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Merge pull request #80 from clarencecastillo/master
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Fixed unpredictable exec lines in database_calls when run on py3 and optimised file writing in analytics
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@mauriceling
mauriceling committed Oct 10, 2015
2 parents ac3e4ab + dfe88f3 commit d211679
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Showing 2 changed files with 56 additions and 49 deletions.
57 changes: 34 additions & 23 deletions dose/analytics.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -112,27 +112,28 @@ def analyze_individual_status_by_generation(self, csv_output, status,
aggregate_functions = None,
generations = 'all'):
print('\n[INDIVIDUAL ' + status.upper() + ' STATUS ANALYSIS]')
print('Opening outputfile: ' + csv_output + '...')
outputfile = open(csv_output, 'w')
print('Getting population size...')
pop_size = \
database_calls.db_reconstruct_simulation_parameters(self.cur,
self.starting_time)['population_size']
print('Constructing generations list...')
if generations == 'all':
generation_list = database_calls.db_list_generations(self.cur,
self.starting_time)
else:
generation_list = [str(gen) for gen in generations]
print('Preparing outputfile: ' + csv_output + '...')
outputfile = open(csv_output, 'w')
print('Writing outputfile header...')
header = ['Generation'] + [str(i) for i in range(1, pop_size + 1)]
if aggregate_functions != None:
header = header + \
[key for key in list(aggregate_functions.keys())]
outputfile.write(','.join(header) + '\n')
outputfile.close()
print('Starting main analysis...')
if generations == 'all':
generation_list = database_calls.db_list_generations(self.cur,
self.starting_time)
else:
generation_list = [str(gen) for gen in generations]
for generation in generation_list:
print('Analyzing generation ' + str(generation) + '...')
print()
status_list = \
[status_analysis(stat)
for stat in self.get_individual_status_list_by_generation(status, generation)]
Expand All @@ -141,22 +142,25 @@ def analyze_individual_status_by_generation(self, csv_output, status,
if aggregate_functions != None:
for key in list(aggregate_functions.keys()):
status_row.append(str(aggregate_functions[key](status_list)))
outputfile = open(csv_output, 'a')
outputfile.write(','.join(status_row) + '\n')
outputfile.close()

print('\nIndividual [' + status + '] analysis complete!')

def analyze_status_group_count_by_generation(self, csv_output, status,
stats,
aggregate_functions = None,
generations = 'all'):
print('\n[' + status.upper() + ' STATUS GROUP COUNT ANALYSIS]')
print('Opening outputfile: ' + csv_output + '...')
outputfile = open(csv_output, 'w')
print('Constructing generations list...')
if generations == 'all':
generation_list = database_calls.db_list_generations(self.cur,
self.starting_time)
else:
generation_list = generations
print('Preparing outputfile: ' + csv_output + '...')
outputfile = open(csv_output, 'w')
print('Writing outputfile header...')
header = [str(stat).replace(", ","-") for stat in stats]
if aggregate_functions == None:
Expand All @@ -165,10 +169,10 @@ def analyze_status_group_count_by_generation(self, csv_output, status,
header = ['Generation'] + header + \
[key for key in list(aggregate_functions.keys())]
outputfile.write(','.join(header) + '\n')
outputfile.close()
print('Starting main analysis...')
for generation in generation_list:
print('Analyzing generation ' + str(generation) + '...')
print()
status_list = \
self.get_individual_status_list_by_generation(status,
generation)
Expand All @@ -178,31 +182,34 @@ def analyze_status_group_count_by_generation(self, csv_output, status,
if aggregate_functions != None:
for key in list(aggregate_functions.keys()):
status_row.append(str(aggregate_functions[key]([status_list.count(target_stat) for target_stat in stats])))
outputfile.write(','.join(status_row) + '\n')
outputfile = open(csv_output, 'a')
outputfile.write(','.join(status_row) + '\n')
outputfile.close()
print('\nGrouped [' + status + '] count analysis complete!')

def analyze_individual_genomes_by_generation(self, csv_output,
genome_analysis,
aggregate_functions = None,
generations = 'all'):
print('\n[INDIVIDUAL GENOME ANALYSIS]')
print('Opening outputfile: ' + csv_output + '...')
outputfile = open(csv_output, 'w')
print('Getting population size...')
pop_size = database_calls.db_reconstruct_simulation_parameters(self.cur, self.starting_time)['population_size']
print('Constructing generations list...')
if generations == 'all':
generation_list = database_calls.db_list_generations(self.cur, self.starting_time)
else:
generation_list = generations
print('Preparing outputfile: ' + csv_output + '...')
outputfile = open(csv_output, 'w')
print('Writing outputfile header...')
header = ['Generation'] + [str(i) for i in range(1, pop_size + 1)]
if aggregate_functions != None:
header = header + [key for key in list(aggregate_functions.keys())]
outputfile.write(','.join(header) + '\n')
outputfile.close()
print('Starting main analysis...')
if generations == 'all':
generation_list = database_calls.db_list_generations(self.cur, self.starting_time)
else:
generation_list = generations
for generation in generation_list:
print('Analyzing generation ' + str(generation) + '...')
print()
genome_list = [genome_analysis(genome)
for genome in self.get_individual_genome_list_by_generation(generation)]
status_row = [str(generation)] + \
Expand All @@ -211,7 +218,9 @@ def analyze_individual_genomes_by_generation(self, csv_output,
if aggregate_functions != None:
for key in list(aggregate_functions.keys()):
status_row.append(str(aggregate_functions[key](genome_list)))
outputfile = open(csv_output, 'a')
outputfile.write(','.join(status_row) + '\n')
outputfile.close()
print('\nIndividual genome analysis complete!')

def analyze_status_group_genome_by_generation(self, csv_output,
Expand All @@ -220,13 +229,13 @@ def analyze_status_group_genome_by_generation(self, csv_output,
aggregate_functions = None,
generations = 'all'):
print('\n[' + status.upper() + ' STATUS GROUP GENOME ANALYSIS]')
print('Opening outputfile: ' + csv_output + '...')
outputfile = open(csv_output, 'w')
print('Constructing generations list...')
if generations == 'all':
generation_list = database_calls.db_list_generations(self.cur, self.starting_time)
else:
generation_list = generations
print('Preparing outputfile: ' + csv_output + '...')
outputfile = open(csv_output, 'w')
print('Writing outputfile header...')
header = [str(stat).replace(", ","-") for stat in stats]
if aggregate_functions == None:
Expand All @@ -235,10 +244,10 @@ def analyze_status_group_genome_by_generation(self, csv_output,
header = ['Generation'] + header + \
[key for key in list(aggregate_functions.keys())]
outputfile.write(','.join(header) + '\n')
outputfile.close()
print('Starting main analysis...')
for generation in generation_list:
print('Analyzing generation ' + str(generation) + '...')
print()
analyzed_genome_list = \
[genome_analysis(self.get_status_group_genome_by_generation(status,
target_status, generation))
Expand All @@ -249,5 +258,7 @@ def analyze_status_group_genome_by_generation(self, csv_output,
if aggregate_functions != None:
for key in list(aggregate_functions.keys()):
status_row.append(str(aggregate_functions[key](analyzed_genome_list)))
outputfile.write(','.join(status_row) + '\n')
outputfile = open(csv_output, 'a')
outputfile.write(','.join(status_row) + '\n')
outputfile.close()
print('\nGrouped [' + status + '] genome analysis complete!')
48 changes: 22 additions & 26 deletions dose/database_calls.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
Date created: 10th October 2013
'''
import os, copy
import os, copy, ast
import sqlite3 as s

def connect_database(dbpath, sim_parameters=None):
Expand Down Expand Up @@ -434,15 +434,13 @@ def db_reconstruct_simulation_parameters(cur, start_time):
start_time = '%s'" % start_time)
for r in cur.fetchall():
if str(r[0]) == 'population_names':
value = str(r[1]).split('|')
exec("parameters['population_names'] = %s" % str(value))
parameters['population_names'] = str(r[1]).split('|')
elif str(r[0]) == 'population_locations':
exec("parameters['population_locations'] = %s" % str(r[1]))
parameters['population_locations'] = r[1]
elif str(r[0]) == 'deployment_code':
parameters['deployment_code'] = int(r[1])
elif str(r[0]) == 'chromosome_bases':
value = str(r[1]).split('|')
exec("parameters['chromosome_bases'] = %s" % str(value))
parameters['chromosome_bases'] = str(r[1]).split('|')
elif str(r[0]) == 'background_mutation':
parameters['background_mutation'] = float(r[1])
elif str(r[0]) == 'additional_mutation':
Expand All @@ -456,9 +454,9 @@ def db_reconstruct_simulation_parameters(cur, start_time):
elif str(r[0]) == 'max_tape_length':
parameters['max_tape_length'] = int(r[1])
elif str(r[0]) == 'clean_cell':
exec("parameters['clean_cell'] = %s" % str(r[1]))
parameters['clean_cell'] = r[1]
elif str(r[0]) == 'interpret_chromosome':
exec("parameters['interpret_chromosome'] = %s" % str(r[1]))
parameters['interpret_chromosome'] = r[1]
elif str(r[0]) == 'max_codon':
parameters['max_codon'] = int(r[1])
elif str(r[0]) == 'population_size':
Expand All @@ -473,7 +471,7 @@ def db_reconstruct_simulation_parameters(cur, start_time):
parameters['world_z'] = int(r[1])
elif str(r[0]) == 'goal':
try: parameters['goal'] = float(r[1])
except ValueError: exec("parameters['goal'] = %s" % str(r[1]))
except: parameters['goal'] = r[1]
elif str(r[0]) == 'maximum_generations':
parameters['maximum_generations'] = int(r[1])
elif str(r[0]) == 'fossilized_ratio':
Expand All @@ -487,8 +485,7 @@ def db_reconstruct_simulation_parameters(cur, start_time):
if version == '0.1': parameters['ragaraja_version'] = 0.1
else: parameters['ragaraja_version'] = int(r[1])
elif str(r[0]) == 'ragaraja_instructions':
value = str(r[1]).split('|')
exec("parameters['ragaraja_instructions'] = %s" % str(value))
parameters['ragaraja_instructions'] = str(r[1]).split('|')
elif str(r[0]) == 'eco_buried_frequency':
parameters['eco_buried_frequency'] = int(r[1])
elif str(r[0]) == 'database_file':
Expand Down Expand Up @@ -540,7 +537,7 @@ def db_reconstruct_world(cur, start_time, generation):
z = int(r[2])
key = str(r[3])
value = str(r[4])
exec("ecosystem[%i][%i][%i]['%s'] = %s" % (x, y, z, key, value))
ecosystem[x][y][z][key] = value
World = dose_world.World(1, 1, 1)
World.ecosystem = ecosystem
return World
Expand Down Expand Up @@ -584,36 +581,33 @@ def db_reconstruct_organisms(cur, start_time, population_name, generation):
key = str(r[0])
value = str(r[1])
if key == 'alive':
exec("org.status['alive'] = %s" % str(value))
org.status['alive'] = value
elif key == 'vitality':
org.status['vitality'] = float(value)
elif key == 'parents':
if value == '': value = '[]'
else: value = value.split('|')
exec("org.status['parents'] = %s" % str(value))
org.status['parents'] = value
elif key == 'age':
org.status['age'] = float(value)
elif key == 'gender':
exec("org.status['gender'] = %s" % str(value))
org.status['gender'] = value
elif key == 'lifespan':
org.status['lifespan'] = float(value)
elif key == 'fitness':
exec("f = '%s'" % str(value))
if type(f) == type(1) or type(f) == type(1.0):
org.status['fitness'] = float(value)
else:
exec("org.status['fitness'] = %s" % str(value))
try: org.status['fitness'] = ast.literal_eval(value)
except: org.status['fitness'] = value
elif key == 'blood':
if value == '': value = '[]'
else: value = value.split('|')
exec("org.status['blood'] = %s" % str(value))
org.status['blood'] = value
elif key == 'deme':
org.status['deme'] = str(value)
elif key == 'location':
value = tuple([int(x) for x in value.split('|')])
exec("org.status['location'] = %s" % str(value))
org.status['location'] = value
elif key == 'death':
exec("org.status['death'] = %s" % str(value))
org.status['death'] = value
elif key.startswith('chromosome'):
chr_position = key.split('_')[1]
sequence = [str(x) for x in str(value)]
Expand All @@ -625,12 +619,13 @@ def db_reconstruct_organisms(cur, start_time, population_name, generation):
key='chromosome_bases' and start_time='%s'" %
start_time)
bases = str(cur.fetchone()[0]).split('|')
exec("chromosome_bases = %s" % bases)
chromosome_bases = bases
chromosome = g.Chromosome(sequence, chromosome_bases,
background_mutation)
org.genome.append(chromosome)
else:
exec("org.status['%s'] = %s" % (str(key), str(value)))
try: org.status[key] = ast.literal_eval(value)
except: org.status[key] = value
agents[i] = org
return agents

Expand All @@ -653,7 +648,8 @@ def db_reconstruct_population(cur, start_time,
cur.execute("select value from parameters where \
key='goal' and start_time='%s'" % start_time)
g = cur.fetchone()[0]

try: goal = float(g)
except ValueError: exec("goal = %s" % str(g))
except: goal = str(g)
return genetic.Population(goal, 1e24, agents)

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