def getAverageMagnitude(m, me, idx):
if len(idx) > 1:
m_good = m[idx]
m_weight = 1.0 / me[idx]**2
flux_tmp = 10**(m_good/-2.5)
flux_avg = statsWeighted.mean_wgt(flux_tmp, m_weight)
flux_std = statsWeighted.std_wgt(flux_tmp, m_weight)
m_avg = -2.5 * math.log10(flux_avg)
me_avg = 2.5 * math.log10(math.e) * flux_std / flux_avg
# Use the input magnitude errors if they are larger than
# the spread in the magnitude measurements. This is because
# we have so few measurements for some stars, there is a
# reasonable change that the photometric errors are underestimated.
# This is the conservative thing to do I think.
magerr_avg = me[idx].mean()
if magerr_avg > me_avg:
me_avg = magerr_avg
if len(idx) == 1:
m_avg = m[idx[0]]
me_avg = me[idx[0]]
if len(idx) == 0:
m_avg = 0.0
me_avg = 0.0
return m_avg, me_avg
def getAveragePosition(p, pe, idx):
if (len(idx) > 1):
p_good = p[idx]
p_weight = 1.0 / pe[idx]**2
# Handle a rare case where pe == 0 due to not enough decimals in
# our files.
zeros = np.where(pe[idx] == 0)[0]
non_zeros = np.where(pe[idx] != 0)[0]
if len(zeros) > 0:
min_err = pe[idx[non_zeros]].min()
p_weight[zeros] = 1.0 / (min_err * 0.5)
# for positions, get the weighted average
# for errors, get the straight average
p_avg = statsWeighted.mean_wgt(p_good, p_weight)
#pe_avg = statsWeighted.std_wgt(p_good, p_weight)
pe_avg = pe[idx].mean()
# -------------------
# JLu had this next part originally, but we are already using
# the average error, so not needed...for now
## Use the input magnitude errors if they are larger than
## the spread in the magnitude measurements. This is because
## we have so few measurements for some stars, there is a
## reasonable chance that the photometric errors are underestimated.
## This is the conservative thing to do I think.
#poserr_avg = pe[idx].mean()
#if poserr_avg > pe_avg:
# pe_avg = poserr_avg
# -------------------
if len(idx) == 1:
p_avg = p[idx[0]]
pe_avg = pe[idx[0]]
if len(idx) == 0:
p_avg = 0.0
pe_avg = 0.0
return p_avg, pe_avg
def makeNewRefList(alignRoot, refList, starPrefix='ep0'):
print 'Making new reference list', refList
s = starset.StarSet(alignRoot)
# Get the zeropoint offset to convert to
magRef = s.getArrayFromEpoch(0, 'mag')
magLis = s.getArrayFromEpoch(1, 'mag')
idx = np.where((magRef != 0) & (magLis != 0))[0]
# Only use the first 10 stars
if len(idx) > 10:
idx = idx[0:10]
zp = (magRef[idx] - magLis[idx]).mean()
print 'Zeropoint for %s is %.2f' % (starPrefix, zp)
_out = open(refList, 'w')
for star in s.stars:
inRef = False
inLis = False
if star.e[0].x > -999:
inRef = True
if star.e[1].x > -999:
inLis = True
if inRef and inLis:
name = star.e[0].name
# Rename new stars from the mosaiced images.
# Don't rename reference list sources, so we can reject
# them later on.
if name.startswith('star') and starPrefix != None:
name = star.e[1].name.replace('star', starPrefix)
# get errors and combine them
# centroid, distortion, and residual distortion
xe0 = star.e[0].xpixerr_p
ye0 = star.e[0].ypixerr_p
# centroid, distortion, and residual distortion
xe1 = star.e[1].xpixerr_p
ye1 = star.e[1].ypixerr_p
# align error
xea = star.e[1].xpixerr_a
yea = star.e[1].ypixerr_a
# add the alignment error in quadrature to the frame's other errors
xe1_tot = np.hypot(xe1, xea)
ye1_tot = np.hypot(ye1, yea)
m = star.e[1].mag + zp
# get original and aligned positions, then take weighted ave
# weight by each field's errors (which contain centroid,
# distortion, and residual distortion errors already)
x0 = star.e[0].xpix
y0 = star.e[0].ypix
x1 = star.e[1].xpix
y1 = star.e[1].ypix
xwt0 = 1. / xe0**2
ywt0 = 1. / ye0**2
xwt1 = 1. / xe1_tot**2
ywt1 = 1. / ye1_tot**2
x = statsWeighted.mean_wgt(np.array([x0,x1]), np.array([xwt0,xwt1]))
y = statsWeighted.mean_wgt(np.array([y0,y1]), np.array([ywt0,ywt1]))
# For the next reference list's new positional error, we'll
# take the average error of the ref and lis errors
xerr = (xe0 + xe1_tot) / 2.0
yerr = (ye0 + ye1_tot) / 2.0
else:
if inRef:
name = star.e[0].name
x = star.e[0].xpix
y = star.e[0].ypix
xe = star.e[0].xpixerr_p
ye = star.e[0].ypixerr_p
m = star.e[0].mag
# just maintain the frame's (centroid+distortion+residual)
# errors
xerr = xe
yerr = ye
if inLis:
name = star.e[1].name
# Rename new stars from the narrow camera stuff.
# Don't rename wide camera sources, so we can reject
# them later on.
if name.startswith('star') and starPrefix != None:
name = name.replace('star', starPrefix)
x = star.e[1].xpix
y = star.e[1].ypix
xe = star.e[1].xpixerr_p
ye = star.e[1].ypixerr_p
xea = star.e[1].xpixerr_a
yea = star.e[1].ypixerr_a
m = star.e[1].mag + zp
# just maintain the frame's (centroid+distortion+residual)
# errors.
xerr = xe
yerr = ye
date = star.years[0]
_out.write('%-13s %6.3f %9.4f %11.5f %11.5f %8.5f %8.5f 1 1 1 1\n' %
(name, m, date, x, y, xerr, yerr))
_out.close()