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Functions

 square.SquareModelData.buildModel (self)
 adding the variables and constraints to the model
 
 square.SquareModelData.evaluateNonlinearTerm (self, x, rowno, ignerr, thread)
 callback method for evaluating the nonlinear terms in a given row
 
 square.SquareModelData.evaluateNonlinearJacobian (self, x, rowno, jacnum, ignerr, thread)
 callback method for evaluating the jacobian for the nonlinear terms in a given row
 

Detailed Description

This is a square model where we pretend that the second constraint is completely nonlinear.

\[ x1 + x2 = 10 \]

\[ x1 - x2 = 0 \]

For more information about the individual callbacks, please have a look at the source code.

Function Documentation

◆ buildModel()

square.SquareModelData.buildModel ( self)

adding the variables and constraints to the model

Definition at line 21 of file square.py.

◆ evaluateNonlinearTerm()

square.SquareModelData.evaluateNonlinearTerm ( self,
x,
rowno,
ignerr,
thread )

callback method for evaluating the nonlinear terms in a given row

Parameters
xthe solution vector that needs to be evaluated.
rownothe number for the row in which the nonlinear term exists.
ignerra boolean to indicate whether the current point is safe or unsafe.
threadthe index of the thread from which this method is being called from.
Returns
the value of the nonlinear terms.

Notes: an error in the evaluation is reported by calling errorInEvaluation()

Definition at line 40 of file square.py.

◆ evaluateNonlinearJacobian()

square.SquareModelData.evaluateNonlinearJacobian ( self,
x,
rowno,
jacnum,
ignerr,
thread )

callback method for evaluating the jacobian for the nonlinear terms in a given row

Parameters
xthe solution vector that needs to be evaluated.
rownothe number for the row in which the nonlinear term exists.
jacnumvector with a list of column numbers for the nonlinear nonzero Jacobian elements in the row.
ignerra boolean to indicate whether the current point is safe or unsafe.
threadthe index of the thread from which this method is being called from.
Returns
a vector the length of jacnum that contains the jacobian values for the referenced elements.

Notes: an error in the evaluation is reported by calling errorInEvaluation()

Definition at line 54 of file square.py.