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rot_conv.py
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rot_conv.py
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#!/usr/bin/python
import numpy as np
import scipy
import Cfunctions
from scipy import optimize
from scipy import interpolate
from scipy.interpolate import griddata
def conv2(lam,flu,ac,bc,rot):
lux = 299792.458
WAV = np.array([3530,4860,6260,7670,8350])
"""Determining Limb Darkening Coefficients"""
tck = interpolate.splrep(WAV,ac,k=3,s=0)
A = interpolate.splev(lam,tck,der=0)
tck = interpolate.splrep(WAV,bc,k=3,s=0)
B = interpolate.splev(lam,tck,der=0)
F = flu.copy()
MIN = lam * ( 1. - float(rot) / lux )
MAX = lam * ( 1. + float(rot) / lux )
lar = len(F)
if rot > 0.0:
H = Cfunctions.Conv(lam.astype("double"),flu.astype("double"),F.astype("double"), \
A.astype("double"),B.astype("double"),MIN.astype("double"),MAX.astype("double"),rot,lar)
else:
H = flu
Fnu = np.array(H)
return Fnu
def get_ldcoef(TEFF, LOG_G, FEH, MT, path = 'qua_coe_sloan2.dat'):
f = open(path,'r')
lines = f.readlines()
f.close()
if MT == 1:
FEH =0.
else:
if FEH < -2.5:
FEH = 2.5
elif FEH > 0.5:
FEH = 0.5
if TEFF < 3500:
TEFF = 3500
if LOG_G > 5.0:
LOG_G = 5.0
th = np.loadtxt(path)
n1 = th[:,0]
qc = th[:,1]
tur = th[:,2]
lg = th[:,3]
te = th[:,4]
me = th[:,5]
su = th[:,6]
sg = th[:,7]
sr = th[:,8]
si = th[:,9]
sz = th[:,10]
I = np.where(tur == MT)[0]
qc = qc[I]
te = te[I]
lg = lg[I]
me = me[I]
su = su[I]
sg = sg[I]
sr = sr[I]
si = si[I]
sz = sz[I]
I = np.where( (np.absolute(lg - LOG_G) <= 1) & (np.absolute(me - FEH) <= 1) & (np.absolute(te - TEFF) <= 500) )[0]
qc = qc[I]
te = te[I]
lg = lg[I]
me = me[I]
su = su[I]
sg = sg[I]
sr = sr[I]
si = si[I]
sz = sz[I]
I = np.where(qc == 0.)[0]
W = np.where(qc == 1.)[0]
if MT == 2.:
apoints = np.zeros((len(I),3))
apoints[:,0] = te[I]
apoints[:,1] = lg[I]
apoints[:,2] = me[I]
bpoints = np.zeros((len(W),3))
bpoints[:,0] = te[W]
bpoints[:,1] = lg[W]
bpoints[:,2] = me[W]
asu = griddata(apoints, su[I], (TEFF, LOG_G, FEH), method='linear')
asg = griddata(apoints, sg[I], (TEFF, LOG_G, FEH), method='linear')
asr = griddata(apoints, sr[I], (TEFF, LOG_G, FEH), method='linear')
asi = griddata(apoints, si[I], (TEFF, LOG_G, FEH), method='linear')
asz = griddata(apoints, sz[I], (TEFF, LOG_G, FEH), method='linear')
bsu = griddata(bpoints, su[W], (TEFF, LOG_G, FEH), method='linear')
bsg = griddata(bpoints, sg[W], (TEFF, LOG_G, FEH), method='linear')
bsr = griddata(bpoints, sr[W], (TEFF, LOG_G, FEH), method='linear')
bsi = griddata(bpoints, si[W], (TEFF, LOG_G, FEH), method='linear')
bsz = griddata(bpoints, sz[W], (TEFF, LOG_G, FEH), method='linear')
else:
apoints = np.zeros((len(I),2))
apoints[:,0] = te[I]
apoints[:,1] = lg[I]
bpoints = np.zeros((len(W),2))
bpoints[:,0] = te[W]
bpoints[:,1] = lg[W]
asu = griddata(apoints, su[I], (TEFF, LOG_G), method='linear')
asg = griddata(apoints, sg[I], (TEFF, LOG_G), method='linear')
asr = griddata(apoints, sr[I], (TEFF, LOG_G), method='linear')
asi = griddata(apoints, si[I], (TEFF, LOG_G), method='linear')
asz = griddata(apoints, sz[I], (TEFF, LOG_G), method='linear')
bsu = griddata(bpoints, su[W], (TEFF, LOG_G), method='linear')
bsg = griddata(bpoints, sg[W], (TEFF, LOG_G), method='linear')
bsr = griddata(bpoints, sr[W], (TEFF, LOG_G), method='linear')
bsi = griddata(bpoints, si[W], (TEFF, LOG_G), method='linear')
bsz = griddata(bpoints, sz[W], (TEFF, LOG_G), method='linear')
ac = np.array([asu,asg,asr,asi,asz])
bc = np.array([bsu,bsg,bsr,bsi,bsz])
return ac,bc
def get_ldcoef2(TEFF, LOG_G, FEH, MT, path = 'qua_coe_sloan2.dat'):
d = np.loadtxt(path)
ldn = d[:,1].astype('int')
ms = d[:,2]
ts = d[:,4]
ats = np.unique(ts)
gs = d[:,3]
ags = np.unique(gs)
zs = d[:,5]
azs = np.unique(zs)
TT = ats[np.argmin((ats - TEFF)**2)]
GG = ags[np.argmin((ags - LOG_G)**2)]
ZZ = azs[np.argmin((azs - FEH)**2)]
cond = True
I = np.where((ts==TT) & (gs==GG) & (zs==ZZ))[0]
if len(I)>0:
cond = False
deltz = 0.1
while cond:
ZZ1 = ZZ - deltz
ZZ2 = ZZ + deltz
I = np.where((ts==TT) & (gs==GG) & (zs==ZZ1))[0]
if len(I)>0:
cond = False
ZZ = ZZ1
break
I = np.where((ts==TT) & (gs==GG) & (zs==ZZ2))[0]
if len(I)>0:
cond = False
ZZ = ZZ2
break
ams = np.unique(ms[I])
MM = ams[np.argmin((ams - MT)**2)]
Ia = np.where((ts==TT) & (gs==GG) & (zs==ZZ) & (ms==MM) & (ldn==0))[0][0]
Ib = np.where((ts==TT) & (gs==GG) & (zs==ZZ) & (ms==MM) & (ldn==1))[0][0]
ac = d[Ia][6:]
bc = d[Ib][6:]
return ac,bc