def check_recombine(obsID, directory=None, required_size=327680000, \
required_size_ics=30720000, startsec=None, n_secs=None):
'''
Checks that the number of files in directory (/astro/mwaops/vcs/[obsID]/combined/) is ....
as that found on the archive and also checks that all files have the same size (327680000 by default).
'''
if not directory:
directory = "/astro/mwaops/vcs/{0}/combined/".format(obsID)
base = "\n Checking file size and number of files for obsID {0} in {1} for ".format(
obsID, directory)
n_secs = n_secs if n_secs else 1
logger.info(base +
"gps times {0} to {1}".format(startsec, startsec + n_secs -
1) if startsec else base +
"the whole time range.")
required_size = required_size
# we need to get the number of unique seconds from the file names
meta = getmeta(service='obs', params={'obs_id': obsID})
files = np.array(list(meta['files'].keys()))
mask = np.array(['.dat' in file for file in files])
if not startsec:
times = [time[11:21] for time in files[mask]]
n_secs = len(set(times))
command = "ls -l %s/*ch*.dat | ((tee /dev/fd/5 | wc -l >/dev/fd/4) 5>&1 | " %(directory) + \
"awk '($5!=%s){print $9}' | tee >> %s/%s_all.txt | xargs rm -rf) 4>&1;" %(required_size, directory, obsID) + \
"cat %s/%s_all.txt; rm -rf %s/%s_all.txt" %(directory, obsID, directory, obsID)
output = subprocess.Popen([command],
stdout=subprocess.PIPE,
shell=True).stdout
else:
output = subprocess.Popen(["count=0;for sec in `seq -w %s %s `;do let count=${count}+`ls -l %s/*${sec}*ch*.dat | " %(startsec, startsec+n_secs-1, directory) + \
"((tee /dev/fd/5 | wc -l >/dev/fd/4) 5>&1 | awk '($5!=%s) " %(required_size) + \
"{print $9}' | tee >> %s/errors_%s.txt | xargs rm -rf) 4>&1`;done;" %(directory,startsec) +\
"echo ${count}; cat %s/errors_%s.txt;rm -rf %s/errors_%s.txt" %(directory,startsec,directory,startsec)],
stdout=subprocess.PIPE, shell=True).stdout
output = output.readlines()
files_in_dir = int(output[0].strip())
expected_files = n_secs * 25
error = False
error, n_ics = check_recombine_ics(directory=directory, \
startsec=startsec, n_secs=n_secs, required_size=required_size_ics)
files_in_dir += n_ics
if not files_in_dir == expected_files:
logger.error("We have {0} files but expected {1}".format(
files_in_dir, expected_files))
error = True
for line in output[1:]:
if b'dat' in line:
logger.warning("Deleted {0} due to wrong size.".format(
line.strip()))
error = True
if not error:
logger.info("We have all {0} files as expected.".format(files_in_dir))
return error
def get_delay_steps(obs):
beam_meta_data = getmeta(service='obs', params={'obs_id':obs})
ra = beam_meta_data[u'metadata'][u'ra_pointing']
dec = beam_meta_data[u'metadata'][u'dec_pointing']
duration = beam_meta_data[u'stoptime'] - beam_meta_data[u'starttime'] #gps time
xdelays = beam_meta_data[u'rfstreams'][u"0"][u'xdelays']
minfreq = float(min(beam_meta_data[u'rfstreams'][u"0"][u'frequencies']))
maxfreq = float(max(beam_meta_data[u'rfstreams'][u"0"][u'frequencies']))
channels = beam_meta_data[u'rfstreams'][u"0"][u'frequencies']
centrefreq = 1.28 * (minfreq + (maxfreq - minfreq) / 2)
return obs, ra, dec, duration, xdelays, centrefreq, channels
def get_obs_metadata(obs):
beam_meta_data = getmeta(service='obs', params={'obs_id': obs})
channels = beam_meta_data[u'rfstreams'][u"0"][u'frequencies']
freqs = [float(c) * 1.28 for c in channels]
xdelays = beam_meta_data[u'rfstreams'][u"0"][u'xdelays']
#pythodelays = beam_meta_data[u'rfstreams'][u"0"][u'xdelays']
ydelays = beam_meta_data[u'rfstreams'][u"0"][u'ydelays']
_, pointing_AZ, pointing_ZA = mwa_alt_az_za(obs)
return {
"channels": channels,
"frequencies": freqs,
"xdelays": xdelays,
"ydelays": ydelays,
"az": pointing_AZ,
"za": pointing_ZA
}
def get_files_and_sizes(obsID, mode):
if mode == 'raw':
suffix = '.dat'
elif mode == 'tar_ics':
suffix = '.tar'
elif mode == 'ics':
suffix = '_ics.dat'
else:
logger.error("Wrong mode supplied. Options are raw, tar_ics, and ics")
return
logger.info(
"Retrieving file info from MWA database for all {0} files...".format(
suffix))
meta = getmeta(service='obs', params={'obs_id': obsID, 'nocache': 1})
# 'nocache' is used above so we get don't use the cached metadata as that could
# be out of data so we force it to get up to date values
files = np.array(list(meta['files'].keys()))
files_masked = []
sizes = []
for f in files:
if suffix in f:
sizes.append(meta['files'][f]['size'])
files_masked.append(f)
#mask = np.array([suffix in file for file in files])
#files = files[mask]
#sizes=np.array([meta['files'][f]['size'] for f in files])
logger.info(
"...Done. Expect all on database to be {0} bytes in size...".format(
sizes[0]))
size_check = True
for s in sizes:
if not s == sizes[0]:
size_check = False
#if np.all(sizes == sizes[0]): #this stopped working for some reason
if size_check:
logger.info("...yep they are. Now checking on disk.")
return files_masked, suffix, sizes[0]
else:
logger.error("Not all files have the same size. Check your data!")
logger.error("{0}".format(np.vstack((files, sizes)).T))
return
def find_obsids_meta_pages(params={'mode': 'VOLTAGE_START'}):
"""
Loops over pages for each page for MWA metadata calls
"""
obsid_list = []
temp = []
page = 1
#need to ask for a page of results at a time
while len(temp) == 200 or page == 1:
params['page'] = page
logger.debug("Page: {0} params: {1}".format(page, params))
temp = getmeta(service='find', params=params)
if temp is not None:
# if there are non obs in the field (which is rare) None is returned
for row in temp:
obsid_list.append(row[0])
else:
temp = []
page += 1
return obsid_list
def construct_base_string(self):
"""Construct the basic string to be written to the RTS config file.
This string will then be edit with regexp to update the relevant details.
Returns
-------
file_str : str
The base string to be written to an RTS configuration srcipt after manipulation.
Raises
------
CalibrationError
When there is a problem with some of the observation information and/or its manipulation.
"""
# get calibrator observation information from database
logger.info("Querying metadata database for obsevation information...")
obsinfo = getmeta(service='obs',
params={'obs_id': str(self.cal_obsid)})
# quick check to make sure what's returned is actually real data
if obsinfo[u'metadata'] is None:
errmsg = "Metadata database error (metadata empty). Maybe an invalid obs ID?"
logger.error(errmsg)
raise CalibrationError(errmsg)
# get the RA/Dec pointing for the primary beam
ra_pointing_degs = obsinfo['metadata']['ra_pointing']
dec_pointing_degs = obsinfo['metadata']['dec_pointing']
# now get the absolute channels
self.channels = obsinfo[u'rfstreams'][u"0"][u'frequencies']
# and figure out the MaxFrequency parameter
self.max_frequency = 1.28 * (
max(self.channels) + 1
) # this way we ensure that MaxFrequency is applicable for ALL subbands
# use the same operations as in timeconvert.py for our specific need
logger.info("Converting times with astropy")
#mwa_loc = EarthLocation.of_site('Murchison Widefield Array')
mwa_loc = EarthLocation.from_geodetic(lon="116:40:14.93",
lat="-26:42:11.95",
height=377.8)
#Astropy formating
utctime = strptime(self.utctime, '%Y%m%d%H%M%S')
a_time = strftime('%Y-%m-%dT%H:%M:%S', utctime)
obstime = Time(a_time, format='fits', scale='utc', location=mwa_loc)
lst_in_hours = obstime.sidereal_time('apparent').hourangle
jd = obstime.jd
logger.info(" LST: {0}".format(lst_in_hours))
logger.info(" JD : {0}".format(jd))
# set the HA of the image centre to the primary beam HA
logger.debug("Determining HA and DEC for primary beam")
self.JD = jd
pb_ha_hours = (ra_pointing_degs / 360.0) * 24.0
self.PB_HA = lst_in_hours - pb_ha_hours
self.PB_DEC = dec_pointing_degs
logger.debug("Primary beam: HA = {0} hrs, Dec = {1} deg".format(
self.PB_HA, self.PB_DEC))
logger.debug("JD = {0}".format(self.JD))
# get the lowest frequency channel
freqs = obsinfo['rfstreams']['0']['frequencies']
start_channel = freqs[0]
self.freq_base = start_channel * 1.28e6 - 0.64e6 + 15e3 # frequency base in Hz (based on Steve Ord's logic)
self.freq_base = self.freq_base / 1.0e6 # convert to MHz
logger.debug("Frequency lower edge = {0} MHz".format(self.freq_base))
# make metafits file formatted for RTS
self.metafits_RTSform = self.metafits.split("_metafits_ppds.fits")[0]
logger.debug("RTS form metafits location: {0}".format(
self.metafits_RTSform))
# create the final file string, expanding symlinks to real paths
logger.info("Constructing base RTS configuration script content")
file_str = """
ReadAllFromSingleFile=
BaseFilename={base}/*_gpubox
ReadGpuboxDirect={read_direct}
UseCorrelatorInput={use_corr_input}
ReadMetafitsFile=1
MetafitsFilename={metafits_file}
DoCalibration=
doMWArxCorrections=1
doRawDataCorrections=1
doRFIflagging=0
useFastPrimaryBeamModels={beam_model_bool}
generateDIjones=1
applyDIcalibration=1
UsePacketInput=0
UseThreadedVI=1
MaxFrequency={max_freq}
ObservationFrequencyBase={base_freq}
ObservationTimeBase={base_time}
ObservationPointCentreHA={obs_ha}
ObservationPointCentreDec={obs_dec}
ChannelBandwidth={fcbw}
NumberOfChannels={nchan}
CorrDumpsPerCadence={corr_dumps_per_cadence}
CorrDumpTime={corr_dump_time}
NumberOfIntegrationBins={n_int_bins}
NumberOfIterations=1
StartProcessingAt=0
ArrayPositionLat={array_lat}
ArrayPositionLong={array_lon}
ArrayNumberOfStations=128
ArrayFile=
SourceCatalogueFile={source_list}
NumberOfCalibrators=1
NumberOfSourcesToPeel=0
calBaselineMin=20.0
calShortBaselineTaper=40.0
FieldOfViewDegrees=1""".format(base=self.data_dir,
read_direct=self.readDirect,
use_corr_input=self.useCorrInput,
metafits_file=self.metafits_RTSform,
beam_model_bool=self.beam_model_bool,
max_freq=self.max_frequency,
base_freq=self.freq_base,
base_time=self.JD,
obs_ha=self.PB_HA,
obs_dec=self.PB_DEC,
fcbw=self.fine_cbw,
nchan=self.nfine_chan,
corr_dumps_per_cadence=self.n_dumps_to_average,
corr_dump_time=self.corr_dump_time,
n_int_bins=self.n_integration_bins,
array_lat=self.ArrayPositionLat,
array_lon=self.ArrayPositionLong,
source_list=self.source_list)
return file_str
obsid = args.observation
# Check if already spliced
if glob.glob('{0}/{1}*fits'.format(args.work_dir, args.observation)) and \
not glob.glob('{0}/*_{1}*fits'.format(args.work_dir, args.observation)):
print('All files are already spliced so exiting')
exit()
# Get frequency channels
if args.channels:
channels = args.channels
else:
print(
"Obtaining metadata from http://mwa-metadata01.pawsey.org.au/metadata/ for OBS ID: "
+ str(obsid))
beam_meta_data = meta.getmeta(service='obs', params={'obs_id': obsid})
channels = beam_meta_data[u'rfstreams'][u"0"][u'frequencies']
print("Chan order: {}".format(channels))
#hostname = socket.gethostname()
hostname = 'temp'
if hostname.startswith('john') or hostname.startswith('bryan'):
#If on ozstar use their SSD to improve I/O
SSD_file_dir = '{}/'.format(os.environ['JOBFS'])
print(SSD_file_dir)
else:
SSD_file_dir = ''
# Move into working dir
old_dir = os.getcwd()
if hostname.startswith('john') or hostname.startswith('bryan'):
def get_files_and_sizes(obsID, mode, mintime=0, maxtime=2000000000):
"""
Get files and sizes from the MWA metadata server and check that they're all the same size
Parameters:
-----------
obsID: int
The MWA observation ID
mode: str
The typ of file from 'raw', 'tar_ics' and 'ics'
mintime: int
The minimum GPS time of observations to check (inclusive, >=) Default: 0
maxtime: int
The maximum GPS time of observations to check (exculsive, <) Default: 2000000000
Returns:
--------
files_masked, suffix, sizes[0]: list
files_masked: list of the files with the input mode/suffix
suffix: '.dat', '.tar' or '_ics.dat' depnding on the input mode
sizes[0]: size of files in bytes
"""
if mode == 'raw':
suffix = '.dat'
elif mode == 'tar_ics':
suffix = '.tar'
elif mode == 'ics':
suffix = '_ics.dat'
else:
logger.error("Wrong mode supplied. Options are raw, tar_ics, and ics")
return
logger.info(
"Retrieving file info from MWA database for all {0} files...".format(
suffix))
files_meta = getmeta(service='data_files',
params={
'obs_id': obsID,
'nocache': 1,
'mintime': mintime,
'maxtime': maxtime
})
# 'nocache' is used above so we get don't use the cached metadata as that could
# be out of data so we force it to get up to date values
files = np.array(list(files_meta.keys()))
files_masked = []
sizes = []
for f in files:
if suffix in f:
sizes.append(files_meta[f]['size'])
files_masked.append(f)
logger.info(
"...Done. Expect all on database to be {0} bytes in size...".format(
sizes[0]))
size_check = True
for s in sizes:
if not s == sizes[0]:
size_check = False
if size_check:
logger.info("...yep they are. Now checking on disk.")
return files_masked, suffix, sizes[0]
else:
logger.error("Not all files have the same size. Check your data!")
logger.error("{0}".format(np.vstack((files, sizes)).T))
return
def find_sources_in_obs(obsid_list, names_ra_dec,
obs_for_source=False, dt_input=100, beam='analytic',
min_power=0.3, cal_check=False, all_volt=False,
degrees_check=False, metadata_list=None):
"""
Either creates text files for each MWA obs ID of each source within it or a text
file for each source with each MWA obs is that the source is in.
Args:
obsid_list: list of MWA obs IDs
names_ra_dec: [[source_name, ra, dec]]
dt: the time step in seconds to do power calculations
beam: beam simulation type ['analytic', 'advanced', 'full_EE']
min_power: if above the minium power assumes it's in the beam
cal_check: checks the MWA pulsar database if there is a calibration for the obsid
all_volt: Use all voltages observations including some inital test data
with incorrect formats
degrees_check: if false ra and dec is in hms, if true in degrees
Output [output_data, obsid_meta]:
output_data: The format of output_data is dependant on obs_for_source.
If obs_for_source is True:
output_data = {jname:[[obsid, duration, enter, exit, max_power],
[obsid, duration, enter, exit, max_power]]}
If obs_for_source is False:
ouput_data = {obsid:[[jname, enter, exit, max_power],
[jname, enter, exit, max_power]]}
obsid_meta: a list of the output of get_common_obs_metadata for each obsid
"""
#prepares metadata calls and calculates power
powers = []
#powers[obsid][source][time][freq]
obsid_meta = []
obsid_to_remove = []
for i, obsid in enumerate(obsid_list):
if metadata_list:
beam_meta_data, full_meta = metadata_list[i]
else:
beam_meta_data, full_meta = get_common_obs_metadata(obsid, return_all=True)
#beam_meta_data = obsid,ra_obs,dec_obs,time_obs,delays,centrefreq,channels
if dt_input * 4 > beam_meta_data[3]:
# If the observation time is very short then a smaller dt time is required
# to get enough ower imformation
dt = int(beam_meta_data[3] / 4.)
else:
dt = dt_input
logger.debug("obsid: {0}, time_obs {1} s, dt {2} s".format(obsid, beam_meta_data[3], dt))
#check for raw volatge files
filedata = getmeta(service='data_files', params={'obs_id':obsid, 'nocache':1})
keys = filedata.keys()
check = False
for k in keys:
if '.dat' in k: #TODO check if is still robust
check = True
if check or all_volt:
powers.append(get_beam_power_over_time(beam_meta_data, names_ra_dec,
dt=dt, centeronly=True, verbose=False,
option=beam, degrees=degrees_check))
obsid_meta.append(beam_meta_data)
else:
logger.warning('No raw voltage files for %s' % obsid)
obsid_to_remove.append(obsid)
for otr in obsid_to_remove:
obsid_list.remove(otr)
#chooses whether to list the source in each obs or the obs for each source
output_data = {}
if obs_for_source:
for sn, source in enumerate(names_ra_dec):
source_data = []
for on, obsid in enumerate(obsid_list):
source_ob_power = powers[on][sn]
if max(source_ob_power) > min_power:
duration = obsid_meta[on][3]
centre_freq = obsid_meta[on][5] #MHz
channels = obsid_meta[on][6]
bandwidth = (channels[-1] - channels[0] + 1.)*1.28 #MHz
logger.debug("Running beam_enter_exit on obsid: {}".format(obsid))
enter, exit = beam_enter_exit(source_ob_power,duration,
dt=dt, min_power=min_power)
if enter is not None:
source_data.append([obsid, duration, enter, exit,
max(source_ob_power)[0],
centre_freq, bandwidth])
# For each source make a dictionary key that contains a list of
# lists of the data for each obsid
output_data[source[0]] = source_data
else:
#output a list of sorces for each obs
for on, obsid in enumerate(obsid_list):
duration = obsid_meta[on][3]
obsid_data = []
for sn, source in enumerate(names_ra_dec):
source_ob_power = powers[on][sn]
if max(source_ob_power) > min_power:
enter, exit = beam_enter_exit(source_ob_power, duration,
dt=dt, min_power=min_power)
obsid_data.append([source[0], enter, exit, max(source_ob_power)[0]])
# For each obsid make a dictionary key that contains a list of
# lists of the data for each source/pulsar
output_data[obsid] = obsid_data
return output_data, obsid_meta
def plotSkyMap(obsfile, targetfile, oname, show_psrcat=False, show_mwa_sky=False, show_mwa_unique=False):
fig = plt.figure()
ax = fig.add_subplot(111, projection="mollweide")
mwa_dec_lim = 30
mwa_only_dec_lim = -50
if show_mwa_sky:
# Make a patch that is transformable through axis projection
# and highlight the visible sky for the MWA
Path = mpath.Path
ra_start = -np.pi
ra_end = np.pi
dec_start = -np.pi / 2
dec_end = np.radians(mwa_dec_lim)
path_data = [
(Path.MOVETO, (ra_start, dec_start)),
(Path.LINETO, (ra_start, dec_end)),
(Path.LINETO, (ra_end, dec_end)),
(Path.LINETO, (ra_end, dec_start)),
(Path.CLOSEPOLY, (ra_end, dec_start)),
]
codes, verts = zip(*path_data)
path = mpath.Path(verts, codes)
patch = mpatches.PathPatch(path, lw=0, ec="lightskyblue", fc="lightskyblue", label="All MWA sky")
ax.add_patch(patch)
if show_mwa_unique:
# Make a patch that is transformable through axis projection
# and highlight the part of the sky ONLY visible to the MWA
ra_start = -np.pi
ra_end = np.pi
dec_start = -np.pi / 2
dec_end = np.radians(mwa_only_dec_lim)
path_data = [
(Path.MOVETO, (ra_start, dec_start)),
(Path.LINETO, (ra_start, dec_end)),
(Path.LINETO, (ra_end, dec_end)),
(Path.LINETO, (ra_end, dec_start)),
(Path.CLOSEPOLY, (ra_end, dec_start)),
]
codes, verts = zip(*path_data)
path = mpath.Path(verts, codes)
patch = mpatches.PathPatch(path, lw=0, ec="lightgreen", fc="lightgreen", label="Unique MWA sky")
ax.add_patch(patch)
if show_psrcat:
# Retrieve the local installed PSRCAT catalogue and plot those pulsar positions
cmd = 'psrcat -o short_csv -nocand -nonumber -c "Jname RAJ DECJ" | sed "2d" > psrcat.csv'
subprocess.call(cmd, shell=True)
psrcat_coords = read_data("psrcat.csv", delim=";")
os.remove("psrcat.csv")
# Create a mask for pulsar in and out of the declination limit of the MWA
maskGood = psrcat_coords.dec.wrap_at(180*u.deg).deg < mwa_dec_lim
maskBad = psrcat_coords.dec.wrap_at(180*u.deg).deg >= mwa_dec_lim
psrcat_ra_good = -psrcat_coords.ra.wrap_at(180*u.deg).rad[maskGood] # negative because RA increases to the West
psrcat_dec_good = psrcat_coords.dec.wrap_at(180*u.deg).rad[maskGood]
psrcat_ra_bad = -psrcat_coords.ra.wrap_at(180*u.deg).rad[maskBad] # negative because RA increases to the West
psrcat_dec_bad = psrcat_coords.dec.wrap_at(180*u.deg).rad[maskBad]
# Now plot the pulsar locations
ax.scatter(psrcat_ra_good, psrcat_dec_good, 0.01, marker="x", color="0.4", zorder=1.4)
ax.scatter(psrcat_ra_bad, psrcat_dec_bad, 0.01, marker="x", color="0.8", zorder=1.4)
# Calculate beam patterns and plot contours
levels = np.arange(0.25, 1., 0.05)
cmap = plt.get_cmap("cubehelix_r")
obsids = read_data(obsfile, coords=False)["OBSID"]
for obsid in obsids:
#print "Accessing database for observation: {0}".format(obsid)
logger.info("Accessing database for observation: {0}".format(obsid))
# TODO: I think this process is now implemented in a function in mwa_metadb_utils, need to double check
beam_meta_data = getmeta(service='obs', params={'obs_id': obsid})
ra = beam_meta_data[u'metadata'][u'ra_pointing']
dec = beam_meta_data[u'metadata'][u'dec_pointing']
duration = beam_meta_data[u'stoptime'] - beam_meta_data[u'starttime'] #gps time
delays = beam_meta_data[u'rfstreams'][u'0'][u'xdelays']
minfreq = float(min(beam_meta_data[u'rfstreams'][u"0"][u'frequencies']))
maxfreq = float(max(beam_meta_data[u'rfstreams'][u"0"][u'frequencies']))
centrefreq = 1.28e6 * (minfreq + (maxfreq-minfreq)/2) #in MHz
channels = beam_meta_data[u'rfstreams'][u"0"][u'frequencies']
metadata = [obsid, ra, dec, duration, delays, centrefreq, channels]
beam_meta_data, full_meta = get_common_obs_metadata(obsid, return_all = True)
# Create a meshgrid over which to iterate
Dec = [] ; RA = []
map_dec_range = np.arange(-89, 90, 3)
map_ra_range = np.arange(0, 360, 3)
for i in map_dec_range:
for j in map_ra_range:
Dec.append(i)
RA.append(j)
RADecIndex = np.arange(len(RA))
names_ra_dec = np.column_stack((RADecIndex, RA, Dec))
#print "Creating beam patterns..."
time_intervals = 600 # seconds
powout = get_beam_power_over_time(beam_meta_data, names_ra_dec, dt=time_intervals, degrees=True)
z=[] ; x=[] ; y=[]
for c in range(len(RA)):
temppower = 0.
for t in range(powout.shape[1]):
power_ra = powout[c,t,0]
if power_ra > temppower:
temppower = power_ra
z.append(temppower)
if RA[c] > 180:
x.append(-RA[c]/180.*np.pi+2*np.pi)
else:
x.append(-RA[c]/180.*np.pi)
y.append(Dec[c]/180.*np.pi)
nx=np.array(x) ; ny=np.array(y); nz=np.array(z)
#print "Plotting beam pattern contours..."
logger.info("Plotting beam pattern contours...")
# Set vmin and vmax to ensure the beam patterns are on the same color scale
# and plot the beam pattern contours on the map
#c = ax.tricontour(wrapped_ra, wrapped_dec, final_pattern_power, levels=levels, cmap=cmap, vmin=levels.min(), vmax=levels.max(), zorder=1.3)
c = ax.tricontour(nx, ny, nz, levels=levels, cmap=cmap, vmin=levels.min(), vmax=levels.max(), zorder=1.3)
# Make a figure color scale based on the contour sets (which all have the same max/min values
fig.colorbar(c, fraction=0.02, pad=0.03, label="Zenith normalised power")
# Plot the target positions, using Astropy to wrap at correct RA
target_coords = read_data(targetfile)
wrapped_target_ra = -target_coords.ra.wrap_at(180*u.deg).rad # negative because RA increases to the West
wrapped_target_dec = target_coords.dec.wrap_at(180*u.deg).rad
#print "Plotting target source positions..."
logger.info("Plotting target source positions...")
ax.scatter(wrapped_target_ra, wrapped_target_dec, 10, marker="x", color="red", zorder=1.6, label="Target sources")
xtick_labels = ["10h", "8h", "6h", "4h", "2h", "0h", "22h", "20h", "18h", "16h", "14h"]
ax.set_xticklabels(xtick_labels, color="0.2")
ax.set_xlabel("Right Ascension")
ax.set_ylabel("Declination")
ax.grid(True, color="k", lw=0.5, ls=":")
# Place upper-right corner of legend at specified Axis coordinates
ax.legend(loc="upper right", bbox_to_anchor=(1.02, 0.08), numpoints=1, borderaxespad=0., fontsize=6)
plt.savefig(oname, format="eps", bbox_inches="tight")
