wei2 = []
# Create jackknife resamples from data
for i in range(len(data)):
l = []
for j in range(len(data)):
if j != i:
l.append(data[j])
resample_data = N.asarray(l)
# Fit continuum for all spectra
for d in resample_data:
d.cont_fit()
# Create a stack of all the deltas
ll2, de2, wst2 = stack_flux(resample_data, 1)
## Create deltas of the stack (of weighted flux)
# Stack the weighted flux
ll1, st1, wst1 = stack_flux(resample_data, 0)
# Fit the continuum for the stack
g = data[0]
d = forest(ll1, st1, wst1, g.thid, g.ra, g.dec, g.zqso, g.plate, g.mjd,
g.fid, g.order)
try:
d.cont_fit()
except:
print 'Error fitting continuum: ' + str(g.thid)
break
# Create deltas and weights in same bin widths as before
# Fit the continua
newdata = []
for d in data:
d.cont_fit()
if d.bad_cont is not None:
print 'bad cont: ' + str(T)
continue
else:
newdata.append(d)
data = N.asarray(newdata)
# Define g in order to retrieve thid, etc for stats, continuum fitting and plot
g = data[0]
# Stack the weighted flux
ll1, st1, wst1 = stack_flux(data, 0)
# Fit the continuum for the stack
d = forest(ll1, st1, wst1, g.thid, g.ra, g.dec, g.zqso, g.plate, g.mjd, g.fid, g.order)
d.cont_fit()
# Create continuum in same bin widths as before
nstack = int((forest.lmax - forest.lmin) / forest.dll) + 1
co1 = sp.zeros(nstack)
bins=((d.ll - d.lmin) / d.dll + 0.5).astype(int)
c = sp.bincount(bins, weights = d.co)
co1[:len(c)] += c
# Get mean flux for each epoch
epochflux = []
for f in data:
epochflux.append(N.sum(f.fl * f.iv)/N.sum(f.iv))
l.append(f)
i += 1
data = N.asarray(l)
# Fit continuum for all spectra
for d in data:
d.cont_fit()
# Define g in order to retrieve thid, etc for plot
try:
g = data[0]
except:
continue
# Create a stack of all the deltas
ll2, de2, wst2 = stack_flux(data, 1)
# Create deltas of the stack (of weighted flux)
# Stack the weighted flux
ll1, st1, wst1 = stack_flux(data, 0)
# Fit the continuum for the stack
d = forest(ll1, st1, wst1, g.thid, g.ra, g.dec, g.zqso, g.plate, g.mjd,
g.fid, g.order)
d.cont_fit()
# Create deltas in same bin widths as before
nstack = int((forest.lmax - forest.lmin) / forest.dll) + 1
de1 = sp.zeros(nstack)
bins = ((d.ll - d.lmin) / d.dll + 0.5).astype(int)
c = sp.bincount(bins, weights=d.fl / d.co - 1)
de1[:len(c)] += c