Source code for baseclasses.problems.pyAeroStruct_problem

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# Imports
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from .pyAero_problem import AeroProblem
from .pyStruct_problem import StructProblem
from ..utils import Error, SolverHistory

[docs] class AeroStructProblem: """ The main purpose of this class is to represent all relevant information for a coupled aero-structural analysis. To this end, it maintains a reference to an AaeroProblem and a StructProblem. Parameters ---------- ap : AeroProblem class instance An instance of the AeroProblem class defining the aerodynamic part of the problem. sp : StructProblem class instance An instance of the StructProblem class defining the structural part of the problem """ def __init__(self, ap, sp, **kwargs): if not isinstance(ap, AeroProblem): raise Error("The argument for 'ap' was not an AeroProblem!") if not isinstance(sp, StructProblem): raise Error("The argument for 'sp' was not a StructProblem!") self.AP = ap self.SP = sp # For consistency, we require that the name of the AP and SP # are the same: if != raise Error( "The name of the AeroProblem and the StructProblem \ used to create this clsss *must* be the same" ) = self.funcNames = {} # Solver History self.history = SolverHistory()
[docs] def setDesignVars(self, x): """ Set the variables in the x-dict for this object. Parameters ---------- x : dict Dictionary of variables which may or may not contain the design variable names this object needs """ self.AP.setDesignVars(x) self.SP.setDesignVars(x)
[docs] def addVariablesPyOpt(self, optProb): """ Add the current set of variables to the optProb object. Parameters ---------- optProb : pyOpt_optimization class Optimization problem definition to which variables are added """ self.AP.addVariablesPyOpt(optProb) self.SP.addVariablesPyOpt(optProb)
def __getitem__(self, key): return self.funcNames[key]
[docs] def evalFunctions(self, funcs, evalFuncs): """ Evaluate functions of the AP and SP. """ self.AP.evalFunctions(funcs, evalFuncs, ignoreMissing=True) self.SP.evalFunctions(funcs, evalFuncs, ignoreMissing=True)
[docs] def evalFunctionsSens(self, funcsSens, evalFuncs): """ Evaluate the sensitivity of the desired functions Parameters ---------- funcsSens : dict Dictionary into which the function sensitivities are saved evalFuncs : iterable object containing strings The functions that the user wants evaluated """ self.AP.evalFunctionsSens(funcsSens, evalFuncs, ignoreMissing=True) self.SP.evalFunctionsSens(funcsSens, evalFuncs, ignoreMissing=True)