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RAVEN is a flexible and multi-purpose probabilistic risk analysis, validation and uncertainty quantification, parameter optimization, model reduction and data knowledge-discovering framework.

Home Page: https://raven.inl.gov/

License: Apache License 2.0

Makefile 0.01% Python 13.54% TeX 0.86% Shell 0.23% C++ 81.65% Batchfile 0.01% SWIG 0.02% Assembly 2.81% R 0.01% CMake 0.01% C 0.18% Perl 0.01% MATLAB 0.55% Jupyter Notebook 0.15%

risk-analysis uncertainty-quantification probabilistic-analysis data-mining optimization-algorithms parametric-analysis validation model-reduction model-calibration

raven's Introduction

Raven

Risk Analysis Virtual Environment

RAVEN is designed to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is capable of investigating the system response as well as the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. RAVEN includes the following major capabilities:

Sampling of codes for uncertainty quantification and reliability analyses
Generation and use of reduced-order models (also known as surrogate)
Data post-processing (time dependent and steady state)
Time dependent and steady state, statistical estimation and sensitivity analysis (mean, variance, sensitivity coefficients, etc.).

The RAVEN statistical analysis framework can be employed for several types of applications:

Uncertainty Quantification
Sensitivity Analysis / Regression Analysis
Probabilistic Risk and Reliability Analysis (PRA)
Data Mining Analysis
Model Optimization

RAVEN provides a set of basic and advanced capabilities that ranges from data generation, data processing and data visualization.

Computing environment

Parallel computation capabilities (multi-thread and multi-core)
Supported operating systems: MAC, Linux and Windows
Workstation and high performance computing (HPC) systems

Forward propagation of uncertainties

MonteCarlo sampling
Grid sampling
Stratified Sampling
Factorial design
Response surface design
Generalized Polynomial Chaos (gPC) with sparse grid collocation (SGC)
Generalized Polynomial Chaos (gPC) with sparse grid collocation (SGC) using the High Dimensional Model Representation expansion (HDMR)
General combination of the above sampling strategies

Advance sampling methods

Moment driven adaptive gPC using SGC
Sobol index driven HDMR integrated using SGC over gPC basis
Adaptive sampling for limit surface finding (surrogate and multi grid based accelerations)
Dynamic event tree-based sampling (Dynamic Event Trees, Hybrid Dynamic Event Trees, Adaptive Dynamic Event Trees, Adaptive Hybrid Dynamic Event Trees)

Creation and use of reduced order models

Support Vector Machine-based surrogates
Gaussian process models
Linear models
Multi-class classifiers
Decision trees
Naive Bayes
Neighbors classifiers and regressors
Multi-dimensional interpolators
High dimension model reduction (HDMR)
Morse-Smale complex

Model capabilities

Generic interface with external codes
Custom code interfaces (third-party software(s) currently available:
- RELAP5-3D
- MELCOR
- MAAP5
- MOOSE-BASED Apps
- SCALE
- SERPENT
- CTF - COBRA TF
- SAPHIRE
- MODELICA
- DYMOLA
- BISON
- RATTLESNAKE
- MAMMOTH
- GOTHIC
- PHISICS
- NEUTRINO
- RAVEN running itself
Custom ad-hoc external models (build in python internally to RAVEN)

Data Post-Processing capabilities

Data clustering
Data regression
Data dimensionality Reduction
Custom generic post-processors
Time-dependent data analysis (statistics, clustering and time warping metrics)
Data plotting

Model parameter optimization

Simultaneous perturbation stochastic approximation method

Data management

Data importing and exporting
Databases creation

More information on this project is available at the RAVEN website.

This project is supported by Idaho National Laboratory.

Other Software

Idaho National Laboratory is a cutting edge research facility which is a constantly producing high quality research and software. Feel free to take a look at our other software and scientific offerings at:

Primary Technology Offerings Page

Supported Open Source Software

Raw Experiment Open Source Software

Unsupported Open Source Software

License

Files in crow/contrib, src/contrib and framework/contrib are third party libraries that are not part of Raven and are provided here for covenience. These are under their own, seperate licensing which is described in those directories.

Raven itself is licensed as follows:

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

raven's People

Contributors

Stargazers

Watchers

Forkers

wangcj05 avxale paultalbot-inl world2005 joshua-cogliati-inl bobkinl sonatsen alfoa mattdon gianfabi maljovec kongnuanzhao reakain grseb9s derekstucki jbae11 safruk jdrader86 since801 cnjelita mazzol eycab magrestr waynemorrison elementx54 rainxwang milljm bonifak flanflanagan rubiruchi ldxu93 jiazhou-pu pralhadburli vgurev brandonyuong xuhan425 jiangwen84 flobbidinous rajtapase jimmy-inl emeraldryan khurrumsaleem wangjiaddx volpatto frankyfoody jrincayc fkshi alptezbasaran mmkvdev amoyyy polaris-cn thedoctorrab dylanjm pxm321 archmagethanos tann10 yoshiurr-inl geofiber rinelson456 hcbinl huang714 aalfonsi yuxingxing421 hxdaze hrnciar mgarrouste yenili utjfritz ustbcmspjy drpaulz filin-dev blackb3ard65 rahulprabhakaran dgarrett622 eunseoso yyheo27 greenwoodms06 shimingyin brennanxyz niharika2999 globalhelpforall botroshanna-inl worseliz j-bryan maldil dgardner26 gabrielsoto-inl shism2 haeseongkim-inl junyungkim nhatkhang acrigby jacktang heagysa gonzrl crisluqueg phymucs caldmet70 santoshbalija anthoneygriffith

raven's Issues

Improvements to comparison statistics

From https://hpcgitlab.inl.gov/idaholab/raven/issues/141 and https://hpcgitlab.inl.gov/idaholab/raven/issues/202

There are several features that should be tested in comparison statistics. These need regression tests as well. The comparison statistics should be tested with a discrete distribution. The comparison statistics should be checked with a non-monte carlo sampler.

ProbabilityWeights and PointProbabilities in OutStream printing

First, this feature is undocumented: in the what node of a Print OutStream the user can ask for Input|ProbabilityWeights (similarly for PointProbabilities):

<OutStreams>
  <Print name="dump">
    <type>csv</type>
    <source>data</source>
    <what>Input,Output,Input|ProbabilityWeights</what>
  </Print>

This feature should be documented. In that documentation we should note the weights printed are not necessarily normalized.

In addition, currently some samplers (e.g. MonteCarlo and Custom) do not provide entries to the ProbabilityWeights entry, which causes an error for the user. These should be provided, even if they are assumed to be uniform weights. (This last entry may have been fixed since the original writing of this issue on gitlab).

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Constants in Samplers and Optimizers

Issue Description

What did you expect to see happen?

In any Sampler and Optimizer we should be able to list variables that can be kept constants.

Do you have a suggested fix for the development team?

For example, the following input style can be used:

  <Samplers>
    <MonteCarlo>
       <variable name="a variable"> 
         <distribution>a distribution</distribution>
       </variable>
      <constant name="a constant variable">1.123456789</constant>
    </MonteCarlo>

  </Samplers>

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement? IMPROVEMENT
2. Is it tagged with a priority: critical, normal or minor? NORMAL
3. If it will impact requirements or requirements tests, is it tagged with requirements? NO
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users. NO DEFECT
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.) YES

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Metadata XML writing is intensive

While writing the results of a 10k MC sampling with 671 input variables, the CSV was written successfully but writing the accompanying XML file crashed the available memory on a node on the HPC.

Perhaps we should consider more memory-efficient ways of writing out this file. I suspect the issue is in construction the large XML tree before writing it, as we've run into this before with writing large BasicStatistics XML files.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Add more Distributions

It would be useful to add more probability distributions. From: https://hpcgitlab.inl.gov/idaholab/raven/issues/803

For Change Control Board: Issue Review

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1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Relative path for ExternalXML

Currently when using relative pathing, ExternalXML paths start at the run directory, not the WorkingDir directory. This is confusing from a user standpoint, as most entities have been standardized to work from the working directory.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

ExternalXML efficiency and generality

ExternalXML algorithms currently restart the search through all the XML nodes in the input whenever an ExternalXML node is discovered. This is required because of how xml.etree.ElementTree.Element.iter() works, as it kills the tree when the tree is modified.

This efficiency could be improved by finding a workaround to loop over an unmodified deepcopy of the tree, and analyze each new ExternalXML import for additional ExternalXML nodes, instead of the current approach.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Encapsulating in Samplers

Right now there is a lot of duplicated methods/structures/conditionals in the Samplers, hopefully some of which can be removed. Right now it is a jungle for new developers trying to determine what a Sampler should do, and how. The idea is to list some here as they are seen, which can then be addressed.

Fully Coupled Variables

Often, the following is seen in the localGenerateInput methods:

  for kkey in varID.strip().split(','):
    self.values[kkey] = value

To prevent the developer from knowing WHY he has to loop over entries in varID, and since all samplers do this, we can implement a method in the base class like

  def placeValue(self,variable,value):
    for var in variable.strip().split(','):
      self.values[var] = value

Multidimensional

Each localGenerateInput has some kind of checker to see if the dimensions used is one or more. It would be great if we could abstract the sampling to remove most of the duplicated code in these portions.

Point Probability

Each localGenerateInput sets the self.inputInfo['SampledVarsPb'] using the PDF of the point, which might be through a variety of different methods depending on transformed space, multidimensional distribution, coupled variables, etc. It would be developer-friendly to abstract this if reasonably possible.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Remove mentions of hpcgitlab

Issue Description

What did you expect to see happen?

No mentions of hpcgitlab

What did you see instead?

The manual mentions hpcgitlab several places.

Do you have a suggested fix for the development team?

Move everything that is in hpcgitlab to raven.inl.gov or github.

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Conversion scripts on --tests not searching external XML nodes

Running a conversion script with arguments --tests searches and obtains the XML input files for the regression systems. It does not, however, obtain any ExternalXML node inputs, so some of these may be missed when running conversion scripts.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Inconsistency with _readdressEvaluateFromResponse

Issue Description

What did you expect to see happen?

When the SciKitLearn._readdressEvaluateFromResponse method is called, it should return objects consistent with the ROM.evaluate method that it replaces.

What did you see instead?

_readdressEvaluateFromResponse returns scalar values for applicable targets, and not an array of values if multiple inputs are provided to evaluate.

Do you have a suggested fix for the development team?

Adjust the method to respect the number of inputs provided by checking the length of input arrays.

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

GitHub won't let me attach an XML file. This could be an interesting issue in the future of issue postings. It looks like it does accept ZIP files though.

This came up while using the Optimizer, unnormalized, with inputs of widely-varying scales.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

ROM training status check

Issue Description

What did you expect to see happen?

RAVEN should check if a ROM is actually trained: if I am evaluating a ROM I should receive an error message and actually stop the RAVEN run

What did you see instead?

A message actually appears but it could be improved especially if the RAVEN run stops. You might get this error into a step down the line of the RAVEN analysis

Do you have a suggested fix for the development team?

This error message could be put when the ROM is evaluated. i.e., the evaluate method

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement? improvement
2. Is it tagged with a priority: critical, normal or minor? normal
3. If it will impact requirements or requirements tests, is it tagged with requirements? NA
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users. No
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.) Yes

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Remove use of xml from Distributions

Most of the time, Distributions uses the ParameterInput to get data, this should be used everywhere and the _readMoreXML functions should be removed. Right now they are just used in a few places such as TestDistributions that should be rewritten.

Collocation methods with simultaneously-sampled variables

Currently, it is not possible to use simultaneously sampled variables to construct a collocation-based ROM.

By simultaneously sampled, I mean an entry as follows in the Sampler:

<variable name="x,y">
    <distribution>uni_dist</distribution>
</variable>

This is because the sampler axisName will be "x,y", while there is no way to list this combined axis as a ROM feature in the input.

While this is a defect, the code will not run if it is attempted, so it does not result in erroneous results, only a lack of ability.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Crow tests need to use integer indexs

Issue Description

What did you expect to see happen?

The crow tests to pass with numpy 1.12.1

What did you see instead?

Failures like:

crow.test_svd..................................................................................... FAILED (1)
crow.test_svd: Working Directory: /home/jjc/sub/raven/tests/crow
crow.test_svd: Running command: python test_eigen_svd.py
crow.test_svd: raven_dir /home/jjc/sub/raven
crow.test_svd: Traceback (most recent call last):
crow.test_svd:   File "test_eigen_svd.py", line 70, in <module>
crow.test_svd:     covNp = np.asarray(cov).reshape(-1,sqrt(len(cov)))
crow.test_svd: TypeError: 'float' object cannot be interpreted as an index
crow.test_svd:

Do you have a suggested fix for the development team?

Use int around the sqrt.

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

It is the crow regression tests.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Analytic Batemen example class has no explanatory documentation

Issue Description

What did you expect to see happen?

I expected explanatory docstrings in the user guide example model AnalyticBateman

What did you see instead?

There is a dearth of such docstrings

Do you have a suggested fix for the development team?

I suggest a few explanatory details be placed into the model so that it can provide more insight to the future users of the user guide.

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

See tests/framework/user_guide/physicalCode/analyticalbateman/BatemanClass.py.

For Devs: Issue Review

1. Is it tagged with a type: defect or improvement? tagged
2. Is it tagged with a priority: critical, normal or minor? tagged
3. If it will impact requirements or requirements tests, is it tagged with requirements? n/a
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users. n/a
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.) provided

For Devs: Issue Closure

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
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No-executable interface tests not working as expected

Issue Description

What did you expect to see happen?

No-executable interface tests should be checking the input modification and output parsing functionality of code interfaces.

What did you see instead?

Output reading is not occurring if the executable command returns a nonzero value from the command line. For example, for the test raven/tests/framework/CodeInterfaceTests/test_relap5_code_interface.xml, all of the samples fail on the OS level, so their outputs are not read in. However, RAVEN simply reports these as failed runs and moves on. As far as I can tell, the output is not read into RAVEN.

Do you have a suggested fix for the development team?

This can be solved by adding a dedicated flag or node for indicating "interface only" testing, which would set a Model-level variable that the Step can check next to the check if the OS returned a 0 value for the run.

This can be tested by actually compiling an output CSV from the gold output files and testing its contents (probably with broad tolerance for deltas).

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

See test listed above.

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5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.) rationale is insufficient; there is already a method in place for this.

Issue will be closed without development.

Moose MultiApp interface

This applies specifically to the MOOSE-based app CodeInterface. It is not a main framework issue.

While we do a great job handling single-physics code interfaces for MOOSE-based apps, we don't have a generic tool yet that would handle arbitrary multiapps with multiple input files. It would be simple to prepend the variable lists with the name of the file they come from, or make that an argument to the XML node, or something similar, but this has not been done yet.

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DET-based samplers input creation standardization

Issue Description

What did you like to improve?

The DET-based samplers have a different way to create an input (multiple inputs created at the finalizeActualSampler). This deviation can be corrected restructuring the input creation flow.

What did you see instead?

The DET-bases samplers can use the same approach for input creation used by other samplers

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5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

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Underdefined inputs while using PCA

When using the PCA transform for sampling, the user can specify the number of transform variables to use.

If the user chooses too few tranform variables, there may not be enough to provide values to all the original input space, resulting in zeroes for all under-represented original space variables.

This can result in nonsensical inputs being provided to the model (like a total cross section of zero).

We don't have anything in place to warn the user that this phenomenon is happening.

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Verbosity and DataObjects

Changing the verbosity of a data object in the input does not result in reduced output to screen.

Namely, I set verbosity=silent but still received the message

( 61.47 sec) DataObjects : Message -> Object type csv named "out~25~rinp_raven.csv"

This should be fixed.

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Update NOTICE.txt for Author list

Update the NOTICE.txt file to add all the main contributors of the RAVEN project

limit parameter in Sampler incorrectly parsed

From: https://hpcgitlab.inl.gov/idaholab/raven/issues/683

The 'limit' parameter in the Sampler base class is parsed as a string rather than an int, which makes the count check in Sampler's amIreadyToProvideAnInput erroneously always return True even if the limit has been exceeded.

Changing this line in readSamplerInit(): self.limit = childChild.text to: self.limit = int(childChild.text) fixes the problem.

Message Handling passed through Assembler

@alfoa suggested we might simplify our lives by making the MessageHandler instance an object that is obtained by default through the assembler, instead of passed in instantiation.

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Increased IOStep Explanations in User Guide

Right now there's not much explanation on how to use the IOStep variants in the user manual. While this might be a job for the user guide, somewhere we should explain things like loading CSV into data objects, outstreaming to CSV, what happens when you IO to/from an HDF5, etc.

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missing attribute for SKLearn unsupervised learning nodes

In clustering and PCA postprocessing models, there is a labelFeature attribute used in the test cases that isn't documented in the user manual.

Additionally, postprocessors that add a column to a data object should identify this behavior in the user manual (this might be a bigger issue).

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Remove Crow submodule from manual

Issue Description

What did you expect to see happen?

The install manual would not mention crow.

What did you see instead?

Things like:

git submodule update --init moose crow

Do you have a suggested fix for the development team?

Fix the manual

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

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4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users. n/a
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.) yes

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1. If the issue is a defect, is the defect fixed? improvement
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3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)? improvement
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)? improvement
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided? #23

Documentation for Optimizer

There are a couple things.

First, the gain parameters all have virtually identical documentation, which makes them difficult to differentiate, especially when one does not have access to the reference paper cited.

Second, there is a hard-coded input space for the SolutionExport of an Optimizer-based step, using the input "trajID", but this isn't mentioned in the user manual. I couldn't find an example in the user guide either. Some explanation of the necessary mechanics would be quite helpful.

Third, the node <parameter> is incorrectly listed as in the documentation (the example is correct).

Fourth, in the <Functions> block description, it indicates absence of Functions and the <upperBound> nodes results in an unconstrained problem; however, the <upperBound> nodes are indicated as required for each variable.

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5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.) yes

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Strange results in Ubuntu 16.04

Issue Description

What did you expect to see happen?

More normal Sensitivities.
input.zip

What did you see instead?

Do you have a suggested fix for the development team?

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

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Message Handling in Modules

Currently the message handler is passed only to instances of class objects. This doesn't allow module-level methods to make use of the message handler, which leaves many "print" statements that don't conform to the rest of the code.

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Typo in ImageDiff.py tester

The printout statement has a type that read "godImage" instead of "goldImage". This isn't caught by tests because it is only seen in a failure case.

Issue Review Checklist

1. Is it tagged with a type: defect or improvement? tagged
2. Is it tagged with a priority: critical, normal or minor? tagged
3. If it will impact requirements or requirements tests, is it tagged with requirements? n/a
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users. no, it cannot cause wrong results
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.) provided

Improve the CSV checking

From https://hpcgitlab.inl.gov/idaholab/raven/issues/133

Right now there are two CSV checkers, the CSVDiffer.py and the UnorderedCSVDiffer.py They have somewhat different abilities.

Original Text:
Right now the regression tests only can check CSV files that have one line of header, followed by equal numbers of numbers. It would be useful if this could be changed.

Possibly we should have two comparison, one for column type CSV (what we currently have) and one for free format CSVs, and the freeformat would not have the restrictions, and also would require that the columns stay in the same order.

This will require modification to scripts/TestHarness/testers/RavenFramework.py

Comments on Gitlab:
We can check unordered rows, but we can't check unordered columns, or mismatched lengths, as far as I'm aware. Unless someone else added this....

DataObjects in Code versus ExternalModel

Mainly, we only run DataObject.checkConsistency on a "code" model run (when we run "addOutput" in the collection). The external model collection is submitted to no consistency check. This forked behavior leads to significant differences in behavior at both the Step and DataObject level despite only being a difference in the Model.

This is a problem since it does not align with our intention to have modules act independently of each other, and consistently between options.

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Reading input space from Code output

As per a team meeting discussion held on April 4, 2016, a few concepts about restarts came forward.

When RAVEN stores a sample in a data object, it reads the input space first from the output of the model, if possible, then the internal storage, if not available.

This can create an issue of the output of the model returns low-resolution values, as these values will not match the searched-for values in a restart.

We discussed adding a flag that will trigger the above behavior when desired, but by default will use RAVEN internal values first when possible.

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Regression test for time

From https://hpcgitlab.inl.gov/idaholab/raven/issues/26
It would be useful to have a way of testing for performance regressions. This would require some way of determining if the performance has slowed down compared to previous run times.

framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic randomly fails

The test framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic randomly fails.

Test file does not exist: /home/moosetest/civet/client_root_0/raven/tests/framework/pca_adaptive_sgc/polynomial/csv_database.csv)
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Working Directory: /home/moosetest/civet/client_root_0/raven/tests/framework/pca_adaptive_sgc
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Running command: python /home/moosetest/civet/client_root_0/raven/framework/Driver.py test_adaptive_sgc_poly_pca_analytic.xml
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: /opt/moose/miniconda/lib/python2.7/site-packages/sklearn/qda.py:6: DeprecationWarning: qda.QDA has been moved to discriminant_analysis.QuadraticDiscriminantAnalysis in 0.17 and will be removed in 0.19.
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:   "in 0.17 and will be removed in 0.19.", DeprecationWarning)
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: /opt/moose/miniconda/lib/python2.7/site-packages/sklearn/lda.py:6: DeprecationWarning: lda.LDA has been moved to discriminant_analysis.LinearDiscriminantAnalysis in 0.17 and will be removed in 0.19
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:   "in 0.17 and will be removed in 0.19", DeprecationWarning)
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:       .---.        .------######       #####     ###   ###  ########  ###    ##
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:      /     \  __  /    --###  ###    ###  ###   ###   ###  ###       #####  ##
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:     / /     \(  )/    --###  ###    ###   ###  ###   ###  ######    ### #####
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:    //////   ' \/ `   --#######     #########  ###   ###  ###       ###  ####
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:   //// / // :    :   -###   ###   ###   ###    ######   ####      ###   ###
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:  // /   /  /`    '---###     ### ###   ###      ##     ########  ###    ##
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: //          //..\
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: ===========UU====UU=============================================================
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:            '//||\`
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:              ''``
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:     
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Copyright 2017 Battelle Energy Alliance, LLC
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Licensed under the Apache License, Version 2.0 (the "License");
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: you may not use this file except in compliance with the License.
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: You may obtain a copy of the License at
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: http://www.apache.org/licenses/LICENSE-2.0
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Unless required by applicable law or agreed to in writing, software
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: distributed under the License is distributed on an "AS IS" BASIS,
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: See the License for the specific language governing permissions and
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: limitations under the License.
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:   
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) SIMULATION               : Message         -> Simulation started at 2017-04-05 10:00:41
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) SIMULATION               : Message         -> Global verbosity level is " debug "
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) SIMULATION               : DEBUG           -> -- Reading the block: RunInfo        --
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) SIMULATION               : DEBUG           -> -- Reading the block: DataObjects    --
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) SIMULATION               : DEBUG           -> Reading type PointSet with name dummyIN
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Type           : PointSet
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Class          : PointSet        from <class 'DataObjects.Data.Data'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Name           : dummyIN
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        inParam        : [u'x1', u'x2', u'x3', u'x4', u'x5']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Input_4        : x5
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        hierarchical   : False
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Input_2        : x3
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Input_3        : x4
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Input_0        : x1
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Input_1        : x2
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Output_0       : OutputPlaceHolder
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        outParam       : [u'OutputPlaceHolder']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) DataObjects              : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.00 sec) SIMULATION               : DEBUG           -> Reading type PointSet with name collset
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Type           : PointSet
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Class          : PointSet        from <class 'DataObjects.Data.Data'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Name           : collset
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        inParam        : [u'x1', u'x2', u'x3', u'x4', u'x5', u'y1', u'y2', u'y3', u'y4', u'y5']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Output_0       : ans
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_6        : y2
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_7        : y3
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_4        : x5
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_5        : y1
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_2        : x3
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_3        : x4
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_0        : x1
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_1        : x2
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        hierarchical   : False
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        outParam       : [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_8        : y4
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Input_9        : y5
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DataObjects              : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) SIMULATION               : DEBUG           -> -- Reading the block: Distributions  --
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : Message         -> initialize distribution
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        Type           : MultivariateNormal
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        Class          : MultivariateNormal from <class 'Distributions.NDimensionalDistributions'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        Name           : MVNDist
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        lowerBoundUsed : False
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        hasInfiniteBound: False
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        lowerBound     : 0.0
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        messageHandler : <MessageHandler.MessageHandler object at 0x7f2a74d60b90>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        upperBoundUsed : False
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        upperBound     : 0.0
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        dataFilename   : None
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        dimensionality : None
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        adjustmentType : 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        functionType   : None
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) DISTRIBUTIONS            : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) SIMULATION               : DEBUG           -> -- Reading the block: Samplers       --
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) SIMULATION               : DEBUG           -> Reading type AdaptiveSparseGrid with name asgc
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : Warning         -> Index is not provided for manifestVariables, default index will be used instead!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        Type           : AdaptiveSparseGrid
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        Class          : AdaptiveSparseGrid from <class 'Samplers.SparseGridCollocation.SparseGridCollocation'> <class 'Samplers.AdaptiveSampler.AdaptiveSampler'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        Name           : asgc
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        initial seed   : 1749605806
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        limit          : 9223372036854775807
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        y1             : is sampled using the distribution MVNDist
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        y3             : is sampled using the distribution MVNDist
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        y2             : is sampled using the distribution MVNDist
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        y5             : is sampled using the distribution MVNDist
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        y4             : is sampled using the distribution MVNDist
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        SampledVarsPb  : {}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        PointProbability: None
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        counter        : 0
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        crowDist       : {}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) AdaptiveSparseGrid       : DEBUG           ->        initial seed   : 1749605806
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) SIMULATION               : DEBUG           -> -- Reading the block: Models         --
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) SIMULATION               : DEBUG           -> Reading type ExternalModel with name poly
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (            ) UTILS                    : Message         -> importing module /home/moosetest/civet/client_root_0/raven/tests/framework/pca_adaptive_sgc/polynomial/poly
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) ExternalModel            : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) ExternalModel            : DEBUG           ->        Type           : ExternalModel
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) ExternalModel            : DEBUG           ->        Class          : ExternalModel   from <class 'Models.Dummy'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) ExternalModel            : DEBUG           ->        Name           : poly
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) ExternalModel            : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) ExternalModel            : DEBUG           ->        subType        : 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) ExternalModel            : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) SIMULATION               : DEBUG           -> Reading type ROM with name rom
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) ROM                      : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.01 sec) ROM                      : DEBUG           ->        Type           : ROM
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        Class          : ROM             from <class 'Models.Dummy'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        Name           : rom
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        Target         : [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        PolynomialOrder: 4
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        IndexSet       : TotalDegree
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        Features       : [u'y1', u'y2', u'y3', u'y4', u'y5']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        returnType     : 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        qualityEstType : []
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        name           : rom
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) ROM                      : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : DEBUG           -> -- Reading the block: Steps          --
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : DEBUG           -> Reading type MultiRun with name sample
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           -> move this tests to base class when it is ready for all the classes
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           -> the mapping used in the model for checking the compatibility of usage should be more similar to self.parList to avoid the double mapping below FIXME
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           -> reactivate check on Input as soon as loadCsv gets out from the PostProcessor models!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Type           : MultiRun
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Class          : MultiRun        from <class 'Steps.SingleRun'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Name           : sample
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Sampler        : Class: Samplers Type: AdaptiveSparseGrid  Global name: asgc
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Initial seed   : None
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Input          : Class: DataObjects Type: PointSet  Global name: dummyIN
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Output         : Class: DataObjects Type: PointSet  Global name: collset
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Sleep time     : 0.0001
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Model          : Class: Models Type: ExternalModel  Global name: poly
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP MULTIRUN            : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : DEBUG           -> Reading type IOStep with name print
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           -> move this tests to base class when it is ready for all the classes
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Type           : IOStep
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Class          : IOStep          from <class 'Steps.Step'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Name           : print
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Output         : Class: OutStreams Type: Print  Global name: csv_database
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Input          : Class: DataObjects Type: PointSet  Global name: collset
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Sleep time     : 0.005
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Initial seed   : None
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : DEBUG           -> Reading type IOStep with name stats
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           -> move this tests to base class when it is ready for all the classes
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Type           : IOStep
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Class          : IOStep          from <class 'Steps.Step'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Name           : stats
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Output         : Class: OutStreams Type: Print  Global name: stats_td1
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Input          : Class: Models Type: ROM  Global name: rom
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Sleep time     : 0.005
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Initial seed   : None
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP IOCOMBINED          : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : DEBUG           -> Reading type RomTrainer with name train
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           -> move this tests to base class when it is ready for all the classes
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           ->        Type           : RomTrainer
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           ->        Class          : RomTrainer      from <class 'Steps.Step'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           ->        Name           : train
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           ->        Output         : Class: Models Type: ROM  Global name: rom
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           ->        Input          : Class: DataObjects Type: PointSet  Global name: collset
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           ->        Sleep time     : 0.005
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           ->        Initial seed   : None
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) STEP ROM TRAINER         : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : DEBUG           -> -- Reading the block: OutStreams     --
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : DEBUG           -> Reading type Print with name csv_database
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Type           : OutStreamPrint
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Class          : OutStreamPrint  from <class 'OutStreams.OutStreamManager.OutStreamManager'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Name           : csv_database
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Source Name 0 :: collset
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Specialized Class Type            : OutStreamPrint
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Overwrite output everytime called : True
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Global Class Type                 : OutStreamManager
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : DEBUG           -> Reading type Print with name stats_td1
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           -> ------Reading Completed for:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Type           : OutStreamPrint
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Class          : OutStreamPrint  from <class 'OutStreams.OutStreamManager.OutStreamManager'>
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Name           : stats_td1
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Initialization Parameters:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 10 :: n
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 9 :: a
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Global Class Type                 : OutStreamManager
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 2 :: a
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Specialized Class Type            : OutStreamPrint
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 12 :: e
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 7 :: r
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 11 :: c
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 4 :: ,
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Source Name 0 :: rom
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 8 :: i
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 1 :: e
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 5 :: v
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 6 :: a
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 3 :: n
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Variable Name 0 :: m
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Overwrite output everytime called : True
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) OUTSTREAM MANAGER        : DEBUG           ->        Current Setting:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : DEBUG           -> entering the run
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.02 sec) SIMULATION               : Message         -> -- Beginning step sample of type: MultiRun                          --
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) STEP MULTIRUN            : Message         -> ***  Beginning initialization ***
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) STEP MULTIRUN            : DEBUG           -> jobHandler initialized
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) STEP MULTIRUN            : DEBUG           -> for the role Model  the item of class ExternalModel   and name poly            has been initialized
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) STEP MULTIRUN            : DEBUG           -> for the role Output the item of class PointSet        and name collset         has been initialized
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : Message         -> No restart for AdaptiveSparseGrid
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : DEBUG           ->  INTERPOLATION INFO:
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : DEBUG           ->     Variable | Distribution | Quadrature | Polynomials
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : DEBUG           ->    y1 | MultivariateNormal | Hermite | Hermite
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : DEBUG           ->    y3 | MultivariateNormal | Hermite | Hermite
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : DEBUG           ->    y2 | MultivariateNormal | Hermite | Hermite
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : DEBUG           ->    y5 | MultivariateNormal | Hermite | Hermite
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : DEBUG           ->    y4 | MultivariateNormal | Hermite | Hermite
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : DEBUG           ->     Polynomial Set Type  : adaptive
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.03 sec) AdaptiveSparseGrid       : DEBUG           -> Starting index set generation...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.13 sec) STEP MULTIRUN            : DEBUG           -> for the role of sampler the item of class AdaptiveSparseGrid and name asgc has been initialized
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.13 sec) STEP MULTIRUN            : DEBUG           -> Sampler initialization dictionary: {u'externalSeeding': None}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.13 sec) STEP MULTIRUN            : DEBUG           -> Generating input batch of size 1
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.13 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.13 sec) STEP MULTIRUN            : DEBUG           -> Submitted input 1
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.13 sec) STEP MULTIRUN            : Message         -> ***    Initialization done    ***
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.13 sec) STEP MULTIRUN            : Message         -> ***       Beginning run       ***
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.14 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input      1
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.14 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': 0.29999999999999993, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -1.1, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': 1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': -1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.16 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.6, u'y3': 0.0, u'y2': 0.0, u'y5': 1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.16 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.16 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.0, u'y3': 0.0, u'y2': 0.0, u'y5': -1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.16 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.16 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.16 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.17 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input      2
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.17 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.21 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input      3
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.21 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.22 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input      4
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.22 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.23 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input      5
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.23 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.24 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input      6
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.24 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.25 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input      7
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.25 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.27 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input      8
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.27 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.28 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input      9
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.28 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.28 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     10
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.28 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.29 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     11
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.29 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.60 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.60 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.60 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.60 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.61 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.61 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (0, 2, 0, 0, 0) with expected average impact 0.431356344515
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.69 sec) AdaptiveSparseGrid       : Message         ->   Next: (0, 2, 0, 0, 0) | error: 9.1904e-01 | runs: 13
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.69 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': 0.8124355652982146, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.7320508075688781, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.69 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.69 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -1.6124355652982145, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.7320508075688781, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.69 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.69 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     12
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.70 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.71 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     13
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.71 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.81 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.81 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.81 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.81 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.82 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.82 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (1, 1, 0, 0, 0) with expected average impact 0.197191471778
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.94 sec) AdaptiveSparseGrid       : Message         ->   Next: (1, 1, 0, 0, 0) | error: 9.2593e-01 | runs: 17
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.94 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': 0.29999999999999993, u'y1': 1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.94 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.94 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -1.1, u'y1': 1.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.94 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.94 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': 0.29999999999999993, u'y1': -1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.94 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.94 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -1.1, u'y1': -1.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.95 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.95 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     14
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.95 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.96 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     15
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.96 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.97 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     16
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    0.97 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.01 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     17
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.01 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.13 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.13 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.13 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.13 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.14 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.14 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (0, 1, 0, 1, 0) with expected average impact 0.164663322928
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.26 sec) AdaptiveSparseGrid       : Message         ->   Next: (0, 1, 0, 1, 0) | error: 8.0118e-01 | runs: 21
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.26 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': 0.29999999999999993, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.26 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.26 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': 0.29999999999999993, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.26 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.26 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -1.1, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.26 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.26 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -1.1, u'y1': 0.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.26 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.27 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     18
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.27 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.27 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     19
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.27 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.28 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     20
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.28 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.29 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     21
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.29 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.40 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.40 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.40 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.40 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.42 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.42 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (0, 1, 1, 0, 0) with expected average impact 0.136575372998
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.55 sec) AdaptiveSparseGrid       : Message         ->   Next: (0, 1, 1, 0, 0) | error: 6.1045e-01 | runs: 25
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.55 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': 0.29999999999999993, u'y1': 0.0, u'x3': 0.3, u'y3': 1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.55 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.55 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': 0.29999999999999993, u'y1': 0.0, u'x3': 0.3, u'y3': -1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.55 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.55 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -1.1, u'y1': 0.0, u'x3': 0.3, u'y3': 1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.55 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.55 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -1.1, u'y1': 0.0, u'x3': 0.3, u'y3': -1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.56 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.57 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     22
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.57 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.57 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     23
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.57 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.58 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     24
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.58 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.59 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     25
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.59 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.72 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.72 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.72 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.72 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.73 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.73 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (2, 0, 0, 0, 0) with expected average impact 0.0683090542509
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.88 sec) AdaptiveSparseGrid       : Message         ->   Next: (2, 0, 0, 0, 0) | error: 4.5466e-01 | runs: 27
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.88 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.8856406460551025, u'x2': -0.4, u'y1': 1.7320508075688781, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.88 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.88 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.8856406460551025, u'x2': -0.4, u'y1': -1.7320508075688781, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.88 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.89 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     26
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.89 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.90 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     27
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    1.90 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.04 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.04 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.04 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.04 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.05 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.05 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (0, 1, 0, 0, 1) with expected average impact 0.0646555050752
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.19 sec) AdaptiveSparseGrid       : Message         ->   Next: (0, 1, 0, 0, 1) | error: 3.8636e-01 | runs: 31
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': 0.29999999999999993, u'y1': 0.0, u'x3': 0.6, u'y3': 0.0, u'y2': 1.0, u'y5': 1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': 0.29999999999999993, u'y1': 0.0, u'x3': 0.0, u'y3': 0.0, u'y2': 1.0, u'y5': -1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -1.1, u'y1': 0.0, u'x3': 0.6, u'y3': 0.0, u'y2': -1.0, u'y5': 1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -1.1, u'y1': 0.0, u'x3': 0.0, u'y3': 0.0, u'y2': -1.0, u'y5': -1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.20 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     28
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.20 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.20 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     29
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.20 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.21 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     30
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.21 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.21 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     31
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.21 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.36 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.36 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.36 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.36 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.38 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.38 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (1, 0, 0, 1, 0) with expected average impact 0.0629440553664
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.55 sec) AdaptiveSparseGrid       : Message         ->   Next: (1, 0, 0, 1, 0) | error: 3.1620e-01 | runs: 35
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.55 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.55 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.55 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.55 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.55 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.55 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.55 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 0.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.55 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.57 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     32
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.57 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.58 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     33
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.58 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.59 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     34
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.59 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.60 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     35
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.60 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.76 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.76 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.77 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.77 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.80 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.80 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (1, 0, 1, 0, 0) with expected average impact 0.0562772502861
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.98 sec) AdaptiveSparseGrid       : Message         ->   Next: (1, 0, 1, 0, 0) | error: 2.9801e-01 | runs: 39
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.99 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.99 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.99 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     36
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    2.99 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.00 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     37
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.00 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.01 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     38
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.01 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.02 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     39
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.02 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.21 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.21 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.22 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.22 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.24 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.24 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (0, 0, 1, 1, 0) with expected average impact 0.0520498081839
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.46 sec) AdaptiveSparseGrid       : Message         ->   Next: (0, 0, 1, 1, 0) | error: 2.8100e-01 | runs: 43
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.46 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': 1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.46 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.46 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': 1.0, u'y2': 0.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.46 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.47 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': -1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.47 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.47 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': -1.0, u'y2': 0.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.47 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.52 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     40
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.52 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.53 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     41
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.53 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.53 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     42
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.53 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.54 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     43
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.54 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.73 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.73 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.74 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.75 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.78 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.78 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (1, 1, 0, 1, 0) with expected average impact 0.0477146600999
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) AdaptiveSparseGrid       : Message         ->   Next: (1, 1, 0, 1, 0) | error: 2.7840e-01 | runs: 51
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': 0.29999999999999993, u'y1': 1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': 0.29999999999999993, u'y1': 1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -1.1, u'y1': 1.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -1.1, u'y1': 1.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': 0.29999999999999993, u'y1': -1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': 0.29999999999999993, u'y1': -1.0, u'x3': 0.3, u'y3': 0.0, u'y2': 1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -1.1, u'y1': -1.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -1.1, u'y1': -1.0, u'x3': 0.3, u'y3': 0.0, u'y2': -1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.99 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     44
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    3.99 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.00 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     45
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.00 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.01 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     46
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.01 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.02 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     47
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.02 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.03 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     48
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.03 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.03 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     49
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.03 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.04 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     50
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.04 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.05 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     51
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.05 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.23 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.23 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.24 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.24 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.27 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.27 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (0, 0, 2, 0, 0) with expected average impact 0.0457622601776
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.49 sec) AdaptiveSparseGrid       : Message         ->   Next: (0, 0, 2, 0, 0) | error: 2.2574e-01 | runs: 53
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.49 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': 1.7320508075688781, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.966025403784439}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.50 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.50 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.3, u'y3': -1.7320508075688781, u'y2': 0.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.7660254037844391}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.50 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.51 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     52
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.51 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.52 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     53
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.52 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.71 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.71 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.73 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.73 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.76 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.77 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (1, 1, 1, 0, 0) with expected average impact 0.0411197005439
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) AdaptiveSparseGrid       : Message         ->   Next: (1, 1, 1, 0, 0) | error: 1.7998e-01 | runs: 61
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': 0.29999999999999993, u'y1': 1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': 0.29999999999999993, u'y1': 1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -1.1, u'y1': 1.0, u'x3': 0.3, u'y3': 1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -1.1, u'y1': 1.0, u'x3': 0.3, u'y3': -1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': 0.29999999999999993, u'y1': -1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.98 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.99 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': 0.29999999999999993, u'y1': -1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.99 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.99 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -1.1, u'y1': -1.0, u'x3': 0.3, u'y3': 1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.99 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.99 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -1.1, u'y1': -1.0, u'x3': 0.3, u'y3': -1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    4.99 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    5.00 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     54
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    5.00 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    5.01 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     55
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    5.01 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    5.02 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input     56
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (    5.02 s
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: ################################################################################
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Output trimmed
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: 
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: ################################################################################
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: nput     99
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.49 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.50 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    100
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.50 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.51 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    101
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.51 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.52 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    102
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.52 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.53 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    103
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.53 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.54 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    104
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.54 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.55 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    105
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.55 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.84 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.84 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.87 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   10.87 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.00 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.00 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (1, 0, 1, 1, 0) with expected average impact 0.0126067587581
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.37 sec) AdaptiveSparseGrid       : Message         ->   Next: (1, 0, 1, 1, 0) | error: 3.7527e-02 | runs: 113
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.37 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.37 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.37 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 0.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.37 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.37 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.37 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 0.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 0.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 0.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 0.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    106
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.38 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.39 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    107
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.39 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.40 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    108
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.40 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.40 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    109
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.40 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.41 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    110
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.41 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.41 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    111
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.41 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.42 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    112
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.43 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.44 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    113
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.44 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.74 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.74 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.78 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.78 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.92 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   11.92 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (0, 0, 0, 0, 2) with expected average impact 0.0111572956945
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.32 sec) AdaptiveSparseGrid       : Message         ->   Next: (0, 0, 0, 0, 2) | error: 3.5985e-02 | runs: 115
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.32 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.8196152422706633, u'y3': 0.0, u'y2': 0.0, u'y5': 1.7320508075688781, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.32 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.32 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': -0.21961524227066337, u'y3': 0.0, u'y2': 0.0, u'y5': -1.7320508075688781, u'y4': 0.0, u'x4': -0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.32 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.33 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    114
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.33 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.34 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    115
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.34 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.67 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.67 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.70 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.70 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.84 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   12.84 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (1, 1, 1, 1, 0) with expected average impact 0.0111414675535
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) AdaptiveSparseGrid       : Message         ->   Next: (1, 1, 1, 1, 0) | error: 2.4827e-02 | runs: 131
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': 0.29999999999999993, u'y1': 1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': 0.29999999999999993, u'y1': 1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': 0.29999999999999993, u'y1': 1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': 0.29999999999999993, u'y1': 1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -1.1, u'y1': 1.0, u'x3': 0.3, u'y3': 1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.18 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -1.1, u'y1': 1.0, u'x3': 0.3, u'y3': 1.0, u'y2': -1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -1.1, u'y1': 1.0, u'x3': 0.3, u'y3': -1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -1.1, u'y1': 1.0, u'x3': 0.3, u'y3': -1.0, u'y2': -1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': 0.29999999999999993, u'y1': -1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': 0.29999999999999993, u'y1': -1.0, u'x3': 0.3, u'y3': 1.0, u'y2': 1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': 0.29999999999999993, u'y1': -1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': 0.29999999999999993, u'y1': -1.0, u'x3': 0.3, u'y3': -1.0, u'y2': 1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -1.1, u'y1': -1.0, u'x3': 0.3, u'y3': 1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.19 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.20 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -1.1, u'y1': -1.0, u'x3': 0.3, u'y3': 1.0, u'y2': -1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.20 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.20 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -1.1, u'y1': -1.0, u'x3': 0.3, u'y3': -1.0, u'y2': -1.0, u'y5': 0.0, u'y4': 1.0, u'x4': 0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.20 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.20 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -1.1, u'y1': -1.0, u'x3': 0.3, u'y3': -1.0, u'y2': -1.0, u'y5': 0.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.20 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.25 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    116
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.25 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.26 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    117
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.26 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.27 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    118
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.27 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.27 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    119
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.27 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.28 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    120
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.28 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.29 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    121
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.29 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.30 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    122
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.30 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.31 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    123
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.31 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.32 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    124
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.32 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.33 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    125
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.33 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.34 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    126
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.34 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.35 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    127
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.35 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.36 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    128
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.36 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.37 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    129
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.37 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.41 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    130
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.41 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.42 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    131
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.42 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.76 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.76 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.79 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.79 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.91 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   13.91 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (1, 0, 0, 1, 1) with expected average impact 0.00506892887453
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) AdaptiveSparseGrid       : Message         ->   Next: (1, 0, 0, 1, 1) | error: 1.3629e-02 | runs: 139
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.6, u'y3': 0.0, u'y2': 0.0, u'y5': 1.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.0, u'y3': 0.0, u'y2': 0.0, u'y5': -1.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.6, u'y3': 0.0, u'y2': 0.0, u'y5': 1.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.0, u'y3': 0.0, u'y2': 0.0, u'y5': -1.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.6, u'y3': 0.0, u'y2': 0.0, u'y5': 1.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.0, u'y3': 0.0, u'y2': 0.0, u'y5': -1.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.6, u'y3': 0.0, u'y2': 0.0, u'y5': 1.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.30 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.0, u'y3': 0.0, u'y2': 0.0, u'y5': -1.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.1}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.31 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.31 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    132
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.31 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.32 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    133
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.32 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.33 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    134
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.33 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.34 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    135
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.34 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.35 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    136
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.35 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.36 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    137
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.36 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.37 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    138
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.37 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.38 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    139
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.38 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.72 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.72 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.76 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.76 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.92 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   14.93 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (1, 0, 1, 0, 1) with expected average impact 0.00446049391323
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.42 sec) AdaptiveSparseGrid       : Message         ->   Next: (1, 0, 1, 0, 1) | error: 1.2564e-02 | runs: 147
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.42 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.6, u'y3': 1.0, u'y2': 0.0, u'y5': 1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.0, u'y3': 1.0, u'y2': 0.0, u'y5': -1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.6, u'y3': -1.0, u'y2': 0.0, u'y5': 1.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 1.3, u'x2': -0.4, u'y1': 1.0, u'x3': 0.0, u'y3': -1.0, u'y2': 0.0, u'y5': -1.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.6, u'y3': 1.0, u'y2': 0.0, u'y5': 1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.0, u'y3': 1.0, u'y2': 0.0, u'y5': -1.0, u'y4': 0.0, u'x4': -0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.43 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.6, u'y3': -1.0, u'y2': 0.0, u'y5': 1.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.44 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.44 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': -0.30000000000000004, u'x2': -0.4, u'y1': -1.0, u'x3': 0.0, u'y3': -1.0, u'y2': 0.0, u'y5': -1.0, u'y4': 0.0, u'x4': -0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.44 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.45 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    140
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.45 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.46 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    141
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.46 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.47 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    142
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.48 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.49 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    143
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.49 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.50 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    144
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.51 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.51 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    145
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.52 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.52 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    146
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.53 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.60 sec) STEP MULTIRUN            : DEBUG           -> Just collected output  1 of the input    147
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   15.60 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   16.10 sec) GAUSSgpcROM(ans)         : DEBUG           -> training [u'y1', u'y2', u'y3', u'y4', u'y5'] -> [u'ans']
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   16.10 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...checking required points are available...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   16.18 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing translation matrices...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   16.19 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...constructing polynomials...
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   16.52 sec) GAUSSgpcROM(ans)         : DEBUG           -> ...training complete!
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   16.53 sec) AdaptiveSparseGrid       : DEBUG           -> Highest impact point is (0, 0, 1, 1, 1) with expected average impact 0.00409004468934
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) AdaptiveSparseGrid       : Message         ->   Next: (0, 0, 1, 1, 1) | error: 1.1572e-02 | runs: 155
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.6, u'y3': 1.0, u'y2': 0.0, u'y5': 1.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.0, u'y3': 1.0, u'y2': 0.0, u'y5': -1.0, u'y4': 1.0, u'x4': 0.2, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.6, u'y3': 1.0, u'y2': 0.0, u'y5': 1.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.0, u'y3': 1.0, u'y2': 0.0, u'y5': -1.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': 0.6}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.6, u'y3': -1.0, u'y2': 0.0, u'y5': 1.0, u'y4': 1.0, u'x4': 0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.15 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.16 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.0, u'y3': -1.0, u'y2': 0.0, u'y5': -1.0, u'y4': 1.0, u'x4': 0.2, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.16 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.16 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.6, u'y3': -1.0, u'y2': 0.0, u'y5': 1.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.16 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.16 sec) AdaptiveSparseGrid       : DEBUG           -> Found new point to sample: {u'x1': 0.5, u'x2': -0.4, u'y1': 0.0, u'x3': 0.0, u'y3': -1.0, u'y2': 0.0, u'y5': -1.0, u'y4': -1.0, u'x4': -0.6000000000000001, u'x5': -0.4}
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: (   17.16 sec) STEP MULTIRUN            : DEBUG           -> Testing the sampler if it is ready to generate a new input
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Exception RuntimeError: 'maximum recursion depth exceeded while calling a Python object' in <object repr() failed> ignored
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Exception RuntimeError: 'maximum recursion depth exceeded while calling a Python object' in 'garbage collection' ignored
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Fatal Python error: unexpected exception during garbage collection
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic: Aborted
framework/pca_adaptive_sgc.test_adaptive_sgc_poly_pca_analytic:

Consistent Module Imports

Issue Description

What did you expect to see happen?

Consistent, modular imports throughout RAVEN

What did you see instead?

Fiddling with PYTHONPATH and some inconsistency in when some modules can import others safely, as well as occasional imports in the body of python modules

Do you have a suggested fix for the development team?

We should probably continue towards making RAVEN more library-like, so that our imports all happen in a consistent way.

For Devs: Issue Review

1. Is it tagged with a type: defect or improvement? tagged
2. Is it tagged with a priority: critical, normal or minor? tagged
3. If it will impact requirements or requirements tests, is it tagged with requirements? n/a
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users. n/a
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.) provided

For Devs: Issue Closure

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Perturb specified word number in variable potentially broken

This was: https://hpcgitlab.inl.gov/idaholab/raven/issues/635

To perturb a specific entry in a moose based app variable that is a list, the syntax in RAVEN is supposed to be yaml_var_path:word_number. As an example, to perturb the entry that contains 0.4 in the input containing:

[Materials]
  [./a]
    b = 0.1 0.2 0.4 0.5
  [../]
[]

you could specify the variable directly with Materials|a|b:3. Further, the current way to specify which application a variable goes to in the MAMMOTH interface (yaml_var_path:app) conflicts with this syntax, yet there do not appear to be any tests that fail due to this conflict allowing it to be merged without incident. I believe that the culprit is the expandVarNames function in CodeInterfaceBaseClass as this appears to split the provided variable name using the colon as splitting character, but only then appears to use the first part of the key.

def expandVarNames(self,**Kwargs):
    """
      This method will assure the full proper variable names are returned in a dictionary.
      It primarily expands aliases. I will admit I don't know what colons do.
      @ In, Kwargs, dict, keyworded dictionary. Arguments include:
          - alias, the alias -> TrueName dictionary
          - SampleVars, short name -> sampled value dictionary
      @ Out, listDict, list, list of dictionaries. The dictionaries contain:
               ['name'][path,to,name]
               [short varname][var value]
    """
    listDict=[]
    modifDict={}
    for var in Kwargs['SampledVars']:
      if 'alias' in Kwargs.keys() and var in Kwargs['alias'].keys():
        # for understending the alias system, plase check module Models.py (class Code)
        #if var in Kwargs['alias'].keys():
        key = Kwargs['alias'][var].split(':')
      else:
        key = var.split(':')
      modifDict = {}
      if '|' not in key[0]: continue
      modifDict['name'] = key[0].split('|')[:-1]
      modifDict[key[0].split('|')[-1]] = Kwargs['SampledVars'][var]
      listDict.append(modifDict)
      del modifDict
    return listDict

Seeing as the Mammoth interface syntax works, this would suggest that the word number functionality is broken.

file used instead of open

open should be used because that works in Python3.

Spearman rank correlation coefficients

While we offer a plethora of very useful statistical information in the BasicStatistics postprocessor, a commonly-requested matrix is the Spearman rank correlation coefficients.

In order to remain competitive and extraordinarily useful to the statistical community, these Spearman coefficient would be helpful.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

CodeInterface samplers dictionary needs to be updated.

This was https://hpcgitlab.inl.gov/idaholab/raven/issues/648

Inside MooseBasedAppInterface.py, we are using the following to point to the sampler:

    self._samplersDictionary                          = {}
    self._samplersDictionary['MonteCarlo'           ] = self.pointSamplerForMooseBasedApp
    self._samplersDictionary['Grid'                 ] = self.pointSamplerForMooseBasedApp
    self._samplersDictionary['Stratified'           ] = self.pointSamplerForMooseBasedApp
    self._samplersDictionary['DynamicEventTree'     ] = self.dynamicEventTreeForMooseBasedApp
    self._samplersDictionary['StochasticCollocation'] = self.pointSamplerForMooseBasedApp
    self._samplersDictionary['FactorialDesign'      ] = self.pointSamplerForMooseBasedApp
    self._samplersDictionary['ResponseSurfaceDesign'] = self.pointSamplerForMooseBasedApp
    self._samplersDictionary['Adaptive']              = self.pointSamplerForMooseBasedApp
    self._samplersDictionary['SparseGridCollocation'] = self.pointSamplerForMooseBasedApp
    self._samplersDictionary['EnsembleForward'      ] = self.pointSamplerForMooseBasedApp
    self._samplersDictionary['CustomSampler'        ] = self.pointSamplerForMooseBasedApp

Since we do have new Samplers, such as Sobol, AdaptiveSparseGrid, ..., we need to add these new Samplers in the ```self._samplersDictioinary''' so that the user can use it.

The following interfaces will also have the same problem: RELAP5, RELAP7, Rattlesnake, Bison, Mammoth

A suggested fix was:

diff --git a/framework/CodeInterfaces/MooseBasedApp/MooseBasedAppInterface.py b/framework/CodeInterfaces/MooseBasedApp/MooseBasedAppInterface.py
index ae298b2..eae50a8 100644
--- a/framework/CodeInterfaces/MooseBasedApp/MooseBasedAppInterface.py
+++ b/framework/CodeInterfaces/MooseBasedApp/MooseBasedAppInterface.py
@@ -57,18 +57,12 @@ class MooseBasedApp(CodeInterfaceBase):
       @ Out, newInputFiles, list, list of newer input files, list of the new input files (modified and not)
     """
     import MOOSEparser
-    self._samplersDictionary                          = {}
-    self._samplersDictionary['MonteCarlo'           ] = self.pointSamplerForMooseBasedApp
-    self._samplersDictionary['Grid'                 ] = self.pointSamplerForMooseBasedApp
-    self._samplersDictionary['Stratified'           ] = self.pointSamplerForMooseBasedApp
-    self._samplersDictionary['DynamicEventTree'     ] = self.dynamicEventTreeForMooseBasedApp
-    self._samplersDictionary['StochasticCollocation'] = self.pointSamplerForMooseBasedApp
-    self._samplersDictionary['FactorialDesign'      ] = self.pointSamplerForMooseBasedApp
-    self._samplersDictionary['ResponseSurfaceDesign'] = self.pointSamplerForMooseBasedApp
-    self._samplersDictionary['Adaptive']              = self.pointSamplerForMooseBasedApp
-    self._samplersDictionary['SparseGridCollocation'] = self.pointSamplerForMooseBasedApp
-    self._samplersDictionary['EnsembleForward'      ] = self.pointSamplerForMooseBasedApp
-    self._samplersDictionary['CustomSampler'        ] = self.pointSamplerForMooseBasedApp
+    self._samplersDictionary = {}
+    unImplementedSamplers = ['DynamicEventTree', 'LimitSurfaceSearch','AdaptiveDynamicEventTree']
+    if samplerType in unImplementedSamplers:
+      self._samplersDictionary[samplerType] = self.dynamicEventTreeForMooseBasedApp
+    else:
+      self._samplersDictionary[samplerType] = self.pointSamplerForMooseBasedApp
     found = False
     for index, inputFile in enumerate(currentInputFiles):
       inputFile = inputFile.getAbsFile()

Bad message in ExternalXML parsing message

When reading an input XML with ExternalXML nodes, if there is a fundamental XML error (such as mismatched tags), the reported line number for the problem is with respect to the reconstructed XML, not the original, so it's quite difficult to locate what file the error is in.

This could be cleaned up by catching the error and raising it with more useful information when we attempt to read the external XML files.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Cleaning up the Typical History postprocessor

Originally it was believed there was a bug in the TypicalHistory postprocessor; however, it was discovered that its operation is merely obfuscated by some coding choices.

For example, there are literally 0 comments in the postprocessor (aside from function definitions), and variable names such as "tempData" and "tempInp" don't give any clarity to what actions are being performed.

It would be immeasurably helpful in the future to add comments and rename variables so that we can debug/make use of this postprocessor more in the future.

Similarly, the documentation for this postprocessor could benefit from some explanatory examples.

DataObject.getMatchingRealization and PCA transformation

Currently the PCA transformation places the latent/transformed variables directly into the input space of a DataObject storing realizations from a transformed space.

While this is generally desirable, this creates problems with DataObjects.Data.getMatchingRealization(), since the input space of the requested realization is only the manifest variables, while the DataObject internally has the manifest AND latent in the input space.

Currently a workaround bypasses this by checking the requested is a subset of the data set input space, but this is dangerous, as requesting a sample from a higher-dimension data object is not guaranteed to get a desirable point (such as a nominal or reference point in the un-requested dimensions).

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Clean Build issue

Issue Description

What did you expect to see happen?

I expected the tests to be executed. This was a first attempt build on a clean Ubuntu 16.04 Server distro. The build appeared to work.

What did you see instead?

Following the install instructions on the wiki page I got to the point where I ran the following:
./run_test -j2

I got the following errors:
Traceback (most recent call last):
File "./backend_run_test", line 20, in
import path_tool
importError: No module named path_tool

Do you have a suggested fix for the development team?

This might be a missing dependency in your suggested setup for Ubuntu 16.04.

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Adaptive and default parameters in Optimizer

Issue Description

What did you expect to see happen?

Many parameters should self-adjust and have good defaults in the SPSA optimizer sampling.

What did you see instead?

The user currently provides static values or accepts defaults that may correspond poorly to the problem's needs.

Do you have a suggested fix for the development team?

Consider methods for calculating good defaults and adapting on-the-fly based on the optimization development.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

Clean Build Issue Doc user manual

Issue Description

What did you expect to see happen?

I expected to see a user manual of some sorts

What did you see instead?

When attempting to build the user manual by executing 'make' in the /doc/user_manual directory I get an error. The command line tool pdflatex is missing. Another item to add to the dependency list.

Do you have a suggested fix for the development team?

Perhaps you should actually build this project in a clean environment before giving it out to the world. This way you can identify all the dependancies and layout a working build environment for others.

Please attach the input file(s) that generate this error. The simpler the input, the faster we can find the issue.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

HDF5 consistency

Currently we do not prevent the user from doing incompatible things with an HDF5 database. For example, a hierarchical sampling can be sorted into a database initially, then later simple Monte Carlo samples can be added, making an inconsistent and probably unreadable database.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

New issue and merge request templates

Our old gitlab merge request and issue request templates need to be revisited now that the repository is hosted in github.

Our labels aren't set up yet and I can't see where to add them, but this is an Improvement with Normal priority.

Python standards in testing system

While we have an established set of standards for Python when writing Raven framework modules, these standards conflict with the Python-based Moose testing system, since we largely inherit from it.

We should decide what to do about this conflict, and whether our standards apply without exception to the testing system.

For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

1. Is it tagged with a type: defect or improvement?
2. Is it tagged with a priority: critical, normal or minor?
3. If it will impact requirements or requirements tests, is it tagged with requirements?
4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

1. If the issue is a defect, is the defect fixed?
2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
4. If the issue is a defect, does it impact the latest stable branch? If yes, is there any issue tagged with stable (create if needed)?
5. If the issue is being closed without a merge request, has an explanation of why it is being closed been provided?

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