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 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 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_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)
