def get_SDSS_simple(ra, dec, rad=1/60., dir='./', name='', silent=False):
'''
>> data = get_SDSS_simple(ra, dec, rad=1, dir='./' name='mydata')
call the DR12 skyserver with single [ra, dec] and download cvs file
input:
ra, dec (deg)
optional input:
radius=1/60. (deg).
dir='./' directory for fits file
name name for file, if not give we use IAU name of input coords
silent=False shut it.
note, make 1e5 lines are returned, only basic imaging data (magnitudes)
'''
url = SDSSurl_radec.replace('__RA__',str(float(ra))).replace('__DEC__', str(float(dec))).replace('__RAD__',str(rad*60))
#cas = SDSS_cas..replace('__RA__',str(ra)).replace('__DEC__', str(dec)).replace('__RAD__',str(rad))
if not(name):
name = 'SDSS-'+iau_name(ra, dec)+'.csv'
com = '''curl '''+url+''' > ''' +dir+name
if not silent: print com
os.system(com)
# the (stupid?) format with two tables
f = open(dir+name,'r')
lines = ''
for l in f.readlines():
#print l
if l.count('#Table2')==1:
break
lines+=l
lines= lines.split('\n')
print lines[1]
print lines[2:]
data = readascii(lines=lines[2:], delimiter=',', names=lines[1].split(','))
return data
def get_NED_name(name=None,ra=None, dec=None, rad=.1/60., NEDdir=NEDdir, redo=False):
'''
download or read NED page, return NED name of the galaxy
>> get_NED_name(name, NEDdir=NEDdir)
>> get_NED_name(ra=130,dec=-12, rad=0.1/60, NEDdir=NEDdir)
'''
if name is not None:
local_name = name.strip().replace(' ', '_')
else:
local_name = iau_name(ra, dec)
fname = NEDdir+local_name+'.html'
if not(os.path.isfile(fname)):
print fname
print 'not on disk, sendig query to NED'
if not(os.path.isfile(fname)) or redo:
download_NED(name=name, ra=ra,dec=dec, rad=rad, local_name=local_name, NEDdir=NEDdir)
time.sleep(0.5)
return read_NED_mainpage(local_name)
def cutout(filename='', hdu=None, center=[None, None],im_size=0.1,pix=False,
writepdf=False, writefits=False, silent=False):
'''
>> sub_hdu = cutout(filename='file.fits', center=[12,-1.], im_size=0.1,
writepdf=False, writefits=False)
>> sub_hdu = cutout(hdu=hdu, center=[12,-1.], im_size=0.1,
writepdf=False, writefits=False
returns:
pyfits.core.PrimaryHDU
input:
- hdu (pyfits.core.HDUList or pyfits.core.PrimaryHDU ) or filename of fits image
- center=[ra,dec] (deg)
- im_size=0.1 (deg)
optional input:
- pix input center and im_size are in pixel units
- writepdf='name.pdf' or True (write filename_sub.pdf)
- writefits='name.fits' or True (fileanme+sub.fits
the creation of new WCS header doesnt seem to work for all cases...
'''
if (filename=='') and not(hdu):
print 'please give filename= or hdu='
return
if not(hdu) and not(os.path.isfile(filename)):
print 'file :'+ filename+ '\n not found'
return
if not np.isscalar(center[0]):
print 'please give center=[ra, dec]'
return
center = np.array(center)
# read or index to PrimaryHDU
if not(hdu):
hdu = pyfits.open(filename)[0]
elif type(hdu) == pyfits.core.HDUList:
hdu = hdu[0]
elif type(hdu) != pyfits.core.PrimaryHDU:
print 'type(hdu:)', type(hdu)
print 'ERROR: type(hdu) needs to be <pyfits.core.HDUList> or pyfits.core.PrimaryHDU'
return
# get image
im = hdu.data
# get WCS,
if not(pix):
wcs = pywcs.WCS(header=hdu.header, naxis=2) #fobj=hdulist,
if not silent: print 'image shape', im.shape
if (len(im.shape) == 3):
if not silent: print 'using first layer of image'
im = im[0,:,:]
print 'new image shape', im.shape
if (len(im.shape) == 4):
if not silent: print 'using first layer of image'
im = im[0,0,:,:]
if not silent: print 'new image shape', im.shape
# conver center en overplot coordinates
#pcenter = (wcs.wcs_sky2pix([center], 1))[0] # if pywcs
pcenter = (wcs.wcs_world2pix([center],0))[0] # if astropy.wcs
else:
pcenter = center
# slice the image
if not silent: print 'center in pixel coordinates', pcenter
# use true sky location (creates non-square images)
#delta_ax1 = (np.abs(wcs.wcs_sky2pix([ [center[0]-im_size, center[1]] ], 1) - pcenter)/2.)[0][0]
#delta_ax2 = (np.abs(wcs.wcs_sky2pix([ [center[0], center[1]-im_size] ], 1) - pcenter)/2.)[0][1]
#delta = [delta_ax1, delta_ax2]
#delta= np.abs(wcs.wcs_sky2pix( [center-im_size], 1)[0] - pcenter)/2.
# use pixel scale to define boundaries
if not(pix):
delta = np.abs(0.5*im_size / np.array([hdu.header['CDELT1'], hdu.header['CDELT2']]))
else:
delta = (im_size/2., im_size/2.)
ax1l = pcenter[0]-delta[0]
ax1u=pcenter[0]+delta[0]
ax2l = pcenter[1]-delta[1]
ax2u=pcenter[1]+delta[1]
# check limits
if (ax1l < 0): ax1l = 0
if (ax1u > im.shape[1]): ax1u = im.shape[1]
if (ax2l < 0): ax2l = 0
if (ax2u > im.shape[0]): ax2u = im.shape[0]
if not silent: print 'ax2l,ax2u, ax1l,ax1u', ax2l,ax2u,ax1l,ax1u
subim = im[ax2l:ax2u,ax1l:ax1u ]
if not silent: print 'subim shape:',subim.shape
if min(subim.shape) == 0:
print 'ERROR. something is wrong with the cutout (center+/-im_size out of bounds?) '
return None
# set the base of the output file
if (writepdf==True) or (writefits==True):
srem = ['.FITS', '.FIT', '.fit', '.fits']
outname = filename
for srm in srem: outname=outname.split(srm)[0]
if filename =='':
print 'warning, not filename given pdf or fits file, using IAU name'
outname = iau_name(center[0], center[1])
if not silent: print 'base for output file:', outname
if writepdf:
# determine color range, we use arcsinh scaling
scaled_subim = np.arcsinh(subim)
vals = scaled_subim.reshape(subim.shape[0]*subim.shape[1])
#nbins=50
#h_vals = np.histogram(np.log10(vals), new=False, bins=nbins)
svals = np.sort(vals)
slen = len(svals)
vmin = svals[0.01*slen]
vmax = svals[0.99*slen] #np.power(10, h_vals[1][nbins-10])
plt.imshow(scaled_subim, vmin=vmin, vmax=vmax,
cmap='hot', interpolation='bilinear')
# set filename (if not given)
if not(type(writepdf) is str):
outfile = outname+'_sub.pdf'
else: outfile = writepdf
if not silent: print 'writing', outfile
plt.savefig(outfile, format='pdf')
#make new WCS and save fits
sub_hdr = hdu.header.copy() #sub_hdu.header
## this wrong: slightly rotates the image
#sub_hdr['CRVAL1'] = center[0]
#sub_hdr['CRVAL2'] = center[1]
#sub_hdr['CRPIX1'] = pcenter[0]-ax1l
#sub_hdr['CRPIX2'] = pcenter[1]-ax2l
## keep CRVAL1 the same, but swift its pixel coodindates
sub_hdr['CRPIX1'] = np.floor(hdu.header['CRPIX1'] - ax1l ) +1
sub_hdr['CRPIX2'] = np.floor(hdu.header['CRPIX2'] - ax2l ) +1
if not silent: print 'orgininal CRVAL (', hdu.header['CRVAL1'], hdu.header['CRVAL2'],\
') in sub image pixel coordindates:', sub_hdr['CRPIX1'] , sub_hdr['CRPIX2']
# note, after this call sub_hdu.header is differnt the input than sub_hdr
# (eg, NAXIS, NAXIS1, are updated)
sub_hdu = pyfits.PrimaryHDU(data=subim, header=sub_hdr)
# write files
if writefits:
if not(type(writefits) is str):
outfile = outname+'_sub.fits'
else: outfile = writefits
if not silent: print 'writing:', outfile
sub_hdu.writeto(outfile,clobber=True)
return sub_hdu