def set_imagepair(self, val):
if not self.theapp.current_target:
popup = AlertDialog(text='You need to select a target (on the Observing Screen) before proceeding!')
popup.open()
return
header = [[0],[0]]
pair = self.extract_pairs[self.pairstrings.index(val)]
self.current_extraction = self.current_target.extractions.get(str(hash(':'.join(pair))), None)
if not self.current_extraction:
im1, im2 = [fitsimage(os.path.join(self.paths['raw'], x), header[i]) for i, x in enumerate(pair)]
if 'EXREGX1' in header[0] or 'EXREGX1' in header[1]:
for x in ['x1','y1','x2','y2']:
tmp = header[0]['EXREG'+x.upper()] or header[1]['EXREG'+x.upper()]
if tmp:
self.set_coord(x, tmp)
region = map(int,[self.bx1, self.by1, self.bx2, self.by2])
td = int(tracedir(self.current_target.instrument_id) == 'horizontal')
self.current_extraction = extraction(im1, im2, self.current_flats, region,
td, 'Gaussian')
self.current_extraction.file1 = pair[0]
self.current_extraction.file2 = pair[1]
self.current_extraction.flatfile = os.path.join(self.paths['cal'],'Flat.fits')
self.theapp.current_target.extractions[self.current_extraction.name] = self.current_extraction
else:
self.bx1, self.by1, self.bx2, self.by2 = self.current_extraction.region
im = scalable_image(self.current_extraction.diff)
self.ids.ipane.load_data(im)
self.imwid, self.imht = im.dimensions
def go_screen(self, idx):
if (idx > 1 and self.root.ids.sm.screens[1].current_target.targid == ''):
popup = AlertDialog(text='You need to select a target before proceeding!')
popup.open()
return
self.index = idx
self.update_screen()
def go_next_screen(self):
if (self.root.ids.sm.current == 'observing' and
self.root.ids.sm.screens[1].current_target.targid == ''):
popup = AlertDialog(text='You need to select a target before proceeding!')
popup.open()
return
self.index = (self.index + 1) % len(self.screen_names)
self.update_screen()
def check_filestub(self, stub):
placeholder = '#'
reg = placeholder+'+'
if len(re.findall(reg, stub)) != 1:
popup = AlertDialog(text = "File format is not valid; must use '#' as placeholder only")
popup.open()
return
self.current_obsnight.filestub = stub
def wavecal(self):
if not self.linelist:
popup = AlertDialog(text="Please select a line list first.")
popup.open()
return
if not self.assignment.assignment:
popup = AlertDialog(text='Please designate initial line assignments.')
popup.open()
return
calfile = os.path.join(self.paths['cal'],self.speclist[self.spec_index])
if self.ids.lampcal_toggle.state == 'down':
calfile += '-lamp.fits'
else:
calfile += '-sky.fits'
try:
calib = ExtractedSpectrum(str(calfile))
except IOError:
popup = AlertDialog(text="You don't have a calibration of this type...")
popup.open()
return
self.calibration = calibrate_wavelength(medfilt(calib.spec), list(self.synthspec), zip(*self.assignment.assignment))
try:
for i, w in enumerate(self.calibration.parameters):
self.current_spectrum.header['WAVECAL%i'%i] = (w, 'Wavelength calibration coefficient')
self.current_spectrum.wav = self.calibration(range(len(self.current_spectrum.spec)))
self.ids.specdisplay.xmin = float(floor_round(self.current_spectrum.wav.min(), dec=1))
self.ids.specdisplay.xmax = float(ceil_round(self.current_spectrum.wav.max(), dec=1))
self.ids.specdisplay.xlabel = 'Wavelength'
self.current_spectrum.plot.points = zip(self.current_spectrum.wav, self.current_spectrum.spec)
self.save_spectrum()
except Exception as e:
print e
def assign(self):
if not self.linelist:
popup = AlertDialog(text="Please select a line list first.")
popup.open()
return
fext = '-lamp.fits' if self.theapp.current_night.cals else '-sky.fits'
fname = os.path.join(self.paths['cal'],
os.path.basename(self.current_spectrum.filename).replace('.fits', fext))
cal = ExtractedSpectrum(fname)
cal.spec = detrend(medfilt(cal.spec, 3))
srange = [float(self.ids.wmin.text), float(self.ids.wmax.text)]
self.synthspec = synth_from_range(dict(self.linelist), cal.spec.size, srange)
self.assignment = AssignLines(spectrum=cal, synth=self.synthspec, exp_lo=srange[0], exp_hi=srange[1])
self.assignment.open()
def fit_trace(self):
if not self.fit_params or self.fit_params['shape'] not in ('Gaussian','Lorentzian'):
popup = AlertDialog(text='Make sure you set up your fit parameters!')
popup.open()
return
stripe = np.array(self.tracepoints, dtype=np.float64)
wid = self.fit_params['wid']
self.current_extraction.mtype = self.fit_params['shape']
stripex = np.arange(stripe.size, dtype=float)
pos = tuple((interp(stripe, stripex.astype(np.float64), np.array([x.slider.value], dtype=np.float64)),
x.slider.value,
wid) for x in self.apertures['pos']) + \
tuple((interp(stripe, stripex.astype(np.float64), np.array([x.slider.value], dtype=np.float64)),
x.slider.value,
wid) for x in self.apertures['neg'])
for x in self.trace_lines:
if x in self.ids.the_graph.plots:
self.ids.the_graph.remove_plot(x)
if self.fit_params.get('man',False):
popup = DefineTrace(npos=len(self.apertures['pos']), \
nneg=len(self.apertures['neg']), imtexture = self.iregion)
popup.bind(on_dismiss = self.manual_trace(popup.tracepoints))
popup.open()
return
peaks = fitpeaks1d(stripe, pos, model_type=self.fit_params['shape']).individual()
self.fit_params['model'] = [p.parameters.tolist() for p in peaks]
self.fit_params['pmodel'] = [p.parameters.tolist() for p in peaks if p.amplitude > 0]
self.fit_params['nmodel'] = [p.parameters.tolist() for p in peaks if p.amplitude < 0]
pmod = CompositeModel(tuple(self.fit_params['pmodel']), self.fit_params['shape'])
nmod = CompositeModel(tuple(self.fit_params['nmodel']), self.fit_params['shape'])
self.trace_lines[0].points = zip(stripex, pmod(stripex))
self.trace_lines[1].points = zip(stripex, nmod(stripex))
self.ids.the_graph.add_plot(self.trace_lines[0])
self.ids.the_graph.add_plot(self.trace_lines[1])
def extract_spectrum(self):
if not self.fit_params.get('model',False):
popup = AlertDialog(text='Make sure you fit the trace centers first!')
popup.open()
return
self.waiting.open()
self.lamp = np.empty([2,2], dtype=np.float64)
self.lamps = False
if self.theapp.current_night.cals:
self.lamp = self.theapp.current_night.cals if not self.current_flats \
else im_divide(self.theapp.current_night.cals, self.current_flats)
self.lamp = self.lamp[self.region[1]:self.region[3]+1,self.region[0]:self.region[2]+1]
self.lamps = True
t = Thread(target=self.extract_wrapper)
t.start()
def set_imagepair(self, val):
if not self.theapp.current_target:
popup = AlertDialog(text='You need to select a target (on the Observing Screen) before proceeding!')
popup.open()
return
pair_index = self.pairstrings.index(val)
fitsfile = self.paths['out']+re.sub(' ','',re.sub('.fits','',val))+'.fits'
if not os.path.isfile(fitsfile):
im1, im2 = [x for x in copy.deepcopy(self.extract_pairs[pair_index])]
im1.load(); im2.load()
im_subtract(im1, im2, outputfile=os.path.join(self.paths['out'],fitsfile))
self.current_impair = FitsImage(os.path.join(self.paths['out'],fitsfile), load=True)
self.ids.ipane.load_data(self.current_impair)
self.imwid, self.imht = self.current_impair.dimensions
if self.current_impair.get_header_keyword('EXREGX1'):
for x in ['x1', 'y1', 'x2', 'y2']:
tmp = self.current_impair.get_header_keyword('EXREG'+x.upper())
if tmp[0] is not None:
self.set_coord(x, tmp[0])
def fix_distort(self):
popup = AlertDialog(text='This is not yet functional')
popup.open()
return
if not (self.fit_params.get('model',False)):
popup = AlertDialog(text='Make sure you fit the trace centers first!')
popup.open()
return
trace = self.current_extraction.fit_trace(self.fit_params['model'], np.empty(0), False)
#im1, im2 = [x for x in copy.deepcopy(self.theapp.extract_pairs[self.pair_index])]
#im1.load(); im2.load()
#dist_reshape = lambda x, y: x.reshape(len(y), x.size/len(y))
#pdistort = dist_reshape(self.fit_params['pmodel'].parameters, self.apertures['pos'])
#ndistort = dist_reshape(self.fit_params['nmodel'].parameters, self.apertures['neg'])
#im1.data_array = self.current_extraction.fix_distortion(self.fit_params['model'])
#im2.data_array = extract.fix_distortion(im2.data_array, ndistort)
self.current_extraction.fix_distortion(trace)
self.theapp.current_target.extractions[self.current_extraction.name] = self.current_extraction
#im_subtract(im1, im2, outputfile=self.current_impair.fitsfile)
#tmp = self.current_impair
#self.current_impair = FitsImage(self.current_impair.fitsfile)
#self.current_impair.header['EXREGX1'] = (tmp.get_header_keyword('EXREGX1'), 'extraction region coordinate X1')
#self.current_impair.header['EXREGY1'] = (tmp.get_header_keyword('EXREGY1'), 'extraction region coordinate Y1')
#self.current_impair.header['EXREGX2'] = (tmp.get_header_keyword('EXREGX2'), 'extraction region coordinate X2')
#self.current_impair.header['EXREGY2'] = (tmp.get_header_keyword('EXREGY2'), 'extraction region coordinate Y2')
#self.current_impair.update_fits(header_only = True)
self.set_imagepair(self.pairstrings[self.pair_index])
self.fit_params['model'] = None
self.theapp.current_extraction = self.current_extraction
self.theapp.save_current()
#self.fit_params['nmodel'] = None
#self.fit_params['pmodel'] = None
pdb.set_trace()
def wavecal(self):
if not self.linelist:
popup = AlertDialog(text="Please select a line list first.")
popup.open()
return
calfile = self.paths['cal'] + self.speclist[self.spec_index]
if self.ids.lampcal.state == 'down':
calfile += '-lamp.fits'
else:
calfile += '-sky.fits'
try:
calib = ExtractedSpectrum(calfile)
except:
popup = AlertDialog(text="You don't have a calibration of this type...")
popup.open()
return
niter = self.ids.numiter.text
if self.linelist in self.linelists:
#lldb = shelve.open('storage/linelists')
#linelist_path = ird.deserialize(linelistdb[self.lineslist])
linelist_path = linelistdb[self.linelist]
#lldb.close()
else:
linelist_path = self.linelist
self.calibration = calibrate_wavelength(calib, linelist_path, (self.wmin, self.wmax), niter)
for i, w in self.calibration.parameters:
self.current_spectrum.header['WAVECAL%i'%i] = (w, 'Wavelength calibration coefficient')
self.current_spectrum.wav = self.calibration(range(len(self.current_spectrum.spec)))
self.wmin = self.current_spectrum.wav.min()
self.wmax = self.current_spectrum.wav.max()
self.current_spectrum.plot.points = zip(self.current_spectrum.wav, self.current_spectrum.spec)
def set_spectrum(self, spec):
self.spec_index = self.speclist.index(spec)
try:
tmp = ExtractedSpectrum(self.paths['out']+self.speclist[self.spec_index] + '.fits')
except:
popup = AlertDialog(text="You haven't extracted that spectrum yet!")
popup.open()
return
if self.current_spectrum:
self.ids.specdisplay.remove_plot(self.current_spectrum.plot)
self.current_spectrum = tmp
self.current_spectrum.plot = SmoothLinePlot(color=[.9,1,1,1])
if not self.current_spectrum.wav:
self.wmin = 0
self.wmax = len(self.current_spectrum.spec)-1
self.current_spectrum.wav = range(self.wmax)
else:
self.wmin = self.current_spectrum.wav.min()
self.wmax = self.current_spectrum.wav.max()
self.dmin, self.dmax = minmax(self.current_spectrum.spec)
self.current_spectrum.plot.points = zip(self.current_spectrum.wav, self.current_spectrum.spec)
self.ids.specdisplay.add_plot(self.current_spectrum.plot)
def set_imagepair(self, val):
if not self.theapp.current_target:
popup = AlertDialog(text='You need to select a target (on the Observing Screen) before proceeding!')
popup.open()
return
header = [fits.Header()]*2
pair = self.extract_pairs[self.pairstrings.index(val)]
#im1, im2 = [FitsImage(os.path.join(self.paths['raw'], x),
# load=True) for x in pair]
self.current_extraction = self.current_target.extractions.get(str(hash(':'.join(pair))), None)
if not self.current_extraction:
im1, im2 = [fitsimage(os.path.join(self.paths['raw'], x), header[i]) for i, x in enumerate(pair)]
if 'EXREGX1' in header[0] or 'EXREGX1' in header[1]:
for x in ['x1','y1','x2','y2']:
tmp = header[0]['EXREG'+x.upper()] or header[1]['EXREG'+x.upper()]
if tmp:
self.set_coord(x, tmp)
region = map(int,[self.bx1, self.by1, self.bx2, self.by2])
td = int(tracedir(self.current_target.instrument_id) == 'horizontal')
#pdb.set_trace()
self.current_extraction = extraction(im1, im2, self.current_flats, region,
td, 'Gaussian')
self.current_extraction.file1 = pair[0]
self.current_extraction.file2 = pair[1]
self.current_extraction.flatfile = os.path.join(self.paths['cal'],'Flat.fits')
self.theapp.current_target.extractions[self.current_extraction.name] = self.current_extraction
else:
self.bx1, self.by1, self.bx2, self.by2 = self.current_extraction.region
#fitsfile = self.paths['out']+re.sub(' ','',re.sub('.fits','',val))+'.fits'
#im1, im2 = [x for x in copy.deepcopy(self.extract_pairs[pair_index])]
#if not os.path.isfile(fitsfile):
# im1, im2 = [x for x in copy.deepcopy(self.extract_pairs[pair_index])]
# im1.load(); im2.load()
# im_subtract(im1, im2, outputfile=os.path.join(self.paths['out'],fitsfile))
#self.current_impair = FitsImage(os.path.join(self.paths['out'],fitsfile), load=True)
#self.ids.ipane.load_data(self.current_impair)
im = scalable_image(self.current_extraction.diff)
self.ids.ipane.load_data(im)
self.imwid, self.imht = im.dimensions
def set_spectrum(self, spec):
self.spec_index = self.speclist.index(spec)
try:
tmp = ExtractedSpectrum(str(os.path.join(self.paths['out'],self.speclist[self.spec_index] + '.fits')))
except IOError:
popup = AlertDialog(text="You haven't extracted that spectrum yet!")
popup.open()
return
if self.current_spectrum:
self.ids.specdisplay.remove_plot(self.current_spectrum.plot)
if not self.theapp.current_night.cals:
self.ids.lampcal_toggle.state = 'normal'
self.ids.lampcal_toggle.disabled = True
self.ids.skycal_toggle.state = 'down'
self.current_spectrum = tmp
self.current_spectrum.spec = medfilt(self.current_spectrum.spec, 3)
self.current_spectrum.plot = MeshLinePlot(color=[.9,1,1,1])
self.current_spectrum.plot.points = zip(self.current_spectrum.wav, self.current_spectrum.spec)
self.ids.specdisplay.add_plot(self.current_spectrum.plot)
self.ids.specdisplay.xmin = float(floor_round(self.current_spectrum.wav.min(), dec=1))
self.ids.specdisplay.xmax = float(ceil_round(self.current_spectrum.wav.max(), dec=1))
self.ids.specdisplay.ymin = float(floor_round(self.current_spectrum.spec.min(), dec=1))
self.ids.specdisplay.ymax = float(ceil_round(self.current_spectrum.spec.max(), dec=1))
self.ids.specdisplay.xlabel = ['Pixel','Wavelength']['WAVECAL0' in self.current_spectrum.header]
def set_imagepair(self, val):
if not self.theapp.current_target:
popup = AlertDialog(text='You need to select a target (on the Observing Screen) before proceeding!')
popup.open()
return
if self.pairstrings.index(val) == self.pair_index:
return
self.clear_pair()
self.pair_index = self.pairstrings.index(val)
pair = self.theapp.extract_pairs[self.pair_index]
extract_state = self.theapp.current_target.extractions.get(str(hash(':'.join(pair))),None)
if extract_state:
self.current_extraction = extract_state #extraction_from_state(extract_state, self.current_flats)
else:
popup = AlertDialog(text="You have to select an extraction region for this image pair before you can move on to this step.")
popup.open()
return
self.current_impair = scalable_image(self.current_extraction.diff)
self.trace_axis = int(tracedir(self.current_target.instrument_id) == 'horizontal')
idata = ''.join(map(chr,self.current_impair.scaled))
self.itexture.blit_buffer(idata, colorfmt='luminance', bufferfmt='ubyte', \
size = self.current_impair.dimensions)
self.extractregion = self.current_extraction.extract_region
reg = self.current_extraction.region[:]
reg[2] = reg[2] - reg[0]
reg[3] = reg[3] - reg[1]
#if self.trace_axis:
# self.iregion = self.itexture.get_region(*reg)
#else:
# self.iregion = self.itexture.get_region(reg[1],reg[0],reg[3],reg[2])
self.iregion = self.itexture.get_region(*reg)
self.rtx = [0.0] + [[0.0, 1.0][self.trace_axis]]*2 + [1.0, 1.0] + [[1.0, 0.0][self.trace_axis]]*2 + [0.0]
dims = [[0,0],list(self.extractregion.shape)]
dims[0][self.trace_axis] = 0.4 * self.extractregion.shape[self.trace_axis]
dims[1][self.trace_axis] = 0.6 * self.extractregion.shape[self.trace_axis]
self.tracepoints = twod_to_oned(self.extractregion[dims[0][0]:dims[1][0]+1,
dims[0][1]:dims[1][1]+1], axis=self.trace_axis)
points = replace_nans(np.array(self.tracepoints))
self.tplot.points = zip(np.arange(points.size), points)
self.tracepoints = points
self.drange = [float(points.min()), float(points.max())]
self.ids.the_graph.add_plot(self.tplot)
if self.current_extraction.name in self.trace_info:
info = self.trace_info[self.current_extraction.name]
for trace in info['ap']['pos']:
self.add_postrace(val=trace)
for trace in info['ap']['neg']:
self.add_negtrace(val=trace)
self.trace_lines = info['lines']
self.ids.the_graph.add_plot(self.trace_lines[0])
self.ids.the_graph.add_plot(self.trace_lines[1])
self.fit_params = info['par']
else:
self.trace_info[self.current_extraction.name] = {'ap':{'pos':[], 'neg':[]}, 'lines':[]}
def fix_distort(self):
popup = AlertDialog(text='This is not yet functional')
popup.open()
return
if not (self.fit_params.get('model',False)):
popup = AlertDialog(text='Make sure you fit the trace centers first!')
popup.open()
return
trace = self.current_extraction.fit_trace(self.fit_params['model'], np.empty(0), False)
self.current_extraction.fix_distortion(trace)
self.theapp.current_target.extractions[self.current_extraction.name] = self.current_extraction
self.set_imagepair(self.pairstrings[self.pair_index])
self.fit_params['model'] = None
self.theapp.current_extraction = self.current_extraction
self.theapp.save_current()
def alert(self, message, button_message="Close"):
alert = AlertDialog(message, button_message)
self.beep()
alert.show()
alert.exec_()
def set_imagepair(self, val):
if not self.theapp.current_target:
popup = AlertDialog(text='You need to select a target (on the Observing Screen) before proceeding!')
popup.open()
return
self.pair_index = self.pairstrings.index(val)
pair = self.theapp.extract_pairs[self.pair_index]
extract_state = self.theapp.current_target.extractions.get(str(hash(':'.join(pair))),None)
if extract_state:
self.current_extraction = extract_state #extraction_from_state(extract_state, self.current_flats)
else:
popup = AlertDialog(text='You have to select an extraction'\
'region for this image pair \nbefore you can move on to this step.')
popup.open()
return
#fitsfile = self.paths['out']+re.sub(' ','',re.sub('.fits','',val))+'.fits'
#if not os.path.isfile(fitsfile):
# popup = AlertDialog(text='You have to select an extraction'\
# 'region for this image pair \nbefore you can move on to this step.')
# popup.open()
# return
#self.current_impair = FitsImage(fitsfile)
#self.region = self.current_impair.get_header_keyword(*('EXREG' + x for x in ['X1','Y1','X2','Y2']))
#if not any(self.region):
# popup = AlertDialog(text='You have to select an extraction'\
# 'region for this image pair \nbefore you can move on to this step.')
# popup.open()
# return
self.current_impair = scalable_image(self.current_extraction.diff)
idata = ''.join(map(chr,self.current_impair.scaled))
self.itexture.blit_buffer(idata, colorfmt='luminance', bufferfmt='ubyte', \
size = self.current_impair.dimensions)
#self.trace_axis = 0 if tracedir(self.current_target.instrument_id) == 'vertical' else 1
self.trace_axis = int(tracedir(self.current_target.instrument_id) == 'horizontal')
#if self.trace_axis:
#self.trace_axis = 1
# reg = [self.region[x] for x in [1, 0, 3, 2]]
#self.extractregion = make_region(pair[0], pair[1], reg, self.current_flats)#.transpose()
#else:
# self.extractregion = make_region(pair[0], pair[1], self.region, self.current_flats).transpose()
#self.current_extraction = extraction(pair[0].data, pair[0].data, self.current_flats.data,
# self.region, self.trace_axis, 'Gaussian')
self.extractregion = self.current_extraction.extract_region
reg = self.current_extraction.region[:]
reg[2] = reg[2] - reg[0]
reg[3] = reg[3] - reg[1]
self.iregion = self.itexture.get_region(*reg)
dims = [[0,0],list(self.extractregion.shape)]
dims[0][self.trace_axis] = 0.4 * self.extractregion.shape[self.trace_axis]
dims[1][self.trace_axis] = 0.6 * self.extractregion.shape[self.trace_axis]
#self.tracepoints = Robust2D(self.extractregion[dims[0][0]:dims[1][0]+1,
# dims[0][1]:dims[1][1]+1]).combine(axis=self.trace_axis)
self.tracepoints = twod_to_oned(self.extractregion[dims[0][0]:dims[1][0]+1,
dims[0][1]:dims[1][1]+1], axis=self.trace_axis)
#points = RobustData(self.tracepoints, index=True)
#points.replace_nans(inplace=True)
points = replace_nans(np.array(self.tracepoints))
self.tplot.points = zip(np.arange(points.size), points)
self.tracepoints = points
self.drange = [float(points.min()), float(points.max())]
self.ids.the_graph.add_plot(self.tplot)
def extract_spectrum(self):
if not self.fit_params.get('model',False):
popup = AlertDialog(text='Make sure you fit the trace centers first!')
popup.open()
return
#need a calibration, too
self.lamp = np.empty([2,2], dtype=np.float64)
lamps = False
if self.theapp.current_night.cals:
self.lamp = self.theapp.current_night.cals if not self.current_flats \
else im_divide(self.theapp.current_night.cals, self.current_flats)
self.lamp = self.lamp[self.region[1]:self.region[3]+1,self.region[0]:self.region[2]+1]
lamps = True
#im1, im2 = [x for x in copy.deepcopy(self.theapp.extract_pairs[self.pair_index])]
#im1.load(); im2.load()
#im1.data_array = extract.fix_distortion(im1.data_array, pdistort)
#im2.data_array = extract.fix_distortion(im2.data_array, ndistort)
#self.tell = make_region(im1, im2, self.region, flat=self.current_flats, telluric=True)
#self.pextract = extract(self.fit_params['pmodel'], self.extractregion, self.tell, 'pos', lamp = self.lamp)
#self.nextract = extract(self.fit_params['nmodel'], self.extractregion, self.tell, 'neg', lamp = self.lamp)
self.current_extraction.fit_trace(self.fit_params['model'], self.lamp, lamps=lamps, extract=True)
#if self.lamp.size > 0:
# spectra, tellurics, lamps = self.current_extraction.extract(trace,
# self.lamp,
# False)
#else:
# spectra, telluric = self.current_extraction.extract(trace, self.lamp, True)
#write uncalibrated spectra to fits files (will update after calibration)
h1, h2 = fits.Header(), fits.Header()
fitsimage(self.current_extraction.file1, h1)
#im1 = FitsImage(self.current_extraction.file1, load=False)
pstub = os.path.join(self.paths['out'],
re.sub('.fits','-ap%i',
os.path.basename(self.current_extraction.file1)))#im1.fitsfile)
ext = ('.fits','-sky.fits','-lamp.fits')
#h = im1.header
h1['EXREGX1'] = (self.current_extraction.region[0], 'extraction region coordinate X1')
h1['EXREGY1'] = (self.current_extraction.region[1], 'extraction region coordinate Y1')
h1['EXREGX2'] = (self.current_extraction.region[2], 'extraction region coordinate X2')
h1['EXREGY2'] = (self.current_extraction.region[3], 'extraction region coordinate Y2')
fitsimage(self.current_extraction.file2, h2)
nstub = os.path.join(self.paths['out'],
re.sub('.fits','-ap%i',
os.path.basename(self.current_extraction.file2)))#im2.fitsfile)
#h = im2.header
h2['EXREGX1'] = (self.current_extraction.region[0], 'extraction region coordinate X1')
h2['EXREGY1'] = (self.current_extraction.region[1], 'extraction region coordinate Y1')
h2['EXREGX2'] = (self.current_extraction.region[2], 'extraction region coordinate X2')
h2['EXREGY2'] = (self.current_extraction.region[3], 'extraction region coordinate Y2')
for j, typ in enumerate(['spec', 'tell']+['lamp']*lamps):
specs = self.current_extraction.extracts[typ]
if len(specs.shape) == 1:
if self.fit_params['model'][0][0] > 0:
fits.writeto((pstub+ext[j])%0, specs, header=h1)
else:
fits.writeto((nstub+ext[j])%0, specs*-1., header=h2)
else:
specs = specs.T
for i, ap in enumerate(specs):
if self.fit_params['model'][i][0] > 0:
fits.writeto((pstub+ext[j])%i, ap, header=h1)
else:
fits.writeto((nstub+ext[j])%i, ap*-1., header=h2)
return
def alert_aux(self, alert_text, button_text):
self.log(alert_text)
alert = AlertDialog(alert_text, button_text)
self.beep(message="alert")
alert.show()
alert.exec_()
