Added diversity measures at the metapop level

metapypulation/metapopulation.py

@@ -10,7 +10,7 @@
 from typing import List
 
 from .individual import Individual
-from .subpopulation import Subpopulation
+from .subpopulation import Subpopulation, SetOfIndividuals
 
 class Metapopulation():
     def __init__(self, number_of_subpopulations: int, 
@@ -83,6 +83,13 @@ def migrate(self):
         for subpopulation in self.subpopulations:
             subpopulation.incorporate_migrants_in_population() 
 
+
+    def get_metapopulation_size(self) -> int:
+        population_size = 0
+        for subpopulation in self.subpopulations:
+            population_size += subpopulation.get_population_size()
+
+        return population_size
 
     def make_interact(self):
         """Function that starts interactions within each subpopulation.
@@ -91,20 +98,71 @@ def make_interact(self):
             subpopulation.create_interaction()
 
 
-    def metapopulation_shannon_diversity(self) -> List[float]:
+    def shannon_diversity_per_subpopulation(self) -> List[float]:
         subpopulation_shannons = []
         for subpopulation in self.subpopulations:
             subpopulation_shannons.append(subpopulation.shannon_diversity())
 
         return subpopulation_shannons
 
 
-    def metapopulation_count_traits_sets(self) -> List[int]:
+    def traits_sets_per_subpopulation(self) -> List[int]:
         subpopulation_counts = []
         for subpopulation in self.subpopulations:
             subpopulation_counts.append(subpopulation.count_traits_sets())
 
         return subpopulation_counts
+
+
+    def metapopulation_shannon_diversity(self) -> float:
+        """
+        This function counts the shannon diversity over the whole metapopulation. The function first
+        merges all subpopulations into one pot, then measures shannon diversity.
+        """
+        number_of_features = self.number_of_features
+        traits = np.zeros((self.get_metapopulation_size(), number_of_features))
+        i = 0
+        for subpopulation in self.subpopulations:
+            for individual in subpopulation.population:
+                traits[i] = (individual.features)
+                i += 1
+
+        shannons = []
+        # looping over all features, for each feature extract the frequency of each trait in the population
+        for k in range(0, number_of_features):
+            frequencies = []
+            feature_traits = traits[:, k]
+            unique, counts = np.unique(feature_traits, return_counts=True)
+            for trait_count in counts:
+                trait_frequency = trait_count / (self.get_metapopulation_size())
+                frequencies.append(trait_frequency)
+
+            frequencies = np.array(frequencies)
+            shannon_for_trait = -np.sum(frequencies*np.log(frequencies))
+
+            shannons.append(shannon_for_trait)
+
+        shannon_index = np.mean(shannons)
+
+        return shannon_index
+
+
+    def metapopulation_test_sets(self) -> int:
+        """
+        This function counts the total of unique sets of traits in the whole metapopulation. The function first
+        merges all subpopulations into one pot, then counts different sets.
+        """
+        number_of_features = self.number_of_features
+        traits = np.zeros((self.get_metapopulation_size(), number_of_features))
+        i = 0
+        for subpopulation in self.subpopulations:
+            for individual in subpopulation.population:
+                traits[i] = (individual.features)
+                i += 1
+
+        uniques = np.unique(traits, axis = 0)
+
+        return len(uniques)  
 
 
 class SubpopulationIterator(object):

metapypulation/subpopulation.py

@@ -83,7 +83,7 @@ def create_interaction(self) -> None:
 
     def count_traits_sets(self) -> int:
         """
-        This function counts the total of unique sets of traits in the population. For example,
+        This function counts the total of unique sets of traits in the subpopulation. For example,
         [0, 1, 2, 3, 4] is a set different from [1, 1, 2, 3, 4], which is different from [5, 4, 3, 2, 1], etc.    
         """
         number_of_features = self.population.individuals[0].number_of_features
@@ -100,7 +100,7 @@ def count_traits_sets(self) -> int:
 
     def shannon_diversity(self) -> float:
         """
-        Shannon_diversity is measure of the richness / diversity in a patch. The formula is
+        Shannon_diversity is measure of the richness / diversity in a subpopulation. The formula is
         H' = -sum(p_i * ln(p_i))
     
         where p_i is the frequency of each species i in the whole sample. The "species" are each trait separately,

script.py

@@ -16,12 +16,16 @@
 
 shannon = []
 set_counts = []
+metapop_counts = []
+metapop_shannon = []
 
 start_time = time.time()
-for t in range(300001):
+for t in range(200001):
     if t%100 == 0:
-        set_counts.append(metapop.metapopulation_count_traits_sets())
-        shannon.append(metapop.metapopulation_shannon_diversity())
+        set_counts.append(metapop.traits_sets_per_subpopulation())
+        shannon.append(metapop.shannon_diversity_per_subpopulation())
+        metapop_counts.append(metapop.metapopulation_test_sets())
+        metapop_shannon.append(metapop.metapopulation_shannon_diversity())
     if t%50000 == 0:
         print(f"Gen {t}!")
         for subpopulation in metapop.subpopulations:
@@ -42,8 +46,7 @@
 
 print(f"{t} generations ran in {total_time}.")
 
-counts_df = pd.DataFrame(set_counts)
-counts_df.to_csv('./Outputs/island.csv', index=False)
+# counts_df = pd.DataFrame(set_counts)
 # print(counts_df)
-# counts_df.plot()
-# plt.show()
+plt.plot(metapop_shannon)
+plt.show()