def solve(self):
bx = self.bx.get_cvx()
bc = self.bc.get_cvx()
X = conelp(self.c)
X.aux.pushLinConstraint(bx['mat'], bx['vec'])
X.aux.pushLinConstraint(bc['mat'], bc['vec'])
return X.solve()
def solve(self):
c = numpy.concatenate([self.qp.lp.c, self.penalty.v])
X = conelp(c)
bx = self.qp.lp.bx.get_cvx()
bc = self.qp.lp.bc.get_cvx()
qc = self.qp.qc.get_cvx()
p = self.penalty.getCVX()
X.aux.pushLinConstraint(numpy.hstack([bx['mat'], numpy.zeros(bx['mat'].shape)]), bx['vec'])
X.aux.pushLinConstraint(numpy.hstack([bc['mat'], numpy.zeros(bc['mat'].shape)]), bc['vec'])
X.aux.pushLinConstraint(p['mat'], p['vec'])
X.aux.pushQuadConstraint(numpy.hstack([qc['mat'], numpy.zeros(qc['mat'].shape)]), qc['vec'])
x = X.solve()
return x[0][0:len(self.qp.lp.c)], x[1]
