def savedict(filename, results, yaml_kwargs=dict()):
""" Save a dictionary to a file. Choose file format based
upon extension to filename. """
is_results = lambda x: isinstance(x,dict) or isinstance(x,list)
if isinstance(filename,str) and is_results(results):
pass
elif is_results(filename) and isinstance(results, str):
filename, results = results, filename
else:
raise Exception("Unrecoginized types for filename and results")
filename = expandvars(filename)
extension = os.path.splitext(filename)[-1]
if extension == '.yaml':
open(filename, 'w').write(yaml.dump(tolist(results), **yaml_kwargs))
elif extension == '.hdf5':
if not isinstance(results, dict): raise Exception("Can only save dicts to hdf5 format.")
import h5py
f=h5py.File(filename,'w')
for k,v in results.items(): f[k] = v
f.close()
elif extension == '.fits':
if not isinstance(results, dict): raise Exception("Can only save dicts to fits format.")
rec = fromarrays(results.values(), names=results.keys())
makefits(rec, filename, clobber=True)
elif extension == '.xml':
from pyxml2obj import XMLout
open(filename, 'w').write(XMLout(results))
else:
raise Exception("Unrecognized extension %s" % extension)
def write_map(self, name, fun=lambda x:x, title=None, vmax=None, table=None):
""" DISABLED for now
write out image files for a single table
name : string
name of the table, to be loaded by roi_maps.load_tables if table is None
fun : ufunc function
ufunc to apply to each pixel when generating the image files
title : string
title to apply to plots
table : None, or a HEALpix array
"""
if table is None:
table = healpix_map.load_tables(name, outdir=self.outdir)
nside = int(np.sqrt(len(table)/12))
assert len(table)==12*nside**2, 'table length, %d, not HEALpix compatible' % len(table)
filename = '%s_ait.fits' % name
fitsfile = os.path.join(self.pivot_dir,filename)
if os.path.exists(fitsfile):
if self.overwrite: os.remove(fitsfile)
else: fitsfile = ''
outfile=os.path.join(self.pivot_dir,'%s_ait.png'%name)
if fitsfile != '':
# first without the usual scaling function for the FITS version
print 'generating FITS image %s' %fitsfile
q=display_map.skyplot(table, title,
ait_kw=dict(fitsfile=fitsfile,pixelsize=0.1))
del q
if not os.path.exists(outfile) or self.overwrite:
print 'generating %s and its thumbnail...' % outfile
# now with scaling function to generate png
plt.close(30)
fig = plt.figure(30, figsize=(16,8))
q=display_map.skyplot(fun(table), title, axes=fig.gca(),
ait_kw=dict(fitsfile='', pixelsize=0.1), vmax=vmax)
plt.savefig(outfile, bbox_inches='tight', pad_inches=0)
im = PIL.Image.open(outfile)
im.thumbnail((200,100))
im.save(outfile.replace('.png', '_thumbnail.png'))
del q
outfile = os.path.join(self.pivot_dir,'%s_map.fits' % name)
if os.path.exists(outfile):
if self.overwrite: os.remove(outfile)
else: return
print 'generating %s' % outfile
dirs = map(Band(nside).dir, xrange(len(table)))
ra = np.array(map(lambda s: s.ra(), dirs), np.float32)
dec = np.array(map(lambda s: s.dec(),dirs), np.float32)
outrec = np.rec.fromarrays([ra,dec,np.array(table,np.float32)],
names = ['ra','dec', 'value'])
makerec.makefits(outrec, outfile)
def write_FITS(self, TSmin=None):
""" write out the Catalog format FITS version, and the rois """
catname = os.path.join(self.pivot_dir,self.name+'.fits')
if os.path.exists(catname):
if self.overwrite: os.remove(catname)
else:
return
cat = makecat.MakeCat(self.sources, TScut=0 if TSmin is None else TSmin)
cat(catname)
for rec, rectype in ((self.sources, 'sources'), (self.rois,'rois')):
outfile = os.path.join(self.pivot_dir,self.name+'_%s.fits'%rectype)
if os.path.exists(outfile):
if self.overwrite: os.remove(outfile)
else:
print 'file %s exists: set overwrite to replace it' % catname
continue
makerec.makefits(rec, outfile)
print 'wrote %s' %outfile
print '%s - %s/%s' % (results, i, len(all_results))
r = yaml.load(open(results))
if r is None: continue
for i in r:
e=i['mc']['extension']
f=i['mc']['flux']['flux']
index=i['mc']['model']['Index']
e_ul=i['extension_ul']['extension']
#if e_ul is None: e_ul = 0
if e_ul is None:
e_ul = np.nan
ts=max(i['point']['TS'],0)
ts_ext=max(i['TS_ext'],0)
type=i['type']
rec.append(f,index,e,e_ul,ts,ts_ext,type)
rec = rec()
file=join(datadir,'cached.fits')
if exists(file): remove(file)
makefits(rec,file)
