def on_enter(self):
flat = os.path.join(self.paths['cal'],'Flat.fits')
header = [0]
if not os.path.exists(flat):
if self.theapp.current_night.flaton and self.theapp.current_night.flaton[0]:
fon = fitsimage(str(os.path.join(self.paths['cal'], self.theapp.current_night.flaton[0])), header)
if self.theapp.current_night.flatoff and self.theapp.current_night.flatoff[0]:
foff = fitsimage(str(os.path.join(self.paths['cal'], self.theapp.current_night.flatoff[0])), header)
im_subtract(fon, foff, outputfile = flat)
else:
fits.writeto(flat, fon, header=header[0])
self.current_flats = fitsimage(flat, header)
self.pairstrings = ['{0} - {1}'.format(*map(os.path.basename,x)) for x in self.extract_pairs]
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 on_enter(self):
flat = os.path.join(self.paths['cal'],'Flat.fits')
header = object()
if not os.path.exists(flat):
if self.theapp.current_night.flaton and self.theapp.current_night.flaton[0]:
#fon = FitsImage(os.path.join(self.paths['cal'], \
# self.theapp.current_night.flaton[0]), load=True)
fon = fitsimage(os.path.join(self.paths['cal'], self.theapp.current_night.flaton[0]), header)
if self.theapp.current_night.flatoff and self.theapp.current_night.flatoff[0]:
#foff = FitsImage(os.path.join(self.paths['cal'], \
# self.theapp.current_night.flatoff[0]), load=True)
foff = fitsimage(os.path.join(self.paths['cal'], self.theapp.current_night.flatoff[0]), header)
im_subtract(fon, foff, outputfile = flat)
else:
fits.writeto(flat, fon.data_array, header=fon.header)
self.current_flats = fitsimage(flat, header)
self.pairstrings = ['{0} - {1}'.format(*map(os.path.basename,x)) for x in self.extract_pairs]
def set_calfile(self, flist):
caltype = self.ids.caltypes.text[-2]
if caltype == 'e': return
flatfile = os.path.join(self.current_obsnight.calpath,
self.current_obsnight.date + {'N':'-FlatON',
'F':'-FlatOFF',
'p':'-Wavecal'}[caltype]+'.fits')
tmp = {'N':self.current_obsnight.flaton,
'F':self.current_obsnight.flatoff,
'p':self.current_obsnight.cals}[caltype]
if tmp:
tmp[1] = flist
else:
tmp = ['',flist]
try:
header = [0]
fitsimage(flatfile, header)
header = header[0]
if header['FILES'] == flist:
tmp[0] = flatfile
self.ids.calout.txt = flatfile
except:
pass
setattr(self.current_obsnight, {'N':'flaton', 'F':'flatoff', 'p':'cals'}[caltype], tmp)
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 save_spectra(self, *args, **kw):
#write uncalibrated spectra to fits files (will update after calibration)
lamps = self.lamps
h1, h2 = [0], [0]
fitsimage(self.current_extraction.file1, h1)
h1 = h1[0]
pstub = os.path.join(self.paths['out'],
re.sub('.fits','-ap%i',
os.path.basename(self.current_extraction.file1)))
pstub_sky = os.path.join(self.paths['cal'],
re.sub('.fits','-ap%i',
os.path.basename(self.current_extraction.file1)))
ext = ('.fits','-sky.fits','-lamp.fits')
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)
h2 = h2[0]
nstub = os.path.join(self.paths['out'],
re.sub('.fits','-ap%i',
os.path.basename(self.current_extraction.file2)))
nstub_sky = os.path.join(self.paths['cal'],
re.sub('.fits','-ap%i',
os.path.basename(self.current_extraction.file2)))
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:
if typ == 'spec':
popup = ExamineSpectrum(target=self.current_target,
spectrum=specs, header=h1,
outfile=(pstub+ext[j])%0)
popup.open()
else:
fits.writeto((pstub_sky+ext[j])%0, specs, header=h1, clobber=True)
else:
if typ == 'spec':
popup = ExamineSpectrum(target=self.current_target,
spectrum=specs, header=h2,
outfile=(nstub+ext[j])%0)
popup.open()
else:
fits.writeto((nstub_sky+ext[j])%0, specs, header=h2, clobber=True)
else:
specs = specs.T
for i, ap in enumerate(specs):
if self.fit_params['model'][i][0] > 0:
if typ == 'spec':
popup = ExamineSpectrum(target=self.current_target,
spectrum=ap, header=h1,
outfile=(pstub+ext[j])%i)
popup.open()
else:
fits.writeto((pstub_sky+ext[j])%i, ap, header=h1, clobber=True)
else:
if typ == 'spec':
popup = ExamineSpectrum(target=self.current_target,
spectrum=ap, header=h2,
outfile=(nstub+ext[j])%i)
popup.open()
else:
fits.writeto((nstub_sky+ext[j])%i, -ap, header=h2, clobber=True)
self.theapp.current_target = self.current_target
self.theapp.current_extraction = self.current_extraction
self.theapp.save_current()
self.extract_done = False
def launch_header(self):
head = [0]
fitsimage(self.obsfile, head)
self.header_viewer = FitsHeaderDialog(fitsheader = head[0])
self.header_viewer.bind(on_dismiss = self.update_header())
self.header_viewer.open()
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
