def rv(fsci, ftell, rsgmod, xrsg, atspec, hcorr):
"""
Calculate RV for a science spectrum extracted from brighest pixel
Initial guess comes from a cross-correlation for the entire region
This is then improved upon by using specific lines and regions within
the 1.17-1.22um region.
"""
scic = SciComb(pyfits.open(fsci))
# For cross-correlation to rest use telluric index:
it = np.where((scic.x > 1.12) & (scic.x < 1.15))[0]
xtell = scic.x[it]
scixtell = scic.bspec[it]
atxtell = atspec[it]
scixtell_, sr = cc.ccshift(atxtell, scixtell, xtell, quiet=False)
# Implement shift-to-rest (sr) in diagnostic region
xdiag = scic.x[scic.roi]
scidiag = scic.bspec[scic.roi]
atdiag = atspec[scic.roi]
print('[INFO] Shift science spectrum to rest using telluric features:')
scirest, s2 = cc.ccshift(atdiag, scidiag, xdiag, shift1=sr, quiet=False)
# Telluric correct:
print('[INFO] Telluric correct data once shifted onto rest wavelength:')
tellcube = TellCube(ftell)
tspec = tellcube.data[scic.ifu - 1].data
scitc = TellCor(scirest, tspec[scic.roi], scic.x[scic.roi])
# Prepare fake spectrum:
# Match sampling between fake spectrum and observations
# Degrade & resample:
fsam = resam(xrsg, rsgmod, scic.x)
fdeg = degrader(scic.x, fsam, 10000, 3000)
fdiag = fdeg[scic.roi]
print('[INFO] Calculate RV shift:')
scirv, rvs = cc.ccshift(fdiag, scitc.tcor, xdiag, quiet=False, width=20)
rvkms = lambda shift, delta, lam: shift * delta * C / lam
rvi = rvkms(rvs * -1, scic.delt, 1.2)
rvall = rvcorr(rvi, hcorr)
print('[INFO] RV derived using the whole region: {}'.format(rvall))
# Calculate errors:
slbl = linebyline(xdiag, scirv, fdiag) + rvs * -1
slbl = slbl[np.where(slbl != 0.0)]
rvlbl = rvkms(slbl, scic.delt, 1.2)
avrv = rvcorr(np.mean(rvlbl), hcorr)
erv = np.std(rvlbl) / np.sqrt(np.shape(rvlbl)[0])
print('[INFO] Average RV line by line: {} +/- {}'.format(avrv, erv))
print('[INFO] RVs: {}'.format(rvcorr(rvlbl, hcorr)))
return scic, scitc, avrv, erv, sr, rvcorr(rvlbl, hcorr)
def __init__(self, s1, s2, x):
self.sci = s1 / np.median(s1)
self.rawt = s2
self.x = x
self.tcc, self.shift = cc.ccshift(s1, self.rawt, self.x, quiet=False)
self.tsr, self.c = rescale(s1, self.tcc)
self.tcor = self.sci / self.tsr
def linebyline(x, tcspec, fspec):
"""Calculate radial velocity shift for groups of lines individually"""
lines = defidx(x)
# wid = 0.0010
slbl = []
for l in lines:
slbli, tmp = cc.crossc(fspec, tcspec, i1=l[0], i2=l[-1])
slbl = np.append(slbl, slbli * -1)
return slbl
