def build_linear_constraint():
"""Build a linear_constraint with no references to external
objects so its size can be computed."""
return linear_constraint(variables=build_linear_constraint.xlist,
coefficients=build_linear_constraint.clist,
lb=0,
ub=1)
def build_linear_constraint_list():
"""Build a constraint_list of linear_constraints with no references to external
objects so its size can be computed."""
return constraint_list(
linear_constraint(variables=(X_kernel[A_indices[p]] for p in range(A_indptr[i], A_indptr[i+1])),
coefficients=(A_data[p] for p in range(A_indptr[i], A_indptr[i+1])),
rhs=1)
for i in range(N))
def _generate_model(self):
self.model = pmo.block()
model = self.model
model._name = self.description
model.x = pmo.variable(domain=NonNegativeReals)
model.obj = pmo.objective(0.0)
model.con = pmo.linear_constraint(terms=[(model.x, 1.0)], rhs=1.0)
def _generate_model(self):
self.model = pmo.block()
model = self.model
model._name = self.description
model.x = pmo.variable(domain=NonNegativeReals)
model.obj = pmo.objective(0.0)
model.con = pmo.linear_constraint(terms=[(model.x,1.0)],
rhs=1.0)
def build_linear_constraint():
"""Build a linear_constraint with no references to external
objects so its size can be computed."""
return linear_constraint(variables=build_linear_constraint.xlist,
coefficients=build_linear_constraint.clist,
lb=0, ub=1)