defmodule CPSolver.Propagator.Sum do use CPSolver.Propagator import CPSolver.Variable.View.Factory @moduledoc """ The propagator for Sum constraint. Sum(y, x) constrains y to be a sum of variables in the list x. """ @spec new(Common.variable_or_view(), [Common.variable_or_view()]) :: Propagator.t() def new(y, x) do new([minus(y) | x]) end defp initial_state(args) do {sum_fixed, unfixed_vars} = args |> Enum.with_index() |> Enum.reduce({0, MapSet.new()}, fn {var, idx}, {sum_acc, unfixed_acc} -> (fixed?(var) && {sum_acc + min(var), unfixed_acc}) || {sum_acc, MapSet.put(unfixed_acc, idx)} end) %{sum_fixed: sum_fixed, unfixed_ids: unfixed_vars} end @impl true def variables([y | x]) do [ set_propagate_on(y, :domain_change) | Enum.map(x, fn x_el -> set_propagate_on(x_el, :bound_change) end) ] end @impl true def filter(args) do filter(args, initial_state(args)) end def filter(args, nil) do filter(args, initial_state(args)) end @impl true def filter(all_vars, %{sum_fixed: sum_fixed, unfixed_ids: unfixed_ids} = _state) do {unfixed_vars, updated_unfixed_ids, new_sum} = update_unfixed(all_vars, unfixed_ids) updated_sum = sum_fixed + new_sum {sum_min, sum_max} = sum_min_max(updated_sum, unfixed_vars) case filter_impl(unfixed_vars, sum_min, sum_max) do :fail -> fail() :ok -> {:state, %{sum_fixed: updated_sum, unfixed_ids: updated_unfixed_ids}} end end defp update_unfixed(all_vars, unfixed_ids) do Enum.reduce(unfixed_ids, {[], unfixed_ids, 0}, fn pos, {unfixed_acc, ids_acc, sum_acc} -> var = Enum.at(all_vars, pos) (fixed?(var) && {unfixed_acc, MapSet.delete(ids_acc, pos), sum_acc + min(var)}) || {[var | unfixed_acc], ids_acc, sum_acc} end) end defp filter_impl(variables, sum_min, sum_max) do if unsatisfiable(sum_min, sum_max) do fail() else {new_sum_min, new_sum_max} = update_partial_sums(variables, sum_min, sum_max) ## Enforce idempotence: we'll run filtering until there's no changes ((new_sum_min != sum_min || new_sum_max != sum_max) && filter_impl(variables, new_sum_min, new_sum_max)) || :ok end end defp update_partial_sums(variables, sum_min, sum_max) do Enum.reduce(variables, {sum_min, sum_max}, fn v, {s_min, s_max} -> min_v = min(v) max_v = max(v) new_max = maybe_update_max(v, max_v, removeAbove(v, -(s_min - min_v))) new_min = maybe_update_min(v, min_v, removeBelow(v, -(s_max - max_v))) new_sum_min = s_min + new_min - min_v new_sum_max = s_max + max_v - new_max (unsatisfiable(new_sum_min, new_sum_max) && fail()) || {new_sum_min, new_sum_max} end) end ## Some optimization: if removeAbove/removeBelow don't change the domain, ## save the additional max/min call. defp maybe_update_max(_var, current_max, :no_change) do current_max end defp maybe_update_max(var, _current_max, _domain_change) do max(var) end defp maybe_update_min(_var, current_min, :no_change) do current_min end defp maybe_update_min(var, _current_min, _domain_change) do min(var) end defp sum_min_max(sum_fixed, unfixed_variables) do Enum.reduce(unfixed_variables, {sum_fixed, sum_fixed}, fn v, {s_min, s_max} = _acc -> {s_min + min(v), s_max + max(v)} end) end defp unsatisfiable(sum_min, sum_max) do sum_min > 0 || sum_max < 0 end defp fail() do throw(:fail) end end