g = data[8] > subgiant
p1 = data[6][g]
p_err1 = data[7][g]
t1 = data[1][g]
t_err1 = data[2][g]
a1 = data[3][g]
a_errp1 = data[4][g]
a_errm1 = data[5][g]
a_err1 = .5 * (a_errp1 + a_errm1)
logg1 = data[8][g]
logg_err1 = .5*(data[9][g]+data[10][g])
feh1 = data[11][g]
feh_err1 = data[12][g]
flag1 = data[13][g]
bv1, bv_err1 = teff2bv_err(t1, logg1, feh1, t_err1, logg_err1, feh_err1)
# add clusters
data = np.genfromtxt("/Users/angusr/Python/Gyro/data/clusters.txt").T
l = (data[4] != 1.1) * (data[4] != .588)
bv2 = data[0][l]; bv_err2 = data[1][l]
p2 = data[2][l]; p_err2 = data[3][l]
a2 = data[4][l]; a_err2 = data[5][l]; a_errp2 = data[5][l]; a_errm2 = data[5][l]
logg2 = data[6][l]; logg_err2 = data[7][l]
flag2 = data[8][l]
# combine astero and cluster
bv = np.concatenate((bv1, bv2))
bv_err = np.concatenate((bv_err1, bv_err2))
p = np.concatenate((p1, p2))
p_err = np.concatenate((p_err1, p_err2))
def load_dat(fname, tn, cv):
# KID[0], t[1], t_err[2], a[3], a_errp[4], a_errm[5], p[6], p_err[7]
# logg[8], logg_errp[9], logg_errm[10], feh[11], feh_err[12], flag[13]
# data = np.genfromtxt('/Users/angusr/Python/Gyro/data/garcia_all_astero.txt')
data = np.genfromtxt('/Users/angusr/Python/Gyro/data/garcia_irfm.txt')
KID = data[0]
t = data[1]
p = data[6]
g = data[8]
# remove periods <= 0 and teff == 0 FIXME: why is this necessary?
l = (p > 0.)*(t > 100.)*(g > 0.) # *(t<5800)
KID = data[0][l]
p = p[l]
p_err = data[7][l]
t = t[l]
t_err = data[2][l]
g = g[l]
g_errp = data[9][l]
g_errm = data[10][l]
a = data[3][l]
a_errp = data[4][l]
a_errm = data[5][l]
feh = data[11][l]
feh_err = data[12][l]
flag = data[13][l]
# pl.clf()
# l = feh!=-0.2
# print feh[l]
# print feh_err[l]
# pl.hist(feh[l]+0.2, 20)
# pl.show()
# raw_input('enter')
# convert temps to bvs
bv_obs, bv_err = teff2bv_err(t, g, feh, t_err, .5*(g_errp+g_errm), feh_err)
# add clusters FIXME: reddening
data = np.genfromtxt("/Users/angusr/Python/noisy-plane/clusters.txt", skip_header=1).T
bv_obs = np.concatenate((bv_obs, data[0]))
bv_err = np.concatenate((bv_err, data[1]))
p = np.concatenate((p, data[2]))
p_err = np.concatenate((p_err, data[3]))
a = np.concatenate((a, data[4]))
a_errp = np.concatenate((a_errp, data[5]))
a_errm = np.concatenate((a_errm, data[5]))
g = np.concatenate((g, data[6]))
g_errp = np.concatenate((g_errp, data[7]))
g_errm = np.concatenate((g_errm, data[7]))
flag = np.concatenate((flag, data[8]))
# obviously comment these lines out if you want to use temps
t = bv_obs
t_err = bv_err
# select star group
flag[flag==2] = 9
flag -= 3
flag[flag<0] = 0
fnames = ['A', 'H', 'P', 'N', 'C', 'F', 'V']
flist = []
for i in range(len(fnames)):
if fname.find(fnames[i]) >= 0:
print fnames[i], i
flist.append(i)
l = (np.sum([flag == i for i in flist], axis=0)) == 1
t = t[l]; t_err = t_err[l]
p = p[l]; p_err = p_err[l]
a = a[l]; a_errp = a_errp[l]; a_errm = a_errm[l]
g = g[l]; g_errp = g_errp[l]; g_errm = g_errm[l]
flag = flag[l]
# reduce errorbars if they go below zero
# (only necessary if you don't use asym)
g_err = .5*(g_errp+g_errm)
a_err = .5*(a_errp + a_errm)
diff = a - a_err
l = diff < 0
a_err[l] = a_err[l] + diff[l] - np.finfo(float).eps
# LOO
if cv:
print 'cv', cv
tn = np.ones_like(a)
select = cv
print select
tn[select] = 0
tn = tn==1
print len(p), len(p[tn])
if cv:
return a[tn], a_err[tn], a_errp[tn], a_errm[tn], p[tn], p_err[tn], \
t[tn], t_err[tn], g[tn], g_err[tn], g_errp[tn], g_errm[tn], flag[tn]
print len(p)
return a, a_err, a_errp, a_errm, p, p_err, t, t_err, g, g_err, g_errp, g_errm, flag
# KID = data[0]
# teff = data[1]
# age = data[3]
# age_errp = data[4]
# age_errm = data[5]
# teff_err = data[2]
# period = data[6]
# period_err = data[7]
# age_err = .5*(age_errp+age_errm)
# logg = data[8]
# logg_errp = data[9]
# logg_errm = data[10]
# logg_err = .5*(logg_errp+logg_errm)
# feh = data[11]
# feh_err = data[12]
bv, bv_err = teff2bv_err(teff, logg, feh, teff_err, logg_err, feh_err)
# cool dwarfs
pl.clf()
# bv -= kb
pl.errorbar(bv, period, yerr=period_err, xerr=bv_err, color=ocols[1], mec=ocols[1], \
ecolor='.7', capsize=0, fmt='.', markersize=ms)
xp, yp = iso(1000.)
# xp -= .4
pl.plot(xp, yp, linestyle='--', color='.75', label=lab)
xp, yp = iso(2000.)
# xp -= .4
pl.plot(xp, yp, linestyle='--', color='.75')
xp, yp = iso(5000.)
# xp -= .4
pl.plot(xp, yp, linestyle='--', color='.75')
KID = data[0][l]
t1 = data[1][l]
t1_err = data[2][l]
a1 = data[3][l]
a1_errp = data[4][l]
a1_errm = data[5][l]
a1_err = .5*(a1_errp+a1_errm)
p1 = data[6][l]
p1_err = data[7][l]
logg1 = data[8][l]
logg1_errp = data[9][l]
logg1_errm = data[10][l]
logg1_err = .5*(logg1_errp+logg1_errm)
feh1 = data[11][l]
feh1_err = data[12][l]
bv1, bv1_err = teff2bv_err(t1, logg1, feh1, t1_err, logg1_err, feh1_err)
# load travis and victor data
data = np.genfromtxt("/Users/angusr/Python/Gyro/data/vandt.txt", skip_header=1).T
vtKID = data[0]
vtt = data[1]
vtt_err = data[2]
vta = data[3]
vta_errp = data[4]
vta_errm = data[5]
vta_err = .5*(vta_errp+vta_errm)
vtp = data[6]
vtp_err = data[7]
vtlogg = data[8]
vtlogg_errp = data[9]
vtlogg_errm = data[10]
data = np.genfromtxt('/Users/angusr/Python/Gyro/data/garcia_all_astero.txt')
t = data[1]
t_err = data[2]
a = data[3]
a_errp = data[4]
a_errm = data[5]
a_err = .5*(a_errp+a_errm)
p = data[6]
p_err = data[7]
logg = data[8]
logg_errp = data[9]
logg_errm = data[10]
logg_err = .5*(logg_errp+logg_errm)
feh = data[11]
feh_err = data[12]
bv, bv_err = teff2bv_err(t, logg, feh, t_err, logg_err, feh_err)
# periods1 = np.zeros_like(p)
# period_errs1 = np.zeros_like(p)
# periods2 = np.zeros_like(p)
# period_errs2 = np.zeros_like(p)
# for i, ps in enumerate(p):
# periods1[i], period_errs1[i] = MC_errors(pars, errp, errm, a[i], a_err[i], bv[i], bv_err[i], c, nsamp, period_model, model)
# periods2[i], period_errs2[i] = MC_errors_simple(pars, errp, errm, a[i], bv[i], c, nsamp, period_model, model)
# l1 = (period_errs1>0) * (periods1>0)
# l2 = (period_errs2>0) * (periods2>0)
# print 'Typical uncertainty on rotation period, given typical observational uncertainties:'
# print np.median(period_errs1[l1]/periods1[l1])*100, '%'
#
# print 'Typical intrinsic uncertainty on rotation period:'
data = np.genfromtxt('/Users/angusr/Python/Gyro/data/all_astero_plusgarcia.txt')
teff = data[1]
teff_err = data[2]
age = data[3]
age_errp = data[4]
age_errm = data[5]
age_err = .5*(age_errp+age_errm)
period = data[6]
period_err = data[7]
logg = data[8]
logg_errp = data[9]
logg_errm = data[10]
logg_err = .5*(logg_errp+logg_errm)
feh = data[11]
feh_err = data[11]
bv, bv_err = teff2bv_err(teff, logg, feh, teff_err, logg_err, feh_err)
a_errp = age_errp
a_errm = age_errm
p_err = period_err
print period
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')
pl.ylabel("$P_{rot}~\mathrm{(days)}$")
pl.xlabel("$\mathrm{Age~(Gyr)}$")
pl.xlim(0.1, 15)
pl.ylim(0, 70)
pl.savefig('cool_stars5')