Issue 15 fixation (#21)

* #15 tochuu

* approaching #15

* fixation simulation #15

* repeat simulation #15

* #15 solving

* fighting #15

* modified #15

* modifying #15

* Create class Repeat-moran

* Create class Repeat-moran

* solved #15

* delete function of repeat

* Reduce code redundancy

hamazaki1990/individual.py

@@ -13,10 +13,15 @@ def __repr__(self):
         return str(self._id)
 
 
-ind = Individual(42)
-print(ind.get_id())
-print(ind.get_fitness())
+def main():
+    ind = Individual(42)
+    print(ind.get_id())
+    print(ind.get_fitness())
 
-ind2 = Individual(30, 0.8)
-print(ind2.get_id())
-print(ind2.get_fitness())
+    ind2 = Individual(30, 0.8)
+    print(ind2.get_id())
+    print(ind2.get_fitness())
+
+
+if __name__ == '__main__':
+    main()

hamazaki1990/main.py

@@ -1,5 +1,61 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-"""main script
-"""
-print('Hello, world!')
+from population import Population
+
+
+def calculate_ave(seq):
+    return sum(seq)/len(seq)
+
+
+def calculate_var(seq):
+    ave = calculate_ave(seq)
+    sqd = [(seq[x] - ave)**2 for x in range(len(seq))]
+    return sum(sqd)/len(seq)
+
+
+def simulate_fixwf(Population):  # simulate fixation in Wrigft-Fisher model
+    time = 0
+    while Population.is_not_fixed():
+        Population.next_genwf()
+        time += 1
+    return time, Population._inds[0].get_id()
+
+
+def simulate_fixmo(Population):   # simulate fixation in Moran model
+    time = 0
+    while Population.is_not_fixed():
+        Population.next_genmo()
+        time += 1
+    return time, Population._inds[0].get_id()
+
+
+class Repeater:
+    def __init__(self, function, repeat, n, mutantrate=0, s=0):
+        result = []
+        for x in range(repeat):
+            population = Population(n, mutantrate, s)
+            result.append(function(population))
+        self._fixtime = [result[x][0] for x in range(len(result))]
+        fixid = [result[x][1] for x in range(len(result))]
+        wins = [0 for i in range(n)]
+        for x in fixid:
+            wins[x] += 1
+        self._fixprob = {i: wins[i]/repeat for i in range(n)}
+
+    def get_fixtime(self):
+        return self._fixtime
+
+    def get_fixprob(self):
+        return self._fixprob
+
+
+trial1 = Repeater(simulate_fixwf, 1000, 10, 0.1, -0.05)
+print(calculate_ave(trial1.get_fixtime()))
+print(calculate_var(trial1.get_fixtime()))
+print(trial1.get_fixprob())
+
+
+trial2 = Repeater(simulate_fixmo, 1000, 10, 0.1, -0.05)
+print(calculate_ave(trial2.get_fixtime()))
+print(calculate_var(trial2.get_fixtime()))
+print(trial2.get_fixprob())

hamazaki1990/population.py

@@ -39,40 +39,53 @@ def next_genmo(self):
         i_dying = random.randrange(size)
         self._inds[i_dying] = roulettechoice(self._inds, cumsum_fitness)
 
+    def is_not_fixed(self):
+        for x in range(1, len(self._inds)):
+            if self._inds[0] != self._inds[x]:
+                return True
+        else:
+            return False
 
-p1_1 = Population(10)
-p1_1.print_ids()
-p1_1.print_fitness()
 
-for x in range(20):
-    p1_1.next_genwf()
+def main():
+    p1_1 = Population(10)
     p1_1.print_ids()
-p1_1.print_fitness()
+    p1_1.print_fitness()
+    print(p1_1.is_not_fixed())
 
-p1_2 = Population(10, 0.3, 0.2)
-p1_2.print_ids()
-p1_2.print_fitness()
+    for x in range(20):
+        p1_1.next_genwf()
+        p1_1.print_ids()
+        p1_1.print_fitness()
+    print(p1_1.is_not_fixed())
 
-for x in range(20):
-    p1_2.next_genwf()
+    p1_2 = Population(10, 0.3, 0.2)
     p1_2.print_ids()
-p1_2.print_fitness()
+    p1_2.print_fitness()
 
+    for x in range(20):
+        p1_2.next_genwf()
+        p1_2.print_ids()
+    p1_2.print_fitness()
 
-p2_1 = Population(10)
-p2_1.print_ids()
-p2_1.print_fitness()
-
-for x in range(20):
-    p2_1.next_genmo()
+    p2_1 = Population(10)
     p2_1.print_ids()
-p2_1.print_fitness()
+    p2_1.print_fitness()
 
-p2_2 = Population(10, 0.3, 0.2)
-p2_2.print_ids()
-p2_2.print_fitness()
+    for x in range(20):
+        p2_1.next_genmo()
+        p2_1.print_ids()
+        p2_1.print_fitness()
 
-for x in range(20):
-    p2_2.next_genmo()
+    p2_2 = Population(10, 0.3, 0.2)
     p2_2.print_ids()
-p2_2.print_fitness()
+    p2_2.print_fitness()
+
+    for x in range(20):
+        p2_2.next_genmo()
+        p2_2.print_ids()
+    p2_2.print_fitness()
+
+
+if __name__ == '__main__':
+    main()