def solve_trace(self, func, trace):
if func in self._solve_cache:
# trace.log('using cache for %s' % str(func))
return trace.result(self._solve_cache[func])
trace.values(type='series')
with trace.child('dp1') as t:
u1 = self.dp1.solve_trace(func, t)
if do_extra_checks():
R1 = self.dp1.get_res_space()
tr1 = UpperSets(R1)
tr1.belongs(u1)
mcdp_dev_warning('rewrite this keeping structure')
mins = set([])
for u in u1.minimals:
with trace.child('dp2') as t:
v = self.dp2.solve_trace(u, t)
mins.update(v.minimals)
R = self.get_res_space()
minimals = poset_minima(mins, R.leq)
us = UpperSet(minimals, R)
self._solve_cache[func] = us
return trace.result(us)
def solve_f_iterate(dp0, f1, R, S, trace):
"""
Returns the next iteration si \in UR
Min ( h(f1, r20) \cup !r20 )
"""
UR = UpperSets(R)
if do_extra_checks():
UR.belongs(S)
R2 = R[1]
converged = set() # subset of solutions for which they converged
nextit = set()
# find the set of all r2s
for ra in S.minimals:
hr = dp0.solve_trace((f1, ra[1]), trace)
for rb in hr.minimals:
valid = R.leq(ra, rb)
if valid:
nextit.add(rb)
feasible = R2.leq(rb[1], ra[1])
if feasible:
converged.add(rb)
nextit = R.Us(poset_minima(nextit, R.leq))
converged = R.Us(poset_minima(converged, R.leq))
return nextit, converged
def solve_f_iterate(dp0, f1, R, S, trace):
"""
Returns the next iteration si \in UR
Min ( h(f1, r20) \cup !r20 )
"""
UR = UpperSets(R)
if do_extra_checks():
UR.belongs(S)
R2 = R[1]
converged = set() # subset of solutions for which they converged
nextit = set()
# find the set of all r2s
for ra in S.minimals:
hr = dp0.solve_trace((f1, ra[1]), trace)
for rb in hr.minimals:
valid = R.leq(ra, rb)
if valid:
nextit.add(rb)
feasible = R2.leq(rb[1], ra[1])
if feasible:
converged.add(rb)
nextit = R.Us(poset_minima(nextit, R.leq))
converged = R.Us(poset_minima(converged, R.leq))
return nextit, converged
def check_evaluate(id_dp, dp):
""" Test for PrimitiveDP:evaluate() """
print('Testing %s: %s' % (id_dp, dp))
F = dp.get_fun_space()
R = dp.get_res_space()
UR = UpperSets(R)
LF = LowerSets(F)
M = dp.get_imp_space()
# We get a random m
m0 = M.witness()
try:
lf, ur = dp.evaluate(m0)
except NotSolvableNeedsApprox:
return
UR.belongs(ur)
LF.belongs(lf)
if not lf.maximals or not ur.minimals:
msg = 'The point m0 gave empty lf, ur.'
raise_desc(Exception,
msg,
lf=lf,
ur=ur,
m0=M.format(m0),
M=M,
dp=dp.repr_long())
# take one possible feasible pair
_f = list(lf.maximals)[0]
_r = list(ur.minimals)[0]
def eval_constant_uppersetfromcollection(op, context):
x = eval_constant(op.value, context)
v = x.value
u = x.unit
S = u.S
minimals = poset_minima(v.elements, S.leq)
value = UpperSet(minimals, S)
unit = UpperSets(S)
if do_extra_checks():
unit.belongs(value)
vu = ValueWithUnits(value, unit)
return vu
def solveU(self, ufunc):
if do_extra_checks():
UF = UpperSets(self.get_fun_space())
UF.belongs(ufunc)
res = set([])
for m in ufunc.minimals:
u = self.solve(m)
res.update(u.minimals)
ressp = self.get_res_space()
minima = poset_minima(res, ressp.leq)
return ressp.Us(minima)
def eval_constant_uppersetfromcollection(op, context):
x = eval_constant(op.value, context)
v = x.value
u = x.unit
S = u.S
minimals = poset_minima(v.elements, S.leq)
value = UpperSet(minimals, S)
unit = UpperSets(S)
if do_extra_checks():
unit.belongs(value)
vu = ValueWithUnits(value, unit)
return vu
def solveU(self, ufunc):
if do_extra_checks():
UF = UpperSets(self.get_fun_space())
UF.belongs(ufunc)
res = set([])
for m in ufunc.minimals:
u = self.solve(m)
res.update(u.minimals)
ressp = self.get_res_space()
minima = poset_minima(res, ressp.leq)
return ressp.Us(minima)
