def cmd():
synFile = 'syn_nir_d389.0_a600.dat'
results = synthetic.load_nearIR_dict(synFile)
# Lets trim down to the extinction value of interest.
AKs_AV = 0.062 # from Nishiyama+ 2008... GC, but good enough?
AKs = AV * AKs_AV
idx = np.argmin(np.abs(results['AKs'] - AKs))
numAKs = len(results['AKs'])
numTeff = len(results['Teff'])
for key in results.keys():
if ((len(results[key].shape) == 2)
and (results[key].shape[1] == numAKs)):
results[key] = results[key][:, idx]
else:
if len(results[key]) == numAKs:
results[key] = results[key][idx]
HKp = results['H'] - results['Kp']
KpLp = results['Kp'] - results['Lp']
# Fetch a few points at specific masses
massPoints = np.array([30, 10, 5, 2, 1, 0.5])
massIndices = np.zeros(len(massPoints))
massLabels = []
for mm in range(len(massPoints)):
mdx = np.argmin(np.abs(results['mass'] - massPoints[mm]))
massIndices[mm] = mdx
massPoints[mm] = results['mass'][mdx]
massLabels.append('{0:4.1f} Msun'.format(massPoints[mm]))
# Plots
py.clf()
py.plot(HKp, results['H'])
rng = py.axis()
py.xlim(0, 2)
py.ylim(rng[3], rng[2])
py.xlabel('H - Kp')
py.ylabel('H')
py.title('Orion BN/KL Region')
for mm, mmLab in zip(massIndices, massLabels):
py.plot(HKp[mm], results['H'][mm], 'kx')
py.text(HKp[mm], results['H'][mm], mmLab)
py.savefig('orion_cmd_hkp_h.png')
py.clf()
py.plot(HKp, results['Kp'])
rng = py.axis()
py.xlim(0, 2)
py.ylim(rng[3], rng[2])
py.xlabel('H - Kp')
py.ylabel('Kp')
py.title('Orion BN/KL Region')
for mm, mmLab in zip(massIndices, massLabels):
py.plot(HKp[mm], results['Kp'][mm], 'kx')
py.text(HKp[mm], results['Kp'][mm], mmLab)
py.savefig('orion_cmd_hkp_kp.png')
py.clf()
py.plot(KpLp, results['Kp'])
rng = py.axis()
py.xlim(0, 2)
py.ylim(rng[3], rng[2])
py.xlabel('Kp - Lp')
py.ylabel('Kp')
py.title('Orion BN/KL Region')
for mm, mmLab in zip(massIndices, massLabels):
py.plot(KpLp[mm], results['Kp'][mm], 'kx')
py.text(KpLp[mm], results['Kp'][mm], mmLab)
py.savefig('orion_cmd_kplp_kp.png')
py.clf()
py.semilogx(results['Teff'], results['logL'])
rng = py.axis()
py.xlim(rng[1], rng[0])
py.xlabel('Teff')
py.ylabel('log(L)')
py.title('Orion BN/KL Region')
for mm, mmLab in zip(massIndices, massLabels):
py.plot(results['Teff'][mm], results['logL'][mm], 'kx')
py.text(results['Teff'][mm], results['logL'][mm], mmLab)
py.savefig('orion_hr.png')
# Print to a text file for Breann
_out = open('orion_model_isochrone.dat', 'w')
fmt = '#{0:>9s} {1:>10s} {2:>10s} {3:>10s} {4:>10s} {5:>10s} {6:>10s} {7:>10s}\n'
_out.write('# AKs = {0:.2f} age = 1 Myr d = 389 pc\n'.format(AKs))
_out.write(fmt.format('Teff', 'mass', 'logL', 'logg', 'J', 'H', 'Kp',
'Lp'))
for ii in range(len(results['Teff'])):
fmt1 = '{0:10.1f} {1:10.3f} {2:10.4f} {3:10.4f} '
fmt2 = '{0:10.2f} {1:10.2f} {2:10.2f} {3:10.2f}\n'
_out.write(
fmt1.format(results['Teff'][ii], results['mass'][ii],
results['logL'][ii], results['logg'][ii]))
_out.write(
fmt2.format(results['J'][ii], results['H'][ii], results['Kp'][ii],
results['Lp'][ii]))
def plot_cluster_isochrones(redo_iso=False):
"""
Plot isochrones and mass-luminosity functions for M17, Wd 2, Wd 1, and RSGC 1.
"""
# Cluster Info
name = ['M17', 'Wd 2', 'Wd 1', 'RSGC 1', 'RSGC 2']
dist = np.array([2100, 4160, 3600, 6000, 6000])
age = np.array([1., 2., 5., 12., 17.]) * 1.0e6
AV = np.array([5., 6.5, 10., 23., 10.])
# Derived properties
logage = np.log10(age)
AKs = AV / 10.0
iso_all = []
# Loop through the clusters and make the isochrones.
for ii in range(len(name)):
pickleFile = 'syn_nir_d' + str(dist[ii]).zfill(5) + '_a' \
+ str(int(round(logage[ii]*100))).zfill(3) + '.dat'
if (not os.path.exists(pickleFile)) or (redo_iso == True):
AKsGrid = np.array([AKs[ii]])
syn.nearIR(dist[ii], logage[ii], AKsGrid=AKsGrid)
iso_all.append( syn.load_nearIR_dict(pickleFile) )
##########
# Plot CMDs
##########
py.figure(1)
py.clf()
py.subplots_adjust(left=0.15)
colors = ['green', 'cyan', 'blue', 'red', 'purple']
for ii in range(len(iso_all)):
iso = iso_all[ii]
py.plot(iso['J'] - iso['K'], iso['K'], label=name[ii],
linewidth=2, color=colors[ii])
idx1 = np.argmin( np.abs(iso['mass'] - 1.0) )
py.plot(iso['J'][idx1] - iso['K'][idx1], iso['K'][idx1], 'ks',
color=colors[ii], mew=0, ms=8)
py.gca().invert_yaxis()
py.xlabel("J - K color")
py.ylabel("K magnitude")
py.text(iso['J'][idx1] - iso['K'][idx1], iso['K'][idx1],
r'1 M$_\odot$', color=colors[ii],
horizontalalignment='right', verticalalignment='top')
py.legend(loc="lower left")
py.savefig('clusters_cmd_jk.png')
##########
# Plot mass-luminosity relations for each of the filters.
##########
py.figure(2, figsize=(12,4))
py.clf()
py.subplots_adjust(left=0.06, bottom=0.15, wspace=0.22, right=0.97)
py.subplot(1, 3, 1)
for ii in range(len(iso_all)):
iso = iso_all[ii]
py.plot(iso['mass'], iso['J'], linewidth=2,
color=colors[ii], label=name[ii])
py.xlabel(r'Stellar Mass (M$_\dot$)')
py.ylabel('J magnitude')
py.xlim(0, 20)
py.ylim(26, 9)
py.subplot(1, 3, 2)
for ii in range(len(iso_all)):
iso = iso_all[ii]
py.plot(iso['mass'], iso['H'], linewidth=2,
color=colors[ii], label=name[ii])
py.legend(mode="expand", bbox_to_anchor=(-0.5, 0.99, 2.0, 0.08),
loc=3, ncol=4, frameon=False)
py.xlabel(r'Stellar Mass (M$_\dot$)')
py.ylabel('H magnitude')
py.xlim(0, 20)
py.ylim(26, 9)
py.subplot(1, 3, 3)
for ii in range(len(iso_all)):
iso = iso_all[ii]
py.plot(iso['mass'], iso['K'], linewidth=2,
color=colors[ii], label=name[ii])
py.xlabel(r'Stellar Mass (M$_\dot$)')
py.ylabel('K magnitude')
py.xlim(0, 20)
py.ylim(26, 9)
py.savefig('clusters_mass_luminosity_jhk.png')
##########
# Print out 0.1 Msun, 1 Msun, 10 Msun
# photometry table.
##########
for ii in range(len(iso_all)):
iso = iso_all[ii]
print('')
print('Cluster: ' + name[ii])
print('')
hdr = '{0:6s} {1:6s} {2:6s} {3:6s}'
dat = '{0:6.1f} {1:6.2f} {2:6.2f} {3:6.2f}'
print(hdr.format(' Mass', ' J', ' H', ' K'))
print(hdr.format(' ----', ' ---', ' ---', ' ---'))
idx01 = np.argmin( np.abs(iso['mass'] - 0.1) )
print(dat.format(iso['mass'][idx01], iso['J'][idx01][0],
iso['H'][idx01][0], iso['K'][idx01][0]))
idx1 = np.argmin( np.abs(iso['mass'] - 1.0) )
print(dat.format(iso['mass'][idx1], iso['J'][idx1][0],
iso['H'][idx1][0], iso['K'][idx1][0]))
idx10 = np.argmin( np.abs(iso['mass'] - 10.0) )
print(dat.format(iso['mass'][idx10], iso['J'][idx10][0],
iso['H'][idx10][0], iso['K'][idx10][0]))
def cmd():
synFile = 'syn_nir_d389.0_a600.dat'
results = synthetic.load_nearIR_dict(synFile)
# Lets trim down to the extinction value of interest.
AKs_AV = 0.062 # from Nishiyama+ 2008... GC, but good enough?
AKs = AV * AKs_AV
idx = np.argmin(np.abs(results['AKs'] - AKs))
numAKs = len(results['AKs'])
numTeff = len(results['Teff'])
for key in results.keys():
if ((len(results[key].shape) == 2) and
(results[key].shape[1] == numAKs)):
results[key] = results[key][:,idx]
else:
if len(results[key]) == numAKs:
results[key] = results[key][idx]
HKp = results['H'] - results['Kp']
KpLp = results['Kp'] - results['Lp']
# Fetch a few points at specific masses
massPoints = np.array([30, 10, 5, 2, 1, 0.5])
massIndices = np.zeros(len(massPoints))
massLabels = []
for mm in range(len(massPoints)):
mdx = np.argmin(np.abs(results['mass'] - massPoints[mm]))
massIndices[mm] = mdx
massPoints[mm] = results['mass'][mdx]
massLabels.append('{0:4.1f} Msun'.format(massPoints[mm]))
# Plots
py.clf()
py.plot(HKp, results['H'])
rng = py.axis()
py.xlim(0, 2)
py.ylim(rng[3], rng[2])
py.xlabel('H - Kp')
py.ylabel('H')
py.title('Orion BN/KL Region')
for mm, mmLab in zip(massIndices, massLabels):
py.plot(HKp[mm], results['H'][mm], 'kx')
py.text(HKp[mm], results['H'][mm], mmLab)
py.savefig('orion_cmd_hkp_h.png')
py.clf()
py.plot(HKp, results['Kp'])
rng = py.axis()
py.xlim(0, 2)
py.ylim(rng[3], rng[2])
py.xlabel('H - Kp')
py.ylabel('Kp')
py.title('Orion BN/KL Region')
for mm, mmLab in zip(massIndices, massLabels):
py.plot(HKp[mm], results['Kp'][mm], 'kx')
py.text(HKp[mm], results['Kp'][mm], mmLab)
py.savefig('orion_cmd_hkp_kp.png')
py.clf()
py.plot(KpLp, results['Kp'])
rng = py.axis()
py.xlim(0, 2)
py.ylim(rng[3], rng[2])
py.xlabel('Kp - Lp')
py.ylabel('Kp')
py.title('Orion BN/KL Region')
for mm, mmLab in zip(massIndices, massLabels):
py.plot(KpLp[mm], results['Kp'][mm], 'kx')
py.text(KpLp[mm], results['Kp'][mm], mmLab)
py.savefig('orion_cmd_kplp_kp.png')
py.clf()
py.semilogx(results['Teff'], results['logL'])
rng = py.axis()
py.xlim(rng[1], rng[0])
py.xlabel('Teff')
py.ylabel('log(L)')
py.title('Orion BN/KL Region')
for mm, mmLab in zip(massIndices, massLabels):
py.plot(results['Teff'][mm], results['logL'][mm], 'kx')
py.text(results['Teff'][mm], results['logL'][mm], mmLab)
py.savefig('orion_hr.png')
# Print to a text file for Breann
_out = open('orion_model_isochrone.dat', 'w')
fmt = '#{0:>9s} {1:>10s} {2:>10s} {3:>10s} {4:>10s} {5:>10s} {6:>10s} {7:>10s}\n'
_out.write('# AKs = {0:.2f} age = 1 Myr d = 389 pc\n'.format(AKs))
_out.write(fmt.format('Teff', 'mass', 'logL', 'logg',
'J', 'H', 'Kp', 'Lp'))
for ii in range(len(results['Teff'])):
fmt1 = '{0:10.1f} {1:10.3f} {2:10.4f} {3:10.4f} '
fmt2 = '{0:10.2f} {1:10.2f} {2:10.2f} {3:10.2f}\n'
_out.write(fmt1.format(results['Teff'][ii], results['mass'][ii],
results['logL'][ii], results['logg'][ii]))
_out.write(fmt2.format(results['J'][ii], results['H'][ii],
results['Kp'][ii], results['Lp'][ii]))
