tutoriali.TutModelData Class Reference

Public Member Functions
	__init__ (self)
	buildModel (self)
	adding the variables and constraints to the model
	initFDEvaluation (self, x, rowlist, mode, numthread, ignerr)
	callback method for initialising the first derivative evaluation.
	evaluateNonlinearTerm (self, x, rowno, ignerr, thread)
	callback method for evaluating the nonlinear terms in a given row
	evaluateNonlinearJacobian (self, x, rowno, jacnum, ignerr, thread)
	callback method for evaluating the jacobian for the nonlinear terms in a given row
Public Member Functions inherited from pyconopt.ModelData
	__init__ (self)
	init(ModelData self) -> ModelData
	endFDEvaluation (self, ignerr)
	Optional function, if defined, it will be called at the end of the function evaluation stage.
	evaluateSDLagrangian (self, x, u, hessianrow, hessiancol)
	Computes and returns the numerical values of the Lagrangian of the Hessian.
	evaluateSDDirLagrangian (self, x, dx, u, newpoint)
	computes the directional second derivative for the Lagrangian
	evaluateDirectionalSD (self, x, dx, rowno, jacnum, thread)
	computes the directional second derivative for a single constraint
	initDirectionalSDEval (self, x, dx, rowlist, numthread, newpoint)
	a callback for the initialisation of the second derivative evaluation.
	endDirectionalSDEval (self)
	called by CONOPT after a sequence of evaluateDirectionalSD() calls each time either the point or the direction changes.
	errorInEvaluation (self)
	reports that an error occurred in the evaluation.
	setProblemDimension (self, numvar, numcons, numnz, numnlnz)
	sets the problem dimension.
	addConstraint (self, *args)
	Overload 1: adds a constraint to the problem.
	addVariable (self, *args)
	Overload 1: adds a variable to the model.
	setObjectiveElement (self, elem, elemindex)
	sets the index for the objective variable or constraint
	setOptimizationSense (self, sense)
	sets the optimisation direction.
	setInitialStatusOption (self, inistat)
	the setting to indicate how the initial status of the variables and slack variables will be handled.
	numVar (self)
	returns the number of variables in the model
	numCons (self)
	returns the number of constraints in the model
	numHessianNonzeros (self)
	returns the number of non-zeros in the Hessian
	getVariable (self, index)
	returns a reference to the variable object
	getConstraint (self, index)
	returns a reference to the constraint object
	setSDEvaluationType (self, sdevaltype)
	informs CONOPT of the method for evaluating the second derivative
	setSDLagrangianStructure (self, rownum, colnum)
	sets the structure of the second derivatives of the Lagrangian
	__disown__ (self)
Public Member Functions inherited from pyconopt.ConoptModelData
	__init__ (self)
	Constructor.
	readMatrix (self, lower, curr, upper, vsta, type, rhs, esta, colsta, rowno, value, nlflag, numvar, numcon, numnz)
	loads the structure of the model into CONOPT.
	getSDLagrangianRowNumbers (self)
	returns the row numbers in the second derivative of the lagrangian structure
	getSDLagrangianColumnNumbers (self)
	returns the column numbers in the second derivative of the lagrangian structure
	__disown__ (self)

Data Fields
int	L = 0
int	Inp = 0
int	Out = 0
int	P = 0
float	Al = 0.16
float	Ak = 2.0
float	Ainp = 0.16
float	Rho = 1.0
float	K = 4.0
list	hold = [0, 0, 0]
tuple	hold1
	hold2 = pow(self.hold1,( -1./self.Rho ))
tuple	hold3 = self.hold2 / self.hold1

Additional Inherited Members
Properties inherited from pyconopt.ModelData
	thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
Properties inherited from pyconopt.ConoptModelData
	thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")

Detailed Description

Definition at line 16 of file tutoriali.py.

Constructor & Destructor Documentation

__init__()

tutoriali.TutModelData.__init__

(

self

)

Definition at line 17 of file tutoriali.py.

Field Documentation

L

tutoriali.TutModelData.L = 0

Definition at line 18 of file tutoriali.py.

Inp

tutoriali.TutModelData.Inp = 0

Definition at line 19 of file tutoriali.py.

Out

tutoriali.TutModelData.Out = 0

Definition at line 20 of file tutoriali.py.

P

tutoriali.TutModelData.P = 0

Definition at line 21 of file tutoriali.py.

Al

float tutoriali.TutModelData.Al = 0.16

Definition at line 22 of file tutoriali.py.

Ak

float tutoriali.TutModelData.Ak = 2.0

Definition at line 23 of file tutoriali.py.

Ainp

float tutoriali.TutModelData.Ainp = 0.16

Definition at line 24 of file tutoriali.py.

Rho

float tutoriali.TutModelData.Rho = 1.0

Definition at line 25 of file tutoriali.py.

K

float tutoriali.TutModelData.K = 4.0

Definition at line 26 of file tutoriali.py.

hold

list tutoriali.TutModelData.hold = [0, 0, 0]

Definition at line 30 of file tutoriali.py.

hold1

tuple tutoriali.TutModelData.hold1

Initial value:

=  (self.Al*pow(self.L, (-self.Rho)) + \
            self.Ak*pow(self.K, (-self.Rho)) + \
            self.Ainp*pow(self.Inp, (-self.Rho)))

Definition at line 69 of file tutoriali.py.

hold2

tutoriali.TutModelData.hold2 = pow(self.hold1,( -1./self.Rho ))

Definition at line 72 of file tutoriali.py.

hold3

tuple tutoriali.TutModelData.hold3 = self.hold2 / self.hold1

Definition at line 73 of file tutoriali.py.

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The documentation for this class was generated from the following file:

• /builds/devel/conopt/conopt/examples/Python_1thread/tutoriali.py