def format(fname, age, feh, nG, nK, nM, mvG, mvK, mvM, e_bv, use_IMF=False):
ntot = nG + nK + nM
# create arrays of temperature and logg, G : K : M
tf = lambda n, Xmin, Xmax: np.random.uniform(Xmin, Xmax, n)
teffs = np.concatenate((tf(nG, Gmin, Gmax), tf(nK, Kmin, Kmax),
tf(nM, Mmin, Mmax)))
lg = lambda n, logg: np.ones(n) * logg
loggs = np.concatenate((lg(nG, Glogg), lg(nK, Klogg), lg(nM, Mlogg)))
# create arrays of feh, b-v, log(age) and log(teff)
fehs = np.ones(ntot) * feh
bvs = teff2bv_orig(teffs, fehs, loggs) - e_bv
bv_func = lambda n, Xmin, Xmax: np.random.uniform(Xmin, Xmax, n)
bvs = np.concatenate((bv_func(nG, .5, .8), bv_func(nK, .8, 1.1),
tf(nM, 1.1, 1.4)))
logAges = np.ones(ntot) * np.log10(age)
logTeff = np.log10(teffs)
rmag = np.concatenate((V2r(mvG, bvs[:nG]), V2r(mvK, bvs[nG:nG+nK]),
V2r(mvM, bvs[nG+nK:])))
data = np.vstack((logAges, bvs, logTeff, rmag))
np.savetxt("{0}.dat".format(fname), data.T)
return logAges, bvs, logTeff, rmag
def format(fname, age, feh, nG, nK, nM, mvG, mvK, mvM, e_bv, use_IMF=False):
ntot = nG + nK + nM
# create arrays of temperature and logg, G : K : M
tf = lambda n, Xmin, Xmax: np.random.uniform(Xmin, Xmax, n)
teffs = np.concatenate((tf(nG, Gmin, Gmax), tf(nK, Kmin,
Kmax), tf(nM, Mmin, Mmax)))
lg = lambda n, logg: np.ones(n) * logg
loggs = np.concatenate((lg(nG, Glogg), lg(nK, Klogg), lg(nM, Mlogg)))
# create arrays of feh, b-v, log(age) and log(teff)
fehs = np.ones(ntot) * feh
bvs = teff2bv_orig(teffs, fehs, loggs) - e_bv
bv_func = lambda n, Xmin, Xmax: np.random.uniform(Xmin, Xmax, n)
bvs = np.concatenate((bv_func(nG, .5, .8), bv_func(nK, .8,
1.1), tf(nM, 1.1, 1.4)))
logAges = np.ones(ntot) * np.log10(age)
logTeff = np.log10(teffs)
rmag = np.concatenate(
(V2r(mvG, bvs[:nG]), V2r(mvK,
bvs[nG:nG + nK]), V2r(mvM, bvs[nG + nK:])))
data = np.vstack((logAges, bvs, logTeff, rmag))
np.savetxt("{0}.dat".format(fname), data.T)
return logAges, bvs, logTeff, rmag
a_surf = np.linspace(.65, 15, 100)*1000
c_surf = np.linspace(.4, 1.4, 100)
a_surf, c_surf = np.meshgrid(a_surf, c_surf)
p_surf = a_surf**n * a * (c_surf - c)**b
a_surf /= 1000.
# load my data
# data = np.genfromtxt("/Users/angusr/Python/Gyro/data/garcia_all_astero.txt")
# data = np.genfromtxt("/Users/angusr/Python/Gyro/data/garcia_all_astero_no_precise.txt")
data = np.genfromtxt("/Users/angusr/Python/Gyro/data/all_astero_plusgarcia.txt")
t = data[1]
a = data[3]
p = data[6]
logg = data[8]
feh = data[11]
bv = teff2bv_orig(t, logg, feh)
# load precise data
data = np.genfromtxt("/Users/angusr/Python/Gyro/data/vandt.txt", skip_header=1).T
pt = data[1]
pa = data[3]
pp = data[6]
plogg = data[8]
pfeh = data[11]
pbv = teff2bv_orig(pt, plogg, pfeh)
# load cluster and field stars data
data = np.genfromtxt("/Users/angusr/Python/Gyro/data/clusters.txt").T
cbv = data[0]
cp = data[2]
ca = data[4]
# plot
plt.clf()
plt.plot((JK), teff[a], 'k.')
plt.plot(xs, teff_fit, 'b-')
# find teffs
newteff = np.polyval(p, j_k)
plt.plot(j_k, newteff, 'ro')
plt.savefig("JK2teff")
feh = np.zeros_like(newteff)
newlogg = np.zeros_like(newteff)
# find loggs
def find_nearest(array,value):
idx = (np.abs(array-value)).argmin()
return array[idx]
for i, t in enumerate(newteff):
l = teff==find_nearest(teff, t)
newlogg[i] = logg[l][0]
bv = teff2bv_orig(newteff, newlogg, feh)
data = np.zeros((2, len(newteff)))
data[0:] = period
data[1:] = bv
np.savetxt('/Users/angusr/Python/Gyro/data/ComaBer_bv.txt', data.T)
# load Coma Ber
data = np.genfromtxt("/Users/angusr/Python/Gyro/data/ComaBer.txt", skip_header=1).T
j_k = data[2]
# dereddened J-K
j_k = j_k - deltaJK
JK = J-K
# fit a polynomial
a = (.47 < age) * (age < .53) * teff > 3000
JK = J[a] - K[a]
p = np.polyfit(JK, teff[a], 3)
xs = np.linspace(min(JK), max(JK), 1000)
teff_fit = np.polyval(p, xs)
# plot
plt.clf()
plt.plot((JK), teff[a], 'k.')
plt.plot(xs, teff_fit, 'b-')
# find teffs
teff = np.polyval(p, j_k)
print teff
plt.plot(j_k, teff, 'ro')
plt.savefig("JK2teff")
feh = np.zeros_like(teff)
bv = teff2bv_orig(teff, logg, feh)
pl.ylabel("$P_{rot}~\mathrm{(days)}$")
pl.xlabel("$\mathrm{Age~(Gyr)}$")
pl.xlim(0.1, 15)
pl.ylim(0, 70)
pl.savefig('cool_stars5')
# add Amy
data = np.genfromtxt('/Users/angusr/Python/Gyro/data/extra_amy_matched.txt').T
period = np.concatenate((period, data[1]))
period_err = np.concatenate((period_err, data[2]))
teff = np.concatenate((teff, data[3]))
teff_err = np.concatenate((teff_err, data[4]))
age = np.concatenate((age, data[13]))
age_err = np.concatenate((age_err, data[14]))
logg = np.concatenate((logg, data[10]))
bv = teff2bv_orig(teff, logg, np.ones_like(teff)*-.2)
bv_err = np.ones_like(bv)*.01
a_errp = age_err
a_errm = age_err
p_err = period_err
pl.clf()
pl.errorbar(age, period, xerr = (a_errp, a_errm), yerr = p_err, \
color = ocols[1], fmt = 'o', mec = ocols[1], capsize = 0, \
markersize = ms, ecolor = '0.8')
print len(age)
pl.ylabel("$P_{rot}~\mathrm{(days)}$")
pl.xlabel("$\mathrm{Age~(Gyr)}$")
pl.xlim(0.1, 15)
pl.ylim(0, 70)
