def define_model(**kwds):
sense = kwds.pop("sense")
m = pmo.block()
m.x = pmo.variable_list()
m.Fx = pmo.variable_list()
m.piecewise = pmo.block_list()
for i in range(7):
m.x.append(pmo.variable(lb=-5, ub=4))
m.Fx.append(pmo.variable())
m.piecewise.append(
pmo.piecewise(breakpoints, values,
input=m.x[i],
output=m.Fx[i],
**kwds))
m.obj = pmo.objective(expr=sum(m.Fx),
sense=sense)
# fix the answer for testing purposes
m.set_answer = pmo.constraint_list()
m.set_answer.append(pmo.constraint(m.x[0] == -5.0))
m.set_answer.append(pmo.constraint(m.x[1] == -3.0))
m.set_answer.append(pmo.constraint(m.x[2] == -2.5))
m.set_answer.append(pmo.constraint(m.x[3] == -1.5))
m.set_answer.append(pmo.constraint(m.x[4] == 2.0))
m.set_answer.append(pmo.constraint(m.x[5] == 3.5))
m.set_answer.append(pmo.constraint(m.x[6] == 4.0))
return m
def define_model(**kwds):
sense = kwds.pop("sense")
m = block()
m.x = variable_list()
m.Fx = variable_list()
m.piecewise = block_list()
for i in range(4):
m.x.append(variable(lb=0, ub=6))
m.Fx.append(variable())
m.piecewise.append(
piecewise(breakpoints, values,
input=m.x[i],
output=m.Fx[i],
**kwds))
m.obj = objective(expr=sum(m.Fx),
sense=sense)
# fix the answer for testing purposes
m.set_answer = constraint_list()
m.set_answer.append(constraint(m.x[0] == 0.0))
m.set_answer.append(constraint(m.x[1] == 3.0))
m.set_answer.append(constraint(m.x[2] == 5.5))
m.set_answer.append(constraint(m.x[3] == 6.0))
return m
def define_model(**kwds):
sense = kwds.pop("sense")
m = pmo.block()
m.x = pmo.variable_list()
m.Fx = pmo.variable_list()
m.piecewise = pmo.block_list()
for i in range(4):
m.x.append(pmo.variable(lb=0, ub=3))
m.Fx.append(pmo.variable())
m.piecewise.append(
pmo.piecewise(breakpoints, values,
input=m.x[i],
output=m.Fx[i],
**kwds))
m.obj = pmo.objective(expr=sum(m.Fx) + sum(m.x),
sense=sense)
# fix the answer for testing purposes
m.set_answer = pmo.constraint_list()
# Fx1 should solve to 0
m.set_answer.append(pmo.constraint(expr= m.x[0] == 0.5))
m.set_answer.append(pmo.constraint(expr= m.x[1] == 1.0))
m.set_answer.append(pmo.constraint(expr= m.Fx[1] == 0.5))
# Fx[2] should solve to 1
m.set_answer.append(pmo.constraint(expr= m.x[2] == 1.5))
# Fx[3] should solve to 1.5
m.set_answer.append(pmo.constraint(expr= m.x[3] == 2.5))
return m
def define_model(**kwds):
sense = kwds.pop("sense")
m = pmo.block()
m.x = pmo.variable_list()
m.Fx = pmo.variable_list()
m.piecewise = pmo.block_list()
for i in range(7):
m.x.append(pmo.variable(lb=-5, ub=4))
m.Fx.append(pmo.variable())
m.piecewise.append(
pmo.piecewise(breakpoints, values,
input=m.x[i],
output=m.Fx[i],
**kwds))
m.obj = pmo.objective(expr=sum(m.Fx),
sense=sense)
# fix the answer for testing purposes
m.set_answer = pmo.constraint_list()
m.set_answer.append(pmo.constraint(m.x[0] == -5.0))
m.set_answer.append(pmo.constraint(m.x[1] == -3.0))
m.set_answer.append(pmo.constraint(m.x[2] == -2.5))
m.set_answer.append(pmo.constraint(m.x[3] == -1.5))
m.set_answer.append(pmo.constraint(m.x[4] == 2.0))
m.set_answer.append(pmo.constraint(m.x[5] == 3.5))
m.set_answer.append(pmo.constraint(m.x[6] == 4.0))
return m
import pyomo.kernel as pmo
#
# Piecewise linear constraints
#
breakpoints = [1, 2, 3, 4]
values = [1, 2, 1, 2]
x = pmo.variable(lb=1, ub=4)
y = pmo.variable()
p = pmo.piecewise(breakpoints,
values,
input=x,
output=y,
repn='sos2',
bound='eq')
# change the input and output variables
z = pmo.variable(lb=1, ub=4)
q = pmo.variable()
p.input.expr = z
p.output.expr = q
# re-validate the function after changing inputs
# (will raise PiecewiseValidationError when validation fails)
p.validate()
# evaluate the function
assert p(1) == 1
assert p(1.5) == 1.5
import pyomo.kernel as pmo
#
# Piecewise linear constraints
#
breakpoints = [1,2,3,4]
values = [1,2,1,2]
x = pmo.variable(lb=1, ub=4)
y = pmo.variable()
p = pmo.piecewise(breakpoints,
values,
input=x,
output=y,
repn='sos2',
bound='eq')
# change the input and output variables
z = pmo.variable(lb=1, ub=4)
q = pmo.variable()
p.input.expr = z
p.output.expr = q
# re-validate the function after changing inputs
# (will raise PiecewiseValidationError when validation fails)
p.validate()
# evaluate the function
assert p(1) == 1
assert p(1.5) == 1.5
# @SOS_single
# @SOS_dict
m.sd = pmo.sos_dict()
m.sd[1] = pmo.sos1(m.vd.values())
m.sd[2] = pmo.sos1(m.vl)
# @SOS_dict
# @SOS_list
# uses 0-based indexing
m.sl = pmo.sos_list()
for i in m.s:
m.sl.append(pmo.sos1([m.vl[i], m.vd[i]]))
# @SOS_list
# @Suffix_single
m.dual = pmo.suffix(direction=pmo.suffix.IMPORT)
# @Suffix_single
# @Suffix_dict
m.suffixes = pmo.suffix_dict()
m.suffixes['dual'] = pmo.suffix(direction=pmo.suffix.IMPORT)
# @Suffix_dict
# @Piecewise_1d
breakpoints = [1, 2, 3, 4]
values = [1, 2, 1, 2]
m.f = pmo.variable()
m.pw = pmo.piecewise(breakpoints, values, input=m.v, output=m.f, bound='eq')
# @Piecewise_1d
pmo.pprint(m)
# @Suffix_single
m.dual = pmo.suffix(
direction=pmo.suffix.IMPORT)
# @Suffix_single
# @Suffix_dict
m.suffixes = pmo.suffix_dict()
m.suffixes['dual'] = pmo.suffix(
direction=pmo.suffix.IMPORT)
# @Suffix_dict
# @Piecewise_1d
breakpoints = [1,2,3,4]
values = [1,2,1,2]
m.f = pmo.variable()
m.pw = pmo.piecewise(
breakpoints,
values,
input=m.v,
output=m.f,
bound='eq')
# @Piecewise_1d
pmo.pprint(m)