def make_column_density(wavelength, files):
'''
This function uses wavelengths and images at those wavelengths to
generate column density and temperature after properly convolving
and regriding the images.
This uses following functions:
resconvolve and regrid from required_functions
make_maps and make_colour_map from colden_functions
Parameters
----------
wavelengths : 1-D array
array of all the wavelength in micron
file: 1-D array of srings
Path and name of all the required flux files
Returns
-------
Temperature : 2-D array
map of temerature in Kelvin
C_D : 2-D array
map of column density in cm^-2
MassCD : 2-D array
map of column density in M_sun/pc^2
fitheader : header
header needed for final images
'''
print
print "Total number of files:", len(files)
# store all the images in one list
im = []
# resolution for each wavelength
original_res = [beamsize['160'], beamsize['250'], beamsize['350'], beamsize['500']]
# get the template wavelength and file name
# template is the one that is not changed in the end
template_wavelength = wavelength[-1]
template_map_name = files[-1]
print "Template wavelength:", template_wavelength
print "Template image name:", template_map_name
# get the resolution of the template file
if template_wavelength == 160.:
required_res = original_res[0]
elif template_wavelength == 250.:
required_res = original_res[1]
elif template_wavelength == 350.:
required_res = original_res[2]
elif template_wavelength == 500.:
required_res = original_res[3]
print "Template resolution:", required_res
print
# this loops goes though each file
for i in range(len(files)):
print wavelength[i]
# if the file is not the template file then
# 1) it is convolved to the resolution of template map
# 2) it is regrid to the shape and size of template
# 3) saved into an array
if wavelength[i] != template_wavelength:
# file names used
conv_file = files[i][:-5]+'.conv.fits' # convolve file
resamp_file = conv_file[:-5]+'.resamp.fits' # resampled image
print conv_file
print resamp_file
# remove if these files are already there
os.system("rm {0}".format(conv_file))
os.system("rm {0}".format(resamp_file))
# convolve the image
rf.resconvolve(files[i],required_res,original_res[i], resultimage = conv_file)
# resample image
rf.regrid(conv_file, template_map_name, resultimage = resamp_file, header = None)
print
# 3) open the resample file and store the data into the bigger list (im)
image = fits.getdata(resamp_file)
im.append(image)
print "shape:", np.shape(image)
# else if, the file is the template file then
# saved into an array without alteration
elif wavelength[i] == template_wavelength:
image, fitheader= fits.getdata(files[i], header = True)
im.append(image)
print "shape:", np.shape(image)
print
# make wavelength 0 for column density and temp dont have wavelength
try:
fitheader.remove(keyword='WAVELNTH')
except:
print
fitheader['FREQ_0'] = (nu0/1e9, '[GHz] frequency at which the opacity power law is locked')
fitheader['KAPPA_0'] = (kappa0, '[cm^2/g] dust opacity at FREQ_0')
fitheader['BETA'] = (beta, 'Dust emissivity')
fitheader['GAS2DUST'] = (gastodust, 'gas to dus ratio')
#fitheader['AUTHOR'] = ('Ayushi Singh')
# run this function that will make column-density and temperature maps
# parameters are: wavelength [micron], im: all the images in an array [MJy/sr], pixelsize used to calculate radius
# Dataset: used for the title, plots: this is false unless want plot at every 1000 value
if len(files) > 2:
Temperature, C_D, MassCD = cf.make_SED_maps(wavelength, im)
elif len(files) ==2 :
Temperature, C_D, MassCD = cf.make_colour_map(wavelength, im)
return Temperature, C_D, MassCD, fitheader
fits.writeto(T_250,Temperature_250,fithead_250) fithead_250['BUNIT'] = 'cm^-2' fithead_250['HEADER'] = 'Column Density' fits.writeto(CD_250,C_D_250,fithead_250) fithead_250['BUNIT'] = 'Msun/pc^2' fithead_250['HEADER'] = 'Column Density' fits.writeto(CD_M_250,CD_Msun_250,fithead_250) ################################################################################################## # convolve the real file to a given resolution print "Final convolving started." rf.resconvolve(CD_350,beamsize['500'],beamsize['350'], resultimage = CD_350_conv) rf.resconvolve(CD_250,beamsize['350'],beamsize['250'], resultimage = CD_250_conv) rf.resconvolve(T_350,beamsize['500'],beamsize['350'], resultimage = T_350_conv) rf.resconvolve(T_250,beamsize['350'],beamsize['250'], resultimage = T_250_conv) print "Final convolving ended. \n" # resisze these image to the 3" template # using 160 as a guideline for the template image. guide, guideheader = fits.getdata(file160, header = True) high_res_template = np.zeros([np.shape(guide)[0],np.shape(guide)[1]]) #editing the template header try: quideheader.remove(keyword='WAVELNTH') quideheader.remove(keyword='OFFSET')