def image_stack(flist, stub, output = 'imstack.fits'):
imlist, junk = parse_filestring(flist, stub)
imlist = [x.fitsfile for x in imlist]
comb = medcombine(imlist, outputfile = output)
tmp = FitsImage(output)
tmp.flist = flist
tmp.header['FILES'] = flist
tmp.update_fits(header_only = True)
return tmp
def fix_distort(self):
if not (self.fit_params.get('pmodel',False) or \
self.fit_params.get('nmodel',False)):
popup = WarningDialog(text='Make sure you fit the trace centers first!')
popup.open()
return
pdistort, ndistort = draw_trace(self.extractregion, self.xx, self.fit_params['pmodel'], \
self.fit_params['nmodel'], fixdistort = True, fitdegree = self.fit_params['deg'])
im1, im2 = [x for x in copy.deepcopy(self.theapp.extract_pairs[self.pair_index])]
im1.load(); im2.load()
#if self.current_flats:
# im1 = im_divide(im1, self.current_flats)
# im2 = im_divide(im2, self.current_flats)
im1.data_array = undistort_imagearray(im1.data_array, pdistort)
im2.data_array = undistort_imagearray(im2.data_array, ndistort)
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['nmodel'] = None
self.fit_params['pmodel'] = None
def set_imagepair(self, val):
if not self.theapp.current_target:
popup = WarningDialog(text='You need to select a target (on the Observing Screen) before proceeding!')
popup.open()
return
self.pair_index = self.pairstrings.index(val)
fitsfile = self.paths['out']+re.sub(' ','',re.sub('.fits','',val))+'.fits'
if not path.isfile(fitsfile):
popup = WarningDialog(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 = WarningDialog(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.load()
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 get_tracedir(self.current_target.instrument_id) == 'vertical' else 1
#tmp = self.current_impair.data_array[self.region[1]:self.region[3]+1,self.region[0]:self.region[2]+1]
#self.extractregion = med_normal(tmp)
tmp = self.theapp.extract_pairs[self.pair_index]
if self.trace_axis:
#self.trace_axis = 1
reg = [self.region[x] for x in [1, 0, 3, 2]]
self.extractregion = make_region(tmp[0], tmp[1], reg, self.current_flats)#.transpose()
else:
self.extractregion = make_region(tmp[0], tmp[1], self.region, self.current_flats).transpose()
reg = self.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 = robm(self.extractregion[dims[0][0]:dims[1][0]+1,\
dims[0][1]:dims[1][1]+1], axis = self.trace_axis)
self.tplot.points = interp_nan(list(enumerate(self.tracepoints)))
pxs, self.tracepoints = zip(*self.tplot.points)
self.drange = minmax(self.tracepoints)
self.ids.the_graph.add_plot(self.tplot)
def set_imagepair(self, val):
if not self.theapp.current_target:
popup = WarningDialog(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 path.isfile(fitsfile):
im1, im2 = [x for x in copy.deepcopy(self.extract_pairs[pair_index])]
im1.load(); im2.load()
#if self.current_flats:
# tmp = im_divide(im1, self.current_flats)
# im1.header, im1.data_array = tmp
# tmp = im_divide(im2, self.current_flats)
# im2.header, im2.data_array = tmp
im_subtract(im1, im2, outputfile=path.join(self.paths['out'],fitsfile))
self.current_impair = FitsImage(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])
class TracefitScreen(IRScreen):
paths = DictProperty([])
itexture = ObjectProperty(Texture.create(size = (2048, 2048)))
iregion = ObjectProperty(None)
current_impair = ObjectProperty(None)
extractregion = ObjectProperty(None)
tplot = ObjectProperty(MeshLinePlot(color=[1,1,1,1])) #change to SmoothLinePlot when kivy 1.8.1
current_target = ObjectProperty(None)
pairstrings = ListProperty([])
apertures = DictProperty({'pos':[], 'neg':[]})
drange = ListProperty([0,1024])
tracepoints = ListProperty([])
trace_axis = NumericProperty(0)
fit_params = DictProperty({})
trace_lines = ListProperty([MeshLinePlot(color=[0,0,1,1]),MeshLinePlot(color=[0,1,1,1])])
current_flats = ObjectProperty(None)
theapp = ObjectProperty(None)
def on_enter(self):
self.pairstrings = ['{0} - {1}'.format(*[path.basename(x.fitsfile) for x in y]) \
for y in self.theapp.extract_pairs]
def set_imagepair(self, val):
if not self.theapp.current_target:
popup = WarningDialog(text='You need to select a target (on the Observing Screen) before proceeding!')
popup.open()
return
self.pair_index = self.pairstrings.index(val)
fitsfile = self.paths['out']+re.sub(' ','',re.sub('.fits','',val))+'.fits'
if not path.isfile(fitsfile):
popup = WarningDialog(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 = WarningDialog(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.load()
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 get_tracedir(self.current_target.instrument_id) == 'vertical' else 1
#tmp = self.current_impair.data_array[self.region[1]:self.region[3]+1,self.region[0]:self.region[2]+1]
#self.extractregion = med_normal(tmp)
tmp = self.theapp.extract_pairs[self.pair_index]
if self.trace_axis:
#self.trace_axis = 1
reg = [self.region[x] for x in [1, 0, 3, 2]]
self.extractregion = make_region(tmp[0], tmp[1], reg, self.current_flats)#.transpose()
else:
self.extractregion = make_region(tmp[0], tmp[1], self.region, self.current_flats).transpose()
reg = self.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 = robm(self.extractregion[dims[0][0]:dims[1][0]+1,\
dims[0][1]:dims[1][1]+1], axis = self.trace_axis)
self.tplot.points = interp_nan(list(enumerate(self.tracepoints)))
pxs, self.tracepoints = zip(*self.tplot.points)
self.drange = minmax(self.tracepoints)
self.ids.the_graph.add_plot(self.tplot)
def add_postrace(self):
peaks = find_peaks(self.tracepoints, len(self.apertures['pos'])+1, \
tracedir = self.trace_axis)
#new_peak = float(peaks[-1])
new_peak = float(peaks)
peakheight = interp_x(self.tplot.points, new_peak)
plot = MeshLinePlot(color=[0,1,0,1], points=[(new_peak, 0), (new_peak, peakheight)])
self.ids.the_graph.add_plot(plot)
newspin = ApertureSlider(aperture_line = plot, tfscreen = self)
newspin.slider.range = [0, len(self.tracepoints)-1]
newspin.slider.step = 0.1
newspin.slider.value = new_peak
newspin.trash.bind(on_press = lambda x: self.remtrace('pos',newspin))
self.ids.postrace.add_widget(newspin)
self.apertures['pos'].append(newspin)
def add_negtrace(self):
peaks = find_peaks(self.tracepoints, len(self.apertures['neg'])+1, \
tracedir = self.trace_axis, pn='neg')
#new_peak = float(peaks[-1])
new_peak = float(peaks)
peakheight = interp_x(self.tplot.points, new_peak)
plot = MeshLinePlot(color=[1,0,0,1], points=[(new_peak, 0), (new_peak, peakheight)])
self.ids.the_graph.add_plot(plot)
newspin = ApertureSlider(aperture_line = plot, tfscreen = self)
newspin.slider.range = [0, len(self.tracepoints)-1]
newspin.slider.step = 0.1
newspin.slider.value = new_peak
newspin.trash.bind(on_press = lambda x: self.remtrace('neg',newspin))
self.ids.negtrace.add_widget(newspin)
self.apertures['neg'].append(newspin)
def remtrace(self, which, widg):
self.ids.the_graph.remove_plot(widg.aperture_line)
self.apertures[which].remove(widg)
if which == 'pos':
self.ids.postrace.remove_widget(widg)
else:
self.ids.negtrace.remove_widget(widg)
def set_psf(self):
popup = SetFitParams()
popup.bind(on_dismiss = lambda x: self.setfp(popup.fit_args))
popup.open()
def setfp(self, args):
self.fit_params = args
def fit_trace(self):
if not self.fit_params or self.fit_params['shape'] not in ('Gaussian','Lorentzian'):
popup = WarningDialog(text='Make sure you set up your fit parameters!')
popup.open()
return
pos = {'pos':[x.slider.value for x in self.apertures['pos']], \
'neg':[x.slider.value 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
self.xx, self.fit_params['pmodel'], self.fit_params['nmodel'] = \
fit_multipeak(self.tracepoints, pos = pos, wid = self.fit_params['wid'], \
ptype = self.fit_params['shape'])
self.trace_lines[0].points = zip(self.xx, self.fit_params['pmodel'](self.xx))
self.trace_lines[1].points = zip(self.xx, self.fit_params['nmodel'](self.xx))
self.ids.the_graph.add_plot(self.trace_lines[0])
self.ids.the_graph.add_plot(self.trace_lines[1])
def fix_distort(self):
if not (self.fit_params.get('pmodel',False) or \
self.fit_params.get('nmodel',False)):
popup = WarningDialog(text='Make sure you fit the trace centers first!')
popup.open()
return
pdistort, ndistort = draw_trace(self.extractregion, self.xx, self.fit_params['pmodel'], \
self.fit_params['nmodel'], fixdistort = True, fitdegree = self.fit_params['deg'])
im1, im2 = [x for x in copy.deepcopy(self.theapp.extract_pairs[self.pair_index])]
im1.load(); im2.load()
#if self.current_flats:
# im1 = im_divide(im1, self.current_flats)
# im2 = im_divide(im2, self.current_flats)
im1.data_array = undistort_imagearray(im1.data_array, pdistort)
im2.data_array = undistort_imagearray(im2.data_array, ndistort)
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['nmodel'] = None
self.fit_params['pmodel'] = None
def manual_trace(self, traces):
pass #need to figure out how to apply these
def extract_spectrum(self):
if not (self.fit_params.get('pmodel',False) or \
self.fit_params.get('nmodel',False)):
popup = WarningDialog(text='Make sure you fit the trace centers first!')
popup.open()
return
#need a calibration, too
self.lamp = None
if theapp.current_night.cals:
self.lamp = theapp.current_night.cals.data_array if not self.current_flats \
else im_divide(theapp.current_night.cals, self.current_flats).data_array
self.lamp = self.lamp[self.region[1]:self.region[3]+1,self.region[0]:self.region[2]+1]
im1, im2 = [x for x in copy.deepcopy(the_app.extract_pairs[self.pair_index])]
im1.load(); im2.load()
#if self.current_flats:
# im1 = im_divide(im1, self.current_flats)
# im2 = im_divide(im2, self.current_flats)
im1.data_array = undistort_imagearray(im1.data_array, pdistort)
im2.data_array = undistort_imagearray(im2.data_array, ndistort)
self.tell = make_region(im1, im2, self.region, flat=self.current_flats, telluric=True)
#tmp, self.tell = im_minimum(im1.data_array, im2.data_array)
#self.tell = self.tell[self.region[1]:self.region[3]+1,self.region[0]:self.region[2]+1]
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)
#write uncalibrated spectra to fits files (will update after calibration)
pstub = self.paths['out'] + re.sub('.fits','-ap%i',im1.fitsfile)
ext = ('.fits','-sky.fits','-lamp.fits')
h = im1.header
for i, p_ap in enumerate(self.pextract):
for j in range(p_ap.shape[1]):
spec = p_ap[:,j]
write_fits((pstub + ext[i]) % j, h, spec)
nstub = self.paths['out'] + re.sub('.fits','-ap%i',im2.fitsfile)
h = im2.header
for i, n_ap in enumerate(self.nextract):
for j in range(n_ap.shape[1]):
spec = n_ap[:,j]
write_fits((nstub + ext[i]) % j, h, spec)
class ExtractRegionScreen(IRScreen):
paths = DictProperty({})
extract_pairs = ListProperty([])
pairstrings = ListProperty([])
imwid = NumericProperty(1024)
imht = NumericProperty(1024)
bx1 = NumericProperty(0)
bx2 = NumericProperty(1024)
by1 = NumericProperty(0)
by2 = NumericProperty(1024)
imcanvas = ObjectProperty(None)
current_impair = ObjectProperty(None)
current_flats = ObjectProperty(None)
theapp = ObjectProperty(None)
def __init__(self):
super(ExtractRegionScreen, self).__init__()
self.ids.ipane.load_data(default_image)
with self.imcanvas.canvas.after:
c = Color(30./255., 227./255., 224./255.)
self.regionline = Line(points=self.lcoords, close=True, \
dash_length = 2, dash_offset = 1)
def on_enter(self):
flat = path.join(self.paths['cal'],'Flat.fits')
if self.theapp.current_night.flaton and self.theapp.current_night.flaton[0]:
fon = FitsImage(path.join(self.paths['cal'], \
self.theapp.current_night.flaton[0]), load=True)
if self.theapp.current_night.flatoff and self.theapp.current_night.flatoff[0]:
foff = FitsImage(path.join(self.paths['cal'], \
self.theapp.current_night.flatoff[0]), load=True)
im_subtract(fon, foff, outputfile = flat)
else:
write_fits(flat, fon.header, fon.data_array)
self.current_flats = FitsImage(flat, load = True)
self.pairstrings = ['{0} - {1}'.format(*[path.basename(x.fitsfile) for x in y]) for y in self.extract_pairs]
def on_pre_leave(self):
self.theapp.current_impair = self.current_impair
self.theapp.current_flats = self.current_flats
def set_imagepair(self, val):
if not self.theapp.current_target:
popup = WarningDialog(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 path.isfile(fitsfile):
im1, im2 = [x for x in copy.deepcopy(self.extract_pairs[pair_index])]
im1.load(); im2.load()
#if self.current_flats:
# tmp = im_divide(im1, self.current_flats)
# im1.header, im1.data_array = tmp
# tmp = im_divide(im2, self.current_flats)
# im2.header, im2.data_array = tmp
im_subtract(im1, im2, outputfile=path.join(self.paths['out'],fitsfile))
self.current_impair = FitsImage(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 get_coords(self):
xscale = float(self.imcanvas.width) / float(self.imwid)
yscale = float(self.imcanvas.height) / float(self.imht)
x1 = float(self.bx1) * xscale
y1 = float(self.by1) * yscale
x2 = float(self.bx2) * xscale
y2 = float(self.by2) * yscale
return [x1, y1, x1, y2, x2, y2, x2, y1]
lcoords = AliasProperty(get_coords, None, bind=('bx1', 'bx2', 'by1', 'by2', 'imwid', 'imht'))
def set_coord(self, coord, value):
if coord == 'x1':
self.bx1 = value
elif coord == 'x2':
self.bx2 = value
elif coord == 'y1':
self.by1 = value
elif coord == 'y2':
self.by2 = value
self.regionline.points = self.lcoords
def save_region(self):
self.current_impair.header['EXREGX1'] = (self.bx1, 'extraction region coordinate X1')
self.current_impair.header['EXREGY1'] = (self.by1, 'extraction region coordinate Y1')
self.current_impair.header['EXREGX2'] = (self.bx2, 'extraction region coordinate X2')
self.current_impair.header['EXREGY2'] = (self.by2, 'extraction region coordinate Y2')
self.current_impair.update_fits()
factor.disabled = False
val = factor.value_normalized
factor.range = (1, 6)
factor.step = 0.1
factor.value_normalized = val
def reset_zoom(self):
scatr = self.ids.the_scatter
scatr.pos = self.ids.fl.pos
scatr.scale = 1
def submit_changes(self):
self.tmin = float(self.ids.ti_min.text)
self.tmax = float(self.ids.ti_max.text)
factor = self.ids.sfactor.value
if self.ids.smode.text == 'gamma':
factor = 10.**factor
info = {'min':self.tmin, 'max':self.tmax, \
'mode':self.ids.smode.text, 'factor':factor}
self.data.change_parameters(info)
self.update_display()
if __name__ == '__main__':
from kivy.base import runTouchApp
wid = ImagePane()
#wid.load_data(default_image)
im = FitsImage('/Users/gray/Desktop/mdm2013/062413/06242013_tell203-a.fits')
im.load()
wid.load_data(im)
runTouchApp(wid)
