = 
ip_ml_4_filteredChain_computeStats = 0
ip_ml_4_displayCandidates = 0
ip_ml_4_putOutOfBoundsInChain = 0
ip_ml_4_tk_useLocalHessian = 0
ip_ml_4_tk_useNewtonComponent = 1
ip_ml_4_dr_maxNumExtraStages = 0
ip_ml_4_dr_listOfScalesForExtraStages = 
ip_ml_4_dr_duringAmNonAdaptiveInt = 1
ip_ml_4_am_keepInitialMatrix = 0
ip_ml_4_am_initialNonAdaptInterval = 0
ip_ml_4_am_adaptInterval = 0
ip_ml_4_am_eta = 1
ip_ml_4_am_epsilon = 1e-05

In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 1: beginning step 1 of 11
KEY In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 1, currOptions->m_rawChainSize = 5000
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 1, after 1.1e-05 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 2: beginning step 2 of 11
In uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 2, prevLogLikelihoodValues[0] = -1.12006
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 2: prevChain.unifiedSequenceSize() = 5000, currChain.unifiedSequenceSize() = 0, prevLogLikelihoodValues.unifiedSequenceSize() = 5000, currLogLikelihoodValues.unifiedSequenceSize() = 0, prevLogTargetValues.unifiedSequenceSize() = 5000, currLogTargetValues.unifiedSequenceSize() = 0
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 2, after 0.003556 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 3: beginning step 3 of 11
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 3: entering loop for computing next exponent, with nowAttempt = 0
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 3: nowAttempt = 0, prevExponent = 0.381029, exponents[0] = 0.381029, nowExponent = 1, exponents[1] = 1, effectiveSampleSize = 3610.18, weightSequenceSize = 5000, minEffectiveSizeRatio = 0.49, nowEffectiveSizeRatio = 0.722036, maxEffectiveSizeRatio = 0.51
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 3: weightSequence.subSequenceSize() = 5000, weightSequence.unifiedSequenceSize() = 5000, currExponent = 1, effective ratio = 0.722036, log(evidence factor) = -2.17869, evidence factor = 0.11319
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 3, after 0.001817 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 3: copying 'last' level options to current options
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 3: after copying 'last' level options to current options, the current options are
m_prefix = ip_ml_last_
ip_ml_last_checkpointOutputFileName = .
ip_ml_last_stopAtEnd = 0
ip_ml_last_dataOutputFileName = outputData/sipOutput_ml
ip_ml_last_dataOutputAllowedSet = 0 1 
ip_ml_last_loadBalanceAlgorithmId = 2
ip_ml_last_loadBalanceTreshold = 1
ip_ml_last_minEffectiveSizeRatio = 0.49
ip_ml_last_maxEffectiveSizeRatio = 0.51
ip_ml_last_scaleCovMatrix = 1
ip_ml_last_minRejectionRate = 0.24
ip_ml_last_maxRejectionRate = 0.4
ip_ml_last_covRejectionRate = 0.25
ip_ml_last_totallyMute = 1
ip_ml_last_rawChain_dataInputFileName = .
ip_ml_last_rawChain_dataInputFileType = m
ip_ml_last_rawChain_size = 10000
ip_ml_last_rawChain_generateExtra = 0
ip_ml_last_rawChain_displayPeriod = 500
ip_ml_last_rawChain_measureRunTimes = 1
ip_ml_last_rawChain_dataOutputFileName = outputData/rawChain_ml
ip_ml_last_rawChain_dataOutputFileType = m
ip_ml_last_rawChain_dataOutputAllowedSet = 0 
ip_ml_last_rawChain_computeStats = 1
ip_ml_last_filteredChain_generate = 1
ip_ml_last_filteredChain_discardedPortion = 0
ip_ml_last_filteredChain_lag = 2
ip_ml_last_filteredChain_dataOutputFileName = outputData/filtChain_ml
ip_ml_last_filteredChain_dataOutputFileType = m
ip_ml_last_filteredChain_dataOutputAllowedSet = 0 
ip_ml_last_filteredChain_computeStats = 1
ip_ml_last_displayCandidates = 0
ip_ml_last_putOutOfBoundsInChain = 0
ip_ml_last_tk_useLocalHessian = 0
ip_ml_last_tk_useNewtonComponent = 1
ip_ml_last_dr_maxNumExtraStages = 1
ip_ml_last_dr_listOfScalesForExtraStages = 5 
ip_ml_last_dr_duringAmNonAdaptiveInt = 1
ip_ml_last_am_keepInitialMatrix = 0
ip_ml_last_am_initialNonAdaptInterval = 0
ip_ml_last_am_adaptInterval = 0
ip_ml_last_am_eta = 1
ip_ml_last_am_epsilon = 1e-05

In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 4: beginning step 4 of 11
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 4: unifiedCovMatrix = 1802.48 
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 4, after 0.006082 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 5: beginning step 5 of 11
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 4, step 5: unifiedRequestedNumSamples = 10000, unifiedWeightStdVectorAtProc0Only.size() = 5000
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 5, after 0.008671 seconds
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 4, step 6: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 4, step 6: result = 0
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 6, after 1.2e-05 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 7: beginning step 7 of 11
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 7: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 7: subNumSamples = 10000, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 7: minModifiedSubNumSamples = 10000, avgModifiedSubNumSamples = 10000, maxModifiedSubNumSamples = 10000
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 7: numberOfPositionsToGuaranteeForNode = 10000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 7: unbalancedLinkControl.unbLinkedChains.size() = 3735
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 7: balancedLinkControl.balLinkedChains.size() = 0, unbalancedLinkControl.unbLinkedChains.size() = 3735
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 7, after 0.000347 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 8: beginning step 8 of 11
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 8, after 5e-06 seconds
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 4, step 9: beginning step 9 of 11
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 4, step 9: entering loop for assessing rejection rate, with nowAttempt = 0, nowRejectionRate = 0
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 4, step 9: in loop for assessing rejection rate, about to sample 34 indexes, meanRejectionRate = 0.32, covRejectionRate = 0.25
Entering uqMLSampling<P_V,P_M>::sampleIndexes_proc0(), level 4, step 9: unifiedRequestedNumSamples = 34, unifiedWeightStdVectorAtProc0Only.size() = 5000
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 4, step 9: in loop for assessing rejection rate, about to distribute sampled assessment indexes
Entering uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 4, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
Leaving uqMLSampling<P_V,P_M>::decideOnBalancedChains_all(), level 4, step 9: result = 0
Entering uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 9: indexOfFirstWeight = 0, indexOfLastWeight = 4999
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 9: subNumSamples = 34, unifiedIndexCountersAtAllProcs.size() = 5000
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 9: minModifiedSubNumSamples = 34, avgModifiedSubNumSamples = 34, maxModifiedSubNumSamples = 34
KEY In uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 9: numberOfPositionsToGuaranteeForNode = 34
KEY Leaving uqMLSampling<P_V,P_M>::prepareUnbLinkedChains_inter0(), level 4, step 9: unbalancedLinkControl.unbLinkedChains.size() = 34
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 4, step 9: in loop for assessing rejection rate, about to generate assessment chain
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 34, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 4, step 9: chainIdMax = 34, numberOfPositions = 34
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 4, step 9: minNumberOfPositions = 34, avgNumberOfPositions = 34, maxNumberOfPositions = 34
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 4, step 9: in loop for assessing rejection rate, nowAttempt = 0, beforeEta = 0.015625, etas[0] = 0.015625, nowEta = 0.015625, etas[1] = 1, minRejectionRate = 0.24, nowRejectionRate = 0.352941, maxRejectionRate = 0.4
In uqMLSampling<P_V,P_M>::generateSequence_Step09_all(), level 4, step 9: weightSequence.subSequenceSize() = 5000, weightSequence.unifiedSequenceSize() = 5000, currEta = 0.015625, assessed rejection rate = 0.352941
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 9, after 0.012736 seconds
In uqMLSampling<P_V,P_M>::generateSequence(), level 4, step 10: beginning step 10 of 11, currLogLikelihoodValues = 0x7fff29858710
Entering uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(): unbalancedLinkControl.unbLinkedChains.size() = 3735, indexOfFirstWeight = 0
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 4, step 10: chainIdMax = 3735, numberOfPositions = 10000
KEY In uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all(), level 4, step 10: minNumberOfPositions = 10000, avgNumberOfPositions = 10000, maxNumberOfPositions = 10000
Leaving uqMLSampling<P_V,P_M>::generateUnbLinkedChains_all()
In uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 10, after chain generatrion, currLogLikelihoodValues[0] = -2.94507
Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 10, after 0.986472 seconds


-----------------------------------------------------
 Computing statistics for chain 'ip_ml_4_rawChain' ...
-----------------------------------------------------

In uqBaseVectorSequence<V,M>::computeStatistics(): statisticalOptions.initialDiscardedPortions()[0] = 0, initialPosForStatistics[0] = 0
In uqBaseVectorSequence<V,M>::computeStatistics(): initial positions for statistics = 0

-----------------------------------------------------
Computing mean, sample variance and population variance

Estimated variance of sample mean for the whole chain 'ip_ml_4_rawChain', under independence assumption:
0.18083


Estimated standard deviation of sample mean for the whole chain 'ip_ml_4_rawChain', under independence assumption:
0.425241

Sub Mean and variances took 0.007206 seconds

Sub mean, sample std, population std
Parameter    Mean         SampleStd         Popul.Std
           7.0414e+01   4.2524e+01   4.2522e+01

Ended computing mean, sample variance and population variance
-----------------------------------------------------


-----------------------------------------------------
 Computing histogram and/or cdf stacc and/or Kde for chain 'ip_ml_4_rawChain' ...
-----------------------------------------------------


-----------------------------------------------------
Computing min and max for histograms and Kde

Computed min values and max values for chain 'ip_ml_4_rawChain'
Parameter         min         max
           6.8086e+00   1.1884e+02
Chain min and max took 0.002716 seconds

-----------------------------------------------------
Computing Kde
In uqScalarSequence<T>::subInterQuantileRange(): iqrValue = 90.9597, dataSize = 10000, pos1 = 2499, pos3 = 7499, value1 = 10.8434, value3 = 101.803
In uqScalarSequence<T>::subScaleForKde(): iqrValue = 90.9597, meanValue = 70.4141, samValue = 1808.3, dataSize = 10000, scaleValue = 7.14399

Computed inter quantile ranges for chain 'ip_ml_4_rawChain'
Parameter         iqr
           9.0960e+01
Chain Kde took 0.155757 seconds

-----------------------------------------------------
 Finished computing histogram and/or cdf stacc and/or Kde for chain 'ip_ml_4_rawChain'
-----------------------------------------------------



-----------------------------------------------------
 Computing covariance and correlation matrices for chain 'ip_ml_4_rawChain' ...
-----------------------------------------------------


uqBaseVectorSequence<V,M>::computeCovCorrMatrices, chain ip_ml_4_rawChain: contents of covariance matrix are
1808.3 

uqBaseVectorSequence<V,M>::computeCovCorrMatrices, chain ip_ml_4_rawChain: contents of correlation matrix are
1 

-----------------------------------------------------
 Finished computing covariance and correlation matrices for chain 'ip_ml_4_rawChain'
-----------------------------------------------------

All statistics of chain 'ip_ml_4_rawChain' took 0.178709 seconds

-----------------------------------------------------
 Finished computing statistics for chain 'ip_ml_4_rawChain'
-----------------------------------------------------

In uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 11, before calling currLogLikelihoodValues.unifiedWriteContents(), currLogLikelihoodValues[0] = -2.94507
Entering uqSequenceOfVectors<V,M>::filter(): initialPos = 0, spacing = 2, subSequenceSize = 10000
Leaving uqSequenceOfVectors<V,M>::filter(): initialPos = 0, spacing = 2, subSequenceSize = 5000
Entering uqScalarSequence<V,M>::filter(): initialPos = 0, spacing = 2, subSequenceSize = 10000
Leaving uqScalarSequence<V,M>::filter(): initialPos = 0, spacing = 2, subSequenceSize = 5000
Entering uqScalarSequence<V,M>::filter(): initialPos = 0, spacing = 2, subSequenceSize = 10000
Leaving uqScalarSequence<V,M>::filter(): initialPos = 0, spacing = 2, subSequenceSize = 5000


-----------------------------------------------------
 Computing statistics for chain 'ip_ml_last_filtChain' ...
-----------------------------------------------------

In uqBaseVectorSequence<V,M>::computeStatistics(): statisticalOptions.initialDiscardedPortions()[0] = 0, initialPosForStatistics[0] = 0
In uqBaseVectorSequence<V,M>::computeStatistics(): initial positions for statistics = 0

-----------------------------------------------------
Computing mean, sample variance and population variance

Estimated variance of sample mean for the whole chain 'ip_ml_last_filtChain', under independence assumption:
0.362935


Estimated standard deviation of sample mean for the whole chain 'ip_ml_last_filtChain', under independence assumption:
0.602441

Sub Mean and variances took 0.00211 seconds

Sub mean, sample std, population std
Parameter    Mean         SampleStd         Popul.Std
           7.0369e+01   4.2599e+01   4.2595e+01

Ended computing mean, sample variance and population variance
-----------------------------------------------------


-----------------------------------------------------
 Computing histogram and/or cdf stacc and/or Kde for chain 'ip_ml_last_filtChain' ...
-----------------------------------------------------


-----------------------------------------------------
Computing min and max for histograms and Kde

Computed min values and max values for chain 'ip_ml_last_filtChain'
Parameter         min         max
           6.8086e+00   1.1553e+02
Chain min and max took 0.000775 seconds

-----------------------------------------------------
Computing Kde
In uqScalarSequence<T>::subInterQuantileRange(): iqrValue = 91.0568, dataSize = 5000, pos1 = 1249, pos3 = 3749, value1 = 10.8222, value3 = 101.879
In uqScalarSequence<T>::subScaleForKde(): iqrValue = 91.0568, meanValue = 70.369, samValue = 1814.68, dataSize = 5000, scaleValue = 8.22075

Computed inter quantile ranges for chain 'ip_ml_last_filtChain'
Parameter         iqr
           9.1057e+01
Chain Kde took 0.084594 seconds

-----------------------------------------------------
 Finished computing histogram and/or cdf stacc and/or Kde for chain 'ip_ml_last_filtChain'
-----------------------------------------------------



-----------------------------------------------------
 Computing covariance and correlation matrices for chain 'ip_ml_last_filtChain' ...
-----------------------------------------------------


uqBaseVectorSequence<V,M>::computeCovCorrMatrices, chain ip_ml_last_filtChain: contents of covariance matrix are
1814.68 

uqBaseVectorSequence<V,M>::computeCovCorrMatrices, chain ip_ml_last_filtChain: contents of correlation matrix are
1 

-----------------------------------------------------
 Finished computing covariance and correlation matrices for chain 'ip_ml_last_filtChain'
-----------------------------------------------------

All statistics of chain 'ip_ml_last_filtChain' took 0.091371 seconds

-----------------------------------------------------
 Finished computing statistics for chain 'ip_ml_last_filtChain'
-----------------------------------------------------

Leaving uqMLSampling<P_V,P_M>::generateSequence_Step(), level 4, step 11, after 0.410814 seconds
In uqMLSampling<P_V,P_M>::generateSequence(): ending level 4, having generated 5000 chain positions, cumulativeRawChainRunTime = 0.258501 seconds, total level time = 1.43221 seconds, cumulativeRawChainRejections = 1056 (10.56% at this processor) (10.56% over all processors), stopAtEndOfLevel = 0
In uqMLSampling<P_V,P_M>::generateSequence(), level 4: min cumul seconds = 0.258501, avg cumul seconds = 0.258501, max cumul seconds = 0.258501, min level seconds = 1.43221, avg level seconds = 1.43221, max level seconds = 1.43221
In uqMLSampling<P_V,P_M>::generateSequence(), log(evidence) = -6.26693, evidence = 0.00189805
Leaving uqMLSampling<P_V,P_M>::generateSequence()
In uqSequentialVectorRealizer<V,M>::constructor(): m_chain.subSequenceSize() = 5000

numPosTotal = 5000
numPosSmallerThan40 = 1650, ratio = 0.33
seq1.size() = 1650
 seq1.mean() = 10.004
 seq1.std() = 1.0733
seq2.size() = 3350
 seq2.mean() = 100.101
 seq2.std() = 5.3482
seqAll.size() = 5000
 seqAll.mean() = 70.369
 seqAll.std() = 42.599
integral = 1
Ending run at Wed Sep 22 20:35:07 2010
Total run time = 2 seconds
