wavemax=6800., intwave=None):

hdu = pyfits.open(datafile)[0]

numfibers, wavesize = hdu.data.shape

head = hdu.header

cdelt = head['CDELT1']

crval = head['CRVAL1']

crpix = head['CRPIX1']

print 'CDELT1 = ', cdelt

print 'CRVAL1 = ', crval

print 'CRPIX1 = ', crpix

wave = (np.arange(wavesize) - crpix) * cdelt + crval

idx = np.where((wave >= wavemin) & (wave <= wavemax))

redwl = wave[idx]

redchiarray = pyfits.open(chifile)[0].data

coeff = pyfits.open(coeffile)[1].data

meanZ = np.mean(coeff['VSYS'])/3e5 + 1

# Shift all chi's to rest frame

restwl = redwl/(meanZ/3e5 + 1)

if intwave is None:

chiarray = np.zeros(redchiarray.shape)

else:

chiarray = np.zeros((redchiarray.shape[0],intwave.size))

for i in range(redchiarray.shape[0]):

tl = redwl/(coeff['VSYS'][i]/3e5 + 1)

tc = np.interp(restwl,tl,redchiarray[i,:])

if intwave is None:

chiarray[i,:] = tc

else:

chiarray[i,:] = np.interp(intwave, restwl, tc)

### Segregate by fiber size

size = np.loadtxt(location, usecols=(1,), unpack=True)

outputlist = []

for s in np.unique(size):

idx = np.where(size == s)[0]

outputlist.append(chiarray[idx,:])

fib2 = []

fib3 = []

fib4 = []

fib5 = []

fib6 = []

intwave = None

for p in range(6):

base = 'NGC_891_P{}_bin30_allz2'.format(p+1)

chifile = '{}.chi.fits'.format(base)

coeffile = '{}.coef.fits'.format(base)

datafile = 'NGC_891_P{}_bin30.ms.fits'.format(p+1)

location = 'NGC_891_P{}_bin30_locations.dat'.format(p+1)

plist, tw, tZ = size_bin(chifile, coeffile, datafile, location,

intwave=intwave)

if p == 0:

intwave = tw

restwl = tw

meanZ = tZ

fib2.append(plist[0])

fib3.append(plist[1])

fib4.append(plist[2])

fib5.append(plist[3])

fib6.append(plist[4])

if plotblue:

outname = '{}_sizechi.blue.pdf'.format(output)

else:

outname = '{}_sizechi.pdf'.format(output)

pp = PDF(outname)

for s in range(5):

print s+2

chiarray = np.vstack(plist[s])

medchi = np.median(chiarray, axis=0)

mschi = spnd.filters.median_filter(medchi,50)

rms = np.sqrt(np.mean((chiarray - medchi[None,:])**2, axis=0))

nidx = np.isfinite(medchi)

medchi = medchi[nidx]

stdchi = rms[nidx]

mchi = mschi[nidx]

restwl = restwl[nidx]

sk2 = np.array([6300., 5890., 5577.])

# em2 = np.array([6563.8, 4861., 4959., 5006.8, 6716.0, 6583.41, 6548.04])

em2 = np.array([6563.8, 6716.0, 6583.41, 6548.04])

dz = 1500. / 3e5

dzsk = 1500. / 3e5

quality = np.ones(restwl.size)

for ee in em2:

maskout = np.where((restwl > ee*(1-dz)) & (restwl < ee*(1+dz)))

quality[maskout] = 0

for ss in sk2:

maskout = np.where((restwl > ss*(1-dzsk)) & (restwl < ss*(1+dzsk)))

quality[maskout] = 0

ok = quality == 1

if plotblue:

pidx = np.where(restwl < 4500.)

else:

pidx = np.where(restwl == restwl)

fig = plt.figure(figsize=(11,8))

fig.suptitle("{}'' fibers".format(s+2))

rmax = fig.add_subplot(211)

rmax.set_ylabel('<Chi> - Med(<Chi>)')

rmax.set_xlim(restwl[pidx].min(),restwl[pidx].max())

rmax.set_xticklabels([])

rmax.set_ylim(-5,5)

medax = fig.add_subplot(212)

medax.set_xlabel('Wavelength [$\AA$]')

medax.set_ylabel('Median smoothed Chi')

medax.set_xlim(restwl[pidx].min(),restwl[pidx].max())

medax.set_ylim(-5,5)

prms = medchi - mschi

mrms = np.copy(prms)

mrms[ok] = np.NAN

prms[~ok] = np.NAN

rmax.plot(restwl[pidx], prms[pidx], 'k')

rmax.plot(restwl[pidx], mrms[pidx], 'c', lw=3)

pmchi = np.copy(mchi)

mmchi = np.copy(mchi)

mmchi[ok] = np.NAN

pmchi[~ok] = np.NAN

medax.plot(restwl[pidx],pmchi[pidx],'k')

medax.plot(restwl[pidx],mmchi[pidx],'c',lw=3)

medax.fill_between(restwl[pidx], (mchi - stdchi)[pidx],

(mchi + stdchi)[pidx],

color='k', alpha=0.2, edgecolor=None)

sk = np.array([6300., 5890., 5683.8, 5577., 5461., 5199., 4983., 4827.32, 4665.69, 4420.23, 4358., 4165.68, 4047.0])

sknam = ['[OI] (atm)', 'NaD', 'NaI', 'OI (atm)', 'HgI', 'NI (atm)', 'NaI', 'HgI', 'NaI', 'NaI', 'HgI', 'NaI', 'HgI']

em = np.array([6563.8, 6716.0])

emnam = [r'H$\alpha$', 'S2']

ab = np.array([3820.4, 3835.4, 3889.0, 3933.7, 3968.5, 3970.18, 4304.4, 4341., 5175.3, 5894.0, 4861., 4102., 3820.4])

absnam = ['L', r'H$\eta$', r'H$\zeta$', 'K', 'H' , r'H$\epsilon$', 'G', r'H$\gamma$', 'Mg', 'Na', r'H$\beta$', r'H$\delta$', 'L']

ypos = 1

for s, sn in zip(sk/meanZ, sknam):

if s > 5500. and plotblue: continue

tidx = np.where((restwl >= s - 10) & (restwl <= s + 10.))

try:

ypos = np.max(mchi[tidx]) + 3

except ValueError:

pass

if not np.isfinite(ypos):

ypos = 9

rmax.text(s, ypos, sn, fontsize=8, ha='center', va='center')

if plotblue:

rmax.axvline(s, color='k', ls=':', alpha=0.7)

else:

rmax.plot((s,s), (ypos - 0.5, ypos - 1), alpha=0.8, color='k')

prevy = 99

for a, an in zip(ab, absnam):

if a > 5500. and plotblue: continue

tidx = np.where((restwl >= a - 10) & (restwl <= a + 10.))

try:

ypos = np.min(mchi[tidx]) - 2

except ValueError:

pass

if (an == r'H$\gamma$' or

an == r'H$\eta$' or

an == r'H$\epsilon$') and np.abs(ypos - prevy) <= 0.5:

ypos -= 1

prevy = ypos

if np.isnan(ypos) or ypos < rmax.get_ylim()[0]:

ypos = rmax.get_ylim()[0] + 0.5

rmax.text(a, ypos, an, color='r', fontsize=8, ha='center', va='center')

if plotblue:

rmax.axvline(a, color='r', ls=':', alpha=0.7)

else:

rmax.plot((a,a), (ypos + 0.5, ypos + 1), color='r', alpha=0.8)

for e, en in zip(em, emnam):

if e > 5500. and plotblue: continue

tidx = np.where((restwl >= e - 10) & (restwl <= e + 10.))

try:

ypos = np.max(mchi[tidx]) + 3

except ValueError:

pass

if not np.isfinite(ypos):

ypos = 9

rmax.text(e, ypos, en, color='b', fontsize=8, ha='center', va='center')

if plotblue:

rmax.axvline(e, color='b', ls=':', alpha=0.7)

else:

rmax.plot((e,e), (ypos - 0.5, ypos - 1), color='b', alpha=0.8)

fig.subplots_adjust(hspace=0.0001)

pp.savefig(fig)

plt.close(fig)

pp.close()