def mkfluxstar(fluxfile, gratcode):
import pdb
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Cursor
from astropy.io import fits
from tmath.wombat.get_screen_size import get_screen_size
from tmath.wombat.getmswave import getmswave
from tmath.wombat.inputter_single import inputter_single
from tmath.wombat.inputter import inputter
from tmath.wombat.womscipyrebin import womscipyrebin
from tmath.pydux.obs_extinction import obs_extinction
from tmath.pydux.wave_telluric import wave_telluric
from tmath.pydux.fitspl import fitspl
from tmath.pydux.finalscaler import finalscaler
from tmath.pydux.abcalc import abcalc
from tmath.pydux.pacheck import pacheck
screen_width, screen_height = get_screen_size()
plt.ion()
screenpos = '+{}+{}'.format(int(screen_width * 0.2),
int(screen_height * 0.05))
fig = plt.figure()
fig.canvas.manager.window.wm_geometry(screenpos)
fig.canvas.set_window_title('Flux Star')
fig.set_size_inches(18, 12)
# turns off key stroke interaction
fig.canvas.mpl_disconnect(fig.canvas.manager.key_press_handler_id)
# this should bring the window to the top, but it doesn't
wm = plt.get_current_fig_manager()
#fig.canvas.manager.window.attributes('-topmost', 1)
blah = wm.window.attributes('-topmost', 1)
#plt.pause(0.2)
#fig.canvas.manager.window.attributes('-topmost', 0)
blah = wm.window.attributes('-topmost', 0)
#extinction terms from Allen, 3rd edition
extwave= [2400.,2600.,2800.,3000.,3200.,3400.,3600.,3800., \
4000.,4500.,5000.,5500.,6000.,6500.,7000.,8000., \
9000.,10000.,12000.,14000.]
extvals=[68.0,89.0,36.0,4.5,1.30,0.84,0.68,0.55,0.46,0.31, \
0.23,0.195,0.170,0.126,0.092,0.062,0.048,0.039, \
0.028,0.021]
fitsfile = fits.open(fluxfile)
rawdata = fitsfile[0].data
head = fitsfile[0].header
num_apertures = rawdata.shape[1]
wavearr = np.zeros((rawdata.shape[2], rawdata.shape[1]))
objectname = head['OBJECT']
airmass = float(head['AIRMASS'])
exptime = float(head['EXPTIME'])
head = pacheck(head)
if (exptime < 1):
exptime = 1.
observat = head['OBSERVAT'].strip().lower()
sitefactor = obs_extinction(observat)
for i in range(0, num_apertures):
wavearr[:, i] = getmswave(head, i)
if (wavearr[-1, 0] < 3000):
print('************************************************')
print('Spectrum not wavelength calibrated---bailing out')
print('************************************************')
sys.exit(1)
ap_choice = -1
if (num_apertures != 1):
axarr = fig.subplots(num_apertures, sharex=True)
fig.subplots_adjust(hspace=0)
for i in range(0, num_apertures):
x = wavearr[:, i]
y = rawdata[0, i, :]
axarr[i].clear()
plt.pause(0.01)
axarr[i].plot(x, y, drawstyle='steps-mid')
axarr[i].set_ylabel('Aperture {}'.format(i))
plt.pause(0.01)
while (ap_choice < 0) or (ap_choice > num_apertures - 1):
ap_choice = inputter(
'Which aperture do you want to use for the flux star? ', 'int',
False)
fig.clf()
else:
ap_choice = 0
ymin, ymax = finalscaler(rawdata[0, ap_choice, :])
fig.clf()
x1 = wavearr[:, ap_choice]
y1 = rawdata[1, ap_choice, :]
y0 = rawdata[0, ap_choice, :]
plt.plot(x1, y1, drawstyle='steps-mid', color='r')
plt.plot(x1, y0, drawstyle='steps-mid', color='k')
plt.pause(0.01)
plt.ylim([ymin, ymax])
plt.pause(0.01)
print('\nPlotting optimal as black, normal as red')
extract = inputter_single(
'Do you want to use (n)ormal or (o)ptimal extraction? ', 'no')
if (extract == 'o'):
star = rawdata[0, ap_choice, :]
else:
star = rawdata[1, ap_choice, :]
# fix IRAF weirdness where data can go negative in dispcor interpolation
star[np.where(star < 0)] = 0.01
wave = wavearr[:, ap_choice]
extinction = womscipyrebin(extwave, extvals, wave)
extfactor = np.exp(extinction * sitefactor * airmass)
star = star * extfactor
abcurve = abcalc(wave, objectname)
wdata = 10.0**(0.4 * abcurve)
fstar = star * wdata / exptime
print('Now fit the continuum manually\n')
plt.clf()
ax = fig.add_subplot(111)
cursor = Cursor(ax, useblit=True, color='k', linewidth=1)
airlimit = 1.5
splineresult = fitspl(wave, np.log10(fstar), (airmass > airlimit), fig)
splineresult = 10**(splineresult)
plt.cla()
plt.plot(wave, splineresult, drawstyle='steps-mid')
plt.pause(0.01)
delkeylist=['WAT0_001', 'WAT1_001', 'WAT2_001', 'WAT0_002', \
'WAT1_002', 'WAT2_002', 'WAT3_001', 'WAT2_003', \
'CTYPE1', 'CTYPE2', 'CTYPE3', 'CD1_1', 'CD2_2', \
'CD3_3', 'LTM1_1', 'LTM2_2', 'LTM3_3', 'WCSDIM']
for k in delkeylist:
try:
head.remove(k)
except KeyError:
pass
head.set('CRPIX1', 1)
head.set('CRVAL1', wave[0])
head.set('CDELT1', wave[1] - wave[0])
head.set('CTYPE1', 'LINEAR')
head.set('FLUXFILE', fluxfile)
outfile = 'fluxstar' + gratcode + '.fits'
print('Writing data to {}'.format(outfile))
outhdu = fits.PrimaryHDU(splineresult)
hdul = fits.HDUList([outhdu])
hdul[0].header = head.copy()
hdul.writeto(outfile, overwrite=True)
print('mkfluxstar')
print(fluxfile, gratcode)
return
def womcat(hop):
"""concatenate data with overlapping wavelength regions"""
import numpy as np
import logging
import matplotlib.pyplot as plt
from tmath.wombat.inputter import inputter
from tmath.wombat.inputter_single import inputter_single
from tmath.wombat.womget_element import womget_element
from tmath.wombat.yesno import yesno
from tmath.wombat.get_screen_size import get_screen_size
from tmath.wombat.womwaverange2 import womwaverange2
from tmath.wombat import HOPSIZE
from matplotlib.widgets import Cursor
plt.ion()
screen_width, screen_height = get_screen_size()
screenpos = '+{}+{}'.format(int(screen_width * 0.2),
int(screen_height * 0.05))
fig = plt.figure()
ax = fig.add_subplot(111)
cursor = Cursor(ax, useblit=True, color='k', linewidth=1)
fig.canvas.manager.window.wm_geometry(screenpos)
fig.canvas.set_window_title('Cat')
fig.set_size_inches(9, 6)
# turns off key stroke interaction
fig.canvas.mpl_disconnect(fig.canvas.manager.key_press_handler_id)
print("\nThis will combine blue and red pieces from two hoppers\n")
hopnum1 = 0
hopnum2 = 0
while (hopnum1 < 1) or (hopnum1 > HOPSIZE):
hopnum1 = inputter('Enter first hopper: ', 'int', False)
while (hopnum2 < 1) or (hopnum2 > HOPSIZE):
hopnum2 = inputter('Enter second hopper: ', 'int', False)
if (hop[hopnum1].wave[0] > hop[hopnum2].wave[0]):
hopnum1, hopnum2 = hopnum2, hopnum1
wdelt1 = hop[hopnum1].wave[1] - hop[hopnum1].wave[0]
wdelt2 = hop[hopnum2].wave[1] - hop[hopnum2].wave[0]
# check if wavelength dispersion same
if (abs(wdelt1 - wdelt2) > 0.00001):
print('Spectra do not have same Angstrom/pixel')
print('Blue side: {}'.format(wdelt1))
print('Red side: {}'.format(wdelt2))
return hop
if hop[hopnum1].wave[-1] < hop[hopnum2].wave[0]:
print('Spectra do not overlap\n')
return hop
print("\nOverlap range is {} to {}".format(hop[hopnum2].wave[0],
hop[hopnum1].wave[-1]))
print("\nPlotting blue side as blue, red side as red\n")
waveblue = hop[hopnum1].wave.copy()
fluxblue = hop[hopnum1].flux.copy()
varblue = hop[hopnum1].var.copy()
wavered = hop[hopnum2].wave.copy()
fluxred = hop[hopnum2].flux.copy()
varred = hop[hopnum2].var.copy()
indexblue = womget_element(waveblue, wavered[0])
indexred = womget_element(wavered, waveblue[-1])
fluxcor = 1.0
blue_mean = np.mean(fluxblue[indexblue:])
red_mean = np.mean(fluxred[0:indexred + 1])
if (blue_mean / red_mean < 0.8) or (blue_mean / red_mean > 1.2):
fluxcor = blue_mean / red_mean
print("Averages very different, scaling red to blue for plot")
print("Red multiplied by {}".format(fluxcor))
plt.cla()
plt.plot(waveblue[indexblue:],
fluxblue[indexblue:],
drawstyle='steps-mid',
color='b')
plt.plot(wavered[0:indexred],
fluxred[0:indexred] * fluxcor,
drawstyle='steps-mid',
color='r')
plt.xlabel('Wavelength')
plt.ylabel('Flux')
plt.pause(0.01)
print('Change scale?')
answer = yesno('n')
if (answer == 'y'):
xmin_old, xmax_old = plt.xlim()
ymin_old, ymax_old = plt.ylim()
done = False
while (not done):
plt.xlim([xmin_old, xmax_old])
plt.ylim([ymin_old, ymax_old])
print('Click corners of box to change plot scale')
newlims = plt.ginput(2, timeout=-1)
xmin = newlims[0][0]
ymin = newlims[0][1]
xmax = newlims[1][0]
ymax = newlims[1][1]
plt.xlim([xmin, xmax])
plt.ylim([ymin, ymax])
print('Is this OK?')
loopanswer = yesno('y')
if (loopanswer == 'y'):
done = True
print('\nEnter method to select wavelength ranges\n')
mode = inputter_single(
'Enter (w)avelengths or mark with the (m)ouse? (w/m) ', 'wm')
print('\nChoose end points of region to compute average\n')
waveb, waver, mode = womwaverange2(waveblue[indexblue:],
fluxblue[indexblue:],
wavered[0:indexred],
fluxred[0:indexred] * fluxcor, mode)
indexblueb = womget_element(waveblue, waveb)
indexbluer = womget_element(waveblue, waver)
indexredb = womget_element(wavered, waveb)
indexredr = womget_element(wavered, waver)
mean_blue = np.mean(fluxblue[indexblueb:indexbluer + 1])
mean_red = np.mean(fluxred[indexredb:indexredr + 1])
print("\nAverage for {}:{}".format(waveb, waver))
print("Blue side: {}".format(mean_blue))
print("Red side: {}\n".format(mean_red))
brscale = inputter_single('Scale to blue or red (b/r)? ', 'br')
if (brscale == 'b'):
brscalefac = mean_blue / mean_red
logging.info('Cat scaling to blue by {}'.format(brscalefac))
fluxred = fluxred * brscalefac
varred = varred * brscalefac**2
else:
brscalefac = mean_red / mean_blue
logging.info('Cat scaling to red by {}'.format(brscalefac))
fluxblue = fluxblue * brscalefac
varblue = varblue * brscalefac**2
# print("\nPlotting blue side as blue, red side as red\n")
# plt.cla()
# plt.plot(waveblue[indexblueb:indexbluer+1],fluxblue[indexblueb:indexbluer+1],drawstyle='steps-mid',color='b')
# plt.plot(wavered[indexredb:indexredr+1],fluxred[indexredb:indexredr+1],drawstyle='steps-mid',color='r')
# plt.xlabel('Wavelength')
# plt.ylabel('Flux')
# plt.pause(0.01)
# print('Change scale?')
# answer=yesno('n')
# if (answer == 'y'):
# xmin_old,xmax_old=plt.xlim()
# ymin_old,ymax_old=plt.ylim()
# done=False
# while (not done):
# plt.xlim([xmin_old,xmax_old])
# plt.ylim([ymin_old,ymax_old])
# print('Click corners of box to change plot scale')
# newlims=plt.ginput(2,timeout=-1)
# xmin=newlims[0][0]
# ymin=newlims[0][1]
# xmax=newlims[1][0]
# ymax=newlims[1][1]
# plt.xlim([xmin,xmax])
# plt.ylim([ymin,ymax])
# print('Is this OK?')
# loopanswer=yesno('y')
# if (loopanswer == 'y'):
# done=True
# print('\nChoose end points of region to compute average\n')
# waveb,waver,mode=womwaverange2(waveblue[indexblueb:indexbluer+1],
# fluxblue[indexblueb:indexbluer+1],
# wavered[indexredb:indexredr+1],
# fluxred[indexredb:indexredr+1],mode)
# indexblueb=womget_element(waveblue,waveb)
# indexbluer=womget_element(waveblue,waver)
# indexredb=womget_element(wavered,waveb)
# indexredr=womget_element(wavered,waver)
# ewadd=inputter_single('Add overlap region (e)qually or with (w)eights (e/w)?','ew')
# if (ewadd == 'e'):
# overflux=(fluxblue[indexblueb:indexbluer+1]+fluxred[indexredb:indexredr+1])/2.
# overvar=(varblue[indexblueb:indexbluer+1]+varred[indexredb:indexredr+1])
#replacing with inverse variance weighted average
overflux = np.average([
fluxblue[indexblueb:indexbluer + 1], fluxred[indexredb:indexredr + 1]
],
weights=[
1. / varblue[indexblueb:indexbluer + 1],
1. / varred[indexredb:indexredr + 1]
],
axis=0)
overvar = np.sum(
[varblue[indexblueb:indexbluer + 1], varred[indexredb:indexredr + 1]],
axis=0)
logging.info('Cat combined sides with inverse variance weighted average')
# else:
# wei_done = False
# while (not wei_done):
# weiblue=inputter('Enter fractional weight for blue side: ','float',False)
# weired=inputter('Enter fractional weight for red side: ','float',False)
# if (np.abs((weiblue+weired)-1.0) > 0.000001):
# print('Weights do not add to 1.0')
# else:
# wei_done = True
# overflux=(fluxblue[indexblueb:indexbluer+1]*weiblue+
# fluxred[indexredb:indexredr+1]*weired)
# overvar=(varblue[indexblueb:indexbluer+1]*weiblue**2+
# varred[indexredb:indexredr+1]*weired**2)
# logging.info('Cat adds blue side with weight {} and red side with weight {}'.format(weiblue, weired))
newbluewave = waveblue[:indexblueb]
newblueflux = fluxblue[:indexblueb]
newbluevar = varblue[:indexblueb]
overwave = waveblue[indexblueb:indexbluer + 1]
newredwave = wavered[indexredr + 1:]
newredflux = fluxred[indexredr + 1:]
newredvar = varred[indexredr + 1:]
newwave = np.concatenate([newbluewave, overwave, newredwave])
newflux = np.concatenate([newblueflux, overflux, newredflux])
newvar = np.concatenate([newbluevar, overvar, newredvar])
logging.info('File {} and'.format(hop[hopnum1].obname))
logging.info('File {} concatenated'.format(hop[hopnum2].obname))
logging.info('over wavelength range {} to {}'.format(
waveblue[indexblueb], waveblue[indexbluer]))
plt.clf()
axarr = fig.subplots(2)
axarr[0].plot(overwave, overflux, drawstyle='steps-mid', color='k')
axarr[0].plot(waveblue[indexblueb:indexbluer + 1],
fluxblue[indexblueb:indexbluer + 1],
drawstyle='steps-mid',
color='b')
axarr[0].plot(wavered[indexredb:indexredr + 1],
fluxred[indexredb:indexredr + 1],
drawstyle='steps-mid',
color='r')
axarr[0].set_title('Overlap region, with inputs and combination')
axarr[1].set_ylabel('Flux')
axarr[1].plot(newwave, newflux, drawstyle='steps-mid', color='k')
axarr[1].plot(newwave[indexblueb:indexbluer + 1],
newflux[indexblueb:indexbluer + 1],
drawstyle='steps-mid',
color='r')
plt.pause(0.01)
hopout = 0
while (hopout < 1) or (hopout > HOPSIZE):
hopout = inputter('Enter hopper to store combined spectrum: ', 'int',
False)
hop[hopout].wave = newwave
hop[hopout].flux = newflux
hop[hopout].var = newvar
hop[hopout].obname = hop[hopnum1].obname
hop[hopout].header = hop[hopnum1].header
plt.close()
#fig.clf()
#plt.cla()
return hop
def mkbstar(bfile, gratcode):
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Cursor
from astropy.io import fits
from tmath.wombat.get_screen_size import get_screen_size
from tmath.wombat.getmswave import getmswave
from tmath.wombat.inputter_single import inputter_single
from tmath.wombat.inputter import inputter
from tmath.wombat.yesno import yesno
from tmath.pydux.obs_extinction import obs_extinction
from tmath.pydux.wave_telluric import wave_telluric
from tmath.pydux.fitspl import fitspl
from tmath.pydux.bblo import bblo
from tmath.pydux.finalscaler import finalscaler
from tmath.pydux.pacheck import pacheck
screen_width, screen_height = get_screen_size()
plt.ion()
screenpos = '+{}+{}'.format(int(screen_width * 0.2),
int(screen_height * 0.05))
fig = plt.figure()
fig.canvas.manager.window.wm_geometry(screenpos)
fig.canvas.set_window_title('B Star')
fig.set_size_inches(18, 12)
# turns off key stroke interaction
fig.canvas.mpl_disconnect(fig.canvas.manager.key_press_handler_id)
# this should bring the window to the top, but it doesn't
wm = plt.get_current_fig_manager()
#fig.canvas.manager.window.attributes('-topmost', 1)
blah = wm.window.attributes('-topmost', 1)
#plt.pause(0.2)
#fig.canvas.manager.window.attributes('-topmost', 0)
blah = wm.window.attributes('-topmost', 0)
fitsfile = fits.open(bfile)
rawdata = fitsfile[0].data
head = fitsfile[0].header
num_apertures = rawdata.shape[1]
wavearr = np.zeros((rawdata.shape[2], rawdata.shape[1]))
objectname = head['OBJECT']
airmass = float(head['AIRMASS'])
exptime = float(head['EXPTIME'])
if (exptime < 1):
exptime = 1.
head = pacheck(head)
observat = head['OBSERVAT'].strip().lower()
sitefactor = obs_extinction(observat)
for i in range(0, num_apertures):
wavearr[:, i] = getmswave(head, i)
if (wavearr[-1, 0] < 3000):
print('************************************************')
print('Spectrum not wavelength calibrated---bailing out')
print('************************************************')
sys.exit(1)
ap_choice = -1
if (np.mean(rawdata[0, 0, :]) < 1e-7):
rawdata = rawdata * 1e15
# scale to rational numbers for fit (rational as in sane,
# not opposed to irrational)
if (num_apertures != 1):
axarr = fig.subplots(num_apertures, sharex=True)
fig.subplots_adjust(hspace=0)
for i in range(0, num_apertures):
x = wavearr[:, i]
y = rawdata[0, i, :]
axarr[i].clear()
plt.pause(0.01)
axarr[i].plot(x, y, drawstyle='steps-mid')
axarr[i].set_ylabel('Aperture {}'.format(i))
plt.pause(0.01)
while (ap_choice < 0) or (ap_choice > num_apertures - 1):
ap_choice = inputter(
'Which aperture do you want to use for the B star? ', 'int',
False)
fig.clf()
else:
ap_choice = 0
ymin, ymax = finalscaler(rawdata[0, ap_choice, :])
fig.clf()
x1 = wavearr[:, ap_choice]
y1 = rawdata[1, ap_choice, :]
y0 = rawdata[0, ap_choice, :]
plt.plot(x1, y1, drawstyle='steps-mid', color='r')
plt.plot(x1, y0, drawstyle='steps-mid', color='k')
plt.pause(0.01)
plt.ylim([ymin, ymax])
plt.pause(0.01)
print('\nPlotting optimal as black, normal as red')
extract = inputter_single(
'Do you want to use (n)ormal or (o)ptimal extraction? ', 'no')
if (extract == 'o'):
bstar = rawdata[0, ap_choice, :]
else:
bstar = rawdata[1, ap_choice, :]
# fix IRAF weirdness where data can go negative in dispcor interpolation
bstar[np.where(bstar < 0)] = 0.01
wave = wavearr[:, ap_choice]
print('\nAirmass: {}\n'.format(airmass))
airlimit = 0.5
while (airlimit < 1.0) or (airlimit > 10.):
airlimit = inputter('Above what airmass is considered high? ', 'float',
False)
print('\nNow fit the continuum manually\n')
plt.clf()
ax = fig.add_subplot(111)
cursor = Cursor(ax, useblit=True, color='k', linewidth=1)
airlimit = 1.5
splineresult = fitspl(wave, np.log10(bstar), (airmass > airlimit), fig)
splineresult = 10**(splineresult)
plt.cla()
plt.plot(wave, splineresult, drawstyle='steps-mid')
plt.pause(0.01)
bstar = bstar / splineresult
if (airmass > airlimit):
loc = wave_telluric(wave, 'high')
else:
loc = wave_telluric(wave, 'low')
#invert loc and convert all good sections to np.nan so they won't plot
loc = np.invert(loc)
bstar[loc] = 1.0
bstar[np.where(bstar > 1.)] = 1.0
bstar[np.where(bstar <= 0.)] = 0.01
plt.cla()
plt.plot(wave, bstar, drawstyle='steps-mid')
plt.pause(0.01)
print('\nDo you want to blotch the B-star?')
blotch = yesno('n')
if (blotch == 'y'):
bstar = bblo(wave, bstar, (airmass > airlimit), fig)
delkeylist=['WAT0_001', 'WAT1_001', 'WAT2_001', 'WAT0_002', \
'WAT1_002', 'WAT2_002', 'WAT3_001', 'WAT2_003', \
'CTYPE1', 'CTYPE2', 'CTYPE3', 'CD1_1', 'CD2_2', \
'CD3_3', 'LTM1_1', 'LTM2_2', 'LTM3_3', 'WCSDIM']
for k in delkeylist:
try:
head.remove(k)
except KeyError:
pass
plt.cla()
plt.plot(wave, bstar, drawstyle='steps-mid')
plt.pause(0.01)
head.set('CRPIX1', 1)
head.set('CRVAL1', wave[0])
head.set('CDELT1', wave[1] - wave[0])
head.set('CTYPE1', 'LINEAR')
outfile = 'bstar' + gratcode + '.fits'
print('Writing data to {}'.format(outfile))
outhdu = fits.PrimaryHDU(bstar)
hdul = fits.HDUList([outhdu])
hdul[0].header = head.copy()
hdul.writeto(outfile, overwrite=True)
print('mkbstar')
print(bfile, gratcode)
return
def final(objectlist, gratcode, secondord, gratcode2, user):
import matplotlib.pyplot as plt
from matplotlib import gridspec
import numpy as np
from datetime import datetime
import os, pdb
import inspect
import glob
import math
from astropy.io import fits
from astropy import units as u
from astropy.coordinates import SkyCoord
# from astropy.time import Time
from tmath.wombat.get_screen_size import get_screen_size
from tmath.wombat.getmswave import getmswave
from tmath.wombat.inputter_single import inputter_single
from tmath.wombat.inputter import inputter
from tmath.wombat.womcatfinal import womcatfinal
from tmath.pydux.scipyrebinsky import scipyrebinsky
from tmath.wombat.yesno import yesno
from tmath.wombat.womashrebin import womashrebin
from tmath.wombat.wominterpofluxconserving import interpo_flux_conserving
from tmath.wombat.womspectres import spectres
from tmath.pydux.getfitsfile import getfitsfile
from tmath.pydux.pacheck import pacheck
from tmath.pydux.jdcnv import jdcnv
from tmath.pydux.baryvel import baryvel
from tmath.pydux.finalscaler import finalscaler
from tmath.pydux.envelope import envelope
from tmath.pydux.congrid import congrid
from tmath.pydux.xcor import xcor
from tmath.pydux.telluric_remove import telluric_remove
from tmath.pydux.waveparse import waveparse
from tmath.pydux.parsehourangle import parsehourangle
from tmath.pydux import RADEG
plt.ion()
screen_width, screen_height = get_screen_size()
screenpos = '+{}+{}'.format(int(screen_width * 0.2),
int(screen_height * 0.05))
fig = plt.figure()
fig.canvas.manager.window.wm_geometry(screenpos)
fig.canvas.set_window_title('Final Reductions')
fig.set_size_inches(8, 5)
# turns off key stroke interaction
fig.canvas.mpl_disconnect(fig.canvas.manager.key_press_handler_id)
# this should bring the window to the top, but it doesn't
# wm=plt.get_current_fig_manager()
#fig.canvas.manager.window.attributes('-topmost', 1)
# blah=wm.window.attributes('-topmost', 1)
#plt.pause(0.2)
#fig.canvas.manager.window.attributes('-topmost', 0)
# blah=wm.window.attributes('-topmost', 0)
bstarfits = fits.open('bstar' + gratcode + '.fits')
bstarstar = bstarfits[0].data
bstarhead = bstarfits[0].header
bstarwavezero = float(bstarhead['CRVAL1'])
bstarwavedelt = float(bstarhead['CDELT1'])
bstarwave = np.arange(len(bstarstar)) * bstarwavedelt + bstarwavezero
bstarairmass = float(bstarhead['AIRMASS'])
bstarname = bstarhead['OBJECT']
try:
bstarnum = int(bstarhead['OBSNUM'])
except KeyError:
bstarnum = 0
if (secondord):
bstarfits2 = fits.open('bstarstar' + gratcode2 + '.fits')
bstarstar2 = bstarfits[0].data
bstarhead2 = bstarfits[0].header
bstarwavezero2 = float(bstarhead2['CRVAL1'])
bstarwavedelt2 = float(bstarhead2['CDELT1'])
bstarwave2 = np.arange(
len(bstarstar2)) * bstarwavedelt2 + bstarwavezero2
bstarairmass2 = float(bstarhead2['AIRMASS'])
bstarname2 = bstarhead2['OBJECT']
try:
bstarnum2 = int(bstarhead2['OBSNUM'])
except KeyError:
bstarnum2 = 0
observat = bstarhead['OBSERVAT'].strip().lower()
#reduxdir=os.environ['PY_REDUX']
reduxdir = inspect.getfile(xcor)
reduxdir = reduxdir.rsplit('/', 1)[0] + '/'
kecksky=['keck','gemini-north','gemini-n','gemini-south','gemini-s', \
'soar','ctio','vlt','lco','lco-imacs','lapalma']
licksky = ['lick', 'kpno', 'flwo', 'mmto', 'sso']
if (observat in kecksky):
mskyfile = reduxdir + 'kecksky.fits'
elif (observat in licksky):
mskyfile = reduxdir + 'licksky.fits'
else:
print('\nCannot find mastersky file and observatory unknown\n')
mskyfile = getfitsfile('master sky', '.fits')
print('Using {} as master sky'.format(mskyfile))
mskyfits = fits.open(mskyfile)
mskydata = mskyfits[0].data
mskyhead = mskyfits[0].header
mskywavezero = float(mskyhead['CRVAL1'])
mskywavedelt = float(mskyhead['CDELT1'])
mskywave = np.arange(len(mskydata)) * mskywavedelt + mskywavezero
if (np.abs(np.mean(mskydata)) < 1e-7):
mskydata = mskydata * 1e15
print('\nHello {}\n'.format(user))
lat_dict = {
'keck': 19.8283,
'gemini-north': 19.8238,
'gemini-south': -30.228,
'gemini-n': 19.8238,
'gemini-s': -30.228,
'soar': -30.228,
'kpno': 31.9633,
'lick': 37.3414,
'palomar': 33.35611,
'mcdonald': 30.6717,
'flwo': 31.681,
'mmto': 31.688,
'sso': -31.2734,
'vlt': -24.6254,
'lco': -29.01,
'lco-imacs': -29.01,
'lapalma': 28.75833,
'ctio': -30.16894
}
infile = open(objectlist, 'r')
objname = ''
secondtime = False
seconddone = False
for inputfile in infile:
inputfile = inputfile.strip()
if ('.fits' not in inputfile):
inputfile = inputfile + '.fits'
multifits = fits.open('c' + gratcode + inputfile)
multispec = multifits[0].data
mshead = multifits[0].header
num_apertures = multispec.shape[1]
num_bands = multispec.shape[0]
wavearr = np.zeros((multispec.shape[2], multispec.shape[1]))
if (secondord):
multifits2 = fits.open('c' + gratcode2 + inputfile)
multispec2 = multifits2[0].data
mshead2 = multifits2[0].header
pacheck(mshead)
objectname = mshead['OBJECT']
print('The object is: {}'.format(objectname))
observat = mshead['OBSERVAT'].strip().lower()
airmass = float(mshead['AIRMASS'])
if (airmass < 1):
airmass = 1.0
stringra = mshead['RA']
stringdec = mshead['DEC']
geminilist = ['gemini-north', 'gemini-south', 'gemini-n', 'gemini-s']
if (observat) in geminilist:
ra = float(stringra)
dec = float(stringdec)
else:
coords = SkyCoord(stringra, stringdec, unit=(u.hourangle, u.deg))
ra = coords.ra.deg
dec = coords.dec.deg
ra = ra / RADEG
dec = dec / RADEG
haheader = mshead['HA']
ha = parsehourangle(haheader)
ha = ha * (360. / 24.) / RADEG
if (observat in lat_dict):
latitude = lat_dict[observat]
else:
print('Observatory Unknown!!!!!!!')
latitude = 0.0
latitude = latitude / RADEG
# Get Julian date and Earth's velocity
#epoch=float(mshead['EPOCH'])
date = mshead['DATE-OBS'].strip()
# get year,month,day from ISO Y2K format YYYY-MM-DDThh:mm:ss.ssss
# the time following T is optional, so we get T from UTMIDDLE
if (date[4] == '-'):
year = int(date.split('-')[0])
month = int(date.split('-')[1])
day = int(date.split('-')[2].split('T')[0])
printdate = '{}{:02d}{:02d}'.format(year, month, day)
else:
# Old date format DD/MM/YY
year = int(date[6:8])
month = int(date[3:5])
day = int(date[0:2])
# try to catch old format written after 2000
# good until 2050, by which time no one should
# be doing this
if (year > 50):
year = year + 1900
else:
year = year + 2000
printdate = '{}{:02d}{:02d}'.format(year, month, day)
try:
ut = mshead['UTMIDDLE'].strip()
except KeyError:
ut = mshead['UT'].strip()
if ('T' in ut):
ut = ut.split('T')[1]
# some UT/UTMIDDLE values are ISO format
hour = int(ut.split(':')[0])
minute = int(ut.split(':')[1])
second = float(ut.split(':')[2])
julian = jdcnv(year, month, day,
(hour + (minute / 60.) + (second / 3600.)))
vh, vb = baryvel(julian)
# Earth's velocity toward object
v=vb[0]*np.cos(dec)*np.cos(ra) + vb[1]*np.cos(dec)*np.sin(ra) \
+ vb[2]*np.sin(dec)
# Correct for earth's rotation.
# Note that this isn't strictly correct because ha is set to
# the beginning of the observation, while it really should be
# the middle. But this is a small difference and doesn't affect
# the results in any way that we would notice...
v = v - (0.4651 * np.cos(latitude) * np.sin(ha) * np.cos(dec))
print(
'\nThe velocity of the Earth toward the target is {} km/s'.format(
v))
print('\nThere are {} apertures in the spectrum.\n'.format(
num_apertures))
# clean up header
""" delkeylist=['WAT0_001', 'WAT1_001', 'WAT2_001', 'WAT0_002', \
'WAT1_002', 'WAT2_002', 'WAT3_001', 'WAT2_003', \
'CTYPE1', 'CTYPE2', 'CTYPE3', 'CD1_1', 'CD2_2', \
'CD3_3', 'LTM1_1', 'LTM2_2', 'LTM3_3', 'WCSDIM']
for k in delkeylist:
try:
mshead.remove(k)
except KeyError:
pass """
waveb = None
waver = None
bshift = None
for i in range(0, num_apertures):
# plt.close()
# fig=plt.figure()
# plt.plot(multispec[0,i,:], drawstyle='steps-mid',color='r')
# plt.plot(multispec[1,i,:], drawstyle='steps-mid',color='k')
# plt.xlim(1750,1900)
# plt.pause(0.01)
# print('Check plot')
# answer=yesno('y')
print('\nAperture {}:'.format(i + 1))
wave = getmswave(mshead, i)
print(wave[0], wave[-1])
wdelt = wave[1] - wave[0]
mean = np.mean(multispec[0, i, :])
ymin, ymax = finalscaler(multispec[0, i, :])
# plt.clf()
gs = gridspec.GridSpec(2, 1, height_ratios=[4, 1])
ax0 = plt.subplot(gs[0])
ax1 = plt.subplot(gs[1])
fig.subplots_adjust(hspace=0)
ax0.plot(wave,
multispec[1, i, :],
drawstyle='steps-mid',
color='r')
ax0.plot(wave,
multispec[0, i, :],
drawstyle='steps-mid',
color='k')
# ax0.plot(multispec[0,i,:],multispec[2,i,:],drawstyle='steps-mid',color='r')
# ax0.plot(multispec[0,i,:],multispec[1,i,:],drawstyle='steps-mid',color='k')
plt.pause(0.01)
ax0.set_ylim((ymin, ymax))
ax1.semilogy(wave,np.abs(multispec[1,i,:]-multispec[0,i,:])/mean, \
drawstyle='steps-mid',color='k')
ax0.set_ylabel('Flux')
ax1.set_ylabel('Log of fractional residuals')
ax1.set_xlabel('Wavelength')
plt.pause(0.01)
print('\nPlotting optimal as black, normal as red\n')
extract = inputter_single(
'Do you want to use the (n)ormal or the (o)ptimal extraction? ',
'no')
if (extract == 'o'):
object = multispec[0, i, :]
extractcode = 'optimal'
if (secondord):
object2 = multispec2[0, i, :]
else:
object = multispec[1, i, :]
extractcode = 'normal'
if (secondord):
object2 = multispec2[1, i, :]
skyband = 2
if (num_bands == 2):
skyband = 1
if (num_bands > 3):
sigma = multispec[3, i, :]
else:
sigma = np.sqrt(multispec[skyband, i, :])
if (np.abs(np.mean(object)) < 1e-7):
print('\nScaling data up by 10^15\n')
object = object * 1.e15
sigma = sigma * 1.e15
if (secondord):
if (num_bands > 3):
sigma2 = multispec2[3, i, :]
else:
sigma2 = np.sqrt(multispec2[skyband, i, :])
if (np.abs(np.mean(object)) < 1e-7):
object2 = object2 * 1.e15
sigma2 = sigma2 * 1.e15
nandslist = ['gemini-n', 'gemini-s', 'lco-imacs']
if (observat in nandslist):
skyfile = inputfile.replace('tot', 'sky')
skyfits = fits.open(skyfile)
sky = skyfits[0].data[2, 0, :]
else:
sky = multispec[skyband, i, :]
envelope_size = 25
mx, mn = envelope(sky, envelope_size)
skycont = congrid(mn, (len(sky), ), minusone=True)
test_sky = sky
sky = sky - skycont
if (np.abs(np.mean(sky)) < 1.e-7):
sky = sky * 1.e15
print(len(mskywave), len(mskydata))
msky = scipyrebinsky(mskywave, mskydata, wave)
xfactor = 10
maxlag = 200
if 'kast' in mshead.get('VERSION', ''):
shift = xcor(msky[50:-50], sky[50:-50], xfactor, maxlag)
else:
shift = xcor(msky, sky, xfactor, maxlag)
angshift = shift * wdelt
print('wdeltf', wdelt)
print('The x-cor shift in Angstroms is {}'.format(angshift))
wave = wave + angshift #check to make sure signs are right
skyshiftdone = False
npixsky2 = len(sky) // 2
msky_max = np.max(msky[npixsky2 - 1:])
sky_max = np.max(sky[npixsky2 - 1:])
scale = sky_max / msky_max
plt.close()
fig = plt.figure(figsize=[8, 5])
fig.subplots_adjust(hspace=0)
while (not skyshiftdone):
axarr = fig.subplots(2)
waveplus = wave - angshift
if not secondtime:
axarr[0].plot(waveplus[0:npixsky2],scale*msky[0:npixsky2], \
drawstyle='steps-mid',color='k')
axarr[0].plot(wave[0:npixsky2],sky[0:npixsky2], \
drawstyle='steps-mid',color='r')
axarr[1].plot(waveplus[npixsky2-1:],scale*msky[npixsky2-1:], \
drawstyle='steps-mid',color='k')
axarr[1].plot(wave[npixsky2-1:],sky[npixsky2-1:], \
drawstyle='steps-mid',color='r')
plt.pause(0.01)
print('\nBlack spectrum = master sky')
print(
'Red spectrum = object sky shifted to match master sky'
)
print('Is this ok?')
answer = yesno('y')
if (answer == 'n'):
wave = wave - angshift
angshift = inputter(
'Enter desired shift in Angstroms: ', 'float',
False)
wave = wave + angshift
else:
skyshiftdone = True
else:
wave = wave + angshift
skyshiftdone = True
plt.close()
# B star removal
bstarpass = bstarstar
bobj, bsig, bangshift=telluric_remove(bstarwave,bstarpass, bstarairmass, wave, \
object, airmass, sigma, object, shift=bshift)
# bobj, bsig, bangshift=telluric_remove(bstarwave,bstarpass, bstarairmass, wave, \
# test_sky, airmass, sigma, object)
bshift = bangshift
if (secondord):
bobj2, bsig2, bangshift2 =telluric_remove(bstarwave2,bstarpass2, bstarairmass2, \
wave, object2, airmass, sigma2)
print('\nRemoving redshift due to motion of Earth...')
z = -1 * v / 2.99792458e5
wave = wave / (1 + z)
# rebin
fig = plt.figure()
axarr = fig.subplots(1, 2)
ymin, ymax = finalscaler(bobj[0:100])
axarr[0].plot(wave[0:100], bobj[0:100], drawstyle='steps-mid')
axarr[0].set_xlabel('Wavelength')
axarr[0].set_ylabel('Flux')
#axarr[0].set_ylim((ymin,ymax))
if (secondtime):
axarr[0].plot([wavesave0, wavesave0], [ymin, ymax], color='r')
plt.pause(0.01)
ymin, ymax = finalscaler(bobj[-100:])
axarr[1].plot(wave[-100:], bobj[-100:], drawstyle='steps-mid')
axarr[1].set_xlabel('Wavelength')
axarr[1].set_ylabel('Flux')
try:
axarr[1].set_ylim((ymin, ymax))
except ValueError:
bobj_median = np.nanmedian(bobj)
axarr[1].set_ylim((bobj_median / 10., bobj_median * 10.))
if (secondtime):
axarr[1].plot([wavesaven, wavesaven], [ymin, ymax], color='r')
newdelt = 0.0
plt.pause(0.01)
print('\nCurrent A/pix is {}'.format(wave[1] - wave[0]))
if (secondtime):
print('\nPrevious resolution choice: {}'.format(deltsave))
else:
deltsave = 0.0
newdelt = wave[1] - wave[0]
# while (newdelt <= 0) or (newdelt > wave[-1]):
# print('Rebin to how many Angstroms per pixel? ')
# newdelt=inputter(' <CR> selects previous choice: ','float',True,deltsave)
# if (newdelt <= 0) or (newdelt > wave[-1]):
# print('Need positive resoution and smaller than the')
# print('entire spectrum. Try again')
print('\nCurrent range: {} {}'.format(wave[0], wave[-1]))
if (secondtime):
print('\nPrevious selection was {} {} (marked in red on plot)'.
format(wavesave0, wavesaven))
print('\n<CR> selects previous choice\n')
else:
wavesave0 = 0.0
wavesaven = 0.0
print('Enter the new wavelength range desired: ')
waveb, waver = waveparse(wave, wavesave0, wavesaven)
newbin = (waver - waveb) / newdelt + 1.0 #should stay the same now
# frac,whole=np.modf(newbin)
# if (frac > 0.000001):
# testwave=newdelt*whole+waveb
# print('Closest match is: {} to {}'.format(waveb,testwave))
# print('Would you like this wavelength range?')
# answer=yesno('y')
# if (answer == 'y'):
# waver=testwave
wave_locs = np.where((wave > waveb) & (wave < waver))
# deltsave=newdelt
wavesave0 = waveb
wavesaven = waver
waverange = str(waveb) + ' ' + str(waver)
secondtime = True
# nwave=np.arange(0,whole)*newdelt + waveb
# vartmp=bsig*bsig
# olddeltvec=wave-np.roll(wave,1)
# olddelt=np.mean(olddeltvec)
# nwave = wave
# finalobj = bobj
# finalvar = bsig**2.
# finalsig = bsig
#NOT TESTED!!!
nwave = wave[wave_locs]
print(nwave[0], nwave[-1])
finalobj = bobj[wave_locs]
finalvar = bsig[wave_locs]**2.
finalsig = bsig[wave_locs]
# finalobj=womashrebin(wave,bobj,nwave)
# finalvar=womashrebin(wave,vartmp,nwave)
# finalsig=np.sqrt(finalvar)*np.sqrt(olddelt/newdelt)
#Matt's interpolation algorithm. womashrebin is an unreadable monstrosity.
# interp_data = interpo_flux_conserving(wave, bobj, 1./vartmp, waveb, waver, dw=newdelt, testing=False)
# interp_wave = np.arange(math.ceil(wave[0])+1., math.floor(wave[-1])-1., dtype=float, step=newdelt)
# spectres_data = spectres(interp_wave, wave, bobj, spec_errs=bsig)
# trim_range = (interp_data[0] > waveb) & (interp_data[0] < waver)
# nwave = interp_data[0][trim_range]
# finalobj = interp_data[1][trim_range]
# finalvar = 1./interp_data[2][trim_range]
# finalsig = np.sqrt(finalvar)
suffixes = {}
suffixes['ap' + str(i + 1)] = ''
if os.path.isfile('../HOST_AP_DATA.txt'):
with open('../HOST_AP_DATA.txt') as host_ap_data:
h_lines = host_ap_data.readlines()
for l in h_lines:
suffixes[l.split()[0]] = '_' + l.split()[1]
#gonna ignore the second order stuff for now
if (secondord):
vartmp2 = bsig2 * bsig2
finalobj2 = womashrebin(wave, bobj2, nwave)
finalvar2 = womashrebin(wave, vartmp2, nwave)
finalsig2 = np.sqrt(finalvar2) * np.sqrt(olddelt / newdelt)
if (secondord and not seconddone):
finalobj, finalsig, wavebeg, waveend, brscale = secondcat(
nwave, finalobj, finalobj2, finalsig, finalsig2,
secondtime, wavebeg, waveend, brscale)
seconddone = True
ymin, ymax = finalscaler(finalobj)
plt.close()
fig = plt.figure()
plt.plot(nwave, finalobj, drawstyle='steps-mid')
# plt.plot(spectres_data[0],spectres_data[1],drawstyle='steps-mid', color='green')
plt.xlabel('Wavelength')
plt.ylabel('Flux')
plt.title(objectname)
plt.savefig(objectname + '-' + gratcode + '_ap' + str(i + 1) +
suffixes['ap' + str(i + 1)] + '.png')
plt.show()
outputdone = False
while (not outputdone):
print('\nThe file is: {}'.format(inputfile))
print('The object is: {}'.format(objectname))
print('The DATE-OBS is: {}'.format(date))
print('The aperture is: {}'.format(i + 1))
print('The previous name was: {}'.format(objname))
print('\nEnter the object name for the final fits file: ')
# objname=inputter('(UT date and .fits will be added): ','string',False)
objname = objectname + '-' + gratcode
fname = objname + '-' + printdate + '_ap' + str(
i + 1) + suffixes['ap' + str(i + 1)] + '.fits'
sname = objname + '-' + printdate + '_ap' + str(
i + 1) + suffixes['ap' + str(i + 1)] + '-sigma.fits'
outputdone = True
if (os.path.isfile(fname)):
print('{} already exists!!!!'.format(fname))
print('Do you wish to overwrite it? ')
answer = yesno('y')
if (answer == 'y'):
outputdone = True
else:
outputdone = True
# add to header
new_mshead = mshead.copy()
new_mshead.set('CRPIX1', 1)
new_mshead.set('CRVAL1', nwave[0])
new_mshead.set('CDELT1', nwave[1] - nwave[0])
new_mshead.set('CTYPE1', 'LINEAR')
new_mshead.set('W_RANGE', waverange)
new_mshead.set('BSTAR_Z', bstarairmass)
new_mshead.set('BSTARNUM', bstarnum)
new_mshead.set('BSTAROBJ', bstarname)
new_mshead.set('BARYVEL', v)
new_mshead.set('SKYSHIFT', angshift)
new_mshead.set('ATMSHIFT', bangshift)
new_mshead.set('EXTRACT', extractcode)
new_mshead.set('REDUCER', user)
new_mshead.set('RED_DATE',
str(datetime.now()).split()[0],
'EPOCH OF REDUCTION')
new_mshead.set('OBJECT', objectname)
# if (secondord):
# new_mshead.set('SECOND', 'yes', 'Second order correction attempted')
# new_mshead.set('COMBRANGE',combrange)
# new_mshead.set('BSTAR_Z2',bstarairmass2)
# new_mshead.set('BSTARNU2', bstarnum2)
# new_mshead.set('BSTAROB2', bstarname2)
# fluxairmass2=mshead2['FLX2_Z']
# fluxnum2=mshead2['FLX2_NUM']
# fluxname2=mshead2['FLX2_OBJ']
# new_mshead.set('FLX2_Z',fluxairmass2)
# new_mshead.set('FLX2_NUM', fluxnum2)
# new_mshead.set('FLX2_OBJ', fluxname2)
outdata = np.zeros((len(finalobj), 2))
outdata[:, 0] = finalobj.copy()
outdata[:, 1] = finalsig.copy()
outhdu = fits.PrimaryHDU(outdata)
hdul = fits.HDUList([outhdu])
mshead.set('NAXIS2', 2)
hdul[0].header = new_mshead.copy()
hdul.writeto(fname, overwrite=True)
spectxt = objname + '-' + printdate + '_ap' + str(
i + 1) + suffixes['ap' + str(i + 1)] + '.flm'
spectxt = spectxt.strip()
np.savetxt(spectxt,
np.transpose([nwave,
finalobj.copy(),
finalsig.copy()]))
hdul.close()
print('Do you wish to combine with another spectrum? ')
answer = yesno('y')
fname_comb = None
if (answer == 'y'):
plt.close()
done = False
while (not done):
files = glob.glob(objname.split('-')[0] + '*.fits')
print(files)
for f in files:
if objname not in f and ('red' in f or 'blue' in f
) and '_ap' + str(i + 1) in f:
inputfile = f
inputfile = input(
'Name of fits file to be combined? [{}]: '.format(
inputfile)) or inputfile
print(inputfile)
inputfile = inputfile.strip()
if (inputfile == ''):
return hop
if ('.fits' not in inputfile):
inputfile = inputfile + '.fits'
try:
fitsdata = fits.open(inputfile)
except OSError:
print('File {} cannot be opened.'.format(inputfile))
else:
done = True
crval1 = fitsdata[0].header['CRVAL1']
try:
wdelt = fitsdata[0].header['CDELT1']
except KeyError:
wdelt = 0.0000001
if (wdelt < 0.000001):
wdelt = fitsdata[0].header['CD1_1']
try:
objectname = fitsdata[0].header['OBJECT']
if (not isinstance(objectname, str)):
objectname = inputfile
except KeyError:
objectname = inputfile
data_new = fitsdata[0].data
wave_new = np.arange(1, len(data_new) + 1) * wdelt + crval1
if (len(data_new.shape) == 2):
var_new = data_new[:, 1]
var_new = var_new.astype(float)
var_new = var_new * var_new
flux_new = data_new[:, 0]
flux_new = flux_new.astype(float)
else:
flux_new = data_new.astype(float)
var_new = np.ones(data_new.shape)
if 'red' in inputfile:
wavecomb, fluxcomb, varcomb = womcatfinal(
[nwave, finalobj, finalvar],
[wave_new, flux_new, var_new])
nwave = wavecomb
finalobj = fluxcomb
finalsig = np.sqrt(varcomb)
elif 'blue' in inputfile:
wavecomb, fluxcomb, varcomb = womcatfinal(
[wave_new, flux_new, var_new],
[nwave, finalobj, finalvar])
nwave = wavecomb
finalobj = fluxcomb
finalsig = np.sqrt(varcomb)
else:
print(
"Please include 'blue' or 'red' in filename of spectrum to combine"
)
plt.clf()
plt.plot(nwave, finalobj, drawstyle='steps-mid')
plt.xlabel('Wavelength')
plt.ylabel('Flux')
plt.title(objectname)
plt.savefig(objectname + '_combined_ap' + str(i + 1) +
suffixes['ap' + str(i + 1)] + '.png')
outputdone = False
while (not outputdone):
print('\nThe file is: {}'.format(inputfile))
print('The object is: {}'.format(objectname))
print('The DATE-OBS is: {}'.format(date))
print('The aperture is: {}'.format(i + 1))
print('The previous name was: {}'.format(objname))
print('\nEnter the object name for the final fits file: ')
# objname=inputter('(UT date and .fits will be added): ','string',False)
objname = objectname + '-combined'
fname_comb = objname + '-' + printdate + '_ap' + str(
i + 1) + suffixes['ap' + str(i + 1)] + '.fits'
sname_comb = objname + '-' + printdate + '_ap' + str(
i + 1) + suffixes['ap' + str(i + 1)] + '-sigma.fits'
outputdone = True
if (os.path.isfile(fname)):
print('{} already exists!!!!'.format(fname))
print('Do you wish to overwrite it? ')
answer = yesno('y')
if (answer == 'y'):
outputdone = True
else:
outputdone = True
# add to header
mshead_combined = new_mshead.copy()
mshead_combined.set('CRPIX1', 1)
mshead_combined.set('CRVAL1', nwave[0])
mshead_combined.set('CDELT1', nwave[1] - nwave[0])
mshead_combined.set('CTYPE1', 'LINEAR')
mshead_combined.set('W_RANGE', waverange)
mshead_combined.set('BSTAR_Z', bstarairmass)
mshead_combined.set('BSTARNUM', bstarnum)
mshead_combined.set('BSTAROBJ', bstarname)
mshead_combined.set('BARYVEL', v)
mshead_combined.set('SKYSHIFT', angshift)
mshead_combined.set('ATMSHIFT', bangshift)
mshead_combined.set('EXTRACT', extractcode)
mshead_combined.set('REDUCER', user)
mshead_combined.set(
'RED_DATE',
datetime.now().strftime("%Y-%M-%d %I:%M%p"),
'EPOCH OF REDUCTION')
mshead_combined.set('OBJECT', objectname)
if (secondord): #not implemented
mshead_combined.set('SECOND', 'yes',
'Second order correction attempted')
mshead_combined.set('COMBRANGE', combrange)
mshead_combined.set('BSTAR_Z2', bstarairmass2)
mshead_combined.set('BSTARNU2', bstarnum2)
mshead_combined.set('BSTAROB2', bstarname2)
fluxairmass2 = mshead2['FLX2_Z']
fluxnum2 = mshead2['FLX2_NUM']
fluxname2 = mshead2['FLX2_OBJ']
mshead_combined.set('FLX2_Z', fluxairmass2)
mshead_combined.set('FLX2_NUM', fluxnum2)
mshead_combined.set('FLX2_OBJ', fluxname2)
outdata = np.zeros((len(finalobj), 2))
outdata[:, 0] = finalobj.copy()
outdata[:, 1] = finalsig.copy()
outhdu = fits.PrimaryHDU(outdata)
hdul = fits.HDUList([outhdu])
mshead_combined.set('NAXIS2', 2)
hdul[0].header = mshead_combined.copy()
hdul.writeto(fname_comb, overwrite=True)
hdul.close()
spectxt = objname + '-' + printdate + '_ap' + str(
i + 1) + suffixes['ap' + str(i + 1)] + '.flm'
spectxt = spectxt.strip()
np.savetxt(
spectxt,
np.transpose([nwave,
finalobj.copy(),
finalsig.copy()]))
is_final = input('Is this a final reduction? [y]/n: ') or 'y'
if is_final:
if not os.path.isdir('../../final_reductions/'):
os.mkdir('../../final_reductions/')
os.system('cp ' + fname + ' ' + '../../final_reductions/' +
fname)
if fname_comb:
os.system('cp ' + fname_comb + ' ' +
'../../final_reductions/' + fname_comb)
print('final')
print(objectlist, gratcode, secondord, gratcode2)
plt.close()
return