Exemple #1
0
 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
Exemple #2
0
    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)