def apply_flat(scifilename, maskname, band):
''' Divides the contents of scifilename by the flat field and
overwrites scifilename with the same file divided by the flat
Args:
scifilename: Path to science file name.
maskname: The mask name
band: The filter bands
Results:
Overwrites scifilename where the data contents of the file
are divided by the pixel flat
'''
flat = IO.load_flat(maskname, band, {})
flat_data = flat[1].filled(1.0)
header, data = IO.readfits(scifilename)
print("Applying flat to file {0}".format(scifilename))
IO.writefits(data / flat_data,
maskname,
scifilename, {},
header=header,
overwrite=True)
def imcombine(filelist, maskname, fname, options, sum_type):
""" combine the images in file list into fname.
Sum type:
rate -- filelist is in cnt/s
ivar-rate -- filelist is in s/cnt
snr-rate -- filelist is in SNR
"""
ARR = None
hdr = None
i = 1
itime = 0
for file in filelist:
this_hdr, img = IO.readfits(file)
cards = this_hdr.ascardlist()
thisitime = this_hdr["truitime"]
itime += thisitime
if ARR is None:
ARR = np.zeros(img.shape)
if sum_type == "rate":
ARR += img * thisitime
if sum_type == "ivar-rate":
ARR += thisitime / img
if sum_type == "snr-rate":
ARR += img * thisitime
if hdr is None:
hdr = this_hdr
hdr.update("fno%2.2i" % i, file, "--")
for card in cards:
key, value, comment = (card.key, card.value, card.comment)
if hdr.has_key(key) and hdr[key] != value:
key = key + ("_img%2.2i" % i)
if len(key) > 8:
key = "HIERARCH " + key
try:
hdr.update(key, value, comment)
except ValueError:
pass
hdr.update("itime", itime, "Itime for %i rectified images" % len(filelist))
if sum_type == "rate":
ARR /= itime
if sum_type == "ivar-rate":
ARR = itime / ARR
if sum_type == "snr-rate":
ARR /= itime
IO.writefits(ARR, maskname, fname, options, header=hdr, overwrite=True, lossy_compress=True)
def imcombine(filelist, maskname, fname, options, sum_type):
''' combine the images in file list into fname.
Sum type:
rate -- filelist is in cnt/s
ivar-rate -- filelist is in s/cnt
snr-rate -- filelist is in SNR
'''
ARR = None
hdr = None
i = 1
itime = 0
for file in filelist:
this_hdr, img = IO.readfits(file)
cards = this_hdr.ascardlist()
thisitime = this_hdr['truitime']
itime += thisitime
if ARR is None: ARR = np.zeros(img.shape)
if sum_type == 'rate': ARR += img * thisitime
if sum_type == 'ivar-rate': ARR += thisitime / img
if sum_type == 'snr-rate': ARR += img * thisitime
if hdr is None:
hdr = this_hdr
hdr["fno%2.2i" % i] = (file, "--")
for card in cards:
key, value, comment = (card.key, card.value, card.comment)
if hdr.has_key(key) and hdr[key] != value:
key = key + ("_img%2.2i" % i)
if len(key) > 8: key = 'HIERARCH ' + key
try:
hdr[key] = (value, comment)
except ValueError:
pass
hdr['itime'] = (itime, 'Itime for %i rectified images' % len(filelist))
if sum_type == 'rate': ARR /= itime
if sum_type == 'ivar-rate': ARR = itime / ARR
if sum_type == 'snr-rate': ARR /= itime
IO.writefits(ARR,
maskname,
fname,
options,
header=hdr,
overwrite=True,
lossy_compress=True)
def rectify(dname, lamdat, A, B, maskname, band, wavoptions, longoptions):
header, data = IO.readfits(dname)
raw_img = data * Detector.gain / header['TRUITIME']
dlam = Wavelength.grating_results(band)
hpp = np.array(Filters.hpp[band])
ll_fid = np.arange(hpp[0], hpp[1], dlam)
rectified = np.zeros((2048, len(ll_fid)))
from scipy.interpolate import interp1d
for i in xrange(2048):
ll = lamdat[i, :]
ss = raw_img[i, :]
ok = np.isfinite(ll) & np.isfinite(ss) & (ll < hpp[1]) & (ll > hpp[0])
if len(np.where(ok)[0]) < 30:
continue
f = interp1d(ll[ok], ss[ok], bounds_error=False)
rectified[i, :] = f(ll_fid)
header.update("wat0_001", "system=world")
header.update("wat1_001", "wtype=linear")
header.update("wat2_001", "wtype=linear")
header.update("dispaxis", 1)
header.update("dclog1", "Transform")
header.update("dc-flag", 0)
header.update("ctype1", "AWAV")
header.update("cunit1", "Angstrom")
header.update("crval1", ll_fid[0])
header.update("crval2", 0)
header.update("crpix1", 1)
header.update("crpix2", 1)
header.update("cdelt1", 1)
header.update("cdelt2", 1)
header.update("cname1", "angstrom")
header.update("cname2", "pixel")
header.update("cd1_1", dlam)
header.update("cd1_2", 0)
header.update("cd2_1", 0)
header.update("cd2_2", 1)
header.update("object", "rectified [eps]")
IO.writefits(rectified,
maskname,
"rectified_%s" % (dname),
wavoptions,
header=header,
overwrite=True,
lossy_compress=True)
def audit(filename):
header, data = IO.readfits(filename)
ll0 = header['crval1']
dlam = header['cd1_1']
ls = ll0 + dlam * np.arange(data.shape[1])
linelist = Wavelength.pick_linelist(header)
deltas = []
sigs = []
xpos = []
ys = []
for y in np.linspace(750, 1100, 30):
#for y in np.linspace(5, 640, 50):
sp = np.ma.array(data[y,:])
xs, sxs, sigmas = Wavelength.find_known_lines(linelist, ls, sp,
Options.wavelength)
xpos.append(xs)
ys.append([y] * len(xs))
deltas.append(xs - (linelist - ll0)/dlam)
sigs.append(sxs)
xpos, ys, deltas, sigs = map(np.array, [xpos, ys, deltas, sigs])
deltas[np.abs(deltas) > .75] = np.nan
sigs[np.abs(sigs) > .001] = np.nan
pl.clf()
size = 0.003/sigs
size[size > 30] = 30
size[size < 1] = 1
pl.scatter( xpos, ys, c=deltas, s=size)
pl.xlim([0, data.shape[1]])
pl.ylim([0, data.shape[0]])
pl.xlabel("Spectral pixel")
pl.ylabel("Spatial pixel")
pl.title("Night sky line deviation from solution [pixel]")
pl.colorbar()
pl.savefig("audit.pdf")
pdb.set_trace()
def rectify(dname, lamdat, A, B, maskname, band, wavoptions,
longoptions):
header, data = IO.readfits(dname)
raw_img = data * Detector.gain / header['TRUITIME']
dlam = Wavelength.grating_results(band)
hpp = np.array(Filters.hpp[band])
ll_fid = np.arange(hpp[0], hpp[1], dlam)
rectified = np.zeros((2048, len(ll_fid)))
from scipy.interpolate import interp1d
for i in xrange(2048):
ll = lamdat[i,:]
ss = raw_img[i,:]
ok = np.isfinite(ll) & np.isfinite(ss) & (ll < hpp[1]) & (ll >
hpp[0])
if len(np.where(ok)[0]) < 30:
continue
f = interp1d(ll[ok], ss[ok], bounds_error=False)
rectified[i,:] = f(ll_fid)
header.update("wat0_001", "system=world")
header.update("wat1_001", "wtype=linear")
header.update("wat2_001", "wtype=linear")
header.update("dispaxis", 1)
header.update("dclog1", "Transform")
header.update("dc-flag", 0)
header.update("ctype1", "AWAV")
header.update("cunit1", "Angstrom")
header.update("crval1", ll_fid[0])
header.update("crval2", 0)
header.update("crpix1", 1)
header.update("crpix2", 1)
header.update("cdelt1", 1)
header.update("cdelt2", 1)
header.update("cname1", "angstrom")
header.update("cname2", "pixel")
header.update("cd1_1", dlam)
header.update("cd1_2", 0)
header.update("cd2_1", 0)
header.update("cd2_2", 1)
header.update("object", "rectified [eps]")
IO.writefits(rectified, maskname, "rectified_%s" % (dname),
wavoptions, header=header, overwrite=True, lossy_compress=True)
def audit(filename):
header, data = IO.readfits(filename)
ll0 = header['crval1']
dlam = header['cd1_1']
ls = ll0 + dlam * np.arange(data.shape[1])
linelist = Wavelength.pick_linelist(header)
deltas = []
sigs = []
xpos = []
ys = []
for y in np.linspace(750, 1100, 30):
#for y in np.linspace(5, 640, 50):
sp = np.ma.array(data[y, :])
xs, sxs, sigmas = Wavelength.find_known_lines(linelist, ls, sp,
Options.wavelength)
xpos.append(xs)
ys.append([y] * len(xs))
deltas.append(xs - (linelist - ll0) / dlam)
sigs.append(sxs)
xpos, ys, deltas, sigs = map(np.array, [xpos, ys, deltas, sigs])
deltas[np.abs(deltas) > .75] = np.nan
sigs[np.abs(sigs) > .001] = np.nan
pl.clf()
size = 0.003 / sigs
size[size > 30] = 30
size[size < 1] = 1
pl.scatter(xpos, ys, c=deltas, s=size)
pl.xlim([0, data.shape[1]])
pl.ylim([0, data.shape[0]])
pl.xlabel("Spectral pixel")
pl.ylabel("Spatial pixel")
pl.title("Night sky line deviation from solution [pixel]")
pl.colorbar()
pl.savefig("audit.pdf")
pdb.set_trace()
def apply_flat(scifilename, maskname, band):
''' Divides the contents of scifilename by the flat field and
overwrites scifilename with the same file divided by the flat
Args:
scifilename: Path to science file name.
maskname: The mask name
band: The filter bands
Results:
Overwrites scifilename where the data contents of the file
are divided by the pixel flat
'''
flat = IO.load_flat(maskname, band, {})
flat_data = flat[1].filled(1.0)
header, data = IO.readfits(scifilename)
print("Applying flat to file {0}".format(scifilename))
IO.writefits(data/flat_data, maskname, scifilename, {}, header=header,
overwrite=True)
def handle_rectification(maskname, in_files, wavename, band_pass, files, options,
commissioning_shift=3.0, target='default'):
'''Handle slit rectification and coaddition.
Args:
maskname: The mask name string
in_files: List of stacked spectra in electron per second. Will look
like ['electrons_Offset_1.5.txt.fits', 'electrons_Offset_-1.5.txt.fits']
wavename: path (relative or full) to the wavelength stack file, string
band_pass: Band pass name, string
barset_file: Path to a mosfire fits file containing the full set of
FITS extensions for the barset. It can be any file in the list
of science files.
Returns:
None
Writes files:
[maskname]_[band]_[object name]_eps.fits --
The rectified, background subtracted, stacked eps spectrum
[maskname]_[band]_[object name]_sig.fits --
Rectified, background subtracted, stacked weight spectrum (STD/itime)
[maskname]_[band]_[object_name]_itime.fits
Rectified, CRR stacked integration time spectrum
[maskname]_[band]_[object_name]_snrs.fits
Rectified signal to noise spectrum
'''
global edges, dats, vars, itimes, shifts, lambdas, band, fidl, all_shifts
band = band_pass
dlambda = Wavelength.grating_results(band)
hpp = Filters.hpp[band]
fidl = np.arange(hpp[0], hpp[1], dlambda)
lambdas = IO.readfits(wavename, options)
if np.any(lambdas[1].data < 0) or np.any(lambdas[1].data > 29000):
info("***********WARNING ***********")
info("The file {0} may not be a wavelength file.".format(wavename))
info("Check before proceeding.")
info("***********WARNING ***********")
edges, meta = IO.load_edges(maskname, band, options)
shifts = []
posnames = []
postoshift = {}
for file in in_files:
info(":: "+str(file))
II = IO.read_drpfits(maskname, file, options)
off = np.array((II[0]["decoff"], II[0]["raoff"]),dtype=np.float64)
if "yoffset" in II[0]:
off = -II[0]["yoffset"]
else:
# Deal with data taken during commissioning
if II[0]["frameid"] == 'A': off = 0.0
else: off = commissioning_shift
try: off0
except: off0 = off
shift = off - off0
shifts.append(shift)
posnames.append(II[0]["frameid"])
postoshift[II[0]['frameid']] = shift
info("Position {0} shift: {1:2.2f} as".format(off, shift))
# this is to deal with cases in which we want to rectify one single file
if len(set(posnames)) is 1:
plans = [['A']]
else:
plans = Background.guess_plan_from_positions(set(posnames))
all_shifts = []
for plan in plans:
to_append = []
for pos in plan:
to_append.append(postoshift[pos])
all_shifts.append(to_append)
# Reverse the elements in all_shifts to deal with an inversion
all_shifts.reverse()
theBPM = IO.badpixelmask()
all_solutions = []
cntr = 0
if target is 'default':
outname = maskname
else:
outname = target
for plan in plans:
if len(plan) is 1:
p0 = 'A'
p1 = 'B'
else:
p0 = plan[0].replace("'", "p")
p1 = plan[1].replace("'", "p")
suffix = "%s-%s" % (p0,p1)
info("Handling plan %s" % suffix)
fname = "bsub_{0}_{1}_{2}.fits".format(outname,band,suffix)
EPS = IO.read_drpfits(maskname, fname, options)
EPS[1] = np.ma.masked_array(EPS[1], theBPM, fill_value=0)
fname = "var_{0}_{1}_{2}.fits".format(outname, band, suffix)
VAR = IO.read_drpfits(maskname, fname, options)
VAR[1] = np.ma.masked_array(VAR[1], theBPM, fill_value=np.inf)
fname = "itime_{0}_{1}_{2}.fits".format(outname, band, suffix)
ITIME = IO.read_drpfits(maskname, fname, options)
ITIME[1] = np.ma.masked_array(ITIME[1], theBPM, fill_value=0)
dats = EPS
vars = VAR
itimes = ITIME
EPS[0]["ORIGFILE"] = fname
tock = time.time()
sols = range(len(edges)-1,-1,-1)
shifts = all_shifts[cntr]
cntr += 1
p = Pool()
solutions = p.map(handle_rectification_helper, sols)
p.close()
all_solutions.append(solutions)
tick = time.time()
info("-----> Mask took %i. Writing to disk." % (tick-tock))
output = np.zeros((1, len(fidl)))
snrs = np.zeros((1, len(fidl)))
sdout= np.zeros((1, len(fidl)))
itout= np.zeros((1, len(fidl)))
# the barset [bs] is used for determining object position
files = IO.list_file_to_strings(files)
info("Using "+str(files[0])+" for slit configuration.")
x, x, bs = IO.readmosfits(files[0], options)
for i_slit in xrange(len(solutions)):
solution = all_solutions[0][i_slit]
header = EPS[0].copy()
obj = header['OBJECT']
target_name = bs.ssl[-(i_slit+1)]['Target_Name']
header['OBJECT'] = target_name
pixel_dist = np.float(bs.ssl[-(i_slit+1)]['Target_to_center_of_slit_distance'])/0.18
pixel_dist -= solution['offset']
ll = solution["lambda"]
header["wat0_001"] = "system=world"
header["wat1_001"] = "wtype=linear"
header["wat2_001"] = "wtype=linear"
header["dispaxis"] = 1
header["dclog1"] = "Transform"
header["dc-flag"] = 0
header["ctype1"] = "AWAV"
header["cunit1"] = "Angstrom"
header["crval1"] = ll[0]
header["crval2"] = -solution["eps_img"].shape[0]/2 - pixel_dist
header["crpix1"] = 1
header["crpix2"] = 1
#remove redundant CDELTi due to wavelength issues with ds9
#see: https://github.com/Keck-DataReductionPipelines/MosfireDRP/issues/44
#header["cdelt1"] = 1
#header["cdelt2"] = 1
header["cname1"] = "angstrom"
header["cname2"] = "pixel"
header["cd1_1"] = ll[1]-ll[0]
header["cd1_2"] = 0
header["cd2_1"] = 0
header["cd2_2"] = 1
try:
header["BARYCORR"]= (lambdas[0]['BARYCORR'],lambdas[0].comments['BARYCORR'])
except KeyError:
warning( "Barycentric corrections not applied to the wavelength solution")
pass
S = output.shape
img = solution["eps_img"]
std = solution["sd_img"]
tms = solution["itime_img"]
for i_solution in xrange(1,len(all_solutions)):
info("Combining solution %i" %i_solution)
solution = all_solutions[i_solution][i_slit]
img += solution["eps_img"]
std += solution["sd_img"]
tms += solution["itime_img"]
#print "adding in quadrature"
output = np.append(output, img, 0)
output = np.append(output, np.nan*np.zeros((3,S[1])), 0)
snrs = np.append(snrs, img*tms/std, 0)
snrs = np.append(snrs, np.nan*np.zeros((3,S[1])), 0)
sdout = np.append(sdout, std, 0)
sdout = np.append(sdout, np.nan*np.zeros((3,S[1])), 0)
itout = np.append(itout, tms, 0)
itout = np.append(itout, np.nan*np.zeros((3,S[1])), 0)
header['bunit'] = ('electron/second', 'electron power')
IO.writefits(img, maskname,
"{0}_{1}_{2}_eps.fits".format(outname, band, target_name), options,
overwrite=True, header=header, lossy_compress=False)
header['bunit'] = ('electron/second', 'sigma/itime')
IO.writefits(std/tms, maskname,
"{0}_{1}_{2}_sig.fits".format(outname, band, target_name), options,
overwrite=True, header=header, lossy_compress=False)
header['bunit'] = ('second', 'exposure time')
IO.writefits(tms, maskname,
"{0}_{1}_{2}_itime.fits".format(outname, band, target_name), options,
overwrite=True, header=header, lossy_compress=False)
header['bunit'] = ('', 'SNR')
IO.writefits(img*tms/std, maskname,
"{0}_{1}_{2}_snrs.fits".format(outname, band, target_name), options,
overwrite=True, header=header, lossy_compress=False)
header = EPS[0].copy()
header["wat0_001"] = "system=world"
header["wat1_001"] = "wtype=linear"
header["wat2_001"] = "wtype=linear"
header["dispaxis"] = 1
header["dclog1"] = "Transform"
header["dc-flag"] = 0
header["ctype1"] = "AWAV"
header["cunit1"] = ("Angstrom", 'Start wavelength')
header["crval1"] = ll[0]
header["crval2"] = 1
header["crpix1"] = 1
header["crpix2"] = 1
#remove redundant CDELTi due to wavelength issues with ds9
#see: https://github.com/Keck-DataReductionPipelines/MosfireDRP/issues/44
#header["cdelt1"] = 1
#header["cdelt2"] = 1
header["cname1"] = "angstrom"
header["cname2"] = "pixel"
header["cd1_1"] = (ll[1]-ll[0], 'Angstrom/pixel')
header["cd1_2"] = 0
header["cd2_1"] = 0
header["cd2_2"] = 1
try:
header["BARYCORR"]= (lambdas[0]['BARYCORR'],lambdas[0].comments['BARYCORR'])
except KeyError:
warning( "Barycentric corrections not applied to the wavelength solution")
pass
header["bunit"] = "ELECTRONS/SECOND"
info("############ Final reduced file: {0}_{1}_eps.fits".format(outname,band))
IO.writefits(output, maskname, "{0}_{1}_eps.fits".format(outname,
band), options, overwrite=True, header=header,
lossy_compress=False)
header["bunit"] = ""
IO.writefits(snrs, maskname, "{0}_{1}_snrs.fits".format(outname,
band), options, overwrite=True, header=header,
lossy_compress=False)
header["bunit"] = "ELECTRONS/SECOND"
IO.writefits(sdout/itout, maskname, "{0}_{1}_sig.fits".format(outname,
band), options, overwrite=True, header=header,
lossy_compress=False)
header["bunit"] = "SECOND"
IO.writefits(itout, maskname, "{0}_{1}_itime.fits".format(outname,
band), options, overwrite=True, header=header,
lossy_compress=False)
def go(fname):
global plot_arr
print fname
(header, data) = IO.readfits(fname)
bs = CSU.Barset()
bs.set_header(header)
bars = []
means = []
sds = []
deltas = []
deltas_mm = []
poss = []
poss_mm = []
poss_y = []
request = []
qs = []
bars = range(1, 93)
fit_fun = Fit.residual_single
for bar in bars:
pos = bs.get_bar_pix(bar)
if bar % 8 == 0:
print "%2.0i: (%7.2f, %7.2f)" % (bar, pos[0], pos[1])
if is_odd(bar):
if (bs.pos[bar] - bs.pos[bar-1]) < 2.7:
fit_fun = Fit.residual_pair
else:
fit_fun = Fit.residual_single
width = 19
[[xslice, yslice],extent,ystart] = make_slice(pos,0,width,30)
if not is_in_bounds(extent):
fits = [0,0,0,0,0]
[ff,ok] = [np.poly1d(0,0), []]
means.append(fits)
sds.append(fits)
drop_this = True
else:
drop_this = False
fits = []
ys = np.arange(-10,10, dtype=np.float32)
for i in ys:
tofit = data[ystart-i, xslice]
y = median_tails(tofit)
ps = Fit.do_fit(y, fit_fun)
fits.append(ps[0])
fits = np.array(fits)
fits[:,1] += 1
# fit to the ridgeline
[ff, ok] = fit_line_with_sigclip(ys, fits[:,1])
m = [np.mean(fits[:,i]) for i in range(5)]
s = [np.std(fits[:,i]) for i in range(5)]
means.append(m)
sds.append(s)
slit_center_offset = pos[1] - ystart
fc = ff(slit_center_offset)
slit_center_pos = np.float(extent[0] + fc )
if drop_this:
poss.append(NaN)
poss_y.append(NaN)
poss_mm.append(NaN)
else:
poss.append(slit_center_pos)
poss_y.append(ystart)
poss_mm.append(CSU.csu_pix_to_mm_poly(slit_center_pos, ystart)[0])
delta = np.float(slit_center_pos - pos[0])
if drop_this:
deltas.append(NaN)
deltas_mm.append(NaN)
else:
deltas.append(delta)
b = CSU.csu_pix_to_mm_poly(slit_center_pos + delta, ystart)[0]
deltas_mm.append(b - poss_mm[-1])
q = np.float(np.degrees(np.tan(ff(1)-ff(0))))
if drop_this: qs.append(NaN)
qs.append(q)
means = np.array(means)
f = lambda x: np.array(x).ravel()
sds = f(sds)
deltas = f(deltas)
poss = f(poss)
poss_y = f(poss_y)
poss_mm = f(poss_mm)
deltas_mm = f(deltas_mm)
qs = f(qs)
bars = f(bars)
fout = "/users/npk/dropbox/mosfire/cooldown 9/csu_meas/" + fname.split("/")[-1] + ".sav"
print "saving"
tosav = {"bars": bars, "request": bs.pos, "deltas_mm": deltas_mm, "poss": poss, "poss_mm": poss_mm, "deltas": deltas, "means": means, "qs": qs}
scipy.io.savemat(fout, tosav)
save_region(bs, "/users/npk/dropbox/mosfire/cooldown 9/csu_meas/" + fname.split("/")[-1] + ".reg")
print "saved"
regout = "/users/npk/dropbox/mosfire/cooldown 9/csu_meas/" + fname.split("/")[-1] + ".meas.reg"
pairs = np.array([poss,poss_y]).transpose()
s = CSU.to_ds9_region(pairs, dash=0, color="blue", label=False)
try:
f = open(regout, "w")
f.writelines(s)
f.close()
except:
print "Couldn't write: %s" % regout
return [tosav, bs]
x1 = pos[0] + w
if x1 > 2047: x1 = 2047
if x0 > x1: x0 = x1
xs = slice(x0, x1)
y0 = pos[1] - h
if y0 < 0: y0 = 0
y1 = pos[1] + h
if y1 > 2047: y1 = 2047
if y0 > y1: y0 = y1
ys = slice(y0, y1)
return [[xs, ys], [x0, x1, y0, y1]]
(header, data) = IO.readfits("/users/npk/desktop/c8/m101029_0233.ref.fits")
(header2, data2) = IO.readfits("/users/npk/desktop/c8/m101029_0425.ref.fits")
(header3, data3) = IO.readfits("/users/npk/desktop/c8/m101029_0427.ref.fits")
data = data3
deg = np.pi / 180.
np.set_printoptions(precision=3)
np.set_printoptions(suppress=True)
reload(CSU)
reload(IO)
reload(Fit)
reload(Detector)
pl.ion()
import numpy as np
import time
import pylab as pl
import scipy as sp
from scipy import interpolate as II
import spline
import MOSFIRE.Options as options
from MOSFIRE import IO, Fit, Wavelength
path = "/scr2/mosfire/c9_npk/npk_calib4_q1700_pa_0/"
mdat = IO.readmosfits(path + "m110323_2737.fits")
fdat = IO.readfits(path + "pixelflat_2d_H.fits")
ldat = IO.readfits(path + "lambda_solution_m110323_2737.fits")
dat = mdat[1]/fdat[1]
lam = ldat[1]
yroi=slice(707,736)
slit = dat[yroi,:]
lslit = lam[yroi,:]
DRAW = False
if DRAW:
pl.figure(1)
pl.clf()
pl.subplot(2,2,1)
lamroi = slice(500,600)
def handle_flats(flatlist, maskname, band, options, extension=None,edgeThreshold=450,lampOffList=None,longslit=None):
'''
handle_flats is the primary entry point to the Flats module.
handle_flats takes a list of individual exposure FITS files and creates:
1. A CRR, dark subtracted, pixel-response flat file.
2. A set of polynomials that mark the edges of a slit
Inputs:
flatlist:
maskname: The name of a mask
band: A string indicating the bandceil
Outputs:
file {maskname}/flat_2d_{band}.fits -- pixel response flat
file {maskname}/edges.np
'''
tick = time.time()
# Check
bpos = np.ones(92) * -1
#Retrieve the list of files to use for flat creation.
flatlist = IO.list_file_to_strings(flatlist)
# Print the filenames to Standard-out
for flat in flatlist:
info(str(flat))
#Determine if flat files headers are in agreement
for fname in flatlist:
hdr, dat, bs = IO.readmosfits(fname, options, extension=extension)
try: bs0
except: bs0 = bs
if np.any(bs0.pos != bs.pos):
print "bs0: "+str(bs0.pos)+" bs: "+str(bs.pos)
error("Barset do not seem to match")
raise Exception("Barsets do not seem to match")
if hdr["filter"] != band:
error ("Filter name %s does not match header filter name "
"%s in file %s" % (band, hdr["filter"], fname))
raise Exception("Filter name %s does not match header filter name "
"%s in file %s" % (band, hdr["filter"], fname))
for i in xrange(len(bpos)):
b = hdr["B{0:02d}POS".format(i+1)]
if bpos[i] == -1:
bpos[i] = b
else:
if bpos[i] != b:
error("Bar positions are not all the same in "
"this set of flat files")
raise Exception("Bar positions are not all the same in "
"this set of flat files")
bs = bs0
# Imcombine the lamps ON flats
info("Attempting to combine previous files")
combine(flatlist, maskname, band, options)
# Imcombine the lamps OFF flats and subtract the off from the On sets
if lampOffList != None:
#Retrieve the list of files to use for flat creation.
lampOffList = IO.list_file_to_strings(lampOffList)
# Print the filenames to Standard-out
for flat in lampOffList:
info(str(flat))
print "Attempting to combine Lamps off data"
combine(lampOffList, maskname, band, options, lampsOff=True)
combine_off_on( maskname, band, options)
debug("Combined '%s' to '%s'" % (flatlist, maskname))
info("Comgined to '%s'" % (maskname))
path = "combflat_2d_%s.fits" % band
(header, data) = IO.readfits(path, use_bpm=True)
info("Flat written to %s" % path)
# Edge Trace
if bs.long_slit:
info( "Long slit mode recognized")
info( "Central row position: "+str(longslit["row_position"]))
info( "Upper and lower limits: "+str(longslit["yrange"][0])+" "+str(longslit["yrange"][1]))
results = find_longslit_edges(data,header, bs, options, edgeThreshold=edgeThreshold, longslit=longslit)
elif bs.long2pos_slit:
info( "Long2pos mode recognized")
results = find_long2pos_edges(data,header, bs, options, edgeThreshold=edgeThreshold, longslit=longslit)
else:
results = find_and_fit_edges(data, header, bs, options,edgeThreshold=edgeThreshold)
results[-1]["maskname"] = maskname
results[-1]["band"] = band
np.save("slit-edges_{0}".format(band), results)
save_ds9_edges(results, options)
# Generate Flat
out = "pixelflat_2d_%s.fits" % (band)
if lampOffList != None:
make_pixel_flat(data, results, options, out, flatlist, lampsOff=True)
else:
make_pixel_flat(data, results, options, out, flatlist, lampsOff=False)
info( "Pixel flat took {0:6.4} s".format(time.time()-tick))
def handle_background(filelist,
wavename,
maskname,
band_name,
options,
shifts=None,
plan=None,
extension=None):
'''
Perform difference imaging and subtract residual background.
The plan looks something like: [['A', 'B']]
In this case, the number of output files is equal to the length of the list (1).
If you choose to use an ABA'B' pattern then the plan will be: [["A", "B"], ["A'", "B'"]]
the background subtraction code will make and handle two files, "A-B" and "A'-B'".
'''
global header, bs, edges, data, Var, itime, lam, sky_sub_out, sky_model_out, band
band = band_name
flatname = "pixelflat_2d_%s.fits" % band_name
hdr, flat = IO.readfits("pixelflat_2d_%s.fits" % (band_name), options)
if np.abs(np.median(flat) - 1) > 0.1:
raise Exception("Flat seems poorly behaved.")
'''
This next section of the code figures out the observing plan
and then deals with the bookeeping of sending the plan
to the background subtracter.
'''
hdrs = []
epss = {}
vars = {}
bss = []
times = {}
Nframes = []
i = 0
header = pf.Header()
for i in xrange(len(filelist)):
fl = filelist[i]
files = IO.list_file_to_strings(fl)
print "Combining"
if shifts is None: shift = None
else: shift = shifts[i]
hdr, electron, var, bs, time, Nframe = imcombine(files,
maskname,
options,
flat,
outname="%s.fits" %
(fl),
shifts=shift,
extension=extension)
hdrs.append(hdr)
header = merge_headers(header, hdr)
epss[hdr['FRAMEID']] = electron / time
vars[hdr['FRAMEID']] = var
times[hdr['FRAMEID']] = time
bss.append(bs)
Nframes.append(Nframe)
positions = {}
i = 0
for h in hdrs:
positions[h['FRAMEID']] = i
i += 1
posnames = set(positions.keys())
if plan is None:
plan = guess_plan_from_positions(posnames)
num_outputs = len(plan)
edges, meta = IO.load_edges(maskname, band, options)
lam = IO.readfits(wavename, options)
bs = bss[0]
for i in xrange(num_outputs):
posname0 = plan[i][0]
posname1 = plan[i][1]
print "Handling %s - %s" % (posname0, posname1)
data = epss[posname0] - epss[posname1]
Var = vars[posname0] + vars[posname1]
itime = np.mean([times[posname0], times[posname1]], axis=0)
p = Pool()
solutions = p.map(background_subtract_helper, xrange(len(bs.ssl)))
p.close()
write_outputs(solutions, itime, header, maskname, band, plan[i],
options)
def go(maskname,
band,
filenames,
wavefile,
wavoptions,
longoptions,
use_flat=False):
'''
The go command is the main entry point into this module.
Inputs:
maskname: String of the mask name
band: String of 'Y', 'J', 'H', or 'K'
filenames: List of filenames to reduce
wavefile: String of path to FITS file with the wavelength solution
wavoptions: The Wavelength Options dictionary
longoptions: Dictionary containing:
{'yrange': The pixel range to extract over
'row_position': The row to solve the initial wavelength solution on}
use_flat: Boolean False [default] means to use no flat field
Boolean True means to divide by the pixelflat
'''
wavename = Wavelength.filelist_to_wavename(filenames, band, maskname,
wavoptions).rstrip(".fits")
print "Wavefile: {0}".format(wavefile)
lamhdr, lamdat = IO.readfits(wavefile)
positions = []
objname = None
for listfile in filenames:
fnames = IO.list_file_to_strings(listfile)
if len(fnames) != 1:
raise Exception("I currently expect only one file per position. Remove multiple entries and try again")
header, data, bs = IO.readmosfits(fnames[0], wavoptions)
if objname is None:
objname = header["object"]
if objname != header["object"]:
print ("Trying to combine longslit stack of object {0} "
"with object {1}".format(objname, header["object"]))
print("{0:18s} {1:30s} {2:2s} {3:4.1f}".format(file, header["object"],
header["frameid"], header["yoffset"]))
positions.append([fnames[0], header, data, bs])
print("{0:2g} nod positions found. Producing stacked difference" \
" image.".format(len(positions)))
for i in xrange(len(positions)-1):
A = positions[i]
B = positions[i+1]
print("----------- -----".format(A,B))
dname, varname = imdiff(A, B, maskname, band, header, wavoptions)
if use_flat:
apply_flat(dname, maskname, band)
apply_flat(varname, maskname, band)
rectify(dname, lamdat, A, B, maskname, band, wavoptions,
longoptions)
rectify(varname, lamdat, A, B, maskname, band, wavoptions,
longoptions)
print dname
dname, vname = imdiff(B, A, maskname, band, header, wavoptions)
if use_flat:
apply_flat(dname, maskname, band)
apply_flat(vname, maskname, band)
rectify(dname, lamdat, B, A, maskname, band, wavoptions,
longoptions)
rectify(vname, lamdat, B, A, maskname, band, wavoptions,
longoptions)
if False:
fname = os.path.join(path, wavename + ".fits")
B = IO.readfits(fname)
B = [fname, B[0], B[1]]
for i in xrange(len(positions)):
A = positions[i]
imdiff(A, B, maskname, band, wavoptions)
rectify(path, dname, lamdat, A, B, maskname, band, wavoptions,
longoptions)
imdiff(B, A, maskname, band, wavoptions)
rectify(path, dname, lamdat, B, A, maskname, band, wavoptions,
longoptions)
if x0 < 0: x0 = 0
x1 = pos[0] + w
if x1 > 2047: x1 = 2047
if x0 > x1: x0 = x1
xs = slice(x0, x1)
y0 = pos[1]-h
if y0 < 0: y0 = 0
y1 = pos[1]+h
if y1 > 2047: y1 = 2047
if y0 > y1: y0 = y1
ys = slice(y0,y1)
return [[xs,ys],[x0,x1,y0,y1]]
(header, data) = IO.readfits("/users/npk/desktop/c8/m101029_0233.ref.fits")
(header2, data2) = IO.readfits("/users/npk/desktop/c8/m101029_0425.ref.fits")
(header3, data3) = IO.readfits("/users/npk/desktop/c8/m101029_0427.ref.fits")
data = data3
deg = np.pi/180.
np.set_printoptions(precision=3)
np.set_printoptions(suppress=True)
reload(CSU)
reload(IO)
reload(Fit)
reload(Detector)
import scipy.ndimage import matplotlib import pyfits as pf import MOSFIRE.Options as options from MOSFIRE import IO, Fit, Wavelength pl.ion() path = "/users/npk/desktop/c9_reduce/npk_calib3_q1700_pa_0/" path = "/scr2/mosfire/c9_npk/npk_calib3_q1700_pa_0/" path = "/scr2/mosfire/firstlight/NGC5053" mdat = IO.readmosfits(path + "m120406_0291.fits") fdat = IO.readfits(path + "pixelflat_2d_J.fits") ldat = IO.readfits(path + "lambda_solution_m120406_0291.fits") gain = 2.15 dat = mdat[1]/fdat[1] * gain dat = mdat[1] * gain lam = ldat[1] dat[np.logical_not(np.isfinite(dat))] = 0. yroi=slice(86, 160) yroi=slice(173, 203) yroi=slice(1015, 1090) xroi=slice(0,2048)
def go(maskname,
band,
filenames,
wavefile,
wavoptions,
longoptions,
use_flat=False):
'''
The go command is the main entry point into this module.
Inputs:
maskname: String of the mask name
band: String of 'Y', 'J', 'H', or 'K'
filenames: List of filenames to reduce
wavefile: String of path to FITS file with the wavelength solution
wavoptions: The Wavelength Options dictionary
longoptions: Dictionary containing:
{'yrange': The pixel range to extract over
'row_position': The row to solve the initial wavelength solution on}
use_flat: Boolean False [default] means to use no flat field
Boolean True means to divide by the pixelflat
'''
wavename = Wavelength.filelist_to_wavename(filenames, band, maskname,
wavoptions).rstrip(".fits")
print "Wavefile: {0}".format(wavefile)
lamhdr, lamdat = IO.readfits(wavefile)
positions = []
objname = None
for listfile in filenames:
fnames = IO.list_file_to_strings(listfile)
if len(fnames) != 1:
raise Exception(
"I currently expect only one file per position. Remove multiple entries and try again"
)
header, data, bs = IO.readmosfits(fnames[0], wavoptions)
if objname is None:
objname = header["object"]
if objname != header["object"]:
print(
"Trying to combine longslit stack of object {0} "
"with object {1}".format(objname, header["object"]))
print("{0:18s} {1:30s} {2:2s} {3:4.1f}".format(file, header["object"],
header["frameid"],
header["yoffset"]))
positions.append([fnames[0], header, data, bs])
print("{0:2g} nod positions found. Producing stacked difference" \
" image.".format(len(positions)))
for i in xrange(len(positions) - 1):
A = positions[i]
B = positions[i + 1]
print("----------- -----".format(A, B))
dname, varname = imdiff(A, B, maskname, band, header, wavoptions)
if use_flat:
apply_flat(dname, maskname, band)
apply_flat(varname, maskname, band)
rectify(dname, lamdat, A, B, maskname, band, wavoptions, longoptions)
rectify(varname, lamdat, A, B, maskname, band, wavoptions, longoptions)
print dname
dname, vname = imdiff(B, A, maskname, band, header, wavoptions)
if use_flat:
apply_flat(dname, maskname, band)
apply_flat(vname, maskname, band)
rectify(dname, lamdat, B, A, maskname, band, wavoptions, longoptions)
rectify(vname, lamdat, B, A, maskname, band, wavoptions, longoptions)
if False:
fname = os.path.join(path, wavename + ".fits")
B = IO.readfits(fname)
B = [fname, B[0], B[1]]
for i in xrange(len(positions)):
A = positions[i]
imdiff(A, B, maskname, band, wavoptions)
rectify(path, dname, lamdat, A, B, maskname, band, wavoptions,
longoptions)
imdiff(B, A, maskname, band, wavoptions)
rectify(path, dname, lamdat, B, A, maskname, band, wavoptions,
longoptions)
def handle_rectification(maskname, in_files, wavename, band_pass, barset_file, options,
commissioning_shift=3.0):
'''Handle slit rectification and coaddition.
Args:
maskname: The mask name string
in_files: List of stacked spectra in electron per second. Will look
like ['electrons_Offset_1.5.txt.fits', 'electrons_Offset_-1.5.txt.fits']
wavename: path (relative or full) to the wavelength stack file, string
band_pass: Band pass name, string
barset_file: Path to a mosfire fits file containing the full set of
FITS extensions for the barset. It can be any file in the list
of science files.
Returns:
None
Writes files:
[maskname]_[band]_[object name]_eps.fits --
The rectified, background subtracted, stacked eps spectrum
[maskname]_[band]_[object name]_sig.fits --
Rectified, background subtracted, stacked weight spectrum (STD/itime)
[maskname]_[band]_[object_name]_itime.fits
Rectified, CRR stacked integration time spectrum
[maskname]_[band]_[object_name]_snrs.fits
Rectified signal to noise spectrum
'''
global edges, dats, vars, itimes, shifts, lambdas, band, fidl, all_shifts
band = band_pass
dlambda = Wavelength.grating_results(band)
hpp = Filters.hpp[band]
fidl = np.arange(hpp[0], hpp[1], dlambda)
lambdas = IO.readfits(wavename, options)
if np.any(lambdas[1].data < 0) or np.any(lambdas[1].data > 29000):
print "***********WARNING ***********"
print "The file {0} may not be a wavelength file.".format(wavename)
print "Check before proceeding."
print "***********WARNING ***********"
edges, meta = IO.load_edges(maskname, band, options)
shifts = []
posnames = []
postoshift = {}
for file in in_files:
print ":: ", file
II = IO.read_drpfits(maskname, file, options)
off = np.array((II[0]["decoff"], II[0]["raoff"]),dtype=np.float64)
if "yoffset" in II[0]:
off = -II[0]["yoffset"]
else:
# Deal with data taken during commissioning
if II[0]["frameid"] == 'A': off = 0.0
else: off = commissioning_shift
try: off0
except: off0 = off
shift = off - off0
shifts.append(shift)
posnames.append(II[0]["frameid"])
postoshift[II[0]['frameid']] = shift
print "Position {0} shift: {1:2.2f} as".format(off, shift)
plans = Background.guess_plan_from_positions(set(posnames))
all_shifts = []
for plan in plans:
to_append = []
for pos in plan:
to_append.append(postoshift[pos])
all_shifts.append(to_append)
# Reverse the elements in all_shifts to deal with an inversion
all_shifts.reverse()
theBPM = IO.badpixelmask()
all_solutions = []
cntr = 0
for plan in plans:
p0 = plan[0].replace("'", "p")
p1 = plan[1].replace("'", "p")
suffix = "%s-%s" % (p0,p1)
print "Handling plan %s" % suffix
fname = "bsub_{0}_{1}_{2}.fits".format(maskname,band,suffix)
EPS = IO.read_drpfits(maskname, fname, options)
EPS[1] = np.ma.masked_array(EPS[1], theBPM, fill_value=0)
fname = "var_{0}_{1}_{2}.fits".format(maskname, band, suffix)
VAR = IO.read_drpfits(maskname, fname, options)
VAR[1] = np.ma.masked_array(VAR[1], theBPM, fill_value=np.inf)
fname = "itime_{0}_{1}_{2}.fits".format(maskname, band, suffix)
ITIME = IO.read_drpfits(maskname, fname, options)
ITIME[1] = np.ma.masked_array(ITIME[1], theBPM, fill_value=0)
dats = EPS
vars = VAR
itimes = ITIME
EPS[0]["ORIGFILE"] = fname
tock = time.time()
sols = range(len(edges)-1,-1,-1)
shifts = all_shifts[cntr]
cntr += 1
p = Pool()
solutions = p.map(handle_rectification_helper, sols)
#solutions = map(handle_rectification_helper, [15])
p.close()
all_solutions.append(solutions)
tick = time.time()
print "-----> Mask took %i. Writing to disk." % (tick-tock)
output = np.zeros((1, len(fidl)))
snrs = np.zeros((1, len(fidl)))
sdout= np.zeros((1, len(fidl)))
itout= np.zeros((1, len(fidl)))
# the barset [bs] is used for determining object position
x, x, bs = IO.readmosfits(barset_file, options)
for i_slit in xrange(len(solutions)):
solution = all_solutions[0][i_slit]
header = EPS[0].copy()
obj = header['OBJECT']
target_name = bs.ssl[-(i_slit+1)]['Target_Name']
header['OBJECT'] = target_name
pixel_dist = np.float(bs.ssl[-(i_slit+1)]['Target_to_center_of_slit_distance'])/0.18
pixel_dist -= solution['offset']
ll = solution["lambda"]
header["wat0_001"] = "system=world"
header["wat1_001"] = "wtype=linear"
header["wat2_001"] = "wtype=linear"
header["dispaxis"] = 1
header["dclog1"] = "Transform"
header["dc-flag"] = 0
header["ctype1"] = "AWAV"
header["cunit1"] = "Angstrom"
header["crval1"] = ll[0]
header["crval2"] = -solution["eps_img"].shape[0]/2 - pixel_dist
header["crpix1"] = 1
header["crpix2"] = 1
header["cdelt1"] = 1
header["cdelt2"] = 1
header["cname1"] = "angstrom"
header["cname2"] = "pixel"
header["cd1_1"] = ll[1]-ll[0]
header["cd1_2"] = 0
header["cd2_1"] = 0
header["cd2_2"] = 1
S = output.shape
img = solution["eps_img"]
std = solution["sd_img"]
tms = solution["itime_img"]
for i_solution in xrange(1,len(all_solutions)):
print "Combining solution %i" %i_solution
solution = all_solutions[i_solution][i_slit]
img += solution["eps_img"]
std += solution["sd_img"]
tms += solution["itime_img"]
output = np.append(output, img, 0)
output = np.append(output, np.nan*np.zeros((3,S[1])), 0)
snrs = np.append(snrs, img*tms/std, 0)
snrs = np.append(snrs, np.nan*np.zeros((3,S[1])), 0)
sdout = np.append(sdout, std, 0)
sdout = np.append(sdout, np.nan*np.zeros((3,S[1])), 0)
itout = np.append(itout, tms, 0)
itout = np.append(itout, np.nan*np.zeros((3,S[1])), 0)
header['bunit'] = ('electron/second', 'electron power')
IO.writefits(img, maskname,
"{0}_{1}_{2}_eps.fits".format(maskname, band, target_name), options,
overwrite=True, header=header, lossy_compress=False)
header['bunit'] = ('electron/second', 'sigma/itime')
IO.writefits(std/tms, maskname,
"{0}_{1}_{2}_sig.fits".format(maskname, band, target_name), options,
overwrite=True, header=header, lossy_compress=False)
header['bunit'] = ('second', 'exposure time')
IO.writefits(tms, maskname,
"{0}_{1}_{2}_itime.fits".format(maskname, band, target_name), options,
overwrite=True, header=header, lossy_compress=False)
header['bunit'] = ('', 'SNR')
IO.writefits(img*tms/std, maskname,
"{0}_{1}_{2}_snrs.fits".format(maskname, band, target_name), options,
overwrite=True, header=header, lossy_compress=False)
header = EPS[0].copy()
header["wat0_001"] = "system=world"
header["wat1_001"] = "wtype=linear"
header["wat2_001"] = "wtype=linear"
header["dispaxis"] = 1
header["dclog1"] = "Transform"
header["dc-flag"] = 0
header["ctype1"] = "AWAV"
header["cunit1"] = ("Angstrom", 'Start wavelength')
header["crval1"] = ll[0]
header["crval2"] = 1
header["crpix1"] = 1
header["crpix2"] = 1
header["cdelt1"] = 1
header["cdelt2"] = 1
header["cname1"] = "angstrom"
header["cname2"] = "pixel"
header["cd1_1"] = (ll[1]-ll[0], 'Angstrom/pixel')
header["cd1_2"] = 0
header["cd2_1"] = 0
header["cd2_2"] = 1
header["bunit"] = "ELECTRONS/SECOND"
IO.writefits(output, maskname, "{0}_{1}_eps.fits".format(maskname,
band), options, overwrite=True, header=header,
lossy_compress=False)
header["bunit"] = ""
IO.writefits(snrs, maskname, "{0}_{1}_snrs.fits".format(maskname,
band), options, overwrite=True, header=header,
lossy_compress=False)
header["bunit"] = "ELECTRONS/SECOND"
IO.writefits(sdout/itout, maskname, "{0}_{1}_sig.fits".format(maskname,
band), options, overwrite=True, header=header,
lossy_compress=False)
header["bunit"] = "SECOND"
IO.writefits(itout, maskname, "{0}_{1}_itime.fits".format(maskname,
band), options, overwrite=True, header=header,
lossy_compress=False)
def go(fname):
global plot_arr
print fname
(header, data) = IO.readfits(fname)
bs = CSU.Barset()
bs.set_header(header)
cntfit = 1
for i in range(1,8):
continue
pl.figure(i)
pl.clf()
first_time = True
bars = []
means = []
sds = []
deltas = []
deltas_mm = []
poss = []
poss_mm = []
poss_y = []
request = []
qs = []
bars = range(1, 93)
for bar in bars:
pos = bs.get_bar_pix(bar)
if bar % 8 == 0:
print "%2.0i: (%7.2f, %7.2f)" % (bar, pos[0], pos[1])
width = 19
[[xslice, yslice],extent,ystart] = make_slice(pos,0,width,30)
if not is_in_bounds(extent):
fits = [0,0,0,0,0]
[ff,ok] = [np.poly1d(0,0), []]
means.append(fits)
sds.append(fits)
drop_this = True
else:
drop_this = False
fits = []
ys = np.arange(-10,10, dtype=np.float32)
for i in ys:
tofit = data[ystart-i, xslice]
y = median_tails(tofit)
ps = Fit.do_fit(y, Fit.residual_single)
fits.append(ps[0])
fits = np.array(fits)
fits[:,1] += 1
# fit to the ridgeline
[ff, ok] = fit_line_with_sigclip(ys, fits[:,1])
m = [np.mean(fits[:,i]) for i in range(5)]
s = [np.std(fits[:,i]) for i in range(5)]
means.append(m)
sds.append(s)
#if bar == 44: start_shell()
#if bar == 43: start_shell()
# End of measurement logic, PLOTS
plot_arr = [12, 8, cntfit]
cntfit += 1
if False:
plot_stamps(data[yslice, xslice], ps[0])
y0 = median_tails(data[ystart, xslice])
plot_linefits(y0, ff)
plot_ridgeline(fits, ok, ys, ff, bar)
plot_widths(fits, ok, ys)
# End of plots, BOOKEEPING
slit_center_offset = pos[1] - ystart
fc = ff(slit_center_offset)
slit_center_pos = np.float(extent[0] + fc )
if drop_this:
poss.append(NaN)
poss_y.append(NaN)
poss_mm.append(NaN)
else:
poss.append(slit_center_pos)
poss_y.append(ystart)
poss_mm.append(CSU.csu_pix_to_mm_poly(slit_center_pos, ystart)[0])
delta = np.float(slit_center_pos - pos[0])
if drop_this:
deltas.append(NaN)
deltas_mm.append(NaN)
else:
deltas.append(delta)
b = CSU.csu_pix_to_mm_poly(slit_center_pos + delta, ystart)[0]
deltas_mm.append(b - poss_mm[-1])
q = np.float(np.degrees(np.tan(ff(1)-ff(0))))
if drop_this: qs.append(NaN)
qs.append(q)
if False: #is_in_bounds(extent):
pl.figure(2)
pl.text(pos[0], pos[1], 'b%2.0i: w=%3.2f p=%5.2f q=%3.2f d=%1.3f' % (bar, np.mean(fits[:,4]), extent[0]+ff(0), q, delta), fontsize=11, family='monospace', horizontalalignment='center')
means = np.array(means)
f = lambda x: np.array(x).ravel()
sds = f(sds)
deltas = f(deltas)
poss = f(poss)
poss_y = f(poss_y)
poss_mm = f(poss_mm)
deltas_mm = f(deltas_mm)
qs = f(qs)
bars = f(bars)
pl.draw()
if False:
[pf, ok] = fit_line_with_sigclip(bars, deltas)
print "** Residual: %4.3f [pix]" % np.std(deltas[ok]-pf(bars[ok]))
evens = range(0,92,2)
odds = range(1,92,2)
pl.plot(bars[evens], deltas[evens],'r*-')
pl.plot(bars[odds], deltas[odds],'b*-')
pl.title("Red: even, blue: odd")
pl.xlabel("Bar #")
pl.ylabel("Delta pixel (Measured - Predicted)")
pl.plot(bars, pf(bars))
fout = "/users/npk/dropbox/mosfire/cooldown 9/csu_meas/" + fname.split("/")[-1] + ".sav"
print "saving"
tosav = {"bars": bars, "request": bs.pos, "deltas_mm": deltas_mm, "poss": poss, "poss_mm": poss_mm, "deltas": deltas, "means": means, "qs": qs}
scipy.io.savemat(fout, tosav)
save_region(bs, "/users/npk/dropbox/mosfire/cooldown 9/csu_meas/" + fname.split("/")[-1] + ".reg")
print "saved"
regout = "/users/npk/dropbox/mosfire/cooldown 9/csu_meas/" + fname.split("/")[-1] + ".meas.reg"
pairs = np.array([poss,poss_y]).transpose()
s = CSU.to_ds9_region(pairs, dash=0, color="blue", label=False)
try:
f = open(regout, "w")
f.writelines(s)
f.close()
except:
print "Couldn't write: %s" % regout
return [tosav, bs]
def handle_background(filelist, wavename, maskname, band_name, options, shifts=None, plan=None, extension=None):
'''
Perform difference imaging and subtract residual background.
The plan looks something like: [['A', 'B']]
In this case, the number of output files is equal to the length of the list (1).
If you choose to use an ABA'B' pattern then the plan will be: [["A", "B"], ["A'", "B'"]]
the background subtraction code will make and handle two files, "A-B" and "A'-B'".
'''
global header, bs, edges, data, Var, itime, lam, sky_sub_out, sky_model_out, band
band = band_name
flatname = "pixelflat_2d_%s.fits" % band_name
hdr, flat = IO.readfits("pixelflat_2d_%s.fits" % (band_name), options)
if np.abs(np.median(flat) - 1) > 0.1:
raise Exception("Flat seems poorly behaved.")
'''
This next section of the code figures out the observing plan
and then deals with the bookeeping of sending the plan
to the background subtracter.
'''
hdrs = []
epss = {}
vars = {}
bss = []
times = {}
Nframes = []
i = 0
header = pf.Header()
for i in xrange(len(filelist)):
fl = filelist[i]
files = IO.list_file_to_strings(fl)
print "Combining"
if shifts is None: shift = None
else: shift = shifts[i]
hdr, electron, var, bs, time, Nframe = imcombine(files, maskname,
options, flat, outname="%s.fits" % (fl),
shifts=shift, extension=extension)
hdrs.append(hdr)
header = merge_headers(header, hdr)
epss[hdr['FRAMEID']] = electron/time
vars[hdr['FRAMEID']] = var
times[hdr['FRAMEID']] = time
bss.append(bs)
Nframes.append(Nframe)
positions = {}
i = 0
for h in hdrs:
positions[h['FRAMEID']] = i
i += 1
posnames = set(positions.keys())
if plan is None:
plan = guess_plan_from_positions(posnames)
num_outputs = len(plan)
edges, meta = IO.load_edges(maskname, band, options)
lam = IO.readfits(wavename, options)
bs = bss[0]
for i in xrange(num_outputs):
posname0 = plan[i][0]
posname1 = plan[i][1]
print "Handling %s - %s" % (posname0, posname1)
data = epss[posname0] - epss[posname1]
Var = vars[posname0] + vars[posname1]
itime = np.mean([times[posname0], times[posname1]], axis=0)
p = Pool()
solutions = p.map(background_subtract_helper, xrange(len(bs.ssl)))
p.close()
write_outputs(solutions, itime, header, maskname, band, plan[i], options)
def go(fname):
global plot_arr
print fname
(header, data) = IO.readfits(fname)
bs = CSU.Barset()
bs.set_header(header)
bars = []
means = []
sds = []
deltas = []
deltas_mm = []
poss = []
poss_mm = []
poss_y = []
request = []
qs = []
bars = range(1, 93)
fit_fun = Fit.residual_single
for bar in bars:
pos = bs.get_bar_pix(bar)
if bar % 8 == 0:
print "%2.0i: (%7.2f, %7.2f)" % (bar, pos[0], pos[1])
if is_odd(bar):
if (bs.pos[bar] - bs.pos[bar-1]) < 2.7:
fit_fun = Fit.residual_pair
else:
fit_fun = Fit.residual_single
width = 19
[[xslice, yslice],extent,ystart] = make_slice(pos,0,width,30)
if not is_in_bounds(extent):
fits = [0,0,0,0,0]
[ff,ok] = [np.poly1d(0,0), []]
means.append(fits)
sds.append(fits)
drop_this = True
else:
drop_this = False
fits = []
ys = np.arange(-10,10, dtype=np.float32)
for i in ys:
tofit = data[ystart-i, xslice]
y = median_tails(tofit)
ps = Fit.do_fit(y, fit_fun)
fits.append(ps[0])
fits = np.array(fits)
fits[:,1] += 1
# fit to the ridgeline
[ff, ok] = fit_line_with_sigclip(ys, fits[:,1])
m = [np.mean(fits[:,i]) for i in range(5)]
s = [np.std(fits[:,i]) for i in range(5)]
means.append(m)
sds.append(s)
slit_center_offset = pos[1] - ystart
fc = ff(slit_center_offset)
slit_center_pos = np.float(extent[0] + fc )
if drop_this:
poss.append(NaN)
poss_y.append(NaN)
poss_mm.append(NaN)
else:
poss.append(slit_center_pos)
poss_y.append(ystart)
poss_mm.append(CSU.csu_pix_to_mm_poly(slit_center_pos, ystart)[0])
delta = np.float(slit_center_pos - pos[0])
if drop_this:
deltas.append(NaN)
deltas_mm.append(NaN)
else:
deltas.append(delta)
b = CSU.csu_pix_to_mm_poly(slit_center_pos + delta, ystart)[0]
deltas_mm.append(b - poss_mm[-1])
q = np.float(np.degrees(np.tan(ff(1)-ff(0))))
if drop_this: qs.append(NaN)
qs.append(q)
means = np.array(means)
f = lambda x: np.array(x).ravel()
sds = f(sds)
deltas = f(deltas)
poss = f(poss)
poss_y = f(poss_y)
poss_mm = f(poss_mm)
deltas_mm = f(deltas_mm)
qs = f(qs)
bars = f(bars)
fout = "/users/npk/dropbox/mosfire/cooldown 9/csu_meas/" + fname.split("/")[-1] + ".sav"
print "saving"
tosav = {"bars": bars, "request": bs.pos, "deltas_mm": deltas_mm, "poss": poss, "poss_mm": poss_mm, "deltas": deltas, "means": means, "qs": qs}
scipy.io.savemat(fout, tosav)
save_region(bs, "/users/npk/dropbox/mosfire/cooldown 9/csu_meas/" + fname.split("/")[-1] + ".reg")
print "saved"
regout = "/users/npk/dropbox/mosfire/cooldown 9/csu_meas/" + fname.split("/")[-1] + ".meas.reg"
pairs = np.array([poss,poss_y]).transpose()
s = CSU.to_ds9_region(pairs, dash=0, color="blue", label=False)
try:
f = open(regout, "w")
f.writelines(s)
f.close()
except:
print "Couldn't write: %s" % regout
return [tosav, bs]
def handle_flats(flatlist,
maskname,
band,
options,
extension=None,
edgeThreshold=450,
lampOffList=None,
longslit=None):
'''
handle_flats is the primary entry point to the Flats module.
handle_flats takes a list of individual exposure FITS files and creates:
1. A CRR, dark subtracted, pixel-response flat file.
2. A set of polynomials that mark the edges of a slit
Inputs:
flatlist:
maskname: The name of a mask
band: A string indicating the bandceil
Outputs:
file {maskname}/flat_2d_{band}.fits -- pixel response flat
file {maskname}/edges.np
'''
tick = time.time()
# Check
bpos = np.ones(92) * -1
#Retrieve the list of files to use for flat creation.
flatlist = IO.list_file_to_strings(flatlist)
# Print the filenames to Standard-out
for flat in flatlist:
info(str(flat))
#Determine if flat files headers are in agreement
for fname in flatlist:
hdr, dat, bs = IO.readmosfits(fname, options, extension=extension)
try:
bs0
except:
bs0 = bs
if np.any(bs0.pos != bs.pos):
print "bs0: " + str(bs0.pos) + " bs: " + str(bs.pos)
error("Barset do not seem to match")
raise Exception("Barsets do not seem to match")
if hdr["filter"] != band:
error("Filter name %s does not match header filter name "
"%s in file %s" % (band, hdr["filter"], fname))
raise Exception("Filter name %s does not match header filter name "
"%s in file %s" % (band, hdr["filter"], fname))
for i in xrange(len(bpos)):
b = hdr["B{0:02d}POS".format(i + 1)]
if bpos[i] == -1:
bpos[i] = b
else:
if bpos[i] != b:
error("Bar positions are not all the same in "
"this set of flat files")
raise Exception("Bar positions are not all the same in "
"this set of flat files")
bs = bs0
# Imcombine the lamps ON flats
info("Attempting to combine previous files")
combine(flatlist, maskname, band, options)
# Imcombine the lamps OFF flats and subtract the off from the On sets
if lampOffList != None:
#Retrieve the list of files to use for flat creation.
lampOffList = IO.list_file_to_strings(lampOffList)
# Print the filenames to Standard-out
for flat in lampOffList:
info(str(flat))
print "Attempting to combine Lamps off data"
combine(lampOffList, maskname, band, options, lampsOff=True)
combine_off_on(maskname, band, options)
debug("Combined '%s' to '%s'" % (flatlist, maskname))
info("Comgined to '%s'" % (maskname))
path = "combflat_2d_%s.fits" % band
(header, data) = IO.readfits(path, use_bpm=True)
info("Flat written to %s" % path)
# Edge Trace
if bs.long_slit:
info("Long slit mode recognized")
info("Central row position: " + str(longslit["row_position"]))
info("Upper and lower limits: " + str(longslit["yrange"][0]) + " " +
str(longslit["yrange"][1]))
results = find_longslit_edges(data,
header,
bs,
options,
edgeThreshold=edgeThreshold,
longslit=longslit)
elif bs.long2pos_slit:
info("Long2pos mode recognized")
results = find_long2pos_edges(data,
header,
bs,
options,
edgeThreshold=edgeThreshold,
longslit=longslit)
else:
results = find_and_fit_edges(data,
header,
bs,
options,
edgeThreshold=edgeThreshold)
results[-1]["maskname"] = maskname
results[-1]["band"] = band
np.save("slit-edges_{0}".format(band), results)
save_ds9_edges(results, options)
# Generate Flat
out = "pixelflat_2d_%s.fits" % (band)
if lampOffList != None:
make_pixel_flat(data, results, options, out, flatlist, lampsOff=True)
else:
make_pixel_flat(data, results, options, out, flatlist, lampsOff=False)
info("Pixel flat took {0:6.4} s".format(time.time() - tick))
def handle_flats(flatlist, maskname, band, options, extension=None):
'''
handle_flats is the primary entry point to the Flats module.
handle_flats takes a list of individual exposure FITS files and creates:
1. A CRR, dark subtracted, pixel-response flat file.
2. A set of polynomials that mark the edges of a slit
Inputs:
flatlist: Either a string of an input file or a list of file names
maskname: The name of a mask
band: A string indicating the bandceil
Outputs:
file {maskname}/flat_2d_{band}.fits -- pixel response flat
file {maskname}/edges.np
'''
tick = time.time()
# Check
bpos = np.ones(92) * -1
flatlist = IO.list_file_to_strings(flatlist)
print flatlist
for fname in flatlist:
hdr, dat, bs = IO.readmosfits(fname, options, extension=extension)
try: bs0
except: bs0 = bs
if np.any(bs0.pos != bs.pos):
raise Exception("Barsets do not seem to match")
if hdr["filter"] != band:
print ("Filter name %s does not match header filter name "
"%s in file %s" % (band, hdr["filter"], fname))
for i in xrange(len(bpos)):
b = hdr["B{0:02d}POS".format(i+1)]
if bpos[i] == -1:
bpos[i] = b
else:
if bpos[i] != b:
raise Exception("Bar positions are not all the same in "
"this set of flat files")
bs = bs0
# Imcombine
if True:
print "Attempting to combine: ", flatlist
combine(flatlist, maskname, band, options)
print "Combined '%s' to '%s'" % (flatlist, maskname)
path = "combflat_2d_%s.fits" % band
(header, data) = IO.readfits(path, use_bpm=True)
print "Flat written to %s" % path
# Edge Trace
results = find_and_fit_edges(data, header, bs, options)
results[-1]["maskname"] = maskname
results[-1]["band"] = band
np.save("slit-edges_{0}".format(band), results)
save_ds9_edges(results, options)
# Generate Flat
out = "pixelflat_2d_%s.fits" % (band)
make_pixel_flat(data, results, options, out, flatlist)
print "Pixel flat took {0:6.4} s".format(time.time()-tick)
