Scilab Function ccfg - Evaluate constraint functions and possibly their gradients
Calling Sequence
- [c,cjac] = ccfg(x,jtrans)
Parameters
- x
: real vector
- jtrans
: integer flag
- c
: real vector of constraint values
- cjac
: the constraint Jacobian matrix
Description
CCFG Evaluate constraint functions and possibly their gradients at x.
c=ccfg(x) returns the vector of constraint values in C.
[c,cjac]=ccfg(x) also returns the constraint Jacobian matrix in cjac.
cjac(i,j) contains the partial derivative of the i-th constraint
with respect to the j-th variable.
[c,cjac]=ccfg(x,jtrans), with jtrans set to 1, gives the transpose
of the Jacobian, where the i,j-th component is the partial derivative
of the j-th constraint with respect to the i-th variable.
Examples
sifdecode(get_sif_path()+'sif/BT1.SIF',TMPDIR+'/BT1')
buildprob(TMPDIR+'/BT1')
[x,bl,bu,v,cl,cu,equatn,linear] = csetup(TMPDIR+'/BT1/OUTSDIF.d');
c=ccfg(x)
[c,cjac]=ccfg(x)
Authors
Bruno Durand, INRIA
Serge Steer, INRIA
Bibliography
Based on CUTEr authored by
Nicholas I.M. Gould - n.gould@rl.ac.uk - RAL
Dominique Orban - orban@ece.northwestern.edu - Northwestern
Philippe L. Toint - Philippe.Toint@fundp.ac.be - FUNDP
see http://hsl.rl.ac.uk/cuter-www