def sky_transmission_curve(wavels, delta_lambda, zenith_ang):
'''Function that generates a full throughput curve combining
sky transmission & sky extinction.
Inputs:
wavels: array of wavelengths for datacube
delta_lambda: Resolution element [um]
zenith_ang: zenith angle of observation [degrees]
Outputs:
cube_total_sky_trans: array of total throughput
for each wavelength value in wavels
'''
#convert from zenith angle to airmass
X = 1. / n.cos(n.radians(zenith_ang))
inbuilt_airmasses = [1., 1.15, 1.41, 2.]
#determine the closest data to the airmass value given and find it's location in the data file
closest_X = min(inbuilt_airmasses, key=lambda x: abs(x - X))
data_index = inbuilt_airmasses.index(closest_X) + 1
#load sky transmission & extinction files, then reduce to the columns required
sky_trans_all_X = n.genfromtxt(
os.path.join(
tppath,
'ASM_throughput/transmission_0.15_angstroms_resolution.txt'))
sky_trans = n.column_stack(
(sky_trans_all_X[:, 0], sky_trans_all_X[:, data_index]))
print len(sky_trans)
sky_trans_all_X = [] #clean up unused data for sake of memory
#Find start and end wavelength values of curves
st_start_arg = n.where(sky_trans[:, 0] < wavels[0])[0][-1]
st_end_arg = n.where(sky_trans[:, 0] > wavels[-1])[0][0]
sky_trans_slice = sky_trans[st_start_arg:st_end_arg + 1, :]
if type(delta_lambda) == n.ndarray:
#Low resolution mode. Use low_res_mode function to generate sky transmission spectrum
sky_trans_spec = low_res_spec(sky_trans, delta_lambda, True)
sky_total_trans = sky_trans_spec[:, 1].copy()
else:
#Convolve sky transmission array with Gaussian LSF of
#FWHM = sqrt(new_resolution**2-old_resolution**2)
#to fold in spectrum for each spectral pixel.
sigma = n.sqrt(delta_lambda**2 - 0.15E-4**2) / (2. *
n.sqrt(2. * n.log(2.)))
conv_sky_trans = gauss_convolve(sky_trans_slice,
sigma,
lambda_space='Linear')
interp_trans = s.interpolate.interp1d(conv_sky_trans[:, 0],
conv_sky_trans[:, 1],
kind='linear',
bounds_error=False,
fill_value=0)
sky_total_trans = interp_trans(wavels)
sky_total_trans.shape = (len(wavels), 1, 1)
return sky_total_trans, wavels
def sky_background(wavels, delta_lambda, dit):
'''Function that generates a sky background curve combining
sky continuum, sky thermal emission and sky emission lines.
Inputs:
wavels: array of wavelengths for datacube
delta_lambda: resolution element [um]
dit: exposure time [s]. This determins how the sky emission
line amplitudes vary through the exposure.
Outputs:
sky_bg_curve: array of total sky background
[units of photons/s/m^2/um/arcsec^2]
for each wavelength value in wavels
'''
#Load up all datafile using n.genfromtxt(...)
#sky_em = n.genfromtxt(bgpath+'ASM_background/radiance_resolution_0.15_angstroms_MICRONS.txt')
sky_em = n.genfromtxt(
os.path.join(
bgpath,
'ASM_background/radiance_resolution_0.15_angstroms_MICRONS.txt'))
#Cut down data to relevent region.
se_start_arg = n.where(sky_em[:, 0] < wavels[0])[0][-1]
se_end_arg = n.where(sky_em[:, 0] > wavels[-1])[0][0]
sky_em_slice = sky_em[se_start_arg:se_end_arg + 1, :]
if type(delta_lambda) == n.ndarray:
#Low resolution mode. Use low_res_mode function to generate sky emission spectrum
sky_em_spec = low_res_spec(sky_em, delta_lambda, False)
binned_sky_em = sky_em_spec[:, 1].copy()
else:
#Convolve sky transmission array with Gaussian LSF of
#FWHM = sqrt(new_resolution**2-old_resolution**2)
#to fold in spectrum for each spectral pixel.
input_disp = sky_em[1, 0] - sky_em[0, 0]
sigma = n.sqrt(delta_lambda**2 -
input_disp**2) / (2. * n.sqrt(2. * n.log(2.)))
conv_sky_em = gauss_convolve(sky_em_slice,
sigma,
lambda_space='Linear')
###new 30-05-14
conv_sky_em_ph = conv_sky_em[:,
1] * input_disp #convert to units of photons/s/m^2/arcsec^2
binned_sky_em_ph = frebin(
conv_sky_em_ph.reshape(len(conv_sky_em_ph), 1), (1, len(wavels)),
True) #Total photons conserved
binned_sky_em = binned_sky_em_ph / float(
wavels[1] -
wavels[0]) #reconvert back to photons/s/m^2/um/arcsec^2
binned_sky_em.shape = (len(wavels), 1, 1)
return binned_sky_em
def sky_background(wavels, delta_lambda, dit):
'''Function that generates a sky background curve combining
sky continuum, sky thermal emission and sky emission lines.
Inputs:
wavels: array of wavelengths for datacube
delta_lambda: resolution element [um]
dit: exposure time [s]. This determins how the sky emission
line amplitudes vary through the exposure.
Outputs:
sky_bg_curve: array of total sky background
[units of photons/s/m^2/um/arcsec^2]
for each wavelength value in wavels
'''
#Load up all datafile using n.genfromtxt(...)
#sky_em = n.genfromtxt(bgpath+'ASM_background/radiance_resolution_0.15_angstroms_MICRONS.txt')
sky_em = n.genfromtxt(os.path.join(bgpath,'ASM_background/radiance_resolution_0.15_angstroms_MICRONS.txt'))
#Cut down data to relevent region.
se_start_arg = n.where(sky_em[:,0] < wavels[0])[0][-1]
se_end_arg = n.where(sky_em[:,0] > wavels[-1])[0][0]
sky_em_slice = sky_em[se_start_arg:se_end_arg+1,:]
if type(delta_lambda) == n.ndarray:
#Low resolution mode. Use low_res_mode function to generate sky emission spectrum
sky_em_spec = low_res_spec(sky_em, delta_lambda, False)
binned_sky_em = sky_em_spec[:,1].copy()
else:
#Convolve sky transmission array with Gaussian LSF of
#FWHM = sqrt(new_resolution**2-old_resolution**2)
#to fold in spectrum for each spectral pixel.
input_disp = sky_em[1,0] - sky_em[0,0]
sigma = n.sqrt(delta_lambda**2-input_disp**2)/(2.*n.sqrt(2.*n.log(2.)))
conv_sky_em = gauss_convolve(sky_em_slice, sigma, lambda_space='Linear')
###new 30-05-14
conv_sky_em_ph = conv_sky_em[:,1]*input_disp #convert to units of photons/s/m^2/arcsec^2
binned_sky_em_ph = frebin(conv_sky_em_ph.reshape(len(conv_sky_em_ph),1), (1,len(wavels)), True) #Total photons conserved
binned_sky_em = binned_sky_em_ph/float(wavels[1]-wavels[0]) #reconvert back to photons/s/m^2/um/arcsec^2
binned_sky_em.shape = (len(wavels),1,1)
return binned_sky_em
def sky_transmission_curve(wavels, delta_lambda):
'''Function that generates a full throughput curve combining
sky transmission & sky extinction.
Inputs:
wavels: array of wavelengths for datacube
delta_lambda: Resolution element [um]
Outputs:
cube_total_sky_trans: array of total throughput
for each wavelength value in wavels
'''
#NEED TO IMPLEMENT DIFFERENT AIRMASS VALUES AT SOME POINT
#Currently set at 1.15 to match PSFs - Zenith angle = 30deg
#load sky transmission & extinction files
sky_trans = n.genfromtxt(os.path.join(tppath,'ASM_throughput/transmission_resolution_0.15_angstroms_MICRONS.txt'))
#Find start and end wavelength values of curves
st_start_arg = n.where(sky_trans[:,0] < wavels[0])[0][-1]
st_end_arg = n.where(sky_trans[:,0] > wavels[-1])[0][0]
sky_trans_slice = sky_trans[st_start_arg:st_end_arg+1,:]
if type(delta_lambda) == n.ndarray:
#Low resolution mode. Use low_res_mode function to generate sky transmission spectrum
sky_trans_spec = low_res_spec(sky_trans, delta_lambda, True)
sky_total_trans = sky_trans_spec[:,1].copy()
else:
#Convolve sky transmission array with Gaussian LSF of
#FWHM = sqrt(new_resolution**2-old_resolution**2)
#to fold in spectrum for each spectral pixel.
sigma = n.sqrt(delta_lambda**2-0.15E-4**2)/(2.*n.sqrt(2.*n.log(2.)))
conv_sky_trans = gauss_convolve(sky_trans_slice, sigma, lambda_space='Linear')
interp_trans = s.interpolate.interp1d(conv_sky_trans[:,0], conv_sky_trans[:,1],
kind='linear', bounds_error=False, fill_value=0)
sky_total_trans = interp_trans(wavels)
sky_total_trans.shape = (len(wavels),1,1)
return sky_total_trans, wavels