Better non-threading version

__main__.py

@@ -1,10 +1,13 @@
 import numpy as np
 import threading
+import queue
+import time
 
 INPUT_FILE = "data/medium.in"
-POPULATION = 1000
+POPULATION = 50
-MUTATION_AMOUNT = 250
+MUTATION_AMOUNT = 1000
 ITERATIONS = 30
+THREAD_COUNT = 20
 
 data = [line for line in open(INPUT_FILE)]
 params = list(map(int, data[0].split(" ")))
@@ -19,53 +22,6 @@ print(clusters[0])
 values = {}
 first = True
 
-class myThread (threading.Thread):
-    def __init__(self, cluster, clean, id):
-        threading.Thread.__init__(self)
-        self.cluster = cluster
-        self.clean = clean
-        self.id = id
-        self.result = None
-        self.first = False
-        self.values = {}
-        self.vfunc = np.vectorize(self.myfunc)
-
-    def run(self):
-        # calc fitness
-        self.values = {}
-        self.first = True
-        self.vfunc(self.cluster, data)
-        self.result = get_fitness(self.values, clean=self.clean)
-        print("Exit thread", self.id)
-
-    def myfunc(self, a, b):
-        if self.first:
-            self.first = False
-            return
-        if a not in values:
-            self.values[a] = [0, 0]
-            self.values[a][b] += 1
-
-
-def get_fitnesses(clusts, clean=False):
-    threads = []
-    for i, cluster in enumerate(clusters):
-        if i % 20 == 0:
-            print("fitness", i, iteration)
-        # Create new threads
-        thread = myThread(cluster, clean, i)
-        # Start new Threads
-        thread.start()
-
-        # Add threads to thread list
-        threads.append(thread)
-
-    # Wait for all threads to complete
-    for t in threads:
-        t.join()
-    print("Exiting Main Thread")
-    return np.array([thread.result for thread in threads])
-
 def get_fitness(vals, clean=False):
     fit = 0
     for key, val in vals.items():
@@ -180,16 +136,12 @@ def myfunc(a, b):
 vfunc = np.vectorize(myfunc)
 
 # mutation
-xx = MUTATION_AMOUNT
 for i in range(POPULATION):
     if i % 20 == 0:
         print("mutation", i)
-    MUTATION_AMOUNT = 500
     clusters[i] = mutation(clusters[i])
-MUTATION_AMOUNT = xx
 
 for iteration in range(ITERATIONS):
-    fitnesses = get_fitnesses(clusters, clean=False)
     # calc fitness
     fitnesses = np.zeros((POPULATION, ))
     for i, cluster in enumerate(clusters):