def makeRadiusBins(galaxy, basemap, outDir, beam=15.0):
'''
Create bins for the data
basemap: map used to create bins (SpectralCube Projection)
outDir: directory to write output bin image
Date Programmer Description of Changes
----------------------------------------------------------------------
10/29/2020 Yiqing Song Original Code
12/3/2020 A.A. Kepley Added more comments plus moved GCR map
calculate up to other code.
4/15/2021 A.A. Kepley Changes bins to be beam width apart in radius.
'''
minrad = 0.0 + beam / 2.0
maxrad = np.max(
basemap).value + beam # want to add one bin beyond to capture max.
binedge = np.arange(minrad, maxrad, beam)
binedge = np.insert(binedge, 0, 0)
binedge = binedge * basemap.unit
bins = np.digitize(basemap.value, binedge.value)
binlabels = ['{0:1.2f}'.format(i) + ' arcsec' for i in binedge]
# make bins map
binmap = Projection(bins, wcs=basemap.wcs, header=basemap.header)
binmap.write(os.path.join(outDir,
galaxy['NAME'].upper() + '_binsbyradius.fits'),
overwrite=True)
return binmap, binedge, binlabels
def makeBins(galaxy, basemap, bintype, outDir):
'''
Create bins for the data
basemap: map used to create bins (SpectralCube Projection)
bintype: type of bins ('intensity','stellarmass', 'radius')
outDir: directory to write output bin image
Date Programmer Description of Changes
----------------------------------------------------------------------
10/29/2020 Yiqing Song Original Code
12/3/2020 A.A. Kepley Added more comments plus moved GCR map
calculate up to other code.
'''
if bintype == 'intensity' or bintype == 'stellarmass':
#Bin the basemap by brightness
binnum = int(
np.log(np.nanmax(basemap.value) / np.nanmin(basemap.value))) + 1
binedge = np.nanmin(basemap.value) * np.logspace(
0, binnum, num=binnum + 1,
base=np.e) #create bins based on dynamic range of mom0
bins = np.digitize(
basemap.value, binedge
) #this will automatically add an extra bin in the end for nan values
binlabels = [""] + [
'{0:1.2f}'.format(i) + basemap.unit.to_string() for i in binedge
] #need to add units to stellarmass map!!
elif bintype == 'radius':
binnum = 5
binedge = np.zeros(binnum + 1)
binedge[1:] = np.logspace(-1, np.log10(0.5), num=binnum,
base=10) #create bins based on r25
bins = np.digitize(
basemap, binedge
) #this will automatically add an extra bin in the end for nan values
binlabels = [""] + ['{0:1.2f}'.format(i) + 'R25' for i in binedge]
else:
raise Exception(
"bintype should either be 'radius' or 'intensity' or 'stellarmass' "
)
# Blank NaN values
bins[bins == len(binedge)] = 0
# make bins map
binmap = Projection(bins, wcs=basemap.wcs, header=basemap.header)
binmap.write(os.path.join(
outDir, galaxy['NAME'].upper() + '_binsby' + bintype + '.fits'),
overwrite=True)
return binmap, binedge, binlabels
def makeBins(galaxy, basemap, bintype):
if bintype=='intensity' or bintype=='stellarmass':
#Bin the basemap by brightness
binnum=int(np.log(np.nanmax(basemap.value)/np.nanmin(basemap.value)))+1
binedge = np.nanmin(basemap.value)*np.logspace(0, binnum, num=binnum+1, base=np.e) #create bins based on dynamic range of mom0
bins = np.digitize(basemap.value, binedge) #this will automatically add an extra bin in the end for nan values
binlabels=[""]+['{0:1.2f}'.format(i)+basemap.unit.to_string() for i in binedge] #need to add units to stellarmass map!!
elif bintype=='radius':
R_arcmin, R_kpc, R_r25=mapGCR(galaxy,basemap) #can choose from 3 different Rmaps
binnum=5
binedge = np.zeros(binnum+1)
binedge[1:]=np.logspace(-1, np.log10(0.5), num=binnum,base=10)#create bins based on r25
bins = np.digitize(R_r25, binedge) #this will automatically add an extra bin in the end for nan values
binlabels=[""]+['{0:1.2f}'.format(i)+'R25' for i in binedge]
else:
raise Exception ("bintype should either be 'radius' or 'intensity' or 'stellarmass' ")
# Blank NaN values
bins[bins==len(binedge)] = 0
# make bins map
binmap=Projection(bins,wcs=basemap.wcs,header=basemap.header)
binmap.write(datadir+galaxy.upper()+'_binsby'+bintype+'.fits', overwrite=True)
return binmap, binedge, binlabels
def makeMap(cubeFile, outDir, baseName=None,maskFile='',maptype='peakIntensity',order=0 ):
""" Create peak intensity map from a cube
Parameters
cubeFile: str
FITS filename of the cube
outDir: str
Directory in which to place the output FITS file
maskFile: str
FITS filename of the mask. Should have same geometry as
cube. If not use routines in analysis_setup.py to regrid.
maptype: str
type of map to make. Options are peakIntensity, peakVelocity, linewidth,
moment, and mask2D.
order: int
order for moment map
"""
if not baseName:
baseName=os.path.basename(cubeFile).replace('.fits','')
cube = SpectralCube.read(cubeFile).with_spectral_unit(u.km/u.s, velocity_convention='radio')
if maskFile:
maskCube = SpectralCube.read(maskFile).with_spectral_unit(u.km/u.s, velocity_convention='radio')
mask = (maskCube.unitless_filled_data[:,:,:] > 0.5)
maskedCube = cube.with_mask(mask)
else:
maskedCube = cube
if maptype is 'peakIntensity':
mymap = maskedCube.max(axis=0)
outname = baseName+'_peakInt.fits'
elif maptype is 'mask2D':
mymap = maskedCube.max(axis=0)
outname = baseName+'_mask2D.fits'
elif maptype is 'linewidth':
mymap = maskedCube.linewidth_fwhm()
outname = baseName+'_linewidth.fits'
elif maptype is 'moment':
mymap = maskedCube.moment(order=order)
outname = baseName+'_mom'+str(order)+'.fits'
elif maptype is 'peakVelocity':
velocity = maskedCube.spectral_axis
mask = np.sum(maskedCube.get_mask_array(),axis=0) > 1.0
newwcs = maskedCube.wcs.dropaxis(2)
peakind = maskedCube.argmax(axis=0)
peakvel = velocity[peakind]
peakvel[peakvel==velocity[0]] = np.nan
mymap = Projection(peakvel, wcs=newwcs, mask=mask)
outname = baseName + '_peakVelocity.fits'
else:
print('Map type unknown. Options are peakIntensity, linewidth, moment')
return
mymap.meta['MASK'] = maskFile
mymap.write(os.path.join(outDir,outname),overwrite=True)
