diff options
Diffstat (limited to 'src')
| -rw-r--r-- | src/act4e_mcdp_solution/solver_dp.py | 541 |
1 files changed, 521 insertions, 20 deletions
diff --git a/src/act4e_mcdp_solution/solver_dp.py b/src/act4e_mcdp_solution/solver_dp.py index 8a4d58c..d6d1a7a 100644 --- a/src/act4e_mcdp_solution/solver_dp.py +++ b/src/act4e_mcdp_solution/solver_dp.py @@ -1,29 +1,530 @@ -from act4e_mcdp import DPSolverInterface, Interval, LowerSet, PrimitiveDP, UpperSet +from typing import Optional, TypeVar +from act4e_mcdp import * # type: ignore +from decimal import Decimal __all__ = [ "DPSolver", ] +X = TypeVar("X") +FT = TypeVar("FT") +RT = TypeVar("RT") +R1 = TypeVar("R1") +R2 = TypeVar("R2") +F1 = TypeVar("F1") +F2 = TypeVar("F2") + + class DPSolver(DPSolverInterface): - def solve_dp_FixFunMinRes( - self, - dp: PrimitiveDP, - functionality_needed: object, - /, - resolution_optimistic: int = 0, - resolution_pessimistic: int = 0, + # walkthrough: identity + + def solve_dp_FixFunMinRes_IdentityDP( + self, _: IdentityDP[X], query: FixFunMinResQuery[X] + ) -> Interval[UpperSet[X]]: + # Easy: the minimal resources are the functionality itself + f = query.functionality + min_r = f + min_resources = UpperSet.principal(min_r) + + # We need to return an interval of upper sets. It is a degenerate interval + return Interval.degenerate(min_resources) + + def solve_dp_FixResMaxFun_IdentityDP( + self, _: IdentityDP[X], query: FixResMaxFunQuery[X] + ) -> Interval[LowerSet[X]]: + # same as above, but we return lower sets + + r = query.resources + max_f = r + max_functionalities = LowerSet.principal(max_f) + return Interval.degenerate(max_functionalities) + + # walkthrough: constant resources + + def solve_dp_FixFunMinRes_Constant( + self, dp: Constant[X], query: FixFunMinResQuery[tuple[()]] + ) -> Interval[UpperSet[X]]: + # The DP is a relation of the type + # + # 42 ≤ r + + # The functionalities are the empty tuple + + assert query.functionality == (), query.functionality + + # The minimal resources do not depend on functionality + # They are the constant value of the DP + + min_r = dp.c.value + min_resources = UpperSet.principal(min_r) + return Interval.degenerate(min_resources) + + def solve_dp_FixResMaxFun_Constant( + self, dp: Constant[X], query: FixResMaxFunQuery[X] + ) -> Interval[LowerSet[tuple[()]]]: + # The DP is a relation of the type + # + # 42 ≤ r + + # Here we need to check whether the resources are at least 42 + + R = dp.R + if R.leq(dp.c.value, query.resources): + # the functionalities are the empty tuple + max_f = () + return Interval.degenerate(LowerSet.principal(max_f)) + else: + # the given budget is not enough + empty: LowerSet[tuple[()]] = LowerSet.empty() + return Interval.degenerate(empty) + + # exercise: limit + + def solve_dp_FixResMaxFun_Limit(self, dp: Limit[X], query: FixResMaxFunQuery[X]) -> Interval[LowerSet[X]]: + # The DP is a relation of the type + # + # f ≤ 42 + + # This is the dual of Constant above. Swap functionalities and resources. + + raise NotImplementedError + + def solve_dp_FixFunMinRes_Limit( + self, dp: Limit[X], query: FixFunMinResQuery[X] + ) -> Interval[UpperSet[tuple[()]]]: + # The DP is a relation of the type + # + # f ≤ 42 + + # This is the dual of Constant above. Swap functionalities and resources. + + raise NotImplementedError + + # walkthrough: ceil(f) <= r DP + + def solve_dp_FixFunMinRes_M_Ceil_DP( + self, dp: M_Ceil_DP, query: FixFunMinResQuery[Decimal] + ) -> Interval[UpperSet[Decimal]]: + # In the documentation of the class M_Ceil_DP we have + # that the relation is defined as: + # + # ceil(f) ≤ r + + # Therefore, the minimal resources are the ceiling of the functionality + # r >= ceil(f) + f = query.functionality + assert isinstance(f, Decimal) + + # For M_Ceil_DP, the F and R posets are Numbers + R: Numbers = dp.R + F: Numbers = dp.F + + # Note: the f = +inf is a special case for which __ceil__() does not work + if f.is_infinite(): + min_r = f + else: + # otherwise, we just use the ceil function + min_r = Decimal(f.__ceil__()) + + # now, one last detail: in general, the F poset can have + # different upper/lower bound or discretization than the R poset. + # We need to make sure that we provide a valid resource. + + # There is a function largest_upperset_above() that will do this for us. + # See documentation there. + + min_resources = R.largest_upperset_above(min_r) + return Interval.degenerate(min_resources) + + def solve_dp_FixResMaxFun_M_Ceil_DP( + self, dp: M_Ceil_DP, query: FixResMaxFunQuery[Decimal] + ) -> Interval[LowerSet[Decimal]]: + # Now r is fixed + r = query.resources + assert isinstance(r, Decimal), r + + R: Numbers = dp.R + F: Numbers = dp.F + + # For M_Ceil_DP, the F/R posets are Numbers + + # first special case: r = +inf + if r.is_infinite(): + max_f = r + + else: + # what is the maximum f such that + # ceil(f) <= r + # ? + + # for example, if r = 13.2, then the maximum f is 13 + # in fact, we obtain the floor of r + + max_f = Decimal(r.__floor__()) + + # one last detail: we need to make sure that the functionality is valid + # for the F poset. We use the largest_lowerset_below() function in Numbers. + # See documentation there. + + max_functionalities = F.largest_lowerset_below(max_f) + + return Interval.degenerate(max_functionalities) + + # exercise: floor relation + + def solve_dp_FixFunMinRes_M_FloorFun_DP( + self, dp: M_FloorFun_DP, query: FixFunMinResQuery[Decimal] + ) -> Interval[UpperSet[Decimal]]: + # f <= floor(r) + + # This is dual to M_Ceil_DP + + raise NotImplementedError + + def solve_dp_FixResMaxFun_M_FloorFun_DP( + self, dp: M_FloorFun_DP, query: FixResMaxFunQuery[Decimal] + ) -> Interval[LowerSet[Decimal]]: + # f <= floor(r) + + # This is dual to M_Ceil_DP + + raise NotImplementedError + + # exercise: catalogue + + def solve_dp_FixFunMinRes_CatalogueDP( + self, dp: CatalogueDP[FT, RT], query: FixFunMinResQuery[FT] + ) -> Interval[UpperSet[RT]]: + f = query.functionality + F = dp.F + + # Hint: iterate over the entries of the catalogue + name: str + entry_info: EntryInfo[FT, RT] + for name, entry_info in dp.entries.items(): + # Then check if this entry is valid for the functionality + # In that case, the resources of the entry are a valid solution + ... + + raise NotImplementedError + + def solve_dp_FixResMaxFun_CatalogueDP( + self, dp: CatalogueDP[FT, RT], query: FixResMaxFunQuery[RT] + ) -> Interval[LowerSet[FT]]: + # Same pattern as above, but functionalities and resources are swapped. + + raise NotImplementedError + + # exercise: series interconnections + + def solve_dp_FixFunMinRes_DPSeries( + self, dp: DPSeries, query: FixFunMinResQuery[object] ) -> Interval[UpperSet[object]]: - optimistic = pessimistic = UpperSet([]) - return Interval(pessimistic=pessimistic, optimistic=optimistic) - - def solve_dp_FixResMaxFun( - self, - dp: PrimitiveDP, - resource_budget: object, - /, - resolution_optimistic: int = 0, - resolution_pessimistic: int = 0, + # This is the interconnection of a sequence of DPs. + # (You can assume that the sequence is at least 2 DPs). + + # Hint: you should solve each DP in the sequence, and then + # pass it to the next. + # You can use the function self.solve_dp_FixFunMinRes() for this. + + # Note 1: the solve_dp_FixFunMinRes_DPSeries() takes a single functionality. + # But in general the previous DP returns an upperset. You need to call it multiple times. + # Note 2: the solve_dp_FixFunMinRes_DPSeries() returns an *interval* of upper sets. + # Just treat the optimistic and pessimistic cases separately and then combine them in an interval. + + raise NotImplementedError + + def solve_dp_FixResMaxFun_DPSeries( + self, dp: DPSeries, query: FixResMaxFunQuery[object] ) -> Interval[LowerSet[object]]: - optimistic = pessimistic = LowerSet([]) - return Interval(pessimistic=pessimistic, optimistic=optimistic) + # Hint: same as above, but go the other way... + raise NotImplementedError + + # walkthrough: add a constant to functionalities ( f + constant <= r) + + def solve_dp_FixFunMinRes_M_Res_AddConstant_DP( + self, dp: M_Res_AddConstant_DP, query: FixFunMinResQuery[Decimal] + ) -> Interval[UpperSet[Decimal]]: + f: Decimal = query.functionality + assert isinstance(f, Decimal) + + R: Numbers = dp.R + F: Numbers = dp.F + + # the relation is of the type + # + # f + constant <= r + + # therefore, the minimum resource is simply f + constant + min_r = f + dp.vu.value + + # one last detail: we need to make sure that the resource is valid + # for the R poset. We use the largest_upperset_above() function in Numbers. + # See documentation there. + us = R.largest_upperset_above(min_r) + + return Interval.degenerate(us) + + def solve_dp_FixResMaxFun_M_Res_AddConstant_DP( + self, dp: M_Res_AddConstant_DP, query: FixResMaxFunQuery[Decimal] + ) -> Interval[LowerSet[Decimal]]: + r = query.resources + assert isinstance(r, Decimal) + + R: Numbers = dp.R + F: Numbers = dp.F + + # the relation is of the type + # + # f + constant <= r + + # therefore, the maximal functionality is r - constant + + max_f = r - dp.vu.value + + # one last detail: we need to make sure that the functionality is valid + # for the F poset. We use the largest_lowerset_below() function in Numbers. + # See documentation there. + ls = F.largest_lowerset_below(max_f) + + return Interval.degenerate(ls) + + # exercise: add a constant to resource ( f <= r + constant) + + def solve_dp_FixFunMinRes_M_Fun_AddConstant_DP( + self, dp: M_Fun_AddConstant_DP, query: FixFunMinResQuery[Decimal] + ) -> Interval[UpperSet[Decimal]]: + # f <= r + constant + # This is dual to the M_Res_AddConstant_DP case above. + raise NotImplementedError + + def solve_dp_FixResMaxFun_M_Fun_AddConstant_DP( + self, dp: M_Fun_AddConstant_DP, query: FixResMaxFunQuery[Decimal] + ) -> Interval[LowerSet[Decimal]]: + # f <= r + constant + # This is dual to the M_Res_AddConstant_DP case above. + + raise NotImplementedError + + # walkthrough: multiplying constants (f * constant <= r) + def solve_dp_FixFunMinRes_M_Res_MultiplyConstant_DP( + self, dp: M_Res_MultiplyConstant_DP, query: FixFunMinResQuery[Decimal] + ) -> Interval[UpperSet[Decimal]]: + # (f * constant <= r) + + # This is similar to the M_Res_AddConstant_DP case above with + # multiplication instead of addition. + + f = query.functionality + assert isinstance(f, Decimal) + min_r = f * dp.vu.value + + # one last detail: we need to make sure that the resource is valid + # for the R poset. We use the largest_upperset_above() function in Numbers. + # See documentation there. + us = dp.R.largest_upperset_above(min_r) + + return Interval.degenerate(us) + + def solve_dp_FixResMaxFun_M_Res_MultiplyConstant_DP( + self, dp: M_Res_MultiplyConstant_DP, query: FixResMaxFunQuery[Decimal] + ) -> Interval[LowerSet[Decimal]]: + # (f * constant <= r) + + raise NotImplementedError + + # exercise: multiply by constant (f <= r * constant) + + def solve_dp_FixFunMinRes_M_Fun_MultiplyConstant_DP( + self, dp: M_Fun_MultiplyConstant_DP, query: FixFunMinResQuery[Decimal] + ) -> Interval[UpperSet[Decimal]]: + raise NotImplementedError + + def solve_dp_FixResMaxFun_M_Fun_MultiplyConstant_DP( + self, dp: M_Fun_MultiplyConstant_DP, query: FixResMaxFunQuery[Decimal] + ) -> Interval[LowerSet[Decimal]]: + raise NotImplementedError + + # walktrough: multiply functionalities + + def solve_dp_FixResMaxFun_M_Fun_MultiplyMany_DP( + self, dp: M_Fun_MultiplyMany_DP, query: FixResMaxFunQuery[tuple[Decimal, ...]] + ) -> Interval[LowerSet[Decimal]]: + # f <= r1 * r2 * r3 * ... + + # This direction is easy, we just multiply the resources + + res = Decimal(1) + for ri in query.resources: + res *= ri + ls = dp.F.largest_lowerset_below(res) + return Interval.degenerate(ls) + + # exercise: multiply resources + + def solve_dp_FixFunMinRes_M_Res_MultiplyMany_DP( + self, dp: M_Res_MultiplyMany_DP, query: FixFunMinResQuery[tuple[Decimal, ...]] + ) -> Interval[UpperSet[Decimal]]: + # f1 * f2 * f3 * ... <= r + # similar to the above + + # this is the easy direction + + raise NotImplementedError + + # walkthough: add many + + def solve_dp_FixFunMinRes_M_Res_AddMany_DP( + self, dp: M_Res_AddMany_DP, query: FixFunMinResQuery[tuple[Decimal, ...]] + ) -> Interval[UpperSet[Decimal]]: + # f1 + f2 + f3 + ... <= r + + f = query.functionality + F: PosetProduct[Decimal] = dp.F + assert isinstance(f, tuple), f + assert len(f) == len(F.subs), (f, F) + + # This direction is easy, we just add the functionalities + res = f[0] + for fi in f[1:]: + res += fi + + min_r = res + us = dp.R.largest_upperset_above(min_r) + return Interval.degenerate(us) + + # exercise: add many functionalities + + def solve_dp_FixResMaxFun_M_Fun_AddMany_DP( + self, dp: M_Fun_AddMany_DP, query: FixResMaxFunQuery[tuple[Decimal, ...]] + ) -> Interval[LowerSet[Decimal]]: + # this is a relation of the type + # (f1 ≤ r) and (f2 ≤ r) and (f3 ≤ r) and ... + + # This direction is easy, we just add the resources + + raise NotImplementedError + + # exercise: meet + + def solve_dp_FixFunMinRes_MeetNDualDP( + self, dp: MeetNDualDP[X], query: FixFunMinResQuery[X] + ) -> Interval[UpperSet[tuple[X, ...]]]: + # this is a relation of the type + # (f ≤ r₁) and (f ≤ r2) and (f ≤ r3) and ... + + # this direction is very easy, as we can just let each resource + # be equal to the functionality + + f = query.functionality + min_res = (f,) * len(dp.R.subs) + + us = dp.R.largest_upperset_above(min_res) + return Interval.degenerate(us) + + def solve_dp_FixResMaxFun_MeetNDualDP( + self, dp: MeetNDualDP[X], query: FixResMaxFunQuery[X] + ) -> Interval[LowerSet[tuple[X, ...]]]: + raise NotImplementedError + + # exercise: join + + def solve_dp_FixFunMinRes_JoinNDP( + self, dp: JoinNDP[X], query: FixFunMinResQuery[tuple[X, ...]] + ) -> Interval[UpperSet[X]]: + # this is a relation of the type + # (f1 ≤ r) and (f2 ≤ r) and (f3 ≤ r) and ... + + # similar to above + + f = query.functionality + min_r: Optional[X] = dp.opspace.join(f) + if min_r is None: + raise NotImplementedError("TODO: join") + us: UpperSet[X] = dp.R.largest_upperset_above(min_r) + return Interval.degenerate(us) + + def solve_dp_FixResMaxFun_JoinNDP( + self, dp: JoinNDP[X], query: FixResMaxFunQuery[X] + ) -> Interval[LowerSet[tuple[X, ...]]]: + raise NotImplementedError + + # The above are sufficient for lib1 + # + # + # + # + + # The following are only for lib2. + # + # + + def solve_dp_FixResMaxFun_M_Res_DivideConstant_DP( + self, dp: M_Res_DivideConstant_DP, query: FixResMaxFunQuery[Decimal] + ) -> Interval[LowerSet[Decimal]]: + # f/c <= r + + # Similar to a case above + raise NotImplementedError + + def solve_dp_FixFunMinRes_M_Res_DivideConstant_DP( + self, dp: M_Res_DivideConstant_DP, query: FixFunMinResQuery[Decimal] + ) -> Interval[UpperSet[Decimal]]: + # f/c <= r + + # Similar to a case above + raise NotImplementedError + + # Exercise: parallel interconnection + + def solve_dp_FixFunMinRes_ParallelDP( + self, dp: ParallelDP[FT, RT], query: FixFunMinResQuery[tuple[FT, ...]] + ) -> Interval[UpperSet[tuple[RT, ...]]]: + # This is the parallel composition of a sequence of DPs. + + f = query.functionality + + # F and R are PosetProducts + F: PosetProduct[FT] = dp.F + R: PosetProduct[RT] = dp.R + + # and f is a tuple of functionalities + assert isinstance(f, tuple), f + # ... of the same length as the number of DPs + assert len(f) == len(dp.subs), (f, F) + + # You should decompose f into its components, and then solve each DP. + # Then you need to take the *product* of the solutions. + # The product of upper sets is the upper set of the cartesian product + # and it is implemented as UpperSet.product(). + + raise NotImplementedError + + def solve_dp_FixResMaxFun_ParallelDP( + self, dp: ParallelDP[FT, RT], query: FixResMaxFunQuery[tuple[RT, ...]] + ) -> Interval[LowerSet[FT]]: + # Hint: same as above, swapping functionalities and resources + + # You will need to use LowerSet.product() + raise NotImplementedError + + # exercise (advanced): loops! + + def solve_dp_FixFunMinRes_DPLoop2( + self, dp: DPLoop2[F1, R1, object], query: FixFunMinResQuery[F1] + ) -> Interval[UpperSet[R1]]: + # Note: this is an advanced exercise. + + # As in the book, the intermediate goal is to define a function f such that + # the solution is the least fixed point of f. + + raise NotImplementedError + + def solve_dp_FixResMaxFun_DPLoop2( + self, dp: DPLoop2[F1, R1, object], query: FixResMaxFunQuery[R1] + ) -> Interval[LowerSet[F1]]: + # Note: this is an advanced exercise. + + # Hint: same as above, but go the other way... + raise NotImplementedError |