print "Instrumental magnitudes include both grey-scale and color-dependent variations as bandpasses and SEDs change."
print "Calibrated natural magnitudes remove the grey-scale variation, and only show color-dependent/wavelength-dependent"
print " variations in measured magnitudes as the shape of the bandpass or the shape of the SED change. "
print "If the blue stars are used as calibration stars for the instrumental magnitudes (i.e. the zeropoint variation is"
print " removed with the blue stars, so the grey-scale variation is removed), the changes in instrumental magnitudes then"
print " show only the color-dependent changes in reported magnitudes. (this can be done here using matchBlue=True in calcDeltaMags)."
print "The reason that the natural magnitudes show a small change in magnitude even for blue objects is that these are being"
print " referenced against a flat Fnu spectrum, instead of the blue star spectrum. If matchBlue is turned on for changes in magnitudes"
print " calculated using natural magnitudes (calcNatMags), the results are identical to the results for changes in instrumental"
print " magnitudes calculated using matchBlue."
filterlist = ('u', 'g', 'r', 'i', 'z', 'y')
# Read the SED files.
seds, sedlists = pT.readPhotSeds(sedDir='../')
# And redshift the galaxies, quasar, and SN.
# These are just sample redshifts, not supposed to be 'typical'.
redshifts = {}
redshifts['galaxies'] = numpy.array([0.5, 1.0], 'float')
redshifts['quasar'] = numpy.array([1.0, 1.5, 2.5], 'float')
redshifts['sn'] = numpy.array([0.3, 0.8, 1.2, 1.5], 'float')
redshifts['photoZ_outliers'] = numpy.array([0, 0.2, 2.0], 'float')
seds, sedlists = pT.makeRedshiftedSeds(seds, sedlists, redshifts)
# Okay, now let's look at two different bandpass comparisons.
# We will compare the 'normal' base throughputs to a set of throughputs where the bandpasses are shifted by 1%.
# First read the basic components, except for the filters.
componentList_common = ['atmos.dat', 'detector.dat', 'lens1.dat', 'lens2.dat', 'lens3.dat',
'm1_ProtAl_Aged.dat', 'm2_ProtAl_Aged.dat', 'm3_ProtAl_Aged.dat']
# Plot the information from this SED.
if sedname != None:
pylab.plot(sed.wavelen, sed.fnu, label='%s' %(str(sedname)))
else:
pylab.plot(sed.wavelen, sed.fnu)
pylab.xlim(300, 1150)
pylab.xlabel('Wavelength (nm)')
pylab.ylabel(r'F$_\nu$')
if sedname != None:
pylab.title('%s' %(str(sedname)))
if savefig:
if sedname != None:
pylab.savefig('%s.%s' %(str(sedname), figformat), format=figformat)
else:
pylab.savefig('fnu.%s' %(figformat), format=figformat)
return
def plot_all_seds(sedDict):
"""Plot all seds in the sedDict."""
for s in sedDict.keys():
plot_sed(sedDict[s], sedname=s)
return
if __name__ == "__main__":
sedDict, sedlists = pT.readPhotSeds()
plot_all_seds(sedDict)
