def make_rgb_cube(files, output, north=False, system=None, equinox=None):
'''
Make an RGB data cube from a list of three FITS images.
This method can read in three FITS files with different
projections/sizes/resolutions and uses Montage to reproject
them all to the same projection.
Two files are produced by this function. The first is a three-dimensional
FITS cube with a filename give by `output`, where the third dimension
contains the different channels. The second is a two-dimensional FITS
image with a filename given by `output` with a `_2d` suffix. This file
contains the mean of the different channels, and is required as input to
FITSFigure if show_rgb is subsequently used to show a color image
generated from the FITS cube (to provide the correct WCS information to
FITSFigure).
Parameters
----------
files : tuple or list
A list of the filenames of three FITS filename to reproject.
The order is red, green, blue.
output : str
The filename of the output RGB FITS cube.
north : bool, optional
By default, the FITS header generated by Montage represents the
best fit to the images, often resulting in a slight rotation. If
you want north to be straight up in your final mosaic, you should
use this option.
system : str, optional
Specifies the system for the header (default is EQUJ).
Possible values are: EQUJ EQUB ECLJ ECLB GAL SGAL
equinox : str, optional
If a coordinate system is specified, the equinox can also be given
in the form YYYY. Default is J2000.
'''
# Check whether the Python montage module is installed. The Python module
# checks itself whether the Montage command-line tools are available, and
# if they are not then importing the Python module will fail.
try:
import montage_wrapper as montage
except ImportError:
raise Exception("Both the Montage command-line tools and the"
" montage-wrapper Python module are required"
" for this function")
# Check that input files exist
for f in files:
if not os.path.exists(f):
raise Exception("File does not exist : " + f)
# Create work directory
work_dir = tempfile.mkdtemp()
raw_dir = '%s/raw' % work_dir
final_dir = '%s/final' % work_dir
images_raw_tbl = '%s/images_raw.tbl' % work_dir
header_hdr = '%s/header.hdr' % work_dir
# Create raw and final directory in work directory
os.mkdir(raw_dir)
os.mkdir(final_dir)
# Create symbolic links to input files
for i, f in enumerate(files):
os.symlink(os.path.abspath(f), '%s/image_%i.fits' % (raw_dir, i))
# List files and create optimal header
montage.mImgtbl(raw_dir, images_raw_tbl, corners=True)
montage.mMakeHdr(images_raw_tbl, header_hdr, north_aligned=north, system=system, equinox=equinox)
# Read header in with astropy.io.fits
header = fits.Header.fromtextfile(header_hdr)
# Find image dimensions
nx = int(header['NAXIS1'])
ny = int(header['NAXIS2'])
# Generate emtpy datacube
image_cube = np.zeros((len(files), ny, nx), dtype=np.float32)
# Loop through files
for i in range(len(files)):
# Reproject channel to optimal header
montage.reproject('%s/image_%i.fits' % (raw_dir, i),
'%s/image_%i.fits' % (final_dir, i),
header=header_hdr, exact_size=True, bitpix=-32)
# Read in and add to datacube
image_cube[i, :, :] = fits.getdata('%s/image_%i.fits' % (final_dir, i))
# Write out final cube
fits.writeto(output, image_cube, header, clobber=True)
# Write out collapsed version of cube
fits.writeto(output.replace('.fits', '_2d.fits'), \
np.mean(image_cube, axis=0), header, clobber=True)
# Remove work directory
shutil.rmtree(work_dir)
def mosaic(input_files, mosaic_file, work_dir, ext=0, background_match=False,
cdelt=None, density=False, equinox=None, header=None,
level_only=False, north_aligned=False, postprocess=None,
preprocess=None, system=None, weights_file=None):
"""Make a mosiac.
High-level wrapper around several Montage operations similar to
`montage_wrapper.mosaic`. The main differences are 1) added support for
preprocessing the input images before reprojection and postprocessing
the final image after mosaicking, 2) options for using images in total
flux units instead of flux density (as assumed by Montage), 3) more of
the `montage_wrapper.mMakeHdr` keywords available for header creation,
and 4) the `whole` keyword for `montage_wrapper.mProjExec` is
automatically set to True when `background_match` is True. The latter
is important since backround matching behaves unreliably otherwise.
Parameters
----------
input_files : list or string
List of paths to the input images. This may also be the path to a
directory containing all input images, in which case `input_files`
will automatically be set to a list of all files in the directory
ending with ".fits".
mosaic_file : str
Path to the output mosaic file. The final mosaic always has the
same units as the `input_files` images.
work_dir : str
Path to the working directory for all intermediate files produced
by Montage. The directory has the following structure::
work_dir/
input/
Contains either symlinks to `input_files` or new files
depending on the `preprocess` and `density` keywords.
Assuming the `density` keyword has been set correctly, these
images will always be in flux density units.
reprojected/
The reprojected images.
differences/
Difference calculations for background matching (only if
`background_match` is True).
corrected/
Background-matched images (only if `background_match` is
True).
output/
The intermediate mosiac used to produce the final mosaic
file, depending on the `density` and `postprocess` keywords.
background_match : bool, optional
If True, match the background levels of the reprojected images
before mosaicking. Automatically sets ``whole = True`` in
`montage_wrapper.mProjExec`. Default is False.
cdelt : float, optional
See `header` and `montage_wrapper.mMakeHdr`. Default is None.
density : bool, optional
If True, the input images are in flux density units (i.e., signal
per unit pixel area). If False (default), the input images are
assumed to be in units of total flux, and are automatically scaled
to flux density before reprojection.
equinox : str, optional
See `header` and `montage_wrapper.mMakeHdr`. Default is None.
header : str, optional
Path to the template header file describing the output mosaic.
Default is None, in which case a template header is created
automatically using `montage_wrapper.mMakeHdr` and the `cdelt`,
`equinox`, `north_aligned`, and `system` keyword arguments.
level_only : bool, optional
See `montage_wrapper.mBgModel`. Ignored if `background_match` is
False. Default is False.
north_aligned : bool, optional
See `header` and `montage_wrapper.mMakeHdr`. Default is None.
postprocess, preprocess : function, optional
Functions for processing the raw input images before the input
density images are created (`preprocess`) and after the final
mosaic is created (`postprocess`). The function arguments should be
the image data array and the image header
(`astropy.io.fits.Header`), and the return values should be the
same. Default is None.
system : str, optional
See `header` and `montage_wrapper.mMakeHdr`. Default is None.
weights_file : str, optional
Path to output pixel weights file. Pixel weights are derived from
the final mosaic area file. Weights are normalized to 1, and
represent coverage of the mosaic area by the input images. Unlike
Montage area files, regions where the input images overlap are not
considered. Default is None.
Returns
-------
None
"""
# Get list of files if input_files is a directory name
if isinstance(input_files, basestring):
dirname = os.path.dirname(input_files)
input_files = [os.path.join(dirname, basename)
for basename in os.listdir(dirname)
if os.path.splitext(basename)[1] == '.fits']
# Create working directory
try:
os.makedirs(work_dir)
except OSError:
shutil.rmtree(work_dir)
os.makedirs(work_dir)
# Create input directory, populate it, and get image metadata
input_dir = os.path.join(work_dir, 'input')
os.mkdir(input_dir)
if preprocess or not density or ext>0:
# Create new input files
for input_file in input_files:
data, hdr = astropy.io.fits.getdata(input_file, header=True,
ext=ext)
if preprocess:
data, hdr = preprocess(data, hdr)
if not density:
# Convert total flux into flux density
dx, dy = wcs.calc_pixscale(hdr, ref='crpix').arcsec
pixarea = dx * dy # arcsec2
data /= pixarea
# Write
basename = os.path.basename(input_file)
basename = '_density'.join(os.path.splitext(basename))
new_input_file = os.path.join(input_dir, basename)
hdu = astropy.io.fits.PrimaryHDU(data=data, header=hdr)
hdu.writeto(new_input_file, output_verify='ignore')
else:
# Symlink existing files
for input_file in input_files:
basename = os.path.basename(input_file)
new_input_file = os.path.join(input_dir, basename)
os.symlink(input_file, new_input_file)
input_table = os.path.join(input_dir, 'input.tbl')
montage.mImgtbl(input_dir, input_table, corners=True)
# Template header
if header is None:
template_header = os.path.join(work_dir, 'template.hdr')
montage.mMakeHdr(input_table, template_header, cdelt=cdelt,
equinox=equinox, north_aligned=north_aligned,
system=system)
else:
template_header = header
# Create reprojection directory, reproject, and get image metadata
proj_dir = os.path.join(work_dir, 'reprojected')
os.makedirs(proj_dir)
whole = True if background_match else False
stats_table = os.path.join(proj_dir, 'mProjExec_stats.log')
montage.mProjExec(input_table, template_header, proj_dir, stats_table,
raw_dir=input_dir, whole=whole)
reprojected_table = os.path.join(proj_dir, 'reprojected.tbl')
montage.mImgtbl(proj_dir, reprojected_table, corners=True)
# Background matching
if background_match:
diff_dir = os.path.join(work_dir, 'differences')
os.makedirs(diff_dir)
# Find overlaps
diffs_table = os.path.join(diff_dir, 'differences.tbl')
montage.mOverlaps(reprojected_table, diffs_table)
# Calculate differences between overlapping images
montage.mDiffExec(diffs_table, template_header, diff_dir,
proj_dir=proj_dir)
# Find best-fit plane coefficients
fits_table = os.path.join(diff_dir, 'fits.tbl')
montage.mFitExec(diffs_table, fits_table, diff_dir)
# Calculate corrections
corr_dir = os.path.join(work_dir, 'corrected')
os.makedirs(corr_dir)
corrections_table = os.path.join(corr_dir, 'corrections.tbl')
montage.mBgModel(reprojected_table, fits_table, corrections_table,
level_only=level_only)
# Apply corrections
montage.mBgExec(reprojected_table, corrections_table, corr_dir,
proj_dir=proj_dir)
img_dir = corr_dir
else:
img_dir = proj_dir
# Make mosaic
output_dir = os.path.join(work_dir, 'output')
os.makedirs(output_dir)
out_image = os.path.join(output_dir, 'mosaic.fits')
montage.mAdd(reprojected_table, template_header, out_image,
img_dir=img_dir, exact=True)
# Pixel areas and weights
if weights_file or not density:
area_file = '_area'.join(os.path.splitext(out_image))
area, hdr = astropy.io.fits.getdata(area_file, header=True) # steradians
area *= (180/np.pi*3600)**2 # arcsec2
dx, dy = wcs.calc_pixscale(hdr, ref='crpix').arcsec
pixarea = dx * dy # arcsec2
area = np.clip(area, 0, pixarea) # Don't care about overlaps
if weights_file:
weights = area / pixarea # Normalize to 1
hdu = astropy.io.fits.PrimaryHDU(weights, header=hdr)
try:
hdu.writeto(weights_file)
except IOError:
os.remove(weights_file)
hdu.writeto(weights_file)
# Write final mosaic
dirname = os.path.dirname(mosaic_file)
try:
os.makedirs(dirname)
except OSError:
pass
if postprocess or not density:
# Create new file
data, hdr = astropy.io.fits.getdata(out_image, header=True)
if not density:
# Convert flux density into total flux
data *= pixarea
if postprocess:
data, hdr = postprocess(data, hdr)
# Write
hdu = astropy.io.fits.PrimaryHDU(data, header=hdr)
try:
hdu.writeto(mosaic_file)
except IOError:
os.remove(mosaic_file)
hdu.writeto(mosaic_file)
else:
# Move existing file
os.rename(out_image, mosaic_file)
return
def make_rgb_cube(files, output, north=False, system=None, equinox=None):
'''
Make an RGB data cube from a list of three FITS images.
This method can read in three FITS files with different
projections/sizes/resolutions and uses Montage to reproject
them all to the same projection.
Two files are produced by this function. The first is a three-dimensional
FITS cube with a filename give by `output`, where the third dimension
contains the different channels. The second is a two-dimensional FITS
image with a filename given by `output` with a `_2d` suffix. This file
contains the mean of the different channels, and is required as input to
FITSFigure if show_rgb is subsequently used to show a color image
generated from the FITS cube (to provide the correct WCS information to
FITSFigure).
Parameters
----------
files : tuple or list
A list of the filenames of three FITS filename to reproject.
The order is red, green, blue.
output : str
The filename of the output RGB FITS cube.
north : bool, optional
By default, the FITS header generated by Montage represents the
best fit to the images, often resulting in a slight rotation. If
you want north to be straight up in your final mosaic, you should
use this option.
system : str, optional
Specifies the system for the header (default is EQUJ).
Possible values are: EQUJ EQUB ECLJ ECLB GAL SGAL
equinox : str, optional
If a coordinate system is specified, the equinox can also be given
in the form YYYY. Default is J2000.
'''
# Check whether the Python montage module is installed. The Python module
# checks itself whether the Montage command-line tools are available, and
# if they are not then importing the Python module will fail.
try:
import montage_wrapper as montage
except ImportError:
raise Exception("Both the Montage command-line tools and the"
" montage-wrapper Python module are required"
" for this function")
# Check that input files exist
for f in files:
if not os.path.exists(f):
raise Exception("File does not exist : " + f)
# Create work directory
work_dir = tempfile.mkdtemp()
raw_dir = '%s/raw' % work_dir
final_dir = '%s/final' % work_dir
images_raw_tbl = '%s/images_raw.tbl' % work_dir
header_hdr = '%s/header.hdr' % work_dir
# Create raw and final directory in work directory
os.mkdir(raw_dir)
os.mkdir(final_dir)
# Create symbolic links to input files
for i, f in enumerate(files):
os.symlink(os.path.abspath(f), '%s/image_%i.fits' % (raw_dir, i))
# List files and create optimal header
montage.mImgtbl(raw_dir, images_raw_tbl, corners=True)
montage.mMakeHdr(images_raw_tbl,
header_hdr,
north_aligned=north,
system=system,
equinox=equinox)
# Read header in with astropy.io.fits
header = fits.Header.fromtextfile(header_hdr)
# Find image dimensions
nx = int(header['NAXIS1'])
ny = int(header['NAXIS2'])
# Generate emtpy datacube
image_cube = np.zeros((len(files), ny, nx), dtype=np.float32)
# Loop through files
for i in range(len(files)):
# Reproject channel to optimal header
montage.reproject('%s/image_%i.fits' % (raw_dir, i),
'%s/image_%i.fits' % (final_dir, i),
header=header_hdr,
exact_size=True,
bitpix=-32)
# Read in and add to datacube
image_cube[i, :, :] = fits.getdata('%s/image_%i.fits' % (final_dir, i))
# Write out final cube
fits.writeto(output, image_cube, header, clobber=True)
# Write out collapsed version of cube
fits.writeto(output.replace('.fits', '_2d.fits'), \
np.mean(image_cube, axis=0), header, clobber=True)
# Remove work directory
shutil.rmtree(work_dir)
def _montage_test():
# create density images
input_dir = os.path.dirname(density_files[0])
# image metadata
meta1_file = os.path.join(input_dir, 'meta1.tbl')
montage.mImgtbl(input_dir, meta1_file, corners=True)
# make header
#lon, lat = [], []
#for density_file in density_files:
# data, hdr = astropy.io.fits.getdata(density_file, header=True)
# wcs = astropy.wcs.WCS(hdr)
# x1, y1 = 0.5, 0.5
# y2, x2 = data.shape
# x2, y2 = x2 + 0.5, y2 + 0.5
# x, y = [x1, x2, x2, x1], [y1, y1, y2, y2]
# ln, lt = wcs.wcs_pix2world(x, y, 1)
# lon += list(ln)
# lat += list(lt)
#lon1, lon2 = np.min(lon), np.max(lon)
#lat1, lat2 = np.min(lat), np.max(lat)
hdr_file = os.path.join(os.path.dirname(input_dir), 'test.hdr')
montage.mMakeHdr(meta1_file, hdr_file)
# reproject
proj_dir = os.path.dirname(proj_files[0])
safe_mkdir(proj_dir)
stats_file = os.path.join(proj_dir, 'stats.tbl')
montage.mProjExec(meta1_file, hdr_file, proj_dir, stats_file,
raw_dir=input_dir, exact=True)
# image metadata
meta2_file = os.path.join(proj_dir, 'meta2.tbl')
montage.mImgtbl(proj_dir, meta2_file, corners=True)
# Background modeling
diff_dir = os.path.join(os.path.dirname(proj_dir), 'difference')
safe_mkdir(diff_dir)
diff_file = os.path.join(diff_dir, 'diffs.tbl')
montage.mOverlaps(meta2_file, diff_file)
montage.mDiffExec(diff_file, hdr_file, diff_dir, proj_dir)
fits_file = os.path.join(diff_dir, 'fits.tbl')
montage.mFitExec(diff_file, fits_file, diff_dir)
# Background matching
corr_dir = os.path.join(os.path.dirname(proj_dir), 'correct')
safe_mkdir(corr_dir)
corr_file = os.path.join(corr_dir, 'corrections.tbl')
montage.mBgModel(meta2_file, fits_file, corr_file, level_only=False)
montage.mBgExec(meta2_file, corr_file, corr_dir, proj_dir=proj_dir)
# Native mosaic
projadd_file = config.path('{:s}.reproject.add'.format(kind))
projadd_dir, filename = os.path.split(projadd_file)
filename, ext = os.path.splitext(filename)
filename = '{0:s}_native{1:s}'.format(filename, ext)
projaddnative_file = os.path.join(projadd_dir, filename)
safe_mkdir(projadd_dir)
montage.mAdd(meta2_file, hdr_file, projaddnative_file, img_dir=corr_dir, exact=True)
# Reproject to final header
header_file = config.path('{:s}.hdr'.format(kind))
montage.mProject(projaddnative_file, projadd_file, header_file)
# Postprocess
data, hdr = astropy.io.fits.getdata(projaddnative_file, header=True)
x1, x2 = 900, 1900
y1, y2 = 3000, 4500
val = np.mean(data[y1:y2,x1:x2])
data, hdr = astropy.io.fits.getdata(projadd_file, header=True)
data = data - val
areaadd_file = config.path('{:s}.area.add'.format(kind))
area = astropy.io.fits.getdata(areaadd_file) * (180/np.pi*3600)**2 # arcsec2
data = data * area
add_file = config.path('{:s}.add'.format(kind))
dirname = os.path.dirname(add_file)
safe_mkdir(dirname)
if os.path.exists(add_file):
os.remove(add_file)
hdu = astropy.io.fits.PrimaryHDU(data, header=hdr)
hdu.writeto(add_file)
def mosaic_band(self,band,ra,dec,margin,radius,pgc,survey,remove_bkgrd=False):
'''
Input: source info param
Create a mosaic fit file for the specified band.
Return: String filename of resulting mosaic
'''
print ("------------------mosaic_band----------------------")
print ("Now mosaic_band on {}".format(pgc))
output = open("../rc3_galaxies_outside_{}_footprint".format(survey.name),'a') # 'a' for append #'w')
unclean = open("../rc3_galaxies_unclean_{}".format(survey.name),"a")
filename = str(ra)+str(dec)
if (DEBUG) : print ("Querying data that lies inside margin")
print (ra,dec,margin)
result = survey.data_server.surveyFieldConverter(float(ra),float(dec),float(margin))
clean_result = survey.data_server.surveyFieldConverter(float(ra),float(dec),float(margin),True)
clean = True
if(DEBUG):print ("result: "+str(result))
if(DEBUG):print ("clean_result: "+str(clean_result))
if (len(result)!=len(clean_result)and band=='u'):
# Only print this once in the u band.
# Assume that if it is unclean in u band (ex. cosmic ray, bright star..etc) then it must be unclean in the other bands too.
print ("Data contain unclean images")
clean=False
unclean.write("{} {} {} {} \n".format(self.rc3_ra,self.rc3_dec,self.rc3_radius,self.pgc))
if (len(result)==0):
if (DEBUG): print ('The given ra, dec of this galaxy does not lie in the survey footprint. Onto the next galaxy!')#Exit Program.'
output.write("{} {} {} {} \n".format(str(ra),str(dec),str(radius),str(pgc)))
return -1 #special value reserved for not in survey footprint galaxies
else :
if (DEBUG):
print ( "Complete Query. These data lies within margin: ")
print (result)
os.mkdir(band)
os.chdir(band)
os.mkdir ("rawdir")
os.mkdir ("projdir")
if (remove_bkgrd):
os.mkdir ("diffdir")
os.mkdir ("corrdir")
# os.mkdir("final")
if (DEBUG): print ("Retrieving data from server for "+ band +"band")
os.chdir("rawdir")
out=""
# Raw Imaging Data naming
for i in result :
if (survey.data_server.name=='Gator'):
survey.data_server.getData(band,ra,dec,margin,survey)
out = i # 2MASS designation
print out
elif (survey.data_server.name=='SkyServer'):
survey.data_server.getData(band,str(i[0]), str(i[1]),str(i[2]))
# run-camcol-field
out = "frame-"+str(band)+"-"+str(i[0]).zfill(6)+"-"+str(i[1])+"-"+str(i[2]).zfill(4)
elif (survey.data_server.name=='DSSServer'):
survey.data_server.getData(band,ra,dec,margin)
# Patch for when we can not pass in th pgc number in getData of dssServer class, we rename the file here to conform with RC3's filename expectation for the imaging data
raw_data = glob.glob("raw_*.fits")
print (raw_data)
for i in raw_data:
os.rename(i,"DSS_{}_{}.fits".format(band, self.pgc))
out = "raw_{}_{}".format(band,self.pgc)
print ("dss_out: "+out)
else:
raise TypeError("Missing implementation for data retrieval")
os.chdir("../")
if (DEBUG) : print("Creating mosaic for "+band+" band.")
outfile_r = "{}_{}_{}r.fits".format(survey.name,band,self.pgc)
outfile = "{}_{}_{}.fits".format(survey.name,band,self.pgc)
if (len(result)==1):
#With header info, len of processed result list is 1 if there is only 1 field lying in the margin, simply do mSubImage without mosaicing
print ("Only one field in region of interest")
os.chdir("rawdir")
if (DEBUG):print ("m:{}".format(margin))
try:
if (DEBUG):print ("2m:{}".format(2*margin))
if (DEBUG):print ([outfile_r,outfile,ra,dec,2*margin])
montage.mSubimage(outfile,outfile,ra,dec,2*margin) # mSubImage takes xsize which should be twice the margin (margin measures center to edge of image)
except(montage.status.MontageError):
print ("montage_wrapper.status.MontageError: mSubimage: Region outside image.")
try :#give it one last chance
if (DEBUG):print ("lastchancem:{}".format(margin))
montage.mSubimage(out+".fits",outfile,ra,dec,margin)
except(montage.status.MontageError):
print("Doesn't work after trying half the margin, just keep the raw FITS file")
if (DEBUG):print (out+".fits")
if (DEBUG):print (outfile)
shutil.move(out+".fits","../..")
os.chdir("../../")
os.rename(out+".fits",outfile)
os.system("rm -r {}".format(survey.best_band))
return outfile
if (DEBUG):print (os.getcwd())
os.chdir("../../") #Get out of directory for that galaxy and move on
os.system("rm -r {}".format(survey.best_band))
if (DEBUG):print(os.getcwd())
failed_msubimage = open ("failed_msubimage","a")
failed_msubimage.write("{} {} {} {} \n".format(str(ra),str(dec),str(radius),str(pgc)))
return -1 # masking with special value reserved for not in survey footprint galaxies
hdulist = pyfits.open(outfile)
if (os.path.exists("../../"+outfile)):
os.system("rm ../../"+outfile)
shutil.move(outfile,"../..")
os.chdir("../..")
else:
imgtbl="images-rawdir.tbl"
hdr="template.hdr"
montage.mImgtbl("rawdir",imgtbl)
# montage.mHdr(str(ra)+" "+str(dec),margin,out+".hdr")
montage.mMakeHdr(imgtbl,hdr)
if (DEBUG): print ("Reprojecting images")
# os.chdir("rawdir")
if (DEBUG):print(os.getcwd())
montage.mProjExec(imgtbl,hdr,"projdir", "stats.tbl",raw_dir="rawdir")#, mpi=enable_mpi,debug=True)
if os.listdir("projdir") == []:
print "Projection Failed. No projected images produced. Skip to the next galaxy"
os.chdir("../") #Get out of directory for that galaxy and move on
os.system("rm -r {}".format(survey.best_band))
failed_projection = open ("failed_projection","a")
failed_projection.write("{} {} {} {} \n".format(str(ra),str(dec),str(radius),str(pgc)))
return -1 # masking with special value reserved for not in survey footprint galaxies
if (remove_bkgrd):
if (DEBUG): print "Calling the bash script containing Montage routines to rectify the background"
if os.getcwd()[-4:-2]==str(pgc):
os.system("bash ../../mosaic.sh")
else:
os.system("bash ../mosaic.sh")
print "mSubimage"
montage.mSubimage("mosaic.fits" ,"mosaic.fits",ra,dec,2*margin) # mSubImage takes xsize which should be twice the margin (margin measures center to edge of image)
shutil.move("mosaic.fits","../{}".format(outfile_r))#if change to :-11 then move out of u,g,r,i,z directory, may be more convenient for mJPEG
if (DEBUG) : print ("Completed Mosaic for " + band)
else:
montage.mImgtbl("projdir","pimages.tbl")
os.chdir("projdir")
montage.mAdd("../pimages.tbl","../"+hdr,"{}_{}.fits".format(survey.name,out))#, mpi=enable_mpi)
montage.mSubimage("{}_{}.fits".format(survey.name,out),outfile_r,ra,dec,2*margin) # mSubImage takes xsize which should be twice the margin (margin measures center to edge of image)
shutil.move(outfile_r,"../../{}".format(outfile_r) )#if change to :-11 then move out of u,g,r,i,z directory, may be more convenient for mJPEG
if (DEBUG) : print ("Completed Mosaic for " + band)
os.chdir("..")
os.chdir("../")
hdulist = pyfits.open(outfile_r)
hdulist[0].header['RA']=float(ra)
hdulist[0].header['DEC']=float(dec)
hdulist[0].header['RADIUS']=radius
if (DEBUG):print ("Finished mosaic_band on {}".format(pgc))
hdulist[0].header['PGC']=pgc
hdulist[0].header['NED']=("http://ned.ipac.caltech.edu/cgi-bin/objsearch?objname="+ str(hdulist[0].header['PGC'])+"&extend=no&hconst=73&omegam=0.27&omegav=0.73&corr_z=1&out_csys=Equatorial&out_equinox=J2000.0&obj_sort=RA+or+Longitude&of=pre_text&zv_breaker=30000.0&list_limit=5&img_stamp=YES")
hdulist[0].header['CLEAN']=clean
hdulist[0].header['MARGIN']=margin
if (os.path.exists(outfile)):
os.system("rm "+ outfile)
hdulist.writeto(outfile)
if (os.path.exists(outfile_r)):
os.system("rm "+outfile_r)
os.system("rm -r {}".format(band))
return outfile
