def inequality_constraint(self, x=None):
"""Retrieve the inequality constraint values for your function
Assumptions:
N/A
Source:
N/A
Inputs:
x [vector]
Outputs:
scaled_constraints [vector]
Properties Used:
None
"""
self.evaluate(x)
aliases = self.optimization_problem.aliases
constraints = self.optimization_problem.constraints
results = self.results
# Setup constraints
indices = []
for ii in xrange(0, len(constraints)):
if constraints[ii][1] == ('='):
indices.append(ii)
iqconstraints = np.delete(constraints, indices, axis=0)
if iqconstraints == []:
scaled_constraints = []
else:
constraint_values = help_fun.get_values(self, iqconstraints,
aliases)
constraint_values[iqconstraints[:, 1] == '<'] = -constraint_values[
iqconstraints[:, 1] == '<']
bnd_constraints = constraint_values - help_fun.scale_const_bnds(
iqconstraints)
scaled_constraints = help_fun.scale_const_values(
iqconstraints, constraint_values)
return scaled_constraints
def equality_constraint(self,x = None):
"""Retrieve the equality constraint values for your function
Assumptions:
N/A
Source:
N/A
Inputs:
x [vector]
Outputs:
scaled_constraints [vector]
Properties Used:
None
"""
self.evaluate(x)
aliases = self.optimization_problem.aliases
constraints = self.optimization_problem.constraints
results = self.results
# Setup constraints
indices = []
for ii in xrange(0,len(constraints)):
if constraints[ii][1]=='>':
indices.append(ii)
elif constraints[ii][1]=='<':
indices.append(ii)
eqconstraints = np.delete(constraints,indices,axis=0)
if eqconstraints == []:
scaled_constraints = []
else:
constraint_values = help_fun.get_values(self,eqconstraints,aliases) - help_fun.scale_const_bnds(eqconstraints)
scaled_constraints = help_fun.scale_const_values(eqconstraints,constraint_values)
return scaled_constraints
def equality_constraint(self,x = None):
self.evaluate(x)
aliases = self.optimization_problem.aliases
constraints = self.optimization_problem.constraints
results = self.results
# Setup constraints
indices = []
for ii in xrange(0,len(constraints)):
if constraints[ii][1]=='>':
indices.append(ii)
elif constraints[ii][1]=='<':
indices.append(ii)
eqconstraints = np.delete(constraints,indices,axis=0)
if eqconstraints == []:
scaled_constraints = []
else:
constraint_values = help_fun.get_values(self,eqconstraints,aliases) - help_fun.scale_const_bnds(eqconstraints)
scaled_constraints = help_fun.scale_const_values(eqconstraints,constraint_values)
return scaled_constraints
def equality_constraint(self,x = None):
self.evaluate(x)
aliases = self.optimization_problem.aliases
constraints = self.optimization_problem.constraints
results = self.results
# Setup constraints
indices = []
for ii in xrange(0,len(constraints)):
if constraints[ii][1]=='>':
indices.append(ii)
elif constraints[ii][1]=='<':
indices.append(ii)
eqconstraints = np.delete(constraints,indices,axis=0)
if eqconstraints == []:
scaled_constraints = []
else:
constraint_values = help_fun.get_values(self,eqconstraints,aliases) - help_fun.scale_const_bnds(eqconstraints)
scaled_constraints = help_fun.scale_const_values(eqconstraints,constraint_values)
return scaled_constraints