g[0] = 3 - x0
g[1] = 2 - x1
fail = 0
return f,g,fail
# =============================================================================
#
# =============================================================================
# Instantiate Optimization Problem
opt_prob = Optimization('TOY Constrained Problem',objfunc,use_groups=True)
opt_prob.addVarGroup('a',2,'c',value=1.0, lower=0.0, upper=10)
opt_prob.delVarGroup('a')
opt_prob.addVar('x','c',value=1.0, lower=0.0, upper=10)
opt_prob.addVarGroup('y',2,'c',value=1.0, lower=0.0, upper=10)
opt_prob.delVarGroup('y')
opt_prob.addVarGroup('z',1,'c',value=1.0, lower=0.0, upper=10)
opt_prob.addVarGroup('b',5,'c',value=3.0, lower=0.0, upper=10)
opt_prob.delVarGroup('b')
opt_prob.addObj('f')
opt_prob.addCon('g1','i')
opt_prob.addCon('g2','i')
print(opt_prob)
# Instantiate Optimizer (SLSQP) & Solve Problem
slsqp = SLSQP()
slsqp(opt_prob)
print(opt_prob.solution(0))
g[0] = 3 - x0
g[1] = 2 - x1
fail = 0
return f, g, fail
# =============================================================================
#
# =============================================================================
# Instantiate Optimization Problem
opt_prob = Optimization('TOY Constraint Problem', objfunc, use_groups=True)
opt_prob.addVarGroup('a', 2, 'c', value=1.0, lower=0.0, upper=10)
opt_prob.delVarGroup('a')
opt_prob.addVar('x', 'c', value=1.0, lower=0.0, upper=10)
opt_prob.addVarGroup('y', 2, 'c', value=1.0, lower=0.0, upper=10)
opt_prob.delVarGroup('y')
opt_prob.addVarGroup('z', 1, 'c', value=1.0, lower=0.0, upper=10)
opt_prob.addVarGroup('b', 5, 'c', value=3.0, lower=0.0, upper=10)
opt_prob.delVarGroup('b')
opt_prob.addObj('f')
opt_prob.addCon('g1', 'i')
opt_prob.addCon('g2', 'i')
print opt_prob
# Instantiate Optimizer (PSQP) & Solve Problem
slsqp = SLSQP()
slsqp(opt_prob)
print opt_prob.solution(0)
