def map_pair_cal(uncal_maplist, uncal_weightlist, in_path, out_path,
convolve=False, factorizable_noise=True,
sub_weighted_mean=True):
# load maps into pairs
for mapname, noisename in zip(uncal_maplist, uncal_weightlist):
pair = map_pair.MapPair(map1, map2,
noise_inv1, noise_inv2,
self.freq_list)
pair.set_names(pdict['tag1'], pdict['tag2'])
pair.lags = self.lags
pair.params = self.params
self.pairs[pairitem] = pair
(corr, counts) = pair.correlate(pair.lags, speedup=True)
svd_info = ce.get_freq_svd_modes(corr, len(self.freq_list))
leftmode = svd_info[1][:0]
rightmode =svd_info[2][:0]
# write out the maps and noise
algebra.save(map1_file, pair.map1)
algebra.save(map2_file, pair.map2)
algebra.save(noise_inv1_file, pair.noise_inv1)
algebra.save(noise_inv2_file, pair.noise_inv2)
def map_pair_cal(uncal_maplist, uncal_weightlist, calfactor_outlist,
dirtymap_inlist, dirtymap_outlist,
convolve=True, factorizable_noise=False,
sub_weighted_mean=True, freq_list=range(256)):
map1file = reference_clean
weight1file = reference_weight
#map1file = uncal_maplist.pop(0)
#weight1file = uncal_weightlist.pop(0)
#calfactor_outlist.pop(0)
#dirtymap_out0 = dirtymap_outlist.pop(0)
#dirtymap_in0 = dirtymap_inlist.pop(0)
# do nothing to the reference map
#ref_dirtymap = algebra.make_vect(algebra.load(dirtymap_in0))
#algebra.save(dirtymap_out0, ref_dirtymap)
# load maps into pairs
svdout = shelve.open("correlation_pairs_v2.shelve")
for map2file, weight2file, calfactor_outfile, \
dirty_infile, dirty_outfile in zip(uncal_maplist, \
uncal_weightlist, calfactor_outlist,
dirtymap_inlist, dirtymap_outlist):
print map1file, weight1file, map2file, weight2file
pair = map_pair.MapPair(map1file, map2file,
weight1file, weight2file,
freq_list, avoid_db=True)
if factorizable_noise:
pair.make_noise_factorizable()
if sub_weighted_mean:
pair.subtract_weighted_mean()
if convolve:
pair.degrade_resolution()
(corr, counts) = pair.correlate()
svd_info = ce.get_freq_svd_modes(corr, len(freq_list))
svdout[map2file] = svd_info
# write out the left right and cal factors
leftmode = svd_info[1][0]
rightmode = svd_info[2][0]
calfactor = leftmode/rightmode
facout = open(calfactor_outfile, "w")
for outvals in zip(leftmode, rightmode, calfactor):
facout.write("%10.15g %10.15g %10.15g\n" % outvals)
facout.close()
newmap = algebra.make_vect(algebra.load(dirty_infile))
newmap[freq_list, :, :] *= calfactor[:,np.newaxis,np.newaxis]
algebra.save(dirty_outfile, newmap)
print dirty_outfile
svdout.close()
def calculate_svd(self):
r"""calculate the SVD of all pairs"""
for pairitem in self.pairlist:
filename = self.output_root
filename_corr = filename + "foreground_corr_pair_%s.pkl" % pairitem
filename_svd = filename + "SVD_pair_%s.pkl" % pairitem
print filename_corr
if os.access(filename_corr, os.F_OK):
print "SVD loading corr. functions: " + filename
(corr, counts) = ft.load_pickle(filename_corr)
# (vals, modes1, modes2)
svd_info = ce.get_freq_svd_modes(corr, len(self.freq_list))
ft.save_pickle(svd_info, filename_svd)
else:
print "ERROR: in SVD, correlation functions not loaded"
sys.exit()
def calculate_svd(self):
r"""calculate the SVD of all pairs"""
for pairitem in self.pairlist:
filename = self.output_root
filename_corr = filename + "foreground_corr_pair_%s.pkl" % pairitem
filename_svd = filename + "SVD_pair_%s.pkl" % pairitem
print filename_corr
if os.access(filename_corr, os.F_OK):
print "SVD loading corr. functions: " + filename
(corr, counts) = ft.load_pickle(filename_corr)
# (vals, modes1, modes2)
svd_info = ce.get_freq_svd_modes(corr, len(self.freq_list))
ft.save_pickle(svd_info, filename_svd)
else:
print "ERROR: in SVD, correlation functions not loaded"
sys.exit()
