def calc_average_distance(genomes):
genetic_distance_list = []
for genome in genomes:
chromosome = genome[0].sequence
random_chromosome = random.choice(genomes)[0].sequence
genetic_distance_list.append(analytics.hamming_distance(random_chromosome, chromosome))
return analytics.average(genetic_distance_list)
def calc_average_distance(genomes):
genetic_distance_list = []
for genome in genomes:
chromosome = genome[0].sequence
random_chromosome = random.choice(genomes)[0].sequence
genetic_distance_list.append(
analytics.hamming_distance(random_chromosome, chromosome))
return analytics.average(genetic_distance_list)
organisms = database_calls.db_reconstruct_organisms(cur, starting_time, pop_name, generation)
organism_chromosomes = {}
for location in locations:
organism_chromosomes[location] = []
for organism in organisms:
if organism.status['location'] == location:
organism_chromosomes[location].append(organism.genome[0].sequence)
return organism_chromosomes
print('Writing outputfile header...')
header = [str(locations[i]).replace(", ","-") for i in range(len(locations))]
header = ['Generation'] + header
outputfile.write(','.join(header) + '\n')
print('Starting main analysis...\n')
for generation in range(1, 1001):
print('\rInitializing generation ' + str(generation) + '...')
chromo_db = get_chromosomes_by_location(starting_time, 'pop_01', generation)
result = [str(generation)]
for location in locations:
print('\rAnalyzing location: ' + str(location) + '...')
genetic_distance_list = []
for chromosome in chromo_db[location]:
random_chromosome = random.choice(chromo_db[location])
genetic_distance_list.append(analytics.hamming_distance(random_chromosome, chromosome))
average_distance = float(sum(genetic_distance_list))/len(genetic_distance_list)
result.append(str(average_distance))
outputfile.write(','.join(result) + '\n')
print('\rGeneration ' + str(generation) + ' analysis complete...')
print('\nAnalysis complete!')
if organism.status['location'] == location:
organism_chromosomes[location].append(
organism.genome[0].sequence)
return organism_chromosomes
print('Writing outputfile header...')
header = [str(locations[i]).replace(", ", "-") for i in range(len(locations))]
header = ['Generation'] + header
outputfile.write(','.join(header) + '\n')
print('Starting main analysis...\n')
for generation in range(1, 1001):
print('\rInitializing generation ' + str(generation) + '...')
chromo_db = get_chromosomes_by_location(starting_time, 'pop_01',
generation)
result = [str(generation)]
for location in locations:
print('\rAnalyzing location: ' + str(location) + '...')
genetic_distance_list = []
for chromosome in chromo_db[location]:
random_chromosome = random.choice(chromo_db[location])
genetic_distance_list.append(
analytics.hamming_distance(random_chromosome, chromosome))
average_distance = float(
sum(genetic_distance_list)) / len(genetic_distance_list)
result.append(str(average_distance))
outputfile.write(','.join(result) + '\n')
print('\rGeneration ' + str(generation) + ' analysis complete...')
print('\nAnalysis complete!')
def get_chromosomes_by_location(starting_time, pop_name, generation):
organisms = database_calls.db_reconstruct_organisms(cur, starting_time, pop_name, generation)
organism_chromosomes = {}
for location in locations:
organism_chromosomes[location] = []
for organism in organisms:
if organism.status['location'] == location:
organism_chromosomes[location].append(organism.genome[0].sequence)
return organism_chromosomes
print('Starting main analysis...\n')
for generation in [1, 100, 200, 300, 400,500, 600, 700, 800, 900, 1000]:
print('\rInitializing generation ' + str(generation) + '...')
chromo_db = get_chromosomes_by_location(starting_time, 'pop_01', generation)
results = [str(generation)]
for location1 in locations:
for location2 in locations:
location_results = []
if location1 != location2:
print('\rAnalyzing ' + str(location1) + ' and ' + str(location2) + '...')
for organism1 in chromo_db[location1]:
organism_results = []
for organism2 in chromo_db[location2]:
organism_results.append(analytics.hamming_distance(organism1, organism2))
location_results.append(analytics.average(organism_results))
results.append(str(analytics.average(location_results)))
outputfile.write(','.join(results) + '\n')
print('\rGeneration ' + str(generation) + ' analysis complete...')
print('Simulation Anaysis Complete!')