Key | Value |
---|---|
FileSize | 146952 |
MD5 | BE8DECB8C10024ADEAFBDE915E78B382 |
PackageDescription | Sparse linear algebra extension for Python: documentation This package provides documents and examples for python-sparse, a set of sparse matrix types for Python, with modules which implement: - Iterative methods for solving linear systems of equations - A set of standard preconditioners - An interface to a direct solver for sparse linear systems of equations - The JDSYM eigensolver . All of these modules are implemented as C extension modules based on standard sparse and dense matrix libraries (UMFPACK/AMD, SuperLU, BLAS/LAPACK) for maximum performance. |
PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
PackageName | python-sparse-examples |
PackageSection | python |
PackageVersion | 1.1-1.2build1 |
SHA-1 | 28424E83B1398FA3CB108EC82695366A2F2D8595 |
SHA-256 | 512DFA84CFE89B79D301347074C00E844FEF235537220672059F0E3DFBF10861 |
hashlookup:children-total | 16 |
hashlookup:trust | 50 |
The searched file hash includes 16 children files known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileName | ./usr/lib/python2.7/dist-packages/SparsExamples/pysparse_test.py |
FileSize | 8278 |
MD5 | 18797E10109A79FFA1944A5D0F82F621 |
SHA-1 | 0F44A242E83C7D845FA7BED69BA676359FE2CA58 |
SHA-256 | 4911B5AFB4DDC7686CBC2D756E10A35F506958B139B17630F7CF79204FCCBDB9 |
SSDEEP | 96:longW2foD4/epLe0sKXcnmpnA/oM/DJfDvDhDRDBlD3DbDLDa+DPDhD1DECDtDZQ:QamjsWEoM9JU3h/MlbZ4 |
TLSH | T123026B017D24290BDB4BC868F9F5AC85E90A9889DEEEB415FE8E1784FF03095976CE50 |
Key | Value |
---|---|
FileName | ./usr/lib/python2.7/dist-packages/SparsExamples/poisson_gmres.py |
FileSize | 4280 |
MD5 | 3A93E8EE5F2234646230774D3CC6A91C |
SHA-1 | 12F1EB8694298DF8A43BF898F6CC4B542B872015 |
SHA-256 | DC6FBD269003E90DE93B189431153FE9CE338BBC7E80A108C8176AD1FC5F7B97 |
SSDEEP | 96:W5YYyKonyoWyGF0RoIPOPFL0PXLTrXLoPQFLPQQFLX:FYyKonyoWyGFdIPEyjoP2PQ2X |
TLSH | T13491BD002C792217C6A7C478ADA5EC51FF15A4AEDF6F7010BE8E1A69BF46102473CF46 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sparse-examples/examples/Examples/matmul_perftest.py |
FileSize | 475 |
MD5 | D9C3869091C39B572F90A883E5564173 |
SHA-1 | 46EC387687DD00BD0E5173D27F6CC9BF12B0184F |
SHA-256 | 806E26D845D789F3E1743DA63AF1CB79E80807C74F6EE3675661881B1DC634F6 |
SSDEEP | 12:vTxNdYIOoWz9iKvFYiKvjJLBq9h5F292UvOrCIdgDOv0Wyyeav:vbnmvF6vC55EkCIdt0dOv |
TLSH | T113F0EC02FC641645C0374999DCA16CBA7F619077BF96AD01BD1D0C464F921474776747 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sparse/copyright |
FileSize | 7221 |
MD5 | 085B7563090928F54A9AA31E8D4DD7E1 |
SHA-1 | 4B8BFE8B80B92F35B8E85F109FD7E28813A972C1 |
SHA-256 | E9B386BFD19B28F28D8B4840511EB8E46911C94F7775290B018E59A8CCD37C46 |
SSDEEP | 192:9CYrsqrsAN3r3LaGev0pmvXH3ibadiKxxbxhlSOdjrpp0:97rsqrsA1DLPevmmvXH3vdHXhl10 |
TLSH | T110E1929E6F8857720193CA92379E9588F28D973F76232C053C4C835823A791C97FE1D9 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sparse-examples/examples/Examples/spmatrix_test.py |
FileSize | 3080 |
MD5 | 9C96B896A260FB450FACEF7E45E4593C |
SHA-1 | 4D8D7E0D3D9F296DDFC99158649B8B7F6FF0721A |
SHA-256 | 6770F2D4AF4205BFFEA09BFCBAA98842DB543DBD6DD3CBC48857A460FB03977E |
SSDEEP | 48:EYj7WdWcDXIfrK8zs8r8z7RPvQG9rlY4QRk8N4e1j0wZJHw:Eg7SIfrK8zs8r8z7RPvhc4 |
TLSH | T1EE51CF43E57D4D3CDA9A4864C9599C135F2FA86A1AF2781D7B3E46C88F030570F38B56 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sparse-examples/examples/Examples/ssor_test.py |
FileSize | 926 |
MD5 | 0B7BF41EFF1C3DCCCEECD567E38C3BB2 |
SHA-1 | 52FD5BEC181D0BB0E532AAE681B69B05C776FDEC |
SHA-256 | 5D94FDD5B119CE3BD3AFAA88C38A66486E3955946AD1121C52165B7E28D2D405 |
SSDEEP | 24:n9ey7vMQqEAhLpzaiYVdGOjBuxd3BXRKrjfiG2uCK7e:ZMbEILpOirOjBMhRKrj1Je |
TLSH | T13B11C0226C2132339757C81DACFA7950EF1818479F2EB161F90E8154BF021745B7DF64 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sparse-examples/spmatrix_manual.pdf |
FileSize | 153430 |
MD5 | 293D22DAC21899560EE87FECA4D6E3AD |
SHA-1 | 6BB42340FABA408516CB3DB3D2364C5FE397DD4B |
SHA-256 | 7616EBE4A5CF9FD9F0D1E7F347AE85982DB3AF18CE04A7758720EEA6E9E7F009 |
SSDEEP | 3072:q54a6X/zToy8HL7rjYh8iXIW/1vUo5Sx+bQiHtO:eyUE/XJdb5zbbtO |
TLSH | T169E3E125D79A6C9CE582CD064678313A977EB2377AC838912C7C0684D584E98FBF36C7 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sparse-examples/examples/Examples/poisson_test.py |
FileSize | 3911 |
MD5 | 2F648FD8B7EFCEA7CF3CACE18D334985 |
SHA-1 | 78EF4AFC049071EC5E371A1EA75873D29D4DDE17 |
SHA-256 | 704DEDDC6AD6C9E3D875E40757A1AE0BD3DA5CA56725B63D17AA5208D91373B2 |
SSDEEP | 96:O5YYyKonyoWyGF3llaG5aqL44aULluaULKEQaqL/:NYyKonyoWyGFOGs64jgl5gKEr6/ |
TLSH | T1B381EE002C792617C276C8699D86AD95EF21645EDF6FB8003D8D19ADBF4B153473CF42 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sparse-examples/examples/Examples/tendigit.py |
FileSize | 900 |
MD5 | 04AC2F48E0F9093CF4CDA4CAAC2FC6FD |
SHA-1 | 814ED30C1E6A927B76ACA08D7B20AC7A51FC3511 |
SHA-256 | CA05D94CA25518B7FBC434F90EE2B733FB718037D3A28BCA08F32C5156E21B18 |
SSDEEP | 12:mOZykZPUiTxqE8Kx1fl7e8u7qtpFiP9FDd6RXibFLHT0Ttat4Y7JSXc:mORdhjjfWq8R6RX0TT0ktx1Ss |
TLSH | T10311AB51A9002C09DA07447CDCB8A8241F5E2C4FBF6A751879AC5794BF4604F6B10FA5 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sparse-examples/examples/Examples/sortedLL_test.py |
FileSize | 340 |
MD5 | EB41A5007FAA114637EF3B5BA4FA45CC |
SHA-1 | A903BF87401D8AEE3F3CB08ACE738B6EEFDA21F5 |
SHA-256 | FB52923463EF9A3BA7F4E5635AFBC43A1D4D88FFEC7C2DBE235425C213CC876B |
SSDEEP | 6:1Viz8lMHkEgUxoBF9Ycmok6NGgR29JuvhJCMYeIxhsbCKRMLf92Z4aIsOFiPCVJ4:1ViwWPgUo9nXUgm2SSCKC92Z4aIsAM |
TLSH | T19BE0C00338A1002CD0BA8E13DEC578F81B21A025B6333080221104718F120830ABB948 |