import os
import json
import time
import pickle
import sys
import matplotlib.pyplot as plt
from binarycpython.utils.grid import Population
from binarycpython.utils.functions import get_help_all, get_help
## Script is intended for some testing of grid functionality. Its a bit random, not really structured tbh
test_pop = Population()
## Setting values
# print(test_pop.bse_options['M_1'])
# print(test_pop.bse_options['M_2'])
# test_pop.set(M_1=10, M_2=500)
# print(test_pop.bse_options['M_1'])
# print(test_pop.bse_options['M_2'])
test_pop.set(
M_1=10,
separation=0,
orbital_period=4580,
max_evolution_time=15000,
eccentricity=0.02,
)
# print(test_pop.bse_options)
## Testing single evolution
# test_pop.evolve_single()
# test_pop.test_evolve_single()
## Setting custom value
# test_pop.set(data_dir=os.path.join(os.environ['BINARYC_DATA_ROOT'], 'development_example'))
# print(test_pop.custom_options['data_dir'])
## printing all options
# print(json.dumps(test_pop.return_population_settings(), indent=4))
## return arglines:
# test_pop.set(M_1=10, M_2=500)
# print(test_pop.return_argline())
# test_pop.return_argline()
## return version info
# version_info = test_pop.return_binary_c_version_info()
# print(version_info)
## Use custom arg file
# test_pop.evolve_population(custom_arg_file='/home/david/projects/binary_c_root/binary_c-python/tests/population/custom_arg_file.txt')
## Custom logging:
# test_pop.set(C_auto_logging={'MY_HEADER_LINE': ['star[0].mass', 'star[1].mass', 'model.probability']})
# test_pop.set(C_logging_code='Printf("MY_STELLAR_DATA time=%g mass=%g radius=%g\\n", stardata->model.time, stardata->star[0].mass, stardata->star[0].radius);')
# test_pop.evolve_population()
## Custom logging with bigger print statement:
test_pop.set(M_1=100, M_2=1, metallicity=0.0002, orbital_period=500000000)
test_pop.set(
C_logging_code="""
if(stardata->star[0].stellar_type>=MS)
{
if (stardata->model.time < stardata->model.max_evolution_time)
{
Printf("DAVID_SCO %30.12e %g %g %g %g %d %d\\n",
//
stardata->model.time, // 1
stardata->star[0].mass, //2
stardata->previous_stardata->star[0].mass, //3
stardata->star[0].radius, //4
stardata->previous_stardata->star[0].radius, //5
stardata->star[0].stellar_type, //6
stardata->previous_stardata->star[0].stellar_type //7
);
};
/* Kill the simulation to save time */
// stardata->model.max_evolution_time = stardata->model.time - stardata->model.dtm;
};
"""
)
# test_pop.evolve_population()
## Help all
# print(get_help_all(return_dict=True))
# get_help_all()
# print(get_help('M_1', print_help=False, return_dict=True))
## return all info:
# print(json.dumps(test_pop.return_all_info(), indent=4))
# test_pop.export_all_info(outfile=os.path.join(os.getcwd(), "test_output.txt"))
################# Parse function
## Testing some stuff out with giving a parse_function.
test_pop.set(
C_logging_code="""
if(stardata->star[0].stellar_type>=NS)
{
if (stardata->model.time < stardata->model.max_evolution_time)
{
Printf("DAVID_SCO %30.12e %g %g %g %g %d %d\\n",
//
stardata->model.time, // 1
stardata->star[0].mass, //2
stardata->previous_stardata->star[0].mass, //3
stardata->star[0].radius, //4
stardata->previous_stardata->star[0].radius, //5
stardata->star[0].stellar_type, //6
stardata->previous_stardata->star[0].stellar_type //7
);
};
/* Kill the simulation to save time */
stardata->model.max_evolution_time = stardata->model.time - stardata->model.dtm;
};
"""
)
def output_lines(output):
"""
Function that outputs the lines that were recieved from the binary_c run.
"""
return output.splitlines()
def parse_function(self, output):
# extract info from the population instance
# TODO: think about whether this is smart. Passing around this object might be an overkill
# Get some information from the
data_dir = self.custom_options['data_dir']
base_filename = self.custom_options['base_filename']
outfilename = os.path.join(data_dir, base_filename)
# TODO: make population settings available in this function
for el in output_lines(output):
headerline = el.split()[0]
if (headerline=='DAVID_SCO'):
parameters = ['time', 'mass_1', 'prev_mass_1', 'radius_1', 'prev_radius_1', 'stellar_type_1', 'prev_stellar_type_1']
values = el.split()[1:]
seperator='\t'
if not os.path.exists(outfilename):
with open(outfilename, 'w') as f:
f.write(seperator.join(parameters)+'\n')
with open(outfilename, 'a') as f:
f.write(seperator.join(values)+'\n')
#test_pop.evolve_single(parse_function)
test_pop.set(M_1=90, data_dir=os.path.join(os.environ['BINARYC_DATA_ROOT'], 'testing_python'), base_filename='test_pop.dat')
test_pop.evolve_single(parse_function)
test_pop.set(M_1=80)
test_pop.evolve_single(parse_function)
test_pop.set(M_1=70)
test_pop.evolve_single(parse_function)
test_pop.set(M_1=60)
test_pop.evolve_single(parse_function)
##################
## CHeck size of commands:
## Using pickle to dump it.
## https://stackoverflow.com/questions/563840/how-can-i-check-the-memory-usage-of-objects-in-ipython/565382#565382
# def generate_commands_return_size(amt_systems):
# print("Doing {} systems".format(amt_systems))
# start_generate_time = time.time()
# commands = [test_pop.return_argline() for el in range(amt_systems)]
# stop_generate_time = time.time()
# size = sys.getsizeof(pickle.dumps(commands))
# size_in_mb = size/(1024*1024)
# return size_in_mb
# amounts = [1, 10, 100, 1000, 10000, 100000, 1000000, 10000000]
# sizes = []
# for amount in amounts:
# sizes.append(generate_commands_return_size(amount))
# plt.title('size scaling for binary_c commands with:\n`{}`'.format(test_pop.return_argline()))
# plt.plot(amounts, sizes, 'bo', label='MB for ')
# plt.legend()
# plt.xlabel("Amount of systems")
# plt.ylabel("Size in MB")
# plt.xscale('log')
# plt.yscale('log')
# plt.savefig('sizes_for_commands.png')
# plt.show()