Key | Value |
---|---|
FileSize | 294028 |
MD5 | A8123E3EC44C988630A23120A2114939 |
PackageDescription | examples of OpenTURNS functionalities OpenTURNS is a powerful and generic tool to treat and quantify uncertainties in numerical simulations in design, optimization and control. It allows both sensitivity and reliability analysis studies: * defining the outputs of interest and decision criterion; * quantify and model the source of uncertainties; * propagate uncertainties and/or analyse sensitivity and * rank the sources of uncertainty . OpenTURNS is a large project with more than 300 C++ classes which uses well known and supported software such as R for the statistical methods and BLAS/LAPACK for the linear algebra. . This package provides examples which are written either in C++ or in Python. . They are primarly used as validation tests for the whole platform but they can also be seen as tutorials for beginners. |
PackageMaintainer | Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org> |
PackageName | openturns-examples |
PackageSection | science |
PackageVersion | 1.11-2+b1 |
SHA-1 | 88D494F62AADC4390DF75FC89C3A3AE2154CC54B |
SHA-256 | 35EB460B228E1FDD0462398097EF6EC192A0719745CCBC314C6D568C51B96812 |
hashlookup:children-total | 955 |
hashlookup:trust | 50 |
The searched file hash includes 955 children files known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_RandomMixture_simplification.py |
FileSize | 4275 |
MD5 | 2C5CFB0A641C05FD7205CE5E060DA724 |
SHA-1 | 014F85E2F6254306EF4EFC3081E32E9912EF9CAB |
SHA-256 | B4015A5D15F982B8F357506315854EBE355064D6DA9BDE2555B3AF85B8D3FB33 |
SSDEEP | 96:0EHeWM27y/mO6ZXrBO+hBqhBdId3LbOG3re73LK5iCma91aaCYXgY4w/YXH4w/2K:0SeWQ/C++MzybbOGS7b4ma91anYXgYjk |
TLSH | T11D917CA328C2DC2852CF5628D8666505EF5268E32CC63448B10F8DB21FA7D75DEB5E73 |
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_RegularGrid_std.py |
FileSize | 609 |
MD5 | C809CC60E323BEC2604AE262ADCA2397 |
SHA-1 | 023FF796A17AB5E25745AF021B7B6F11384075C0 |
SHA-256 | C0069592810FCD0D4746F48A34EDBBCB9E9C236FB138CC84CD530D7DE4966BBE |
SSDEEP | 12:9KjPiWbKBVU9mzpp5QVv37nbGxBDex9YjcdcEvZkon:AbuQQ9p5QVv37nqx0YjcdB7 |
TLSH | T1BBF0469AC5FF3E8B460654B9EC469710161B1B3B5D69F81DFE9C07804FA802B600CB3A |
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_Mixture_std.cxx |
FileSize | 9420 |
MD5 | E7850BC1175897C8F9D9309E627B4A9F |
SHA-1 | 027D2B2D19F5AAC120A7066509E84D6C07408F64 |
SHA-256 | DC34AF682B74E86173CEAF3BDF9B5DDE049F2CF94B7EB51D902222EEC9685C49 |
SSDEEP | 192:t0ngByTg1lmZI/iH7SUzb7yl0Bc6CNKV8ktYrGCKs:t0s2i+V8kmrG/s |
TLSH | T1BC12F221A8525A66AAE71E55EB4D01577423800B7FB4F668378F4B073F0F803E5B266B |
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_Normal_large.py |
FileSize | 3790 |
MD5 | E4A194287CF50657BFBAF6D9E44B8395 |
SHA-1 | 027D91A31CEAFC49242B1FAA0041D5E6CB7B4071 |
SHA-256 | 8D5974B7E18689BF0C930DA93E235BF2D20DA13D6F75F1A06537CD98B2D4B2D5 |
SSDEEP | 48:AbEGm0UqxWTMEWz8P/tc3O3O2cnl5FOXj7lURWTMEWrYSE:0ER5uivWzGc3OAFOSRivWrK |
TLSH | T1B87100329C501C458397405AE8E6A00A761BA65357EA7829FDCC82592F1F032EBB5BF7 |
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_GeneralLinearModelAlgorithm_std_hmat.py |
FileSize | 1835 |
MD5 | D7B4BF9886D89EB77464A7BD43B7023D |
SHA-1 | 0281E2546798AA47C0AA32699F544AC438A2FE33 |
SHA-256 | D0327D1D1F98FEF7031C48D68F50CDBF83F42776EE1F968B232BFC8880DEE04E |
SSDEEP | 48:AWy4H5bvE7oevdvzXplXHX4qtjEvUEw49aE45zYC:BlH5bQo8Bbp1xtovLX92ZV |
TLSH | T196310F1A98403CA1532782D5B8DE82114BBAF2A3BFAC2850B58C83501F59B267B13F2D |
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_OptimalLHSExperiment_std.py |
FileSize | 7457 |
MD5 | 7E38377ECFBD147D708AEE052C606470 |
SHA-1 | 02B1E425B880BACCF680B3787D3E2EC0C4C34895 |
SHA-256 | 912D15DEB87741941492401B7D432784BB8AE13C30B1191A48C1B1A7388EA135 |
SSDEEP | 96:BW5gYIchprJWgDRnxJDOLjxbtDORDtdBHD1RszBKONy0gGDpRszBKO16MtHnHmeR:Bx2VJBxMxbmzBj1RkpRCHjR6RPv6Ee |
TLSH | T1BFF11365ECE700FD1EC6F2F8DD598002F62504EACA792518ADDC849EE231056EF9E7B1 |
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_RiceFactory_std.py |
FileSize | 1101 |
MD5 | BE95E4E5CC180EEFFF363B66305B1387 |
SHA-1 | 02B519768B8829DCD000446543BB3242291A1EF3 |
SHA-256 | 22DD22DCA64C435932E12C0BD90D1153E171D4EF25F1AD35AE1BF375864C5893 |
SSDEEP | 24:AbuQkR2lzL7W9+j7WlmL27WgJy2SGgAFxvJBPYDRd7:AbCMFW9+nWOcWhVG7Yn7 |
TLSH | T1F111F63419881A408FC36AD5DD0FD110B72A102B30ADB138B8DEC5502F6F179D6BE6A2 |
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_LogNormal_std.py |
FileSize | 7054 |
MD5 | 6C32B89617990563679E1B4808A7A54E |
SHA-1 | 02D0AB6E984B676D4EDE02F7D962D694B07B43D7 |
SHA-256 | 53009FB555F8837DF399BF0F39BC8B6811A328439E0A9CA6528920FD4491E919 |
SSDEEP | 96:0k56vP//D00RdVgW0qcYMe0Zw7DVFZudlExA:0k5OYegW0q/piw7xrOiA |
TLSH | T12AE1B6706C801A965BD325C9DE655006A23B051FA0EE396CBDCC82642F1F877D633BB7 |
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_RandomVector_constant.py |
FileSize | 947 |
MD5 | 9B2EDF05F937AB671CAD8902511088C1 |
SHA-1 | 02E8AFC21CD28C2111C8BA8C53CA4626D0E221F5 |
SHA-256 | D49948D9CBFC5B70DA9184B7117B6C0265824B98518B194F7FF9C3DD7025FA58 |
SSDEEP | 12:9KjPiWbKBVEEkyoaF7WrHFGh2oCgcRoTFKRaO6Z+2SfFsKmtzwDex9YEnmZkon:Abu53oaF7WrHIhlnTF13zk6dxYEnG |
TLSH | T16C118010B4201DA50BDB589AEC52E80A622B64E360D935A4FEDCC304EF65152EF36F2F |
Key | Value |
---|---|
FileName | ./usr/share/openturns/examples/t_Normal_large.cxx |
FileSize | 5490 |
MD5 | 67FFF369A57F40E7F4838215B01AD77C |
SHA-1 | 0354ABA40A96009F65AC0F118F7B48D1B59B7498 |
SHA-256 | 956CD27B5F98012DEA70FE98CB97C69C2E1EB37660A3185C04B025D0EA6E9393 |
SSDEEP | 48:X0q0qHy3H1IuE5atXArFfo/g38zkiKBU3XMZObzP2+YQFn5D+cfcUIiKB2KHKC:D0nQrFsFkiKBuXiObTCQFnENiKBZKC |
TLSH | T199B14323A85109255AE70D65A7AC428B740381479FF0FA547B8F4B176F0F4529AF0AB3 |