/usr/include/openturns/swig/NLopt_doc.i is in libopenturns-dev 1.7-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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 | %feature("docstring") OT::SLSQP
"Sequential Least-Squares Quadratic Programming solver.
Parameters
----------
problem : :class:`~openturns.OptimizationProblem`
Optimization problem to solve.
See also
--------
AbdoRackwitz, Cobyla, SQP, TNC
Examples
--------
>>> import openturns as ot
>>> dim = 4
>>> bounds = ot.Interval([-3.] * dim, [5.] * dim)
>>> linear = ot.NumericalMathFunction(['x1', 'x2', 'x3', 'x4'], ['y1'], ['x1+2*x2-3*x3+4*x4'])
>>> problem = ot.OptimizationProblem(linear, ot.NumericalMathFunction(), ot.NumericalMathFunction(), bounds)
>>> algo = ot.SLSQP(problem)"
%feature("docstring") OT::LBFGS
"Low-storage BFGS algorithm.
Parameters
----------
problem : :class:`~openturns.OptimizationProblem`
Optimization problem to solve.
See also
--------
AbdoRackwitz, Cobyla, SQP, TNC
Examples
--------
>>> import openturns as ot
>>> dim = 4
>>> bounds = ot.Interval([-3.] * dim, [5.] * dim)
>>> linear = ot.NumericalMathFunction(['x1', 'x2', 'x3', 'x4'], ['y1'], ['x1+2*x2-3*x3+4*x4'])
>>> problem = ot.OptimizationProblem(linear, ot.NumericalMathFunction(), ot.NumericalMathFunction(), bounds)
>>> algo = ot.LBFGS(problem)"
%feature("docstring") OT::NelderMead
"Nelder-Mead simplex algorithm.
Parameters
----------
problem : :class:`~openturns.OptimizationProblem`
Optimization problem to solve.
See also
--------
AbdoRackwitz, Cobyla, SQP, TNC
Examples
--------
>>> import openturns as ot
>>> dim = 4
>>> bounds = ot.Interval([-3.] * dim, [5.] * dim)
>>> linear = ot.NumericalMathFunction(['x1', 'x2', 'x3', 'x4'], ['y1'], ['x1+2*x2-3*x3+4*x4'])
>>> problem = ot.OptimizationProblem(linear, ot.NumericalMathFunction(), ot.NumericalMathFunction(), bounds)
>>> algo = ot.NelderMead(problem)"
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