/usr/include/openturns/swig/NLopt_doc.i is in libopenturns-dev 1.9-5.
This file is owned by root:root, with mode 0o644.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | %feature("docstring") OT::NLopt
"Interface to NLopt.
This class exposes the solvers from the non-linear optimization library [NLopt]_.
More details about available algorithms are available `here <http://ab-initio.mit.edu/wiki/index.php/NLopt_Algorithms>`_.
Parameters
----------
problem : :class:`~openturns.OptimizationProblem`
Optimization problem to solve.
algoName : str
The NLopt identifier of the algorithm.
Use :func:`GetAlgorithmNames()` to list available names.
Notes
-----
This solver does not implement the progress callback.
See also
--------
AbdoRackwitz, Cobyla, SQP, TNC
Examples
--------
>>> import openturns as ot
>>> dim = 4
>>> bounds = ot.Interval([-3.0] * dim, [5.0] * dim)
>>> linear = ot.SymbolicFunction(['x1', 'x2', 'x3', 'x4'], ['x1+2*x2-3*x3+4*x4'])
>>> problem = ot.OptimizationProblem(linear, ot.Function(), ot.Function(), bounds)
>>> algo = ot.NLopt(problem, 'LD_MMA')
>>> algo.setStartingPoint([0.0] * 4)
>>> algo.run()
>>> result = algo.getResult()"
// ---------------------------------------------------------------------
%feature("docstring") OT::NLopt::setAlgorithmName
"Accessor to the algorithm name.
Parameters
----------
algoName : str
The NLopt identifier of the algorithm."
// ---------------------------------------------------------------------
%feature("docstring") OT::NLopt::getAlgorithmName
"Accessor to the algorithm name.
Returns
-------
algoName : str
The NLopt identifier of the algorithm."
// ---------------------------------------------------------------------
%feature("docstring") OT::NLopt::setInitialStep
"Initial local derivative-free algorithms step accessor.
Parameters
----------
dx : sequence of float
The initial step."
// ---------------------------------------------------------------------
%feature("docstring") OT::NLopt::getInitialStep
"Initial local derivative-free algorithms step accessor.
Returns
-------
dx : :class:`~openturns.Point`
The initial step."
// ---------------------------------------------------------------------
%feature("docstring") OT::NLopt::setLocalSolver
"Local solver accessor.
Parameters
----------
solver : :class:`~openturns.NLopt`
The local solver."
// ---------------------------------------------------------------------
%feature("docstring") OT::NLopt::getLocalSolver
"Local solver accessor.
Returns
-------
solver : :class:`~openturns.NLopt`
The local solver."
// ---------------------------------------------------------------------
%feature("docstring") OT::NLopt::GetAlgorithmNames
"Accessor to the list of algorithms provided by NLopt, by names.
Returns
-------
names : :class:`~openturns.Description`
List of algorithm names provided by NLopt, according to its naming convention.
Examples
--------
>>> import openturns as ot
>>> print(ot.NLopt.GetAlgorithmNames())
[AUGLAG,AUGLAG_EQ,GD_MLSL,GD_MLSL_LDS,GD_STOGO,GD_STOGO_RAND,GN_CRS2_LM,GN_DIRECT,GN_DIRECT_L,GN_DIRECT_L_NOSCAL,GN_DIRECT_L_RAND,GN_DIRECT_L_RAND_NOSCAL,GN_DIRECT_NOSCAL,GN_ESCH,GN_ISRES,GN_MLSL,GN_MLSL_LDS,GN_ORIG_DIRECT,GN_ORIG_DIRECT_L,G_MLSL,G_MLSL_LDS,LD_AUGLAG,LD_AUGLAG_EQ,LD_CCSAQ,LD_LBFGS,LD_LBFGS_NOCEDAL,LD_MMA,LD_SLSQP,LD_TNEWTON,LD_TNEWTON_PRECOND,LD_TNEWTON_PRECOND_RESTART,LD_TNEWTON_RESTART,LD_VAR1,LD_VAR2,LN_AUGLAG,LN_AUGLAG_EQ,LN_BOBYQA,LN_COBYLA,LN_NELDERMEAD,LN_NEWUOA,LN_NEWUOA_BOUND,LN_PRAXIS,LN_SBPLX]#43"
// ---------------------------------------------------------------------
%feature("docstring") OT::NLopt::SetSeed
"Initialize the random generator seed.
Parameters
----------
seed : int
The RNG seed."
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