def cross_match(self,
inCatalogFileName,
outCatalogFileName,
radiusArcmin=1.0):
"""Cross matches input and output source catalogs.
"""
inTab = atpy.Table().read(inCatalogFileName)
outTab = atpy.Table().read(outCatalogFileName)
self.inTab, self.outTab, self.rDeg = catalogs.crossMatch(
inTab, outTab, radiusArcmin=radiusArcmin)
'Mpivot': 3.0e+14,
'sigma_int': 0.0
}
tckQFitDict = signals.loadQ("../MFMF_SOSim_3freq_tiles/selFn/QFit.fits")
fRelWeightsDict = signals.loadFRelWeights(
"../MFMF_SOSim_3freq_tiles/selFn/fRelWeights.fits")
# Make combined table
mergedTabFileName = "trueMasses_MFMF_SOSim_3freq_tiles_M500.fits"
if os.path.exists(mergedTabFileName) == False:
halos = atpy.Table().read("../halos.fits")
tab = atpy.Table().read(
"../MFMF_SOSim_3freq_tiles/MFMF_SOSim_3freq_tiles_M500.fits")
tab = tab[tab['fixed_SNR'] > 6]
tab, halos, rDeg = catalogs.crossMatch(tab, halos, radiusArcmin=1.0)
zs = halos['z']
yc = tab['fixed_y_c']
M200m = halos['M200m']
M500c = []
count = 0
for m, z in zip(M200m, zs):
count = count + 1
print(count, len(M200m))
M500c.append(signals.convertM200mToM500c(m, z))
M500c = np.array(M500c)
M500c = M500c[:, 0]
tab['true_M500'] = M500c / 1e14
tab['true_M200'] = M200m / 1e14
tab['redshift'] = zs
yc = {}
ycErr = {}
labels = {}
# Cross match against nemo output
print("Collecting fixed_y_c measurements for each cluster across all maps")
xMatchFiles = glob.glob("outputCatalogs/*.fits")
xMatchFiles.sort()
for f in xMatchFiles:
label = os.path.split(f)[-1].split("_optimal")[0]
print(" %s" % (label))
tab = atpy.Table().read(f)
#tab=tab[tab['fixed_SNR'] > SNRCut]
try:
refMatched, tabMatched, sep = catalogs.crossMatch(refTab,
tab,
radiusArcmin=1.4)
except:
raise Exception(
"Matching probably failed because SNRCut is too low so there were no matches"
)
for ref, match in zip(refMatched, tabMatched):
name = ref['name']
if name not in yc.keys():
yc[name] = []
ycErr[name] = []
labels[name] = []
ycRef[name] = ref['fixed_y_c'] * calFactor
ycErrRef[name] = ref['fixed_err_y_c']
yc[name].append(match['fixed_y_c'])