npars = data.size // infodict['nwave']
data_flat = data.reshape((npars,infodict['nwave']))
# This next bit converts to flambda in vacuum, via the flattened copy:
for i in xrange(npars):
data_flat[i] *= (hires_dwave_air / hires_dwave)
# What is the resolution that we want to add in order
# to make the SDSS pixel width?
sdss_dloglam = 0.0001
sdss_dwave = sdss_dloglam * hires_wave * n.log(10.)
# This constructs the blurring matrix to SDSS resolution.
# We use hires_dwave_air to avoid the 2000Ang airtovac discontinuity
# without being significantly incorrect about wavelength.
sdss_blur = pxs.gauss_blur_matrix(hires_wavebound, n.sqrt(sdss_dwave**2 - hires_dwave_air**2))
# Wavelength range for rebinned SDSS version to be bounded by
# the following, which at least covers ugriz:
wave_sdss_lo = 2900.
wave_sdss_hi = 12000.
coeff1 = sdss_dloglam
coeff0 = coeff1 * n.floor(n.log10(wave_sdss_lo) / coeff1)
naxis1 = int(n.ceil(1. + (n.log10(wave_sdss_hi) - coeff0) / coeff1))
loglam_sdss = coeff0 + coeff1 * n.arange(naxis1)
logbound_sdss = pxs.cen2bound(loglam_sdss)
wavebound_sdss = 10.**logbound_sdss
# Initialize array for rebinned blurred stars:
cap_sdssbin = n.zeros((npars, naxis1), dtype=float)
# This will work: #ssp_dwave = 10.**(ssp_loglam + 0.5 * dloglam) - \ # 10.**(ssp_loglam - 0.5 * dloglam) #ssp_dwave = ssp_wave * (10**(dloglam/2.) - 10.**(-dloglam/2.)) # THIS is the best way to do it!! ssp_dwave = dloglam * ssp_wave * n.log(10.) # What is the resolution that we want to add in order # to make the SDSS pixel width? sdss_dloglam = 0.0001 sdss_dwave = sdss_dloglam * ssp_wave * n.log(10.) # This constructs the blurring matrix to SDSS resolution: sdss_blur = pxs.gauss_blur_matrix(ssp_wavebound, n.sqrt(sdss_dwave**2 - ssp_dwave**2)) # The baseline for log vdisp in km/s: log_vmin = 2.0 log_vstep = 0.2 log_vnum = 4 log_vbase = log_vmin + log_vstep * n.arange(log_vnum) # Compute the velocity-broadening matrices: c_kms = 2.99792458e5 sigma_v_in_ang = ssp_wave.reshape((1,-1)) * (10.**log_vbase).reshape((-1,1)) / c_kms vmatrix_list = [pxs.gauss_blur_matrix(ssp_wavebound, sigma_v_in_ang[i]) for i in xrange(log_vnum)] # Initialize an array to hold the blurred SSPs before downsampling: ssp_vblur = n.zeros((nsub_age, log_vnum, n_pix), dtype=float)
# This will work:
#ssp_dwave = 10.**(ssp_loglam + 0.5 * dloglam) - \
# 10.**(ssp_loglam - 0.5 * dloglam)
#ssp_dwave = ssp_wave * (10**(dloglam/2.) - 10.**(-dloglam/2.))
# THIS is the best way to do it!!
ssp_dwave = dloglam * ssp_wave * n.log(10.)
# What is the resolution that we want to add in order
# to make the SDSS pixel width?
sdss_dloglam = 0.0001
sdss_dwave = sdss_dloglam * ssp_wave * n.log(10.)
# This constructs the blurring matrix to SDSS resolution:
sdss_blur = pxs.gauss_blur_matrix(ssp_wavebound,
n.sqrt(sdss_dwave**2 - ssp_dwave**2))
# The baseline for log vdisp in km/s:
log_vmin = 2.0
log_vstep = 0.2
log_vnum = 4
log_vbase = log_vmin + log_vstep * n.arange(log_vnum)
# Compute the velocity-broadening matrices:
c_kms = 2.99792458e5
sigma_v_in_ang = ssp_wave.reshape((1, -1)) * (10.**log_vbase).reshape(
(-1, 1)) / c_kms
vmatrix_list = [
pxs.gauss_blur_matrix(ssp_wavebound, sigma_v_in_ang[i])
for i in xrange(log_vnum)
]
# This will work:
#ssp_dwave = 10.**(ssp_loglam + 0.5 * dloglam) - \
# 10.**(ssp_loglam - 0.5 * dloglam)
#ssp_dwave = ssp_wave * (10**(dloglam/2.) - 10.**(-dloglam/2.))
# THIS is the best way to do it!!
ssp_dwave = dloglam * ssp_wave * n.log(10.)
# What is the resolution that we want to add in order
# to make the SDSS pixel width?
rebin_dloglam = 0.000025
rebin_dwave = rebin_dloglam * ssp_wave * n.log(10.)
# This constructs the blurring matrix to output resolution:
rebin_blur = pxs.gauss_blur_matrix(ssp_wavebound,
n.sqrt(rebin_dwave**2 - ssp_dwave**2))
# wavelength range for rebinned version to be bounded by:
wave_rebin_lo = 1525.
wave_rebin_hi = 10850.
coeff1 = rebin_dloglam
coeff0 = coeff1 * n.floor(n.log10(wave_rebin_lo) / coeff1)
naxis1 = int(n.ceil(1. + (n.log10(wave_rebin_hi) - coeff0) / coeff1))
loglam_rebin = coeff0 + coeff1 * n.arange(naxis1)
logbound_rebin = pxs.cen2bound(loglam_rebin)
wavebound_rebin = 10.**logbound_rebin
# Initialize array for rebinned blurred SSPs:
ssp_rebin = n.zeros((nsub_age, naxis1), dtype=float)
npars = data.size // infodict['nwave']
data_flat = data.reshape((npars, infodict['nwave']))
# This next bit converts to flambda in vacuum, via the flattened copy:
for i in xrange(npars):
data_flat[i] *= (hires_dwave_air / hires_dwave)
# What is the resolution that we want to add in order
# to make the SDSS pixel width?
sdss_dloglam = 0.0001
sdss_dwave = sdss_dloglam * hires_wave * n.log(10.)
# This constructs the blurring matrix to SDSS resolution.
# We use hires_dwave_air to avoid the 2000Ang airtovac discontinuity
# without being significantly incorrect about wavelength.
sdss_blur = pxs.gauss_blur_matrix(hires_wavebound,
n.sqrt(sdss_dwave**2 - hires_dwave_air**2))
# Wavelength range for rebinned SDSS version to be bounded by
# the following, which at least covers ugriz:
wave_sdss_lo = 2900.
wave_sdss_hi = 12000.
coeff1 = sdss_dloglam
coeff0 = coeff1 * n.floor(n.log10(wave_sdss_lo) / coeff1)
naxis1 = int(n.ceil(1. + (n.log10(wave_sdss_hi) - coeff0) / coeff1))
loglam_sdss = coeff0 + coeff1 * n.arange(naxis1)
logbound_sdss = pxs.cen2bound(loglam_sdss)
wavebound_sdss = 10.**logbound_sdss
# Initialize array for rebinned blurred stars:
cap_sdssbin = n.zeros((npars, naxis1), dtype=float)
# This will work: #ssp_dwave = 10.**(ssp_loglam + 0.5 * dloglam) - \ # 10.**(ssp_loglam - 0.5 * dloglam) #ssp_dwave = ssp_wave * (10**(dloglam/2.) - 10.**(-dloglam/2.)) # THIS is the best way to do it!! ssp_dwave = dloglam * ssp_wave * n.log(10.) # What is the resolution that we want to add in order # to make the SDSS pixel width? rebin_dloglam = 0.000025 rebin_dwave = rebin_dloglam * ssp_wave * n.log(10.) # This constructs the blurring matrix to output resolution: rebin_blur = pxs.gauss_blur_matrix(ssp_wavebound, n.sqrt(rebin_dwave**2 - ssp_dwave**2)) # wavelength range for rebinned version to be bounded by: wave_rebin_lo = 1525. wave_rebin_hi = 10850. coeff1 = rebin_dloglam coeff0 = coeff1 * n.floor(n.log10(wave_rebin_lo) / coeff1) naxis1 = int(n.ceil(1. + (n.log10(wave_rebin_hi) - coeff0) / coeff1)) loglam_rebin = coeff0 + coeff1 * n.arange(naxis1) logbound_rebin = pxs.cen2bound(loglam_rebin) wavebound_rebin = 10.**logbound_rebin # Initialize array for rebinned blurred SSPs: ssp_rebin = n.zeros((nsub_age, naxis1), dtype=float)
