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Add SHA512 digests for distfiles for math category Problems found locating distfiles: Package dfftpack: missing distfile dfftpack-20001209.tar.gz Package eispack: missing distfile eispack-20001130.tar.gz Package fftpack: missing distfile fftpack-20001130.tar.gz Package linpack: missing distfile linpack-20010510.tar.gz Package minpack: missing distfile minpack-20001130.tar.gz Package odepack: missing distfile odepack-20001130.tar.gz Package py-networkx: missing distfile networkx-1.10.tar.gz Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz Package quadpack: missing distfile quadpack-20001130.tar.gz Otherwise, existing SHA1 digests verified and found to be the same on the machine holding the existing distfiles (morden). All existing SHA1 digests retained for now as an audit trail.
2015-11-04 00:33:26 +01:00
$NetBSD: distinfo,v 1.4 2015/11/03 23:33:35 agc Exp $
Import IPOPT version 3.11.5 as math/ipopt Ipopt (Interior Point OPTimizer, pronounced eye-pea-Opt) is a software package for large-scale nonlinear optimization. It is designed to find (local) solutions of mathematical optimization problems of the form min_{x in R^n} f(x) s.t. g_L <= g(x) <= g_U x_L <= x <= x_U where f(x): R^n --> R is the objective function, and g(x): R^n --> R^m are the constraint functions. The vectors g_L and g_U denote the lower and upper bounds on the constraints, and the vectors x_L and x_U are the bounds on the variables x. The functions f(x) and g(x) can be nonlinear and nonconvex, but should be twice continuously differentiable. Note that equality constraints can be formulated in the above formulation by setting the corresponding components of g_L and g_U to the same value. Ipopt is part of the COIN-OR Initiative.
2013-11-14 16:04:12 +01:00
SHA1 (Ipopt-3.11.5.tgz) = 66e3ae03179ba7541a478d185b256f336159fc6d
RMD160 (Ipopt-3.11.5.tgz) = 9fc02e86f9d69a85e77c492ade30df23dba8afc7
Add SHA512 digests for distfiles for math category Problems found locating distfiles: Package dfftpack: missing distfile dfftpack-20001209.tar.gz Package eispack: missing distfile eispack-20001130.tar.gz Package fftpack: missing distfile fftpack-20001130.tar.gz Package linpack: missing distfile linpack-20010510.tar.gz Package minpack: missing distfile minpack-20001130.tar.gz Package odepack: missing distfile odepack-20001130.tar.gz Package py-networkx: missing distfile networkx-1.10.tar.gz Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz Package quadpack: missing distfile quadpack-20001130.tar.gz Otherwise, existing SHA1 digests verified and found to be the same on the machine holding the existing distfiles (morden). All existing SHA1 digests retained for now as an audit trail.
2015-11-04 00:33:26 +01:00
SHA512 (Ipopt-3.11.5.tgz) = c86b73672bc17a6e1d7d126c79e015519364c267a5930d492b7a6b4fcd63d5caed85766f250fd8bc7ebf87fc9da06419b058450750a03e8915e56b9bea07d345
Import IPOPT version 3.11.5 as math/ipopt Ipopt (Interior Point OPTimizer, pronounced eye-pea-Opt) is a software package for large-scale nonlinear optimization. It is designed to find (local) solutions of mathematical optimization problems of the form min_{x in R^n} f(x) s.t. g_L <= g(x) <= g_U x_L <= x <= x_U where f(x): R^n --> R is the objective function, and g(x): R^n --> R^m are the constraint functions. The vectors g_L and g_U denote the lower and upper bounds on the constraints, and the vectors x_L and x_U are the bounds on the variables x. The functions f(x) and g(x) can be nonlinear and nonconvex, but should be twice continuously differentiable. Note that equality constraints can be formulated in the above formulation by setting the corresponding components of g_L and g_U to the same value. Ipopt is part of the COIN-OR Initiative.
2013-11-14 16:04:12 +01:00
Size (Ipopt-3.11.5.tgz) = 4743371 bytes
Fix build.
2013-12-06 22:24:59 +01:00
SHA1 (patch-Ipopt_Makefile.in) = 6582e7425f1d3d8b9b010caa89225fe000e3897a
Fix extraction of rpath options from Fortran linker.
2013-11-29 13:59:31 +01:00
SHA1 (patch-Ipopt_configure) = a8737f537b8638a71d65d83658770826bfefc5e6
SHA1 (patch-ThirdParty_HSLold_configure) = e4993ba13c1c84a4d83992c3ce0c58a500af7462
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