def time_test_imf(massLimits, imfSlopes, totalMass):
tstart = datetime.now()
res = imf.sample_imf(massLimits, imfSlopes, totalMass, makeMultiples=False)
m = res[0]
tend = datetime.now()
print 'N stars = {0:d} Mass = {1:.0f} Msun'.format(len(m), np.sum(m))
dt = tend - tstart
print dt
return m
def model_young_cluster(iso, makeMultiples=True):
c = constants
massLimits = np.array([0.1, 0.5, 150])
imfSlopes = np.array([-1.3, -2.3])
clusterMass = 1e4
MFamp = 0.44
MFindex = 0.51
CSFamp = 0.50
CSFindex = 0.45
CSFmax = 3
qMin = 0.01
qIndex = -0.4
# Sample a power-law IMF randomly
results = imf.sample_imf(massLimits, imfSlopes, clusterMass,
makeMultiples=makeMultiples,
multiMFamp=MFamp, multiMFindex=MFindex,
multiCSFamp=CSFamp, multiCSFindex=CSFindex,
multiCSFmax=CSFmax,
multiQmin=qMin, multiQindex=qIndex)
mass = results[0]
isMultiple = results[1]
compMasses = results[2]
systemMasses = results[3]
mag127m = np.zeros(len(mass), dtype=float)
mag139m = np.zeros(len(mass), dtype=float)
mag153m = np.zeros(len(mass), dtype=float)
magJ = np.zeros(len(mass), dtype=float)
magH = np.zeros(len(mass), dtype=float)
magKp = np.zeros(len(mass), dtype=float)
magLp = np.zeros(len(mass), dtype=float)
temp = np.zeros(len(mass), dtype=float)
isWR = np.zeros(len(mass), dtype=bool)
def match_model_mass(theMass):
dm = np.abs(iso.M - theMass)
mdx = dm.argmin()
# Model mass has to be within 2% of the desired mass
if (dm[mdx] / theMass) > 0.1:
return None
else:
return mdx
def combine_mag(mag1, mdx_cc, iso_mag):
f1 = 10**(-mag1 / 2.5)
f2 = 10**(-iso_mag[mdx_cc] / 2.5)
new_mag = -2.5 * np.log10(f1 + f2)
return new_mag
for ii in range(len(mass)):
# Find the closest model mass (returns None, if nothing with dm = 0.1
mdx = match_model_mass(mass[ii])
if mdx == None:
continue
mag127m[ii] = iso.mag127m[mdx]
mag139m[ii] = iso.mag139m[mdx]
mag153m[ii] = iso.mag153m[mdx]
magJ[ii] = iso.magJ[mdx]
magH[ii] = iso.magH[mdx]
magKp[ii] = iso.magKp[mdx]
magLp[ii] = iso.magLp[mdx]
temp[ii] = iso.T[mdx]
isWR[ii] = iso.isWR[mdx]
# Determine if this system is a binary.
if isMultiple[ii]:
n_stars = len(compMasses[ii])
for cc in range(n_stars):
mdx_cc = match_model_mass(compMasses[ii][cc])
if mdx_cc != None:
mag127m[ii] = combine_mag(mag127m[ii], mdx_cc, iso.mag127m)
mag139m[ii] = combine_mag(mag139m[ii], mdx_cc, iso.mag139m)
mag153m[ii] = combine_mag(mag153m[ii], mdx_cc, iso.mag153m)
magJ[ii] = combine_mag(magJ[ii], mdx_cc, iso.magJ)
magH[ii] = combine_mag(magH[ii], mdx_cc, iso.magH)
magKp[ii] = combine_mag(magKp[ii], mdx_cc, iso.magKp)
magLp[ii] = combine_mag(magLp[ii], mdx_cc, iso.magLp)
else:
print 'Rejected a companion %.2f' % compMasses[ii][cc]
# Get rid of the bad ones
idx = np.where(temp != 0)[0]
cdx = np.where(temp == 0)[0]
if len(cdx) > 0 and verbose:
print 'Found %d stars out of mass range: Minimum bad mass = %.1f' % \
(len(cdx), mass[cdx].min())
mass = mass[idx]
mag127m = mag127m[idx]
mag139m = mag139m[idx]
mag153m = mag153m[idx]
magJ = magJ[idx]
magH = magH[idx]
magKp = magKp[idx]
magLp = magLp[idx]
temp = temp[idx]
isWR = isWR[idx]
isMultiple = isMultiple[idx]
systemMasses = systemMasses[idx]
if makeMultiples:
compMasses = [compMasses[ii] for ii in idx]
idx_noWR = np.where(isWR == False)[0]
mag127m_noWR = mag127m[idx_noWR]
mag139m_noWR = mag139m[idx_noWR]
mag153m_noWR = mag153m[idx_noWR]
magJ_noWR = magJ[idx_noWR]
magH_noWR = magH[idx_noWR]
magKp_noWR = magKp[idx_noWR]
magLp_noWR = magLp[idx_noWR]
num_WR = len(mag127m) - len(idx_noWR)
cluster = dataUtil.DataHolder()
cluster.mass = mass
cluster.Teff = temp
cluster.isWR = isWR
cluster.mag127m = mag127m
cluster.mag139m = mag139m
cluster.mag153m = mag153m
cluster.magJ = magJ
cluster.magH = magH
cluster.magKp = magKp
cluster.magLp = magLp
cluster.isMultiple = isMultiple
cluster.compMasses = compMasses
cluster.systemMasses = systemMasses
cluster.idx_noWR = idx_noWR
cluster.mag127m_noWR = mag127m_noWR
cluster.mag139m_noWR = mag139m_noWR
cluster.mag153m_noWR = mag153m_noWR
cluster.magJ_noWR = magJ_noWR
cluster.magH_noWR = magH_noWR
cluster.magKp_noWR = magKp_noWR
cluster.magLp_noWR = magLp_noWR
cluster.num_WR = num_WR
# Summary parameters
cluster.massLimits = massLimits
cluster.imfSlopes = imfSlopes
cluster.sumIMFmass = clusterMass
cluster.makeMultiples = makeMultiples
cluster.MFamp = MFamp
cluster.MFindex = MFindex
cluster.CSFamp = CSFamp
cluster.CSFindex = CSFindex
cluster.CSFmax = CSFmax
cluster.qMin = qMin
cluster.qIndex = qIndex
return cluster
