From b77b0845015c69c76678b23365656c0723c99880 Mon Sep 17 00:00:00 2001 From: Matteo Tomasini Date: Thu, 11 Jul 2024 08:34:09 +0200 Subject: [PATCH] Added diversity measures at the metapop level --- exploration.ipynb | 23 ++++-------- metapypulation/metapopulation.py | 64 ++++++++++++++++++++++++++++++-- metapypulation/subpopulation.py | 4 +- script.py | 17 +++++---- 4 files changed, 81 insertions(+), 27 deletions(-) diff --git a/exploration.ipynb b/exploration.ipynb index f9663f7..253a6f7 100644 --- a/exploration.ipynb +++ b/exploration.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -185,7 +185,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -198,22 +198,22 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "Text(0.5, 0, 'Generations (x 1000)')" ] }, - "execution_count": 34, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -226,16 +226,9 @@ "df_SS[\"means\"].plot()\n", "df_IM[\"means\"].plot()\n", "plt.legend([\"stepping stone\", \"island\"])\n", - "plt.ylab(\"Different sets of traits\")\n", - "plt.xlab(\"Generations (x 1000)\")" + "plt.ylabel(\"Different sets of traits\")\n", + "plt.xlabel(\"Generations (x 1000)\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/metapypulation/metapopulation.py b/metapypulation/metapopulation.py index 439e4ab..0c7b838 100644 --- a/metapypulation/metapopulation.py +++ b/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. @@ -91,7 +98,7 @@ 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()) @@ -99,12 +106,63 @@ def metapopulation_shannon_diversity(self) -> List[float]: 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): diff --git a/metapypulation/subpopulation.py b/metapypulation/subpopulation.py index 49e0259..dfaab1f 100644 --- a/metapypulation/subpopulation.py +++ b/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, diff --git a/script.py b/script.py index e35aaa7..8d5b6ad 100644 --- a/script.py +++ b/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() \ No newline at end of file +plt.plot(metapop_shannon) +plt.show() \ No newline at end of file