mosaicdirs = [] missingpointing = False scales = [] sdb = SurveysDB() for p in mosaicpointings: if p in ignorepointings: continue print('Wanting to put pointing %s in mosaic' % p) for d in args.directories: rd = d + '/' + p print(rd) if os.path.isfile(rd + '/' + fname): mosaicdirs.append(rd) try: qualitydict = sdb.get_quality(p) currentdict = sdb.get_field(p) print(qualitydict) #scale=qualitydict['scale'] scale = 1.0 / (qualitydict['nvss_scale'] / 5.9124) if scale is None: print('Missing scaling factor for', p) missingpointing = True scale = 1.0 scales.append(scale) except TypeError: missingpointing = True print('No scaling factor for ', p) scales.append(1.0) break else:
print 'Now searching for results directories' cwd=os.getcwd() # find what we need to put in the mosaic mosaicpointings,mosseps = find_pointings_to_mosaic(pointingdict,mospointingname) maxsep=np.max(mosseps) # now find whether we have got these pointings somewhere! mosaicdirs=[] missingpointing = False sdb = SurveysDB() for p in mosaicpointings: print 'Wanting to put pointing %s in mosaic'%p currentdict = sdb.get_field(p) for d in args.directories: rd=d+'/'+p print rd if os.path.isfile(rd+'/image_full_ampphase_di_m.NS_shift.int.facetRestored.fits'): mosaicdirs.append(rd) break else: print 'Pointing',p,'not found' missingpointing = True if not missingpointing and (currentdict['status'] != 'Archived' or currentdict['archive_version'] != 4): print 'Pointing',p,'not archived with archive_version 4' missingpointing = True sdb.close() if not(args.no_check) and missingpointing == True: raise RuntimeError('Failed to find a required pointing')
ax.scatter(np.radians(x), np.radians(Dec), s=10, color='r', zorder=1, alpha=1.0) # convert degrees to radians sdb = SurveysDB() ravals = [] decvals = [] for i in range(0, len(identities)): obsdict = sdb.get_observation(identities[i]) status = obsdict['status'] if status == 'DI_processed' or status == 'DI_Processed': fielddict = sdb.get_field(identities_fields[i]) ravals.append(fielddict['ra']) decvals.append(fielddict['decl']) progressdict[identities_fields[i]][2] = 'partly processed' sdb.close() ravals = np.array(ravals) decvals = np.array(decvals) RA = ravals Dec = decvals org = 180 x = np.remainder(RA + 360 - org, 360) # shift RA values ind = x > 180 x[ind] -= 360 # scale conversion to [-180, 180] x = -x # reverse the scale: East to the left