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ark_idealized_dwarfs_sample
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Tue, Apr 8, 03:34

ark_idealized_dwarfs_sample
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#!/usr/bin/env python3
import argparse
import numpy as np
import os
####################################################################
# option parser
####################################################################
description="""generate a set of idealized dwarf galaxies in the hdf5 mockimg format
"""
epilog ="""
Examples:
--------
ark_idealized_dwarfs_sample --output_directory ../dwarfs -N 50
"""
parser = argparse.ArgumentParser(description=description,epilog=epilog,formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('--output_directory',
dest="output_directory",
type=str,
default='idealized_dwarfs',
help='output directory')
parser.add_argument('--dry-run',
dest="dryrun",
action='store_true',
default=False,
help='dry-run mode')
parser.add_argument('--flat-sfr',
dest="flatsfr",
action='store_true',
default=False,
help='consider a flat sfr')
parser.add_argument('-N',
dest="N",
type=int,
default=10,
help='number of dwarfs')
class Sampler():
def __init__(self):
pass
def sample(self,mass):
mean = np.interp(mass,self.mass,self.mean)
std = np.interp(mass,self.mass,self.std )
return np.random.normal(mean,std,len(mass))
class FeH_Sampler(Sampler):
def __init__(self):
self.mass = np.array([5,6,7,8,9])
self.mean = np.array([-2.2,-1.9,-1.5,-1.1,-0.5])
self.std = np.array([1.0,1.0,1.0,1.0,1.0])*0.2
class R12_Sampler(Sampler):
def __init__(self):
self.mass = np.array([5,6,7,8,9])
self.mean = np.log10(np.array([0.3,0.476,0.75,1.,1.5]))
self.std = np.array([0.2,0.2,0.2,0.2,0.2])
class Age_Sampler(Sampler):
def __init__(self):
self.mass = np.array([5,6.7,8.7])
self.mean = np.array([1,3,6])
self.std = np.array([0.2,0.5,1.0])
####################################################################
# main
####################################################################
opt = parser.parse_args()
# generate a set of masses (in log10)
masses = np.random.uniform(5,9,opt.N)
# Sample FeH
FeH = FeH_Sampler()
fes = FeH.sample(masses)
# Sample R12
R12 = R12_Sampler()
r12s = 10**R12.sample(masses)
# Sample Ages
Age = Age_Sampler()
ages = Age.sample(masses)
#from matplotlib import pylab as plt
#plt.scatter(masses,r12s)
#plt.loglog()
#plt.show()
#exit()
if not os.path.exists(opt.output_directory):
os.makedirs(opt.output_directory)
for i in range(opt.N):
M0 = 10**masses[i]
age = ages[i]
e = r12s[i]
Fe = fes[i]
output_filename = 'M0_{0:10.4e}_e_{1:4.2f}_Fe_{2:5.2f}_age_{3:05.2f}.hdf5'.format(M0,e,Fe,age)
output_filename = os.path.join(opt.output_directory,output_filename)
if opt.flatsfr:
cmd = './ark_idealized_dwarfs_generate --Fe {0:6.3f} --AgeMean {1:6.3f} --M0 {2:10.4e} -e {3:5.3f} -N {4:d} -o {5:s} --AgeFlat'.format(Fe, age,M0, e, 50000, output_filename)
else:
cmd = './ark_idealized_dwarfs_generate --Fe {0:6.3f} --AgeMean {1:6.3f} --M0 {2:10.4e} -e {3:5.3f} -N {4:d} -o {5:s}'.format(Fe, age,M0, e, 50000, output_filename)
# Generate the dwarfs
print(cmd)
if not opt.dryrun:
os.system(cmd)

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