individual.bend source

individual.bend on the hub · documented module

# Individual — C# Unsga3.Algorithm.Individual.# Objectives + decision variables + evaluated + tournament bookkeeping# (rank / niche / associated ref / perp distance).# Constraints are g ≤ 0. `cv` is the sum of the positive parts# (RefreshConstraintViolation). Feasible iff cv ≤ 0. Empty g is cv 0,# so unconstrained ZDT / DTLZ stay on the Pareto path.import Basetype Individual is Data:  MkIndividual{    x: List<&2, F32>    f: List<&2, F32>    g: List<&2, F32>    cv: F32    rnk: Nat    nic: Nat    aref: Nat    dist: F32    ev: Bool  }def pos_part(+x: F32) -> F32:  Bool.pick(F32, F32.is_gt(x, 0.0), x, 0.0)# Sum of g_i where g_i > 0. Non-positive parts add nothing.def sum_pos(xs: List<&2, F32>) -> F32:  match xs:    case Nil{}:      0.0    case +h <> t:      F32.add(pos_part(h), sum_pos(t))# v0 / A/B path: objectives already known; no decision vector.# No constraints → cv 0 (feasible).def from_objectives(+f: List<&2, F32>) -> Individual:  MkIndividual{Nil{}, f, Nil{}, 0.0, 0n, 0n, 0n, 0.0, True{}}# Unevaluated candidate: variables set, objectives zeroed (C# ctor).# Constraints empty until a problem writes them.def from_variables(+x: List<&2, F32>, n_obj: Nat) -> Individual:  MkIndividual{x, List.replicate(F32, n_obj, 0.0), Nil{}, 0.0, 0n, 0n, 0n, 0.0, False{}}def variables(ind: Individual) -> List<&2, F32>:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      xdef objectives(ind: Individual) -> List<&2, F32>:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      fdef constraints(ind: Individual) -> List<&2, F32>:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      gdef constraint_violation(ind: Individual) -> F32:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      cv# C# IsFeasible: ConstraintViolation <= 0.def feasible(ind: Individual) -> Bool:  F32.is_le(constraint_violation(ind), 0.0)def rank(ind: Individual) -> Nat:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      rnkdef evaluated(ind: Individual) -> Bool:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      evdef n_obj(ind: Individual) -> Nat:  List.length(&2, F32, objectives(ind))def n_var(ind: Individual) -> Nat:  List.length(&2, F32, variables(ind))def var_at(ind: Individual, i: Nat) -> F32:  Maybe.default(&2, F32, List.get(&2, F32, variables(ind), i), 0.0)def set_var_at(ind: Individual, i: Nat, v: F32) -> Individual:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      MkIndividual{List.set(&2, F32, x, i, v), f, g, cv, rnk, nic, ar, pd, ev}def set_evaluated(ind: Individual, ev2: Bool) -> Individual:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev2}def niche(ind: Individual) -> Nat:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      nicdef associated_ref(ind: Individual) -> Nat:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      ardef perp_dist(ind: Individual) -> F32:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      pddef set_objectives(ind: Individual, +f2: List<&2, F32>) -> Individual:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      MkIndividual{x, f2, g, cv, rnk, nic, ar, pd, True{}}# Replace g and recompute cv (sum of positive parts).def set_constraints(ind: Individual, +g2: List<&2, F32>) -> Individual:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      MkIndividual{x, f, g2, sum_pos(g2), rnk, nic, ar, pd, ev}def set_rank(ind: Individual, rnk2: Nat) -> Individual:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      MkIndividual{x, f, g, cv, rnk2, nic, ar, pd, ev}def stamp(ind: Individual, +rnk2: Nat, +nic2: Nat, +aref2: Nat, +dist2: F32) -> Individual:  match ind:    case MkIndividual{x, f, g, cv, rnk, nic, ar, pd, ev}:      MkIndividual{x, f, g, cv, rnk2, nic2, aref2, dist2, ev}