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ID | Project | Category | View Status | Date Submitted | Last Update | ||||
0015682 | ParaView | (No Category) | public | 2015-08-26 08:57 | 2016-08-12 09:59 | ||||
Reporter | Vadim SANDLER | ||||||||
Assigned To | Kitware Robot | ||||||||
Priority | normal | Severity | minor | Reproducibility | have not tried | ||||
Status | closed | Resolution | moved | ||||||
Platform | OS | OS Version | |||||||
Product Version | 4.3 | ||||||||
Target Version | Fixed in Version | ||||||||
Summary | 0015682: Extract Bag Plot filter does not have unitary tests | ||||||||
Description | According to the Kitware gitlab, Extract Bag Plot filter does not have unitary tests. The only existing test is an integration test described here: https://gitlab.kitware.com/paraview/paraview/blob/master/Applications/ParaView/Testing/XML/FunctionalBagPlots.xml. [^] According to the user, the data used in that test are not appropriate to test the actual algorithm (sinewaves.csv): the white noise, without temporal covariance, is not consistent to find outliers. Thus, it does not represent a practical case of physics simulation outcome (no regularity of the function). In addition, the paper used in the current test is using nuclear data which are confidental and cannot be integrated to Paraview code. In the attachment please find data (gaussiansine.csv produced with the Scilab script test.sce) and numerical calculation results produced with the statistics software R and a classical PCA (ACP_classique.R). These results can easily be used to build unitary tests comparing numerical values produced by Paravew with those produced by R. Please find a desciption hereafter of the tests which can be built: N is the number of curves and T is the number of points in each curve. We distinguish T>N cases and T<N cases because of calculation performance. The matrix X is sized of T*N. The covariance matrix Xt*X is sized of T*T. If T<N, it is consistent to evaluate the covariance matrix and to compute its T eigenvalues and eigenvectors. If T>N, it is not necessary to evaluate the covariance matrix. One can compute directly the SVD of matrix X which gives N singular non-zero values. T>N is the most classical case. Consequently, the minimal unitary tests list is: test 1 : classical PCA with T>N test 2 : robust PCA with T>N Complementary list is: test 3 : classical PCA with T<N test 4 : robust PCA with T<N | ||||||||
Tags | No tags attached. | ||||||||
Project | ParaViS | ||||||||
Topic Name | |||||||||
Type | usability | ||||||||
Attached Files | gaussiansine.csv [^] (226,137 bytes) 2015-08-26 08:58 test.sce [^] (821 bytes) 2015-08-26 08:58 ACP_classique.R [^] (3,005 bytes) 2015-08-26 08:58 | ||||||||
Relationships | |
Relationships |
Notes | |
(0035815) Joachim Pouderoux (developer) 2016-03-03 08:40 |
Fix in progress - Merge request: https://gitlab.kitware.com/paraview/paraview/merge_requests/580 [^] |
(0038875) Kitware Robot (administrator) 2016-08-12 09:59 |
Resolving issue as `moved`. This issue tracker is no longer used. Further discussion of this issue may take place in the current ParaView Issues page linked in the banner at the top of this page. |
Notes |
Issue History | |||
Date Modified | Username | Field | Change |
2015-08-26 08:57 | Vadim SANDLER | New Issue | |
2015-08-26 08:58 | Vadim SANDLER | File Added: gaussiansine.csv | |
2015-08-26 08:58 | Vadim SANDLER | File Added: test.sce | |
2015-08-26 08:58 | Vadim SANDLER | File Added: ACP_classique.R | |
2016-03-03 08:40 | Joachim Pouderoux | Note Added: 0035815 | |
2016-08-12 09:59 | Kitware Robot | Note Added: 0038875 | |
2016-08-12 09:59 | Kitware Robot | Status | backlog => closed |
2016-08-12 09:59 | Kitware Robot | Resolution | open => moved |
2016-08-12 09:59 | Kitware Robot | Assigned To | => Kitware Robot |
Issue History |
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