def test_metallicity():
"""
Test isochrone generation at different metallicities
"""
# Define isochrone parameters
logAge = np.log10(5 * 10**6.)
AKs = 0.8
dist = 4000
evo_model = evolution.MISTv1()
atm_func = atmospheres.get_phoenixv16_atmosphere
red_law = reddening.RedLawHosek18b()
filt_list = ['wfc3,ir,f127m', 'wfc3,ir,f139m', 'wfc3,ir,f153m']
# Start with a solar metallicity isochrone
metallicity = 0.0
# Make Isochrone object, with high mass_sampling to decrease compute time
my_iso = synthetic.IsochronePhot(logAge,
AKs,
dist,
metallicity=metallicity,
evo_model=evo_model,
atm_func=atm_func,
red_law=red_law,
filters=filt_list,
mass_sampling=10)
# Test isochrone properties
assert my_iso.points.meta['METAL_IN'] == 0.0
assert os.path.exists('iso_6.70_0.80_04000_p00.fits')
# Now for non-solar metallicity
metallicity = -1.5
# Make Isochrone object, with high mass_sampling to decrease compute time
my_iso = synthetic.IsochronePhot(logAge,
AKs,
dist,
metallicity=metallicity,
evo_model=evo_model,
atm_func=atm_func,
red_law=red_law,
filters=filt_list,
mass_sampling=10)
metal_act = np.log10(0.00047 / 0.0142) # For Mist isochrones
# Test isochrone properties
assert my_iso.points.meta['METAL_IN'] == -1.5
assert my_iso.points.meta['METAL_ACT'] == metal_act
assert os.path.exists('iso_6.70_0.80_04000_m15.fits')
return
def test_IsochronePhot(plot=False):
from popstar import synthetic as syn
logAge = 6.7
AKs = 2.7
distance = 4000
filt_list = ['wfc3,ir,f127m', 'nirc2,J']
mass_sampling = 1
startTime = time.time()
iso = syn.IsochronePhot(logAge,
AKs,
distance,
filters=filt_list,
mass_sampling=mass_sampling)
endTime = time.time()
print('Test completed in: %d seconds' % (endTime - startTime))
# Typically takes 120 seconds if file is regenerated.
# Limited by pysynphot.Icat call in atmospheres.py
assert iso.points.meta['LOGAGE'] == logAge
assert iso.points.meta['AKS'] == AKs
assert iso.points.meta['DISTANCE'] == distance
assert len(iso.points) > 100
assert 'm_nirc2_J' in iso.points.colnames
if plot:
plt.figure(1)
iso.plot_CMD('mag814w', 'mag160w')
plt.figure(2)
iso.plot_mass_magnitude('mag160w')
return
def time_test_cluster():
from popstar import synthetic as syn
from popstar import atmospheres as atm
from popstar import evolution
from popstar import reddening
from popstar.imf import imf
from popstar.imf import multiplicity
logAge = 6.7
AKs = 2.7
distance = 4000
cluster_mass = 10**4
startTime = time.time()
evo = evolution.MergedBaraffePisaEkstromParsec()
atm_func = atm.get_merged_atmosphere
red_law = reddening.RedLawNishiyama09()
filt_list = ['nirc2,J', 'nirc2,Kp']
iso = syn.IsochronePhot(logAge, AKs, distance,
evo_model=evo, atm_func=atm_func,
red_law=red_law, filters=filt_list)
print('Constructed isochrone: %d seconds' % (time.time() - startTime))
imf_limits = np.array([0.07, 0.5, 150])
imf_powers = np.array([-1.3, -2.35])
multi = multiplicity.MultiplicityUnresolved()
my_imf = imf.IMF_broken_powerlaw(imf_limits, imf_powers, multiplicity=multi)
print('Constructed IMF with multiples: %d seconds' % (time.time() - startTime))
cluster = syn.ResolvedCluster(iso, my_imf, cluster_mass)
print('Constructed cluster: %d seconds' % (time.time() - startTime))
return
def __init__(self,
age=3.9e6,
ext=2.63,
dist=7.971e3,
met=0.0,
phase=None,
use_atm_func='merged'):
log_age = np.log10(age)
self.log_age = log_age
self.A_Ks = ext
self.dist = dist
self.met = met
# Evolution/Atmosphere Models
evo_model = evolution.MISTv1()
if use_atm_func == 'merged':
atm_func = atmospheres.get_merged_atmosphere
elif use_atm_func == 'phoenix':
atm_func = atmospheres.get_phoenixv16_atmosphere
# Extinction law
red_law = reddening.RedLawNoguerasLara18()
self.ext_alpha = 2.30
## Calculate extinctions implied by isochrone extinction
self.A_B = self.A_Ks * (lambda_Ks / lambda_B)**self.ext_alpha
self.A_R = self.A_Ks * (lambda_Ks / lambda_R)**self.ext_alpha
# Create an isochhrone with the given parameters
self.iso_curAge = synthetic.IsochronePhot(self.log_age,
self.A_Ks,
self.dist,
evo_model=evo_model,
atm_func=atm_func,
red_law=red_law,
metallicity=self.met,
filters=self.filt_list)
# Save out specific stellar parameter columns needed
## If needing specific phase, draw it out before saving
if phase is not None:
phase_check = np.where(
self.iso_curAge.points['phase'] == mist_phase_dict[phase])
else:
phase_check = np.where(self.iso_curAge.points['phase'] >= -1)
self.iso_mass_init = self.iso_curAge.points['mass'][phase_check]
self.iso_mass = self.iso_curAge.points['mass_current'][phase_check]
self.iso_rad = (self.iso_curAge.points['R'][phase_check]).to(u.solRad)
self.iso_lum = self.iso_curAge.points['L'][phase_check]
self.iso_teff = self.iso_curAge.points['Teff'][phase_check]
self.iso_mag_B = self.iso_curAge.points['m_ubv_B'][phase_check]
self.iso_mag_R = self.iso_curAge.points['m_ubv_R'][phase_check]
self.iso_rad_min = np.min(self.iso_rad).value
self.iso_rad_max = np.max(self.iso_rad).value
def animate_ages():
# Define isochrone parameters
dist = 4000 # distance in parsecs
AKs = 1.0 # Ks filter extinction in mags
logAge = np.arange(6, 9, 0.05) # Age in log(years)
# Define extinction law and filters
redlaw = reddening.RedLawCardelli(3.1) # Rv = 3.1
evo_model = evolution.MISTv1()
filt_list = ['nirc2,J', 'nirc2,Kp']
plt.figure(1)
for aa in range(len(logAge)):
iso = synthetic.IsochronePhot(logAge[aa],
AKs,
dist,
filters=filt_list,
red_law=redlaw,
evo_model=evo_model,
mass_sampling=3)
plt.clf()
plt.plot(iso.points['m_nirc2_J'] - iso.points['m_nirc2_Kp'],
iso.points['m_nirc2_J'])
plt.xlabel('J - Kp')
plt.ylabel('J')
plt.gca().invert_yaxis()
plt.title('Age = 10^{0:.2f}'.format(logAge[aa]))
plt.xlim(1, 3)
plt.ylim(28, 6)
plt.savefig(
'/u/jlu/doc/present/2020_06_ucb_lunch/iso_age_{0:.2f}.png'.format(
logAge[aa]))
def make_sim_cluster():
work_dir = '/u/jlu/work/gc/jwst/2018_03_19/'
ages = [4e6, 1e8, 8e9]
cluster_mass = [1e4, 1e4, 1e7]
AKs = 2.7
deltaAKs = 1.0
distance = 8000
mass_sampling = 5
isochrones = []
clusters = []
evo = evolution.MergedBaraffePisaEkstromParsec()
atm_func = atm.get_merged_atmosphere
red_law = reddening.RedLawHosek18()
multi = multiplicity.MultiplicityUnresolved()
imf_mass_limits = np.array([0.07, 0.5, 1, np.inf])
imf_powers_old = np.array([-1.3, -2.3, -2.3])
imf_powers_yng = np.array([-1.3, -1.8, -1.8])
my_imf_old = imf.IMF_broken_powerlaw(imf_mass_limits,
imf_powers_old,
multiplicity=multi)
my_imf_yng = imf.IMF_broken_powerlaw(imf_mass_limits,
imf_powers_yng,
multiplicity=multi)
# Test all filters
filt_list = [
'wfc3,ir,f127m', 'wfc3,ir,f139m', 'wfc3,ir,f153m', 'acs,wfc1,f814w',
'wfc3,ir,f125w', 'wfc3,ir,f160w', 'jwst,F090W', 'jwst,F115W',
'jwst,F164N', 'jwst,F187N', 'jwst,F212N', 'jwst,F323N', 'jwst,F405N',
'jwst,F466N', 'jwst,F470N', 'jwst,F140M', 'jwst,F162M', 'jwst,F182M',
'jwst,F210M', 'jwst,F250M', 'jwst,F300M', 'jwst,F335M', 'jwst,F360M',
'jwst,F410M', 'jwst,F430M', 'jwst,F460M', 'jwst,F480M', 'nirc2,J',
'nirc2,H', 'nirc2,Kp', 'nirc2,Lp', 'nirc2,Ms'
]
startTime = time.time()
for ii in range(len(ages)):
logAge = np.log10(ages[ii])
iso = syn.IsochronePhot(logAge,
AKs,
distance,
evo_model=evo,
atm_func=atm_func,
red_law=red_law,
filters=filt_list,
mass_sampling=mass_sampling,
iso_dir=work_dir)
print('Constructed isochrone: %d seconds' % (time.time() - startTime))
if ii < 2:
imf_ii = my_imf_yng
else:
imf_ii = my_imf_old
cluster = syn.ResolvedClusterDiffRedden(iso, imf_ii, cluster_mass[ii],
deltaAKs)
# Save generated clusters to file.
save_file_fmt = '{0}/clust_{1:.2f}_{2:4.2f}_{3:4s}.fits'
save_file_txt = save_file_fmt.format(work_dir, logAge, AKs,
str(distance).zfill(5))
save_file = open(save_file_txt, 'wb')
pickle.dump(cluster, save_file)
return
return
def test_phot_consistency(filt='all'):
"""
Test photometric consistency of generated isochrone (IsochronePhot)
against pre-generated isochrone with native filter sampling. Requires
consistency to within 0.005 mag.
Base isochrone is at 5 Myr, AKs = 0, 1000 pc, mass_sampling=10
Paramters:
----------
filt: 'all', 'hst', 'vista', 'decam', 'ps1', 'jwst'
Specify what filter set you want to test
"""
from astropy.table import Table
import os
# Load pre-generated isochrone, located in popstar tests directory
direct = os.path.dirname(__file__)
orig = Table.read(direct + '/iso_6.70_0.00_01000.fits', format='fits')
# Generate new isochrone with popstar code
if filt == 'all':
filt_list = [
'wfc3,ir,f127m', 'wfc3,ir,f139m', 'wfc3,ir,f153m',
'acs,wfc1,f814w', 'wfc3,ir,f125w', 'wfc3,ir,f160w', 'decam,y',
'decam,i', 'decam,z', 'decam,u', 'decam,g', 'decam,r', 'vista,Y',
'vista,Z', 'vista,J', 'vista,H', 'vista,Ks', 'ps1,z', 'ps1,g',
'ps1,r', 'ps1,i', 'ps1,y', 'jwst,F070W', 'jwst,F090W',
'jwst,F115W', 'jwst,F140M', 'jwst,F150W', 'jwst,F150W2',
'jwst,F162M', 'jwst,F164N', 'jwst,F182M', 'jwst,F187N',
'jwst,F200W', 'jwst,F212N', 'jwst,F210M', 'jwst,F250M',
'jwst,F277W', 'jwst,F300M', 'jwst,F322W2', 'jwst,F323N',
'jwst,F335M', 'jwst,F356W', 'jwst,F360M', 'jwst,F405N',
'jwst,F410M', 'jwst,F430M', 'jwst,F444W', 'jwst,F460M',
'jwst,F466N', 'jwst,F470N', 'jwst,F480M', 'nirc2,J', 'nirc2,H',
'nirc2,Kp', 'nirc2,K', 'nirc2,Lp', 'nirc2,Hcont', 'nirc2,FeII',
'nirc2,Brgamma', 'jg,J', 'jg,H', 'jg,K', 'nirc1,K', 'nirc1_H',
'ctio_osiris,K', 'ctio_osiris,H', 'naco,H', 'naco,Ks', 'ztf,g',
'ztf,r', 'ztf,i'
]
elif filt == 'decam':
filt_list = [
'decam,y', 'decam,i', 'decam,z', 'decam,u', 'decam,g', 'decam,r'
]
elif filt == 'vista':
filt_list = ['vista,Y', 'vista,Z', 'vista,J', 'vista,H', 'vista,Ks']
elif filt == 'ps1':
filt_list = ['ps1,z', 'ps1,g', 'ps1,r', 'ps1,i', 'ps1,y']
elif filt == 'jwst':
filt_list = [
'jwst,F070W', 'jwst,F090W', 'jwst,F115W', 'jwst,F140M',
'jwst,F150W', 'jwst,F150W2', 'jwst,F162M', 'jwst,F164N',
'jwst,F182M', 'jwst,F187N', 'jwst,F200W', 'jwst,F212N',
'jwst,F210M', 'jwst,F250M', 'jwst,F277W', 'jwst,F300M',
'jwst,F322W2', 'jwst,F323N', 'jwst,F335M', 'jwst,F356W',
'jwst,F360M', 'jwst,F405N', 'jwst,F410M', 'jwst,F430M',
'jwst,F444W', 'jwst,F460M', 'jwst,F466N', 'jwst,F470N',
'jwst,F480M'
]
elif filt == 'hst':
filt_list = [
'wfc3,ir,f127m', 'wfc3,ir,f139m', 'wfc3,ir,f153m',
'acs,wfc1,f814w', 'wfc3,ir,f125w', 'wfc3,ir,f160w'
]
elif filt == 'nirc2':
filt_list = [
'nirc2,J', 'nirc2,H', 'nirc2,Kp', 'nirc2,K', 'nirc2,Lp',
'nirc2,Ms', 'nirc2,Hcont', 'nirc2,FeII', 'nirc2,Brgamma'
]
elif filt == 'jg':
filt_list = ['jg,J', 'jg,H', 'jg,K']
elif filt == 'ztf':
filt_list = ['ztf,g', 'ztf,r', 'ztf,i']
elif filt == 'misc':
filt_list = [
'nirc1,K', 'nirc1,H', 'ctio_osiris,K', 'ctio_osiris,H', 'naco,H',
'naco,Ks'
]
print('Making isochrone')
iso = synthetic.IsochronePhot(6.7,
0,
1000,
mass_sampling=10,
filters=filt_list,
rebin=True)
iso = iso.points
# First find masses that are the same
foo = []
for ii in iso['mass']:
tmp = np.where(orig['mass'] == ii)[0][0]
foo.append(tmp)
assert len(foo) == len(iso)
orig = orig[foo]
# Identify the photometry columns
cols = list(iso.keys())
idx = []
for ii in range(len(cols)):
if cols[ii].startswith('mag'):
idx.append(ii)
mag_cols = np.array(cols)[idx]
# Test the consistency of each column with the original isochrone
for ii in mag_cols:
orig_mag = orig[ii]
new_mag = iso[ii]
np.testing.assert_allclose(orig_mag,
new_mag,
rtol=0.01,
err_msg="{0} failed".format(ii))
# Also report median abs difference
diff = abs(orig_mag - new_mag)
print(('{0} median abs diff: {1}'.format(ii, np.median(diff))))
print(('Phot consistency test successful for {0}'.format(filt)))
# Remove iso file we just wrote, since it was only a test
os.remove('iso_6.70_0.00_01000.fits')
return
def time_test_mass_match():
from popstar import synthetic as syn
from popstar import atmospheres as atm
from popstar import evolution
from popstar.imf import imf
from popstar.imf import multiplicity
log_age = 6.7
AKs = 2.7
distance = 4000
cluster_mass = 5e3
imf_in = imf.Kroupa_2001(multiplicity=None)
start_time = time.time()
iso = syn.IsochronePhot(log_age, AKs, distance)
iso_masses = iso.points['mass']
print('Generated iso masses in {0:.0f} s'.format(time.time() - start_time))
start_time = time.time()
star_masses, isMulti, compMass, sysMass = imf_in.generate_cluster(
cluster_mass)
print('Generated cluster masses in {0:.0f} s'.format(time.time() -
start_time))
def match_model_masses1(isoMasses, starMasses):
indices = np.empty(len(starMasses), dtype=int)
for ii in range(len(starMasses)):
theMass = starMasses[ii]
dm = np.abs(isoMasses - theMass)
mdx = dm.argmin()
# Model mass has to be within 10% of the desired mass
if (dm[mdx] / theMass) > 0.1:
indices[ii] = -1
else:
indices[ii] = mdx
return indices
def match_model_masses2(isoMasses, starMasses):
isoMasses_tmp = isoMasses.reshape((len(isoMasses), 1))
kdt = KDTree(isoMasses_tmp)
starMasses_tmp = starMasses.reshape((len(starMasses), 1))
q_results = kdt.query(starMasses_tmp, k=1)
indices = q_results[1]
dm_frac = np.abs(starMasses - isoMasses[indices]) / starMasses
idx = np.where(dm_frac > 0.1)[0]
indices[idx] = -1
return indices
print('Test #1 START')
start_time = time.time()
idx1 = match_model_masses1(iso_masses, star_masses)
stop_time = time.time()
print('Test #1 STOPPED after {0:.0f} seconds'.format(stop_time -
start_time))
print('Test #2 START')
start_time = time.time()
idx2 = match_model_masses2(iso_masses, star_masses)
stop_time = time.time()
print('Test #2 STOPPED after {0:.0f} seconds'.format(stop_time -
start_time))
return
def test_ifmr_multiplicity():
from popstar import synthetic as syn
from popstar import atmospheres as atm
from popstar import evolution
from popstar import reddening
from popstar import ifmr
from popstar.imf import imf
from popstar.imf import multiplicity
# Define cluster parameters
logAge = 9.7
AKs = 0.0
distance = 1000
cluster_mass = 1e6
mass_sampling = 5
# Test all filters
filt_list = ['nirc2,Kp', 'nirc2,H', 'nirc2,J']
startTime = time.time()
evo = evolution.MISTv1()
atm_func = atm.get_merged_atmosphere
ifmr_obj = ifmr.IFMR()
red_law = reddening.RedLawNishiyama09()
iso = syn.IsochronePhot(logAge,
AKs,
distance,
evo_model=evo,
atm_func=atm_func,
red_law=red_law,
filters=filt_list,
mass_sampling=mass_sampling)
print('Constructed isochrone: %d seconds' % (time.time() - startTime))
# Now to create the cluster.
imf_mass_limits = np.array([0.07, 0.5, 1, np.inf])
imf_powers = np.array([-1.3, -2.3, -2.3])
##########
# Start without multiplicity and IFMR
##########
my_imf1 = imf.IMF_broken_powerlaw(imf_mass_limits,
imf_powers,
multiplicity=None)
print('Constructed IMF: %d seconds' % (time.time() - startTime))
cluster1 = syn.ResolvedCluster(iso, my_imf1, cluster_mass, ifmr=ifmr_obj)
clust1 = cluster1.star_systems
print('Constructed cluster: %d seconds' % (time.time() - startTime))
##########
# Test with multiplicity and IFMR
##########
multi = multiplicity.MultiplicityUnresolved()
my_imf2 = imf.IMF_broken_powerlaw(imf_mass_limits,
imf_powers,
multiplicity=multi)
print('Constructed IMF with multiples: %d seconds' %
(time.time() - startTime))
cluster2 = syn.ResolvedCluster(iso, my_imf2, cluster_mass, ifmr=ifmr_obj)
clust2 = cluster2.star_systems
comps2 = cluster2.companions
print('Constructed cluster with multiples: %d seconds' %
(time.time() - startTime))
##########
# Tests
##########
# Check that we have black holes, neutron stars, and white dwarfs in both.
assert len(np.where(clust1['phase'] == 101)) > 0 # WD
assert len(np.where(clust2['phase'] == 101)) > 0
assert len(np.where(clust1['phase'] == 102)) > 0 # NS
assert len(np.where(clust2['phase'] == 102)) > 0
assert len(np.where(clust1['phase'] == 103)) > 0 # BH
assert len(np.where(clust2['phase'] == 103)) > 0
# Now check that we have companions that are WDs, NSs, and BHs
assert len(np.where(comps2['phase'] == 101)) > 0
assert len(np.where(comps2['phase'] == 102)) > 0
assert len(np.where(comps2['phase'] == 103)) > 0
# Make sure no funky phase designations (due to interpolation effects)
# slipped through
idx = np.where((clust1['phase'] > 5) & (clust1['phase'] < 101)
& (clust1['phase'] != 9))
idx2 = np.where((comps2['phase'] > 5) & (comps2['phase'] < 101)
& (comps2['phase'] != 9))
assert len(idx[0]) == 0
return
def test_iso_wave():
"""
Test to make sure isochrones generated have spectra with the proper
wavelength range, and that the user has control over that wavelength
range (propagated through IsochronePhot)
"""
# Define isochrone parameters
logAge = np.log10(5 * 10**6.) # Age in log(years)
AKs = 0.8 # extinction in mags
dist = 4000 # distance in parsec
# Define evolution/atmosphere models and extinction law (optional)
evo_model = evolution.MergedBaraffePisaEkstromParsec()
atm_func = atmospheres.get_merged_atmosphere
red_law = reddening.RedLawHosek18b()
# Also specify filters for synthetic photometry (optional). Here we use
# the HST WFC3-IR F127M, F139M, and F153M filters
filt_list = ['wfc3,ir,f127m']
# First, let's make sure the vega spectrum has the proper limits
vega = synthetic.Vega()
assert np.min(vega.wave) == 995
assert np.max(vega.wave) == 100200
# Make Isochrone object. Will use wave_range = [3000,52000].
# Make sure range matches to resolution of atmosphere.
wave_range1 = [3000, 52000]
my_iso = synthetic.IsochronePhot(logAge,
AKs,
dist,
evo_model=evo_model,
atm_func=atm_func,
red_law=red_law,
filters=filt_list,
mass_sampling=10,
wave_range=wave_range1,
recomp=True)
test = my_iso.spec_list[0]
assert np.min(test.wave) == 3010
assert np.max(test.wave) == 51900
# Now let's try changing the wave range. Is it carried through
# properly?
wave_range2 = [1200, 90000]
my_iso = synthetic.IsochronePhot(logAge,
AKs,
dist,
evo_model=evo_model,
atm_func=atm_func,
red_law=red_law,
filters=filt_list,
mass_sampling=10,
wave_range=wave_range2,
recomp=True)
test2 = my_iso.spec_list[0]
assert np.min(test2.wave) == 1205
assert np.max(test2.wave) == 89800
# Does the error exception catch the bad wave_range?
wave_range3 = [1200, 1000000]
try:
my_iso = synthetic.IsochronePhot(logAge,
AKs,
dist,
evo_model=evo_model,
atm_func=atm_func,
red_law=red_law,
filters=filt_list,
mass_sampling=10,
wave_range=wave_range3,
recomp=True)
print(
'WAVE TEST FAILED!!! Should have crashed here, wavelength range out of bounds'
)
pdb.set_trace()
except:
print('Wavelength out of bound condition passed. Test is good')
pass
return
def test_cluster_mass():
from popstar import synthetic as syn
from popstar import atmospheres as atm
from popstar import evolution
from popstar import reddening
from popstar import ifmr
from popstar.imf import imf
from popstar.imf import multiplicity
# Define cluster parameters
logAge = 6.7
AKs = 2.4
distance = 4000
cluster_mass = 10**5.
mass_sampling = 5
# Test filters
filt_list = ['nirc2,J', 'nirc2,Kp']
startTime = time.time()
# Define evolution/atmosphere models and extinction law
evo = evolution.MISTv1()
atm_func = atmospheres.get_merged_atmosphere
red_law = reddening.RedLawHosek18b()
iso = syn.IsochronePhot(logAge,
AKs,
distance,
evo_model=evo,
atm_func=atm_func,
red_law=red_law,
filters=filt_list,
mass_sampling=mass_sampling)
print('Constructed isochrone: %d seconds' % (time.time() - startTime))
# Now to create the cluster.
imf_mass_limits = np.array([0.2, 0.5, 1, 120.0])
imf_powers = np.array([-1.3, -2.3, -2.3])
# IFMR
my_ifmr = ifmr.IFMR()
##########
# Start without multiplicity
##########
my_imf1 = imf.IMF_broken_powerlaw(imf_mass_limits,
imf_powers,
multiplicity=None)
print('Constructed IMF: %d seconds' % (time.time() - startTime))
cluster1 = syn.ResolvedCluster(iso, my_imf1, cluster_mass, ifmr=my_ifmr)
clust1 = cluster1.star_systems
print('Constructed cluster: %d seconds' % (time.time() - startTime))
# Check that the total mass is within tolerance of input mass
cluster_mass_out = clust1['systemMass'].sum()
assert np.abs(cluster_mass_out -
cluster_mass) < 200.0 # within 200 Msun of desired mass.
print('Cluster Mass: IN = ', cluster_mass, " OUT = ", cluster_mass_out)
##########
# Test with multiplicity
##########
multi = multiplicity.MultiplicityUnresolved()
my_imf2 = imf.IMF_broken_powerlaw(imf_mass_limits,
imf_powers,
multiplicity=multi)
print('Constructed IMF with multiples: %d seconds' %
(time.time() - startTime))
cluster2 = syn.ResolvedCluster(iso, my_imf2, cluster_mass, ifmr=my_ifmr)
clust2 = cluster2.star_systems
print('Constructed cluster with multiples: %d seconds' %
(time.time() - startTime))
# Check that the total mass is within tolerance of input mass
cluster_mass_out = clust2['systemMass'].sum()
assert np.abs(cluster_mass_out -
cluster_mass) < 200.0 # within 200 Msun of desired mass.
print('Cluster Mass: IN = ', cluster_mass, " OUT = ", cluster_mass_out)
return
def test_IsochronePhot(plot=False):
from popstar import synthetic as syn
from popstar import evolution, atmospheres, reddening
logAge = 6.7
AKs = 2.7
distance = 4000
filt_list = ['wfc3,ir,f127m', 'nirc2,J']
mass_sampling = 1
iso_dir = 'iso/'
evo_model = evolution.MISTv1()
atm_func = atmospheres.get_merged_atmosphere
redlaw = reddening.RedLawNishiyama09()
startTime = time.time()
iso = syn.IsochronePhot(logAge,
AKs,
distance,
evo_model=evo_model,
atm_func=atm_func,
red_law=redlaw,
filters=filt_list,
mass_sampling=mass_sampling,
iso_dir=iso_dir)
endTime = time.time()
print('IsochronePhot generated in: %d seconds' % (endTime - startTime))
# Typically takes 120 seconds if file is regenerated.
# Limited by pysynphot.Icat call in atmospheres.py
assert iso.points.meta['LOGAGE'] == logAge
assert iso.points.meta['AKS'] == AKs
assert iso.points.meta['DISTANCE'] == distance
assert len(iso.points) > 100
assert 'm_nirc2_J' in iso.points.colnames
if plot:
plt.figure(1)
iso.plot_CMD('mag814w', 'mag160w')
plt.figure(2)
iso.plot_mass_magnitude('mag160w')
# Finally, let's test the isochronePhot file generation
assert os.path.exists('{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}_p00.fits'.format(
iso_dir, logAge, AKs,
str(distance).zfill(5)))
# Check 1: If we try to remake the isochrone, does it read the file rather than
# making a new one
iso_new = syn.IsochronePhot(logAge,
AKs,
distance,
evo_model=evo_model,
atm_func=atm_func,
red_law=redlaw,
filters=filt_list,
mass_sampling=mass_sampling,
iso_dir=iso_dir)
assert iso_new.recalc == False
# Check 2: If we change evo model, atmo model, or redlaw,
# does IsochronePhot regenerate the isochrone and overwrite the existing one?
evo2 = evolution.MergedBaraffePisaEkstromParsec()
mass_sampling = 20
iso_new = syn.IsochronePhot(logAge,
AKs,
distance,
evo_model=evo2,
atm_func=atm_func,
red_law=redlaw,
filters=filt_list,
mass_sampling=mass_sampling,
iso_dir=iso_dir)
assert iso_new.recalc == True
redlaw2 = reddening.RedLawHosek18b()
iso_new = syn.IsochronePhot(logAge,
AKs,
distance,
evo_model=evo2,
atm_func=atm_func,
red_law=redlaw2,
filters=filt_list,
mass_sampling=mass_sampling,
iso_dir=iso_dir)
assert iso_new.recalc == True
atm2 = atmospheres.get_castelli_atmosphere
iso_new = syn.IsochronePhot(logAge,
AKs,
distance,
evo_model=evo2,
atm_func=atm2,
red_law=redlaw2,
filters=filt_list,
mass_sampling=mass_sampling,
iso_dir=iso_dir)
assert iso_new.recalc == True
return
def test_ResolvedCluster():
from popstar import synthetic as syn
from popstar import atmospheres as atm
from popstar import evolution
from popstar import reddening
from popstar.imf import imf
from popstar.imf import multiplicity
# Define cluster parameters
logAge = 6.7
AKs = 2.4
distance = 4000
cluster_mass = 10**5.
mass_sampling=5
# Test all filters
filt_list = ['wfc3,ir,f127m', 'wfc3,ir,f139m', 'wfc3,ir,f153m', 'acs,wfc1,f814w',
'wfc3,ir,f125w', 'wfc3,ir,f160w', 'decam,y', 'decam,i', 'decam,z',
'decam,u', 'decam,g', 'decam,r', 'vista,Y', 'vista,Z',
'vista,J', 'vista,H', 'vista,Ks', 'ps1,z', 'ps1,g', 'ps1,r',
'ps1,i', 'ps1,y', 'jwst,F090W', 'jwst,F164N', 'jwst,F212N',
'jwst,F323N', 'jwst,F466N', 'nirc2,J', 'nirc2,H', 'nirc2,Kp',
'nirc2,K', 'nirc2,Lp', 'nirc2,Ms', 'nirc2,Hcont', 'nirc2,FeII',
'nirc2,Brgamma', 'jg,J', 'jg,H', 'jg,K']
startTime = time.time()
evo = evolution.MergedBaraffePisaEkstromParsec()
atm_func = atm.get_merged_atmosphere
red_law = reddening.RedLawNishiyama09()
iso = syn.IsochronePhot(logAge, AKs, distance,
evo_model=evo, atm_func=atm_func,
red_law=red_law, filters=filt_list,
mass_sampling=mass_sampling)
print('Constructed isochrone: %d seconds' % (time.time() - startTime))
# Now to create the cluster.
imf_mass_limits = np.array([0.07, 0.5, 1, np.inf])
imf_powers = np.array([-1.3, -2.3, -2.3])
##########
# Start without multiplicity
##########
my_imf1 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
multiplicity=None)
print('Constructed IMF: %d seconds' % (time.time() - startTime))
cluster1 = syn.ResolvedCluster(iso, my_imf1, cluster_mass)
clust1 = cluster1.star_systems
print('Constructed cluster: %d seconds' % (time.time() - startTime))
plt.figure(3)
plt.clf()
plt.plot(clust1['m_nirc2_J'] - clust1['m_nirc2_Kp'], clust1['m_nirc2_J'], 'r.')
plt.plot(iso.points['m_nirc2_J'] - iso.points['m_nirc2_Kp'], iso.points['m_nirc2_J'], 'c.')
plt.gca().invert_yaxis()
# *** Visual Inspections: ***
# - check that points (red) fall between isochrone points (blue)
##########
# Test with multiplicity
##########
multi = multiplicity.MultiplicityUnresolved()
my_imf2 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
multiplicity=multi)
print('Constructed IMF with multiples: %d seconds' % (time.time() - startTime))
cluster2 = syn.ResolvedCluster(iso, my_imf2, cluster_mass)
clust2 = cluster2.star_systems
print('Constructed cluster with multiples: %d seconds' % (time.time() - startTime))
##########
# Plots
##########
# Plot an IR CMD and compare cluster members to isochrone.
plt.figure(1)
plt.clf()
plt.plot(clust1['m_nirc2_J'] - clust1['m_nirc2_Kp'], clust1['m_nirc2_J'], 'r.')
plt.plot(clust2['m_nirc2_J'] - clust2['m_nirc2_Kp'], clust2['m_nirc2_J'], 'b.')
plt.plot(iso.points['m_nirc2_J'] - iso.points['m_nirc2_Kp'], iso.points['m_nirc2_J'], 'c-')
plt.gca().invert_yaxis()
plt.xlabel('J - Kp (mag)')
plt.ylabel('J (mag')
# Plot a mass-magnitude relationship.
plt.figure(2)
plt.clf()
plt.semilogx(clust1['mass'], clust1['m_nirc2_J'], 'r.')
plt.semilogx(clust2['mass'], clust2['m_nirc2_J'], 'r.')
plt.gca().invert_yaxis()
plt.xlabel('Mass (Msun)')
plt.ylabel('J (mag)')
# # Plot the spectrum of the most massive star
# idx = cluster.mass.argmax()
# plt.clf()
# plt.plot(cluster.stars[idx].wave, cluster.stars[idx].flux, 'k.')
# # Plot an integrated spectrum of the whole cluster.
# wave, flux = cluster.get_integrated_spectrum()
# plt.clf()
# plt.plot(wave, flux, 'k.')
return
def likelihood(cube, ndim, nparams):
##########
# Priors (I think order matters)
##########
parName = [
'distance', 'LogAge', 'AKs', 'dAKs', 'alpha1', 'alpha2', 'mbreak',
'Mcl'
]
par, par_prior_logp = get_prior_info(cube, parName)
sysMass = np.zeros(len(t))
##########
# Load up the model cluster.
##########
imf_mass_limits = np.array([imf_mmin, par['mbreak'], imf_mmax])
imf_powers = np.array([par['alpha2'], par['alpha1']])
imf_multi = None
new_imf = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
imf_multi)
print 'Getting Isochrone'
new_iso = synthetic.IsochronePhot(par['LogAge'],
par['AKs'],
par['distance'],
evo_model=evo_model,
atm_func=atm_func,
red_law=red_law)
print 'Getting Cluster'
cluster = synthetic.ResolvedClusterDiffRedden(new_iso,
new_imf,
Mcl_sim,
par['dAKs'],
red_law=red_law)
# Convert simulated cluster into agnitude-color-color histogram
mag = cluster.star_systems['mag160w']
col1 = cluster.star_systems['mag814w'] - mag
col2 = cluster.star_systems['mag125w'] - mag
data = np.array([mag, col1, col2]).T
bins = np.array([bins_mag, bins_col1, bins_col2])
H_sim_c, edges = np.histogramdd(data, bins=bins, normed=True)
H_sim = H_sim_c * completeness_map
# Convert Observed cluster into magnitude-color-color histogram
mag = t['m_2010_F160W']
col1 = t['m_2005_F814W'] - t['m_2010_F160W']
col2 = t['m_2010_F125W'] - t['m_2010_F160W']
data = np.array([mag, col1, col2]).T
bins = np.array([bins_mag, bins_col1, bins_col2])
H_obs, edges = np.histogramdd(data, bins=bins)
# Plotting
extent = (bins_col1[0], bins_col2[-1], bins_mag[0], bins_mag[-1])
py.figure(1)
py.clf()
py.imshow(H_sim_c.sum(axis=2), extent=extent)
py.gca().invert_yaxis()
py.colorbar()
py.axis('tight')
py.title('Sim Complete')
py.figure(2)
py.clf()
py.imshow(H_sim.sum(axis=2), extent=extent)
py.gca().invert_yaxis()
py.colorbar()
py.axis('tight')
py.title('Sim Incomplete')
py.figure(3)
py.clf()
py.imshow(H_obs.sum(axis=2), extent=extent)
py.gca().invert_yaxis()
py.colorbar()
py.axis('tight')
py.title('Obs Incomplete')
py.figure(4)
py.clf()
py.imshow(completeness_map.mean(axis=2), extent=extent, vmin=0, vmax=1)
py.gca().invert_yaxis()
py.colorbar()
py.axis('tight')
py.title('Completeness Map')
pdb.set_trace()
mcc_cluster = 1
print likei.sum()
return likei.sum()
import numpy as np
import pandas as pd
from astropy.io import ascii
from astropy.io import fits
import matplotlib.pyplot as plt
from popstar import synthetic, evolution, atmospheres, reddening, ifmr
from popstar.imf import imf, multiplicity
# Define isochrone parameters
logAge = 9.6 # Age in log(years)
AKs = 0 # extinction in mags
dist = 1000 # distance in parsec
metallicities = [-1] # Metallicity in [M/H]
# Define evolution/atmosphere models and extinction law
evo_model = evolution.MISTv1()
atm_func = atmospheres.get_merged_atmosphere
red_law = reddening.RedLawHosek18b()
# Also specify filters for synthetic photometry (optional). Here we use
# the HST WFC3-IR F127M, F139M, and F153M filters
filt_list = ['wfc3,ir,f127m', 'wfc3,ir,f139m', 'wfc3,ir,f153m']
# Make Isochrone object. Note that is calculation will take a few minutes, unless the
# isochrone has been generated previously.
for metallicity in metallicities:
my_iso = synthetic.IsochronePhot(logAge, AKs, dist, metallicity=metallicity,
evo_model=evo_model, atm_func=atm_func, red_law=red_law, filters=filt_list)
print(my_iso.save_file)
def test_ResolvedClusterDiffRedden():
from popstar import synthetic as syn
from popstar import atmospheres as atm
from popstar import evolution
from popstar import reddening
from popstar.imf import imf
from popstar.imf import multiplicity
logAge = 6.7
AKs = 2.4
distance = 4000
cluster_mass = 10**5.
deltaAKs = 0.05
mass_sampling = 5
# Test filters
filt_list = ['nirc2,J', 'nirc2,Kp']
startTime = time.time()
evo = evolution.MergedBaraffePisaEkstromParsec()
atm_func = atm.get_merged_atmosphere
red_law = reddening.RedLawNishiyama09()
iso = syn.IsochronePhot(logAge,
AKs,
distance,
evo_model=evo,
atm_func=atm_func,
red_law=red_law,
filters=filt_list,
mass_sampling=mass_sampling)
print('Constructed isochrone: %d seconds' % (time.time() - startTime))
imf_mass_limits = np.array([0.07, 0.5, 1, np.inf])
imf_powers = np.array([-1.3, -2.3, -2.3])
##########
# Start without multiplicity
##########
my_imf1 = imf.IMF_broken_powerlaw(imf_mass_limits,
imf_powers,
multiplicity=None)
print('Constructed IMF: %d seconds' % (time.time() - startTime))
cluster1 = syn.ResolvedClusterDiffRedden(iso, my_imf1, cluster_mass,
deltaAKs)
clust1 = cluster1.star_systems
print('Constructed cluster: %d seconds' % (time.time() - startTime))
assert len(clust1) > 0
plt.figure(3)
plt.clf()
plt.plot(clust1['m_nirc2_J'] - clust1['m_nirc2_Kp'], clust1['m_nirc2_J'],
'r.')
plt.plot(iso.points['m_nirc2_J'] - iso.points['m_nirc2_Kp'],
iso.points['m_nirc2_J'], 'c.')
plt.gca().invert_yaxis()
# *** Visual Inspections: ***
# - check that points (red) fall between isochrone points (blue)
##########
# Test with multiplicity
##########
multi = multiplicity.MultiplicityUnresolved()
my_imf2 = imf.IMF_broken_powerlaw(imf_mass_limits,
imf_powers,
multiplicity=multi)
print('Constructed IMF with multiples: %d seconds' %
(time.time() - startTime))
cluster2 = syn.ResolvedClusterDiffRedden(iso, my_imf2, cluster_mass,
deltaAKs)
clust2 = cluster2.star_systems
print('Constructed cluster with multiples: %d seconds' %
(time.time() - startTime))
assert len(clust2) > 0
assert len(cluster2.companions) > 0
assert np.sum(clust2['N_companions']) == len(cluster2.companions)
##########
# Plots
##########
# Plot an IR CMD and compare cluster members to isochrone.
plt.figure(1)
plt.clf()
plt.plot(clust1['m_nirc2_J'] - clust1['m_nirc2_Kp'], clust1['m_nirc2_J'],
'r.')
plt.plot(clust2['m_nirc2_J'] - clust2['m_nirc2_Kp'], clust2['m_nirc2_J'],
'b.')
plt.plot(iso.points['m_nirc2_J'] - iso.points['m_nirc2_Kp'],
iso.points['m_nirc2_J'], 'c-')
plt.gca().invert_yaxis()
plt.xlabel('J - Kp (mag)')
plt.ylabel('J (mag')
# Plot a mass-magnitude relationship.
plt.figure(2)
plt.clf()
plt.semilogx(clust1['mass'], clust1['m_nirc2_J'], 'r.')
plt.semilogx(clust2['mass'], clust2['m_nirc2_J'], 'r.')
plt.gca().invert_yaxis()
plt.xlabel('Mass (Msun)')
plt.ylabel('J (mag)')
return
def __init__(self,
age=3.9e6,
ext=2.63,
dist=7.971e3,
met=0.0,
phase=None,
use_atm_func='merged'):
log_age = np.log10(age)
self.log_age = log_age
self.A_Ks = ext
self.dist = dist
self.met = met
# Evolution/Atmosphere Models
evo_model = evolution.MISTv1()
if use_atm_func == 'merged':
atm_func = atmospheres.get_merged_atmosphere
elif use_atm_func == 'castelli':
atm_fun = atmospheres.get_castelli_atmosphere
elif use_atm_func == 'phoenix':
atm_func = atmospheres.get_phoenixv16_atmosphere
# Extinction law
red_law = reddening.RedLawNoguerasLara18()
self.ext_alpha = 2.30
## Calculate extinctions implied by isochrone extinction
self.A_Lp = self.A_Ks * (lambda_Ks / lambda_Lp)**self.ext_alpha
self.A_Kp = self.A_Ks * (lambda_Ks / lambda_Kp)**self.ext_alpha
self.A_H = self.A_Ks * (lambda_Ks / lambda_H)**self.ext_alpha
# Create an isochrone with the given parameters
self.iso_curAge = synthetic.IsochronePhot(self.log_age,
self.A_Ks,
self.dist,
evo_model=evo_model,
atm_func=atm_func,
red_law=red_law,
metallicity=self.met,
filters=self.filt_list)
## Create another isochrone for absolute mags / passband luminosities
self.iso_absMag = synthetic.IsochronePhot(self.log_age,
0.0,
10.0,
evo_model=evo_model,
atm_func=atm_func,
red_law=red_law,
metallicity=self.met,
filters=self.filt_list)
# Save out specific stellar parameter columns needed
## If needing specific phase, draw it out before saving
if phase is not None:
phase_check = np.where(
self.iso_curAge.points['phase'] == mist_phase_dict[phase])
else:
phase_check = np.where(self.iso_curAge.points['phase'] >= -1)
self.iso_mass_init = (self.iso_curAge.points['mass'][phase_check]).to(
u.solMass)
self.iso_mass = self.iso_curAge.points['mass_current'][phase_check]
self.iso_rad = (self.iso_curAge.points['R'][phase_check]).to(u.solRad)
self.iso_lum = self.iso_curAge.points['L'][phase_check]
self.iso_teff = self.iso_curAge.points['Teff'][phase_check]
self.iso_logg = self.iso_curAge.points['logg'][phase_check]
self.iso_mag_Lp = self.iso_curAge.points['m_nirc2_Lp'][phase_check]
self.iso_mag_Kp = self.iso_curAge.points['m_nirc2_Kp'][phase_check]
self.iso_mag_H = self.iso_curAge.points['m_nirc2_H'][phase_check]
## Stellar parameters from the absolute magnitude isochrones
self.iso_absMag_mass_init = self.iso_absMag.points['mass'][phase_check]
self.iso_absMag_mass = self.iso_absMag.points['mass_current'][
phase_check]
self.iso_absMag_rad = (self.iso_absMag.points['R'][phase_check]).to(
u.solRad)
self.iso_absMag_Lp = self.iso_absMag.points['m_nirc2_Lp'][phase_check]
self.iso_absMag_Kp = self.iso_absMag.points['m_nirc2_Kp'][phase_check]
self.iso_absMag_H = self.iso_absMag.points['m_nirc2_H'][phase_check]
## Maximum bounds on the radius in isochrone
self.iso_rad_min = np.min(self.iso_rad).value
self.iso_rad_max = np.max(self.iso_rad).value
## Maximum bounds on the initial mass in isochrone
self.iso_mass_init_min = np.min(self.iso_mass_init).value
self.iso_mass_init_max = np.max(self.iso_mass_init).value