fix: linting

README.md

@@ -0,0 +1,6 @@
+things to install:
+
+- LKH binary (either install from source or just download)
+- setup dwave.conf in user directory
+- install poetry to use as a package manager for the python libraries
+- install rust nightly version from 2023-07-01. use rustup to change the version used in this directory

python/lkh-interface/src/main.py

@@ -1,30 +1,34 @@
 import argparse
-from lkh import solve, LKHProblem
+
+from lkh import LKHProblem, solve
 from tsplib95.models import StandardProblem
 
 parser = argparse.ArgumentParser(
-    prog='LKH-3 Interface',
-    description='A CLI Program to initiate solving CVRP files with LKH-3',
-    epilog='Made by Lucas Berger for scientific purposes')
+    prog="LKH-3 Interface",
+    description="A CLI Program to initiate solving CVRP files with LKH-3",
+    epilog="Made by Lucas Berger for scientific purposes",
+)
 
 
-parser.add_argument('tsplib_file')
-parser.add_argument('--lkh-instance', default='../../bin/LKH')
-parser.add_argument('--output-file')
-parser.add_argument('-t', '--max-trials', default=1000)
-parser.add_argument('-r', '--runs', default=10)
+parser.add_argument("tsplib_file")
+parser.add_argument("--lkh-instance", default="../../bin/LKH")
+parser.add_argument("--output-file")
+parser.add_argument("-t", "--max-trials", default=1000)
+parser.add_argument("-r", "--runs", default=10)
 
 args = parser.parse_args()
-    
-    
+
+
 problem = LKHProblem.load(args.tsplib_file)
 
 if sum(problem.demands.values()) <= problem.capacity:
     problem.type = "TSP"
 
 if len(problem.node_coords.values()) > 2:
     extra = {}
-    tours = solve(args.lkh_instance, problem=problem, max_trials=args.max_trials, **extra)
+    tours = solve(
+        args.lkh_instance, problem=problem, max_trials=args.max_trials, **extra
+    )
 
     tour = StandardProblem()
 
@@ -33,11 +37,12 @@
     tour.name = problem.name + " solution"
 else:
     tour = StandardProblem()
-    tour.tours = [filter(lambda key: key not in problem.depots, problem.node_coords.keys())]
+    tour.tours = [
+        filter(lambda key: key not in problem.depots, problem.node_coords.keys())
+    ]
     tour.type = "TOUR"
     tour.name = problem.name + " solution"
 
 
-
-if (args.output_file is not None):
-    tour.save(args.output_file)
+if args.output_file is not None:
+    tour.save(args.output_file)

python/qubo_solver/README.md

@@ -1 +1 @@
-qubo-solver
+# Python QUBO Solver

python/qubo_solver/src/main.py

@@ -1,40 +1,41 @@
+import argparse
+import os
 from datetime import datetime
 from typing import Literal
-import os
-from dimod import BINARY, BinaryQuadraticModel
-import argparse
 
+from dimod import BINARY, BinaryQuadraticModel
 from solver import solve_with
 
 
 def main():
-
     parser = argparse.ArgumentParser(
-    prog='DWave QUBO solver',
-    description='A CLI Program to initiate solving COOrdinate files with DWave Systems',
-    epilog='Made by Lucas Berger for scientific purposes')
+        prog="DWave QUBO solver",
+        description="A CLI Program to initiate solving COOrdinate files with DWave Systems",
+        epilog="Made by Lucas Berger for scientific purposes",
+    )
 
+    parser.add_argument("coo_file")
+    parser.add_argument(
+        "type", default="sim", choices=["sim", "hybrid", "qbsolv", "direct"]
+    )
+    parser.add_argument("--output-file")
 
-    parser.add_argument('coo_file')
-    parser.add_argument('type', default='sim', choices=['sim', 'hybrid', 'qbsolv', 'direct'])
-    parser.add_argument('--output-file')
-
     args = parser.parse_args()
-    type: Literal['sim', 'hybrid', 'qbsolv', 'direct'] = args.type
+    type: Literal["sim", "hybrid", "qbsolv", "direct"] = args.type
 
     with open(args.coo_file) as problem:
         bqm = BinaryQuadraticModel.from_coo(problem, vartype=BINARY)
-        
+
         filename = os.path.basename(args.coo_file)
-        
+
         last = datetime.now().timestamp()
         print("started")
-        
+
         sampleset = solve_with(bqm, type, filename)
-        
+
         now = datetime.now().timestamp()
         print(f"ended after {now - last}")
-        
+
         if args.output_file:
             with open(args.output_file, "w") as out:
                 out.writelines([f"{bin}\n" for bin in sampleset.first.sample.values()])

python/qubo_solver/src/solver.py

@@ -1,28 +1,30 @@
 from typing import Literal
-from dimod import BinaryQuadraticModel, Sampler, SimulatedAnnealingSampler, SampleSet
+
+from dimod import BinaryQuadraticModel, Sampler, SampleSet, SimulatedAnnealingSampler
 from dwave.system import DWaveSampler, EmbeddingComposite, LeapHybridSampler
 from hybrid import SimplifiedQbsolv, State
 
-solvertype = Literal['sim', 'hybrid', 'qbsolv', 'direct']
+solvertype = Literal["sim", "hybrid", "qbsolv", "direct"]
+
 
 def solve_with(bqm: BinaryQuadraticModel, type: solvertype, label: str) -> SampleSet:
-
-    if type == 'sim':
+    if type == "sim":
         sampler: Sampler = SimulatedAnnealingSampler()
         return sampler.sample(bqm)
-    elif type == 'direct':
+    elif type == "direct":
         sampler: Sampler = EmbeddingComposite(DWaveSampler())
         return sampler.sample(
-            bqm, num_reads=250, label=f"DWaveSampler with embedding num_reads=250 {label}"
+            bqm,
+            num_reads=250,
+            label=f"DWaveSampler with embedding num_reads=250 {label}",
         )
-    elif type == 'hybrid':
+    elif type == "hybrid":
         sampler: Sampler = LeapHybridSampler()
         return sampler.sample(
             bqm, time_limit=10, label=f"LeapHybridSampler num_reads=250: {label}"
         )
-    elif type == 'qbsolv':
+    elif type == "qbsolv":
         init_state = State.from_problem(bqm)
         workflow = SimplifiedQbsolv()
         final_state = workflow.run(init_state).result()
         return final_state.samples
-

src/logic/clustering/cluster_tsp.rs

@@ -18,12 +18,12 @@ fn distance(a: &Vec<f64>, b: &Vec<f64>) -> Option<f64> {
 }
 
 impl ClusterTspClustering {
-    fn choose_core<'a>(&'a self, problem: &Tsp, rest: &'a Vec<usize>) -> Option<&usize> {
+    fn choose_core<'a>(&'a self, _problem: &Tsp, rest: &'a [usize]) -> Option<&usize> {
         rest.first()
     }
 
     fn center(&self, problem: &Tsp, cluster: &Vec<usize>) -> Vec<f64> {
-        if cluster.len() == 0 {
+        if cluster.is_empty() {
             return vec![
                 0.0f64;
                 problem
@@ -53,7 +53,7 @@ impl ClusterTspClustering {
             .collect()
     }
 
-    fn cluster_demand(&self, problem: &Tsp, cluster: &Vec<usize>) -> f64 {
+    fn cluster_demand(&self, problem: &Tsp, cluster: &[usize]) -> f64 {
         problem
             .demands()
             .iter()
@@ -84,9 +84,8 @@ impl ClusteringTrait for ClusterTspClustering {
         let mut assignments: Vec<Vec<usize>> = vec![];
 
         loop {
-            let core = match self.choose_core(problem, &not_assigned) {
-                Some(core) => core,
-                None => break,
+            if self.choose_core(problem, &not_assigned).is_none() {
+                break;
             };
 
             let mut cluster = vec![];
@@ -118,8 +117,7 @@ impl ClusteringTrait for ClusterTspClustering {
                     cluster.push(closest.id());
                     not_assigned = not_assigned
                         .iter()
-                        .filter(|id| **id != closest.id())
-                        .map(|id| *id)
+                        .filter_map(|id| if *id != closest.id() { Some(*id) } else { None })
                         .collect()
                 } else {
                     break 'inner;