def coordshift(ra, dec, rashift, decshift):
# shift ra and dec by rashift and decshift
# ra: string in the hh:mm:ss.ss format
# dec: string in the dd.mm.ss.ss format
# rashift: float in arcsec
# dechift: float in arcsec
(hh, mm, ss) = cm.ratohms(cm.hmstora(*ra.split(":")) + rashift/3600)
ra = str(hh)+":"+str(mm)+":"+ '%.3f' % ss
(dd, mm, ss) = cm.dectodms(cm.dmstodec(*dec.split(".",2)) + decshift/3600)
dec = "+"+str(dd)+"."+str(mm)+"."+ '%.3f' % ss
return ra, dec
# toplabel in months
#ax.set_(r'')
types = np.dtype({'names':['name', 'ra', 'dec'], 'formats':['S100','S100','S100']})
data = np.loadtxt(sys.argv[1], comments='#', usecols=(0,1,2), unpack=False, dtype=types)
me = pm.measures()
position = me.position('wgs84',qa.quantity(3826600.961,'m'),qa.quantity(460953.402,'m'),qa.quantity(5064881.136,'m')) # superterp
me.doframe(position)
y=1
for obj in data:
print "Work on: ", obj['name']
rah, ram, ras = obj['ra'].split(':')
ra = cm.hmstora(float(rah), float(ram), float(ras)) # in deg
decd, decm, decs = obj['dec'].split(':')
dec = cm.dmstodec(float(decd), float(decm), float(decs)) # in deg
for d in xrange(360):
# count how many h the source is at elev>30 when sun is at elev<0
observable = 0
for h in xrange(24):
t = 2456293.5-2400000.5+d+h/24. # MJD for 1/1/2013 + the hours
obj_elev, sun_elev = get_elev(t,ra,dec)
#print "RESULTS:", obj_elev, sun_elev
if obj_elev>30 and sun_elev<0: observable+=1
# plot in greyscale from 0 to 12 h
print d,y,observable
ax.plot(d,y,c=str(observable/24.))
ax.text(1,y,obj['name'])
y+=1
ax.set_ylim(ymin=0, ymax=y)
def read_skymodel(skymodel, fields=[]):
"""
Read a skymodel file (BBS format)
skymodel -- the skymodel file generated by PyBDSM
fields -- list of fields to load
Return:
numpy array with all the sources in the skymodel
"""
names = []
formats = []
usecols = []
converters = {}
filling_values = {}
f = open(skymodel, 'r')
header = f.readline()
# remove useless part of the header
header = re.sub(r'\s', '', header)
header = re.sub(r'\)=format', '', header)
header = re.sub(r'#\(', '', header)
headers = header.split(',')
for i, h in enumerate(headers):
if not h in fields and fields != []: continue
# if there's a default value, set it and remove it from the header name
if re.search('=', h):
default_value = re.sub(r'.*=', '', h).replace('\'','')
filling_values[i]=default_value
h = re.sub(r'=.*', '', h)
names.append(h)
usecols.append(i)
if h == "Ra":
formats.append(np.float)
converters[i] = lambda x: cm.hmstora(float(x.split(':')[0]),float(x.split(':')[1]),float(x.split(':')[2])) if x else 0.0
elif h == "Dec":
formats.append(np.float)
converters[i] = lambda x: cm.dmstodec(float(x.split('.')[0]),float(x.split('.')[1]),float(x.split('.')[2])) if x else 0.0
elif h == "I" or h == "Q" or h == "U" or h == "V" or h == "ReferenceFrequency" or h == "MajorAxis" or h == "MinorAxis" or h == "Orientation":
formats.append(np.float)
if not i in filling_values:
if h == "I": filling_values[i]=1
else: filling_values[i]=0
else:
filling_values[i]=np.float(filling_values[i])
# note that SpectralIndex also end up as a string with no comma!!
else:
formats.append('S100')
types = np.dtype({'names':names,'formats':formats})
n = len(types)-1
# generator
def fileiter(skymodel, n):
for line in open(skymodel,'r'):
# remove comments, patches and white lines
if line[0] == '#' or line[0] == ',' or len(line) == 1: continue
# remove commas inside [] for spidx and leave one space
spidx_part = re.search(r'\[.*\]', line).group(0).replace(',',' ')
spidx_part = re.sub('\s{2,}', ' ', spidx_part)
line = re.sub(r'\[.*\]', spidx_part, line)
# add the missing commas at the end of the lines
n_commas = line.count(',')
missing_commas = n - n_commas
yield line+','*missing_commas
skymodel_data = np.genfromtxt(fileiter(skymodel, n), names=names, comments='#', unpack=True, dtype=formats, delimiter=',', autostrip=True, usecols=usecols, converters=converters, filling_values=filling_values)
if 'SpectralIndex' in skymodel_data.dtype.fields:
for skymodel_datum in skymodel_data:
skymodel_datum['SpectralIndex'] = skymodel_datum['SpectralIndex'].replace(' ',',')
return skymodel_data
ccname = cc[PosName]
ccra = cc[PosRA]
ccdec = cc[PosDec]
ccpatch = cc[PosPatch]
ccspidx = cc[PosSpidx]
ccI = float(cc[PosI])
# first do the coordinate shift (assuming mask and spidx image have correct coordinates!)
if shift != None:
(ra, dec) = coordshift(ra, dec, rashift, decshift)
ccra = ra; ccdec = dec
if mask != None:
(a,b,_,_) = maskdata.toworld([0,0,0,0])
(_, _, pixY, pixX) = maskdata.topixel([a, b, \
math.radians(cm.dmstodec(*ccdec.split(".",2))), math.radians(cm.hmstora(*ccra.split(":")))])
try:
# != is a XOR for booleans
if (not maskval[math.floor(pixY)][math.floor(pixX)]) != reverse:
totFluxMask += ccI
if patchprefix == None:
if verbose: print("Removing component \"",ccname,"\" because it is masked.")
continue
else:
if verbose: print("Renameing patch for \"",ccname,"\" because it is masked.")
# add to the list of patches to update
if ccpatch not in patchtoupdate: patchtoupdate.append(ccpatch)
else:
totFluxOutMask += ccI
except:
usecols=(0, 1, 2),
unpack=False,
dtype=types)
me = pm.measures()
position = me.position('wgs84', qa.quantity(3826600.961, 'm'),
qa.quantity(460953.402, 'm'),
qa.quantity(5064881.136, 'm')) # superterp
me.doframe(position)
y = 1
for obj in data:
print("Work on: ", obj['name'])
rah, ram, ras = obj['ra'].split(':')
ra = cm.hmstora(float(rah), float(ram), float(ras)) # in deg
decd, decm, decs = obj['dec'].split(':')
dec = cm.dmstodec(float(decd), float(decm), float(decs)) # in deg
for d in range(360):
# count how many h the source is at elev>30 when sun is at elev<0
observable = 0
for h in range(24):
t = 2456293.5 - 2400000.5 + d + h / 24. # MJD for 1/1/2013 + the hours
obj_elev, sun_elev = get_elev(t, ra, dec)
#print "RESULTS:", obj_elev, sun_elev
if obj_elev > 30 and sun_elev < 0: observable += 1
# plot in greyscale from 0 to 12 h
print(d, y, observable)
ax.plot(d, y, c=str(observable / 24.))
ax.text(1, y, obj['name'])
y += 1
ax.set_ylim(ymin=0, ymax=y)
