| Key | Value |
|---|---|
| FileSize | 1707988 |
| MD5 | A9268ED5C23C9927A4581F5EE98E0F68 |
| PackageDescription | python package for convex optimization CVXOPT is a Python package for convex optimization. It includes * Python classes for storing and manipulating dense and sparse matrices * an interface to most of the double-precision real and complex BLAS * an interface to the dense linear equation solvers and eigenvalue routines from LAPACK * interfaces to the sparse LU and Cholesky solvers from UMFPACK and CHOLMOD. * routines for solving convex optimization problems, an interface to the linear programming solver in GLPK, and interfaces to the linear and quadratic programming solvers in MOSEK * a modeling tool for specifying convex piecewise-linear optimization problems. . |
| PackageMaintainer | Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com> |
| PackageName | python-cvxopt |
| PackageSection | python |
| PackageVersion | 0.9-0ubuntu1 |
| SHA-1 | 582AE777B6247361C26BA3975FCBAFE7A96F72B0 |
| SHA-256 | 9516A00BD0F84BA367819C53E2306DCDC6E203D54834CEAED55DDD2AF4B48B5F |
| hashlookup:children-total | 80 |
| hashlookup:trust | 50 |
The searched file hash includes 80 children files known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-cvxopt/examples/filterdemo/README |
| FileSize | 445 |
| MD5 | 1836C6FE26415939D5A6F32D3E1A1E34 |
| SHA-1 | 020D546E5EF64BE6333D2E45BE1B1DFC32F83C35 |
| SHA-256 | E0BD74AB3AB9E69F55A77A6DEDC7BDE44750C3D250DAFABB2FC61E121AF03095 |
| SSDEEP | 12:eZsDkMJ4/REY7AIKI08goCShQRv26NepL5XFHncqCcoCPPpG:oKkMJ/Y72I0KCQ0v26UpLZFHncjCZG |
| TLSH | T123F02300C40D7DF4E342201BFD321470D8B5C90C23EA30195CFC56E55943DB0D4D1A90 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-cvxopt/examples/book/chap6/old/tv.gz |
| FileSize | 2607 |
| MD5 | CD7ABDCBA3D755684426A86A878D7C34 |
| SHA-1 | 03EA92BE77916455FFEED0A6521BCDB6A917A7C9 |
| SHA-256 | 8FA68D2E7592A7D101A2AA9CDC809E9FB1BFF4A612A1BA7443290907542831D8 |
| SSDEEP | 48:XUm9jh/6z4R5ofpW4GWoloWW28r5em/Fv7ZYckh9cIDZnl9TocURME4:E6hSzUuW4Gz6M07FTZYcsD/9Tocul4 |
| TLSH | T148514D66B31810A74D2868F8A2354E3C69C350F656F9066C0345BDA25EF87D2420C19B |
| Key | Value |
|---|---|
| FileName | ./usr/lib/python2.4/site-packages/cvxopt/random.so |
| FileSize | 13164 |
| MD5 | 8DA659EDE38827BB501E78A866CC23E2 |
| SHA-1 | 04D9F4F6208E38967DF75EA20D9C24C85A5C56F7 |
| SHA-256 | E92173B80AB272CD176B62BDB12D5486774F9F4E5CE16E35DC10D5230BF6F3F7 |
| SSDEEP | 192:rxLAulj1bEPbwCXtkR6FQ1HxHTEEeqBIPAOl9jaBhVeeaRjAx4:rRpjOPbRkA+1RghqgT9Qly |
| TLSH | T1B442A3A3B7A76B77C8611D7800EB6323732D8F059DA4836FB16D44862F966406D3B7C1 |
| Key | Value |
|---|---|
| FileName | ./usr/lib/python2.5/site-packages/cvxopt/cholmod.so |
| FileSize | 292428 |
| MD5 | 4E438C50C045E6D7996EB3C553D158A7 |
| SHA-1 | 072D344A47834058D37C8810F264A71183EB9AB9 |
| SHA-256 | 731FD2C5F07B6AADC71CF89EB52264846764D323D3D7035865D54EFACFA4ED90 |
| SSDEEP | 6144:CEkTtvcdFKMVlhjzYupBrhjNth1SQBlEbTGoRN:XRVzdNtCbn |
| TLSH | T1E6543B237FE58627C2E075B5B2D34323B3BB4FC42464500BBA528C9D5EAE590266B3F5 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-cvxopt/examples/book/chap8/floorplan.gz |
| FileSize | 1634 |
| MD5 | 52241D5DECD88B959E20DC3835AA1E11 |
| SHA-1 | 074DA68E5032525316E2C31DEDE77DFF4EC5138E |
| SHA-256 | BDD2A20F6EC0F6FCE1A0E3D3174711DBAE268D27F91A4BA03052186EE1A5EEA3 |
| SSDEEP | 24:XS36SF/smAxCJldjT98Exdo/cr/4Vz5zk5xft5aJwM8+RGB/BqfDEptgX:XSKSFIE/9LpQYxCJp8sGC7Ep2 |
| TLSH | T123313A1DFAB4F714DCDD3929D25FC485652AC64CDF34782A0C7A118828817F108B900B |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-cvxopt/examples/book/chap4/portfolio |
| FileSize | 1675 |
| MD5 | E5660F0311FDE26B3F0ECEB30A4985B3 |
| SHA-1 | 0ECEAF8078915D415386CC1A8D50E75CCE36CC93 |
| SHA-256 | F8D2C99B58682A5A2B511139187DB9F2EACE2403A6AD0423EAB6E699C1AD46B2 |
| SSDEEP | 24:j3HIBd7kF7l77TknCW8ZmEVmQ9ag4A2FeLJXt1QcFXMUy/bv9x7/dN/kXygO6mvI:jXvrIuDcQJ4tgZt1Tx8vH7jEy3FER |
| TLSH | T19731BC0FA2C668540B6BD0C9CAD976407F7BF0261D2F604A76AF4F808F5B5D9C933A64 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-cvxopt/examples/book/chap6/basispursuit.gz |
| FileSize | 2546 |
| MD5 | B4EAEEF5AB4E38C9ACDBD779BC2B18DF |
| SHA-1 | 10F2EBCE23EEB95794717FB1B23FE201CC38CFA9 |
| SHA-256 | 3AA3A93362607A783A9F418D207E3460C7969282F4D4B762A0095B3EE32418CD |
| SSDEEP | 48:XGmOUIC///gjZT22EvMLw4b+e5KlhU9L5vR0SpiZdvVXbZnxXeo9LFHZDY:WmOAol04b+ek4L5a6mnxXeebY |
| TLSH | T1A4514CAABE0D81FD373204D452081289865BE7B78288623377742ADF4AF75775013F64 |
| Key | Value |
|---|---|
| FileName | ./usr/share/pycentral/python-cvxopt/site-packages/cvxopt/info.py |
| FileSize | 1854 |
| MD5 | 1051DFEF3EAB7EDE810F2C4EC5963BC1 |
| SHA-1 | 126A15EFF8BDB55D515DD7551E7901A59E969ED0 |
| SHA-256 | F12BCC81ECF79AE32C7FEF52F9BD5FA20B2D4797EBA0A2F8DA739C3729BD193E |
| SSDEEP | 24:nss6P+Xz7WtyPOkHMlCTbVOnZbnXa0osub0PrT5a0DGJ0c7XJyZFg75mO:J6P67iyZHcdnK0oz0340S0cbkUIO |
| TLSH | T17131421E2228C6364A8006D6664B49CEF7743793B2AA005E641CC25E1E24E3A1BF5594 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-cvxopt/cvxopt.pdf |
| FileSize | 621329 |
| MD5 | 9C90E06EF5F17D0D492BB1C25714C458 |
| SHA-1 | 15C32129A41B5C43F20EEDD0338C98170E9036B4 |
| SHA-256 | F3A65CDF9A63392EB402CE952EB86D4BEC5A078985912E2FC83844D58FF9166F |
| SSDEEP | 12288:TYscJLam1Aqb095soJWpeC353yKx8ck5RkSh6:Usg/2qI9jGeC353b25U |
| TLSH | T144D4CFE8E9A62C9CFC52CA0251BE343D4A7EB266B3C874C21D7C0F45A244D05DE57AE7 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc-base/cvxopt |
| FileSize | 903 |
| MD5 | 64324B3CA2DEAF59A011718AAEBF27D7 |
| SHA-1 | 1A1CFB1882540453377A77FC146C042B2BCA9E7C |
| SHA-256 | 19CD22B69E021EFFDE2EEECCAE950F6B0941ED3C44707AB2E3DE51C7F5BDA1CD |
| SSDEEP | 24:6tAyp0aJbWGfxyq8EiKKAuCYqZNpNqDEpb6oYqRzeMz38SsMdVlE:QKCbuq8EiK9Ykz9NxYi/zTxdVlE |
| TLSH | T12411564CD66675B8561275CD96421E208F3815B9720F63450CB841F223CBAE9937F3EB |