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// This file is part of Substrate. // Copyright (C) 2020-2021 Parity Technologies (UK) Ltd. // SPDX-License-Identifier: Apache-2.0 // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. //! Implementation of the sequential-phragmen election method. //! //! This method is ensured to achieve PJR, yet, it does not achieve a constant factor approximation //! to the Maximin problem. use crate::{ balancing, setup_inputs, CandidatePtr, ElectionResult, ExtendedBalance, IdentifierT, PerThing128, VoteWeight, Voter, }; use sp_arithmetic::{ helpers_128bit::multiply_by_rational, traits::{Bounded, Zero}, Rational128, }; use sp_std::prelude::*; /// The denominator used for loads. Since votes are collected as u64, the smallest ratio that we /// might collect is `1/approval_stake` where approval stake is the sum of votes. Hence, some number /// bigger than u64::MAX is needed. For maximum accuracy we simply use u128; const DEN: ExtendedBalance = ExtendedBalance::max_value(); /// Execute sequential phragmen with potentially some rounds of `balancing`. The return type is list /// of winners and a weight distribution vector of all voters who contribute to the winners. /// /// - This function is a best effort to elect `rounds` members. Nonetheless, if less candidates are /// available, it will only return what is available. It is the responsibility of the call site to /// ensure they have provided enough members. /// - If `balance` parameter is `Some(i, t)`, `i` iterations of balancing is with tolerance `t` is /// performed. /// - Returning winners are sorted based on desirability. Voters are unsorted. Nonetheless, /// seq-phragmen is in general an un-ranked election and the desirability should not be /// interpreted with any significance. /// - The returning winners are zipped with their final backing stake. Yet, to get the exact final /// weight distribution from the winner's point of view, one needs to build a support map. See /// [`crate::SupportMap`] for more info. Note that this backing stake is computed in /// ExtendedBalance and may be slightly different that what will be computed from the support map, /// due to accuracy loss. /// - The accuracy of the returning edge weight ratios can be configured via the `P` generic /// argument. /// - The returning weight distribution is _normalized_, meaning that it is guaranteed that the sum /// of the ratios in each voter's distribution sums up to exactly `P::one()`. /// /// This can only fail of the normalization fails. This can happen if for any of the resulting /// assignments, `assignment.distribution.map(|p| p.deconstruct()).sum()` fails to fit inside /// `UpperOf<P>`. A user of this crate may statically assert that this can never happen and safely /// `expect` this to return `Ok`. /// /// This can only fail if the normalization fails. /// /// Note that rounding errors can potentially cause the output of this function to fail a t-PJR /// check where t is the standard threshold. The underlying algorithm is sound, but the conversions /// between numeric types can be lossy. pub fn seq_phragmen<AccountId: IdentifierT, P: PerThing128>( rounds: usize, initial_candidates: Vec<AccountId>, initial_voters: Vec<(AccountId, VoteWeight, Vec<AccountId>)>, balance: Option<(usize, ExtendedBalance)>, ) -> Result<ElectionResult<AccountId, P>, crate::Error> { let (candidates, voters) = setup_inputs(initial_candidates, initial_voters); let (candidates, mut voters) = seq_phragmen_core::<AccountId>(rounds, candidates, voters)?; if let Some((iterations, tolerance)) = balance { // NOTE: might create zero-edges, but we will strip them again when we convert voter into // assignment. let _iters = balancing::balance::<AccountId>(&mut voters, iterations, tolerance); } let mut winners = candidates .into_iter() .filter(|c_ptr| c_ptr.borrow().elected) // defensive only: seq-phragmen-core returns only up to rounds. .take(rounds) .collect::<Vec<_>>(); // sort winners based on desirability. winners.sort_by_key(|c_ptr| c_ptr.borrow().round); let mut assignments = voters.into_iter().filter_map(|v| v.into_assignment()).collect::<Vec<_>>(); let _ = assignments .iter_mut() .map(|a| a.try_normalize().map_err(|e| crate::Error::ArithmeticError(e))) .collect::<Result<(), _>>()?; let winners = winners .into_iter() .map(|w_ptr| (w_ptr.borrow().who.clone(), w_ptr.borrow().backed_stake)) .collect(); Ok(ElectionResult { winners, assignments }) } /// Core implementation of seq-phragmen. /// /// This is the internal implementation that works with the types defined in this crate. see /// `seq_phragmen` for more information. This function is left public in case a crate needs to use /// the implementation in a custom way. /// /// This can only fail if the normalization fails. // To create the inputs needed for this function, see [`crate::setup_inputs`]. pub fn seq_phragmen_core<AccountId: IdentifierT>( rounds: usize, candidates: Vec<CandidatePtr<AccountId>>, mut voters: Vec<Voter<AccountId>>, ) -> Result<(Vec<CandidatePtr<AccountId>>, Vec<Voter<AccountId>>), crate::Error> { // we have already checked that we have more candidates than minimum_candidate_count. let to_elect = rounds.min(candidates.len()); // main election loop for round in 0..to_elect { // loop 1: initialize score for c_ptr in &candidates { let mut candidate = c_ptr.borrow_mut(); if !candidate.elected { // 1 / approval_stake == (DEN / approval_stake) / DEN. If approval_stake is zero, // then the ratio should be as large as possible, essentially `infinity`. if candidate.approval_stake.is_zero() { candidate.score = Bounded::max_value(); } else { candidate.score = Rational128::from(DEN / candidate.approval_stake, DEN); } } } // loop 2: increment score for voter in &voters { for edge in &voter.edges { let mut candidate = edge.candidate.borrow_mut(); if !candidate.elected && !candidate.approval_stake.is_zero() { let temp_n = multiply_by_rational( voter.load.n(), voter.budget, candidate.approval_stake, ) .unwrap_or(Bounded::max_value()); let temp_d = voter.load.d(); let temp = Rational128::from(temp_n, temp_d); candidate.score = candidate.score.lazy_saturating_add(temp); } } } // loop 3: find the best if let Some(winner_ptr) = candidates .iter() .filter(|c| !c.borrow().elected) .min_by_key(|c| c.borrow().score) { let mut winner = winner_ptr.borrow_mut(); // loop 3: update voter and edge load winner.elected = true; winner.round = round; for voter in &mut voters { for edge in &mut voter.edges { if edge.who == winner.who { edge.load = winner.score.lazy_saturating_sub(voter.load); voter.load = winner.score; } } } } else { break } } // update backing stake of candidates and voters for voter in &mut voters { for edge in &mut voter.edges { if edge.candidate.borrow().elected { // update internal state. edge.weight = multiply_by_rational(voter.budget, edge.load.n(), voter.load.n()) // If result cannot fit in u128. Not much we can do about it. .unwrap_or(Bounded::max_value()); } else { edge.weight = 0 } let mut candidate = edge.candidate.borrow_mut(); candidate.backed_stake = candidate.backed_stake.saturating_add(edge.weight); } // remove all zero edges. These can become phantom edges during normalization. voter.edges.retain(|e| e.weight > 0); // edge of all candidates that eventually have a non-zero weight must be elected. debug_assert!(voter.edges.iter().all(|e| e.candidate.borrow().elected)); // inc budget to sum the budget. voter.try_normalize_elected().map_err(|e| crate::Error::ArithmeticError(e))?; } Ok((candidates, voters)) }