Result for 12642408EA5EF122787F42396EF48E4CED32189E

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Children (88)

Query result

Key Value
FileSize1404626
MD58F90BB9A9523560DC39BDB7E711C6452
PackageDescriptionPython 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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-cvxopt
PackageSectionpython
PackageVersion1.1.3-2fakesync1
SHA-112642408EA5EF122787F42396EF48E4CED32189E
SHA-256DF2B5F256CE41790008D9D181A027736BE0DE8AE10329F62BD943A60BCFD5326
hashlookup:children-total88
hashlookup:trust50

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Children (Total: 88)

The searched file hash includes 88 children files known and seen by metalookup. A sample is included below:

Key Value
FileName./usr/share/doc/python-cvxopt/examples/filterdemo/README
FileSize445
MD51836C6FE26415939D5A6F32D3E1A1E34
SHA-1020D546E5EF64BE6333D2E45BE1B1DFC32F83C35
SHA-256E0BD74AB3AB9E69F55A77A6DEDC7BDE44750C3D250DAFABB2FC61E121AF03095
SSDEEP12:eZsDkMJ4/REY7AIKI08goCShQRv26NepL5XFHncqCcoCPPpG:oKkMJ/Y72I0KCQ0v26UpLZFHncjCZG
TLSHT123F02300C40D7DF4E342201BFD321470D8B5C90C23EA30195CFC56E55943DB0D4D1A90
Key Value
FileName./usr/lib/python2.7/dist-packages/cvxopt/fftw.so
FileSize22372
MD5A7E8BD586718D8D308D5F91F7AEA8D71
SHA-1058AED8EB06A4E3F22A6D3427630AE97EB797C30
SHA-256C582EDF252337456F685D32BB5AE8BC4F70D22B2637A08BE9597E33166513E92
SSDEEP384:HLd6z+HtikultePnp8W0KzpCk+n3QX8NSmrTOTMvT7qT+dTiGTf:HJC+IVnevp8oJ+AX8B/MmUyff
TLSHT1C9A209A47956A373D95B40B8FA658F5B4B39C04D21A78AA235DCC0743BC35218633FAE
Key Value
FileName./usr/share/pyshared/cvxopt/msk.py
FileSize30303
MD5BE75B79CF584BCE72E192EBA9F18795C
SHA-10973A4BF52618DFC6A43690840B0A405B77DFE6A
SHA-256A79578F461864CEDF023EEB5E62E086A6FF384DBC9F33772396BEC757B9A5A95
SSDEEP384:K7R5stI/7kyl/sdF48C/eQsweUAq/MlXiI/l0kwCkHI/yr:Uvstkgyl/sdF48ODsweiaXik6kXkHkW
TLSHT11CD2830558400D3AA2A3817D8CD7CC097F6195633D8B2D7A386C91B86F1B737D7B87AA
Key Value
FileName./usr/share/doc/python-cvxopt/examples/book/chap6/regsel.py
FileSize3149
MD5437919296D51AC8F69D12500C0807F42
SHA-1097BB7690701B72F1ABB505DCC1016A792BE9EC9
SHA-25624429B539050989ACBB789680C3E5E10574C938435FDFAB373A23F7C0BA58B01
SSDEEP96:S3HRpoF7BL4lCI1wz9WAdB+73DXLv18byir:G7lCvRK3Db98bye
TLSHT142516544F4423C76865BD1A9E4D134204F2AD4272D1F289AFFAE3E888F478F54674389
Key Value
FileName./usr/share/doc/python-cvxopt/examples/book/chap6/consumerpref.py
FileSize3991
MD55CCD74DD7D1E5423D4C8C18F3FEFCC2F
SHA-10FB481D08091F23B0622C13CC9F8ABFB75FF9BC3
SHA-256806DD9B8F6944C06A04A87D8FB2F986747E900D0136FFCFB5F40CA007D98891B
SSDEEP96:AJOmZEEFIXIZJj0SRQwC5Aw212g0SRojzhze:AImWCIXIZJj0S+wCCXgg0SiVe
TLSHT15D81EC03127AE9344A07D7FEE5913310A92DD8EB6D1A3886306E0E875F175ED6232D5F
Key Value
FileName./usr/share/doc/python-cvxopt/examples/doc/chap9/floorplan.py.gz
FileSize1507
MD53D46A3E0091B6C5456B860784E4ED58B
SHA-110B5C849601281E41F0E47BEA7D21D09AAE4391A
SHA-256B3D430325563926C6520EFC4BB2EF20814B6811390A6A6D86832690D27874061
SSDEEP24:Xby2zMH0eOxdTGRnLyIkbUNICSbQ8bd9iwZgbd0a5YmStsd/8y7BPL7wvBT7:XbrwitG1vNuQ0iw0+a5HSQ/z7Za7
TLSHT1FC310A927C3839084128FE4A0E861EEF602EC01F68A120A1347E301B9F096C780E53E9
Key Value
FileName./usr/share/doc/python-cvxopt/examples/doc/chap8/conelp.py
FileSize815
MD5EA54E397E3093B100C5BBF14C3A4E06D
SHA-114BC88EA42FD67A8DCA767FADCAAC178D8332816
SHA-256949E33AE7959C59A90D10159DA32363FDD36BB226DE58E1F3A4569FB46433DA2
SSDEEP12:UIFEa7NQBQMLt1YcTYeul+RHbq4Gn+1G2rAoDo29gzKaneSnYtfszECro:UI57NEnZful+xua/A8mKank2vc
TLSHT1AC01D49F91873CF4432E8B74A0471D1467B6C83979D73188387E8E2DAB3DB8496ACE54
Key Value
FileName./usr/share/doc/python-cvxopt/examples/book/chap7/expdesign.py.gz
FileSize1632
MD5B92636BDEC1E72ED7947008F204DB178
SHA-1152161D93560EC30BFAFA8017701AB5241DBAAD3
SHA-256AE8841BD9EE34A4791315BAC1D324BE5002ED9465C3E62DA0E635996D5371B38
SSDEEP24:X0rQx03RUiO+idzDxx0/mkPjclwGWdxE/ABToGpwVxf/La9CYIs2P:XmQu3NidztSdbciGIxAWTPwVg5Q
TLSHT1CE310A0790A731969639DD3EE84A5619306734F79C268ABC65782439B15322A3159339
Key Value
FileName./usr/share/doc/python-cvxopt/examples/doc/chap8/coneqp.py
FileSize614
MD546E747A1F071EA1BD1DCEAA534FFB4BC
SHA-1154D12C7989123F054D2B63E021B3A17E17B3958
SHA-256FC8AE59A551F2C6568F26EC693C2DF1A26109650963664F48AA2CC1E858F1443
SSDEEP12:BMztjXK/sOf7NQULrVlBE9I81NaJnjkar4nkMIal3nV7:0tjnC7NfPB+I8ijkdkMlF7
TLSHT102F02D4BC407B85CE6B4E029981A1C950E79CD086D2EB0003D3E54A18FBA262CE35756
Key Value
FileName./usr/share/doc/python-cvxopt/examples/book/chap8/centers.py.gz
FileSize1933
MD5F7B5DEE8D9495C381E979D693BD993DC
SHA-1182FABA97575AFC16D5C1E2BBF6334767FB846BE
SHA-25629FF3FFA1481694FE4141CBA512C0F296DEE065245E67E95DDA23A8F514BB154
SSDEEP48:Xb8Y3PWGfvrF3Wu7HHa8JdfOGP7fYDiy7rB93ND0/wCeF:t3xr8u7nNd5PDOrBrJ
TLSHT13F413D7187C1A209D86F447C395B5410C693C93135EFF2E424626441EA7FB1852A3DFB





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