def __init__(self, fitsfns):
from formats import psrfits
super(NuppiSplitPsrfitsData, self).__init__(fitsfns)
self.obstype = 'Nuppi'
self.beam_id = 0
# Parse filename to get the scan number
m = self.fnmatch(fitsfns[0])
self.scan_num = m.groupdict()['scan']
self.obs_name = m.groupdict()['source']
self.num_ifs = self.specinfo.hdus[1].header['NPOL']
dayfrac = calendar.MJD_to_date(self.timestamp_mjd)[-1]%1
self.start_ast = int((dayfrac*24)*3600)
self.start_ast %= 24*3600
self.specinfo = psrfits.SpectraInfo(self.fns)
self.original_file = os.path.split(sorted(self.specinfo.filenames)[0])[-1]
self.project_id = self.specinfo.project_id
self.observers = self.specinfo.observer
self.source_name = self.specinfo.source
self.center_freq = self.specinfo.fctr
self.num_channels_per_record = self.specinfo.num_channels
self.channel_bandwidth = self.specinfo.df*1000.0 # In kHz
self.sample_time = self.specinfo.dt*1e6 # In microseconds
self.sum_id = int(self.specinfo.summed_polns)
self.timestamp_mjd = self.specinfo.start_MJD[0]
self.start_lst = self.specinfo.start_lst
self.orig_start_az = self.specinfo.azimuth
self.orig_start_za = self.specinfo.zenith_ang
self.ra_deg = self.specinfo.ra2000
self.dec_deg = self.specinfo.dec2000
self.right_ascension = float(protractor.convert(self.ra_deg, \
'deg', 'hmsstr')[0].replace(':', ''))
self.declination = float(protractor.convert(self.dec_deg, \
'deg', 'dmsstr')[0].replace(':', ''))
l, b = sextant.equatorial_to_galactic(self.ra_deg, self.dec_deg, \
'deg', 'deg', J2000=True)
self.galactic_longitude = float(l)
self.galactic_latitude = float(b)
self.file_size = int(sum([os.path.getsize(fn) for fn in fitsfns]))
self.observation_time = self.specinfo.T
self.num_samples = self.specinfo.N
self.data_size = self.num_samples * \
self.specinfo.bits_per_sample/8.0 * \
self.num_channels_per_record
self.num_samples_per_record = self.specinfo.spectra_per_subint
self.header_version = float(self.specinfo.header_version)
def get_correct_positions(self):
"""Reconstruct original wapp filename and check
for correct beam positions from the coordinates
table.
Returns nothing, updates object in place.
"""
fn0 = os.path.basename(min(self.fns)).lstrip('4bit-').replace(
's0g0', '').replace('s1g0', '').replace('00100', '00000')
# Get corrected beam positions
matches = [line for line in open(config.basic.mock_coords_table, 'r') if \
line.replace('s0g0','').startswith(fn0)]
if len(matches) > 1:
matches = [matches[0]]
if len(matches) == 0 and self.timestamp_mjd > 55378:
# No corrected coords found, but coordinate problem is fixed,
# so use header values.
# MJD=55378 is July 1st 2010, it is a recent date by which
# the coord problem is definitely corrected. (The problem
# occured from Feb 2009 to Jan 28, 2010).
self.right_ascension = self.orig_right_ascension
self.declination = self.orig_declination
self.ra_deg = self.orig_ra_deg
self.dec_deg = self.orig_dec_deg
self.galactic_longitude = self.orig_galactic_longitude
self.galactic_latitude = self.orig_galactic_latitude
elif len(matches) == 1:
# Use values from coords table
self.posn_corrected = True
# Format of mock coords table is:
# <first sub0 filename> <ra deg> <dec deg> <frac year> <lst hrs> <ALFA rot deg>
split = matches[0].split()
self.ra_deg = float(split[1])
self.dec_deg = float(split[2])
self.correct_ra = protractor.convert(self.ra_deg, 'deg',
'hmsstr')[0]
self.correct_decl = protractor.convert(self.dec_deg, 'deg',
'dmsstr')[0]
self.right_ascension = float(self.correct_ra.replace(':', ''))
self.declination = float(self.correct_decl.replace(':', ''))
l, b = sextant.equatorial_to_galactic(self.ra_deg, self.dec_deg, \
'deg', 'deg', J2000=True)
self.galactic_longitude = float(l)
self.galactic_latitude = float(b)
else:
raise ValueError("Bad number of matches (%d) in coords table! " \
"(Files: %s)" % (len(matches), ", ".join(self.fns)))
def get_correct_positions(self):
"""Reconstruct original wapp filename and check
for correct beam positions from the coordinates
table.
Returns nothing, updates object in place.
"""
wappfn = '.'.join([self.project_id, self.source_name, \
"wapp%d" % (self.beam_id/2+1), \
"%5d" % int(self.timestamp_mjd), \
self.fnmatch(self.original_file).groupdict()['scan']])
# Get corrected beam positions
matches = [line for line in open(COORDS_TABLE, 'r') if \
line.startswith(wappfn)]
if len(matches) == 0 and self.timestamp_mjd > 54651:
# No corrected coords found, but coordinate problem is fixed,
# so use header values.
# MJD=54651 is July 4th 2008, it is a recent date by which
# the coord problem is definitely corrected. (The problem
# was discovered and fixed in ~2005).
self.right_ascension = self.orig_right_ascension
self.declination = self.orig_declination
self.ra_deg = self.orig_ra_deg
self.dec_deg = self.orig_dec_deg
self.galactic_longitude = self.orig_galactic_longitude
self.galactic_latitude = self.orig_galactic_latitude
elif len(matches) == 1:
# Use values from coords table
self.posn_corrected = True
if self.beam_id % 2:
# Even beam number. Use columns 2 and 3.
self.correct_ra, self.correct_decl = matches[0].split()[1:3]
else:
self.correct_ra, self.correct_decl = matches[0].split()[3:5]
self.right_ascension = float(self.correct_ra.replace(':', ''))
self.declination = float(self.correct_decl.replace(':', ''))
self.ra_deg = float(
protractor.convert(self.correct_ra, 'hmsstr', 'deg')[0])
self.dec_deg = float(
protractor.convert(self.correct_decl, 'dmsstr', 'deg')[0])
l, b = sextant.equatorial_to_galactic(self.correct_ra, self.correct_decl, \
'sexigesimal', 'deg', J2000=True)
self.galactic_longitude = float(l[0])
self.galactic_latitude = float(b[0])
else:
raise ValueError("Bad number of matches (%d) in coords table!" %
len(matches))
def get_correct_positions(self):
"""Reconstruct original wapp filename and check
for correct beam positions from the coordinates
table.
Returns nothing, updates object in place.
"""
import config.basic
wappfn = '.'.join([self.project_id, self.source_name, \
"wapp%d" % (self.beam_id/2+1), \
"%5d" % int(self.timestamp_mjd), \
self.fnmatch(self.original_file).groupdict()['scan']])
# Get corrected beam positions
matches = [line for line in open(config.basic.coords_table, 'r') if \
line.startswith(wappfn)]
if len(matches) == 0 and self.timestamp_mjd > 54651:
# No corrected coords found, but coordinate problem is fixed,
# so use header values.
# MJD=54651 is July 4th 2008, it is a recent date by which
# the coord problem is definitely corrected. (The problem
# was discovered and fixed in ~2005).
self.right_ascension = self.orig_right_ascension
self.declination = self.orig_declination
self.ra_deg = self.orig_ra_deg
self.dec_deg = self.orig_dec_deg
self.galactic_longitude = self.orig_galactic_longitude
self.galactic_latitude = self.orig_galactic_latitude
elif len(matches) == 1:
# Use values from coords table
self.posn_corrected = True
if self.beam_id % 2:
# Even beam number. Use columns 2 and 3.
self.correct_ra, self.correct_decl = matches[0].split()[1:3]
else:
self.correct_ra, self.correct_decl = matches[0].split()[3:5]
self.right_ascension = float(self.correct_ra.replace(':', ''))
self.declination = float(self.correct_decl.replace(':', ''))
self.ra_deg = float(protractor.convert(self.correct_ra, 'hmsstr', 'deg')[0])
self.dec_deg = float(protractor.convert(self.correct_decl, 'dmsstr', 'deg')[0])
l, b = sextant.equatorial_to_galactic(self.correct_ra, self.correct_decl, \
'sexigesimal', 'deg', J2000=True)
self.galactic_longitude = float(l[0])
self.galactic_latitude = float(b[0])
else:
raise DataFileError("Bad number of matches (%d) in coords table! " \
"(Files: %s)" % (len(matches), ", ".join(self.fns)))
def __init__(self, fitsfns):
"""PSR fits Header object constructor.
"""
import psrfits
#from formats import psrfits
super(PsrfitsData, self).__init__(fitsfns)
# Read information from files
self.specinfo = psrfits.SpectraInfo(self.fns)
self.original_file = os.path.split(sorted(
self.specinfo.filenames)[0])[-1]
self.project_id = self.specinfo.project_id
self.observers = self.specinfo.observer
self.source_name = self.specinfo.source
self.center_freq = self.specinfo.fctr
self.num_channels_per_record = self.specinfo.num_channels
self.channel_bandwidth = self.specinfo.df * 1000.0 # In kHz
self.sample_time = self.specinfo.dt * 1e6 # In microseconds
self.sum_id = int(self.specinfo.summed_polns)
self.timestamp_mjd = self.specinfo.start_MJD[0]
self.start_lst = self.specinfo.start_lst
self.orig_start_az = self.specinfo.azimuth
self.orig_start_za = self.specinfo.zenith_ang
self.orig_ra_deg = self.specinfo.ra2000
self.orig_dec_deg = self.specinfo.dec2000
self.orig_right_ascension = float(protractor.convert(self.orig_ra_deg, \
'deg', 'hmsstr')[0].replace(':', ''))
self.orig_declination = float(protractor.convert(self.orig_dec_deg, \
'deg', 'dmsstr')[0].replace(':', ''))
l, b = sextant.equatorial_to_galactic(self.orig_ra_deg, self.orig_dec_deg, \
'deg', 'deg', J2000=True)
self.orig_galactic_longitude = float(l)
self.orig_galactic_latitude = float(b)
self.get_correct_positions()
self.file_size = int(sum([os.path.getsize(fn) for fn in fitsfns]))
self.observation_time = self.specinfo.T
self.num_samples = self.specinfo.N
self.data_size = self.num_samples * \
self.specinfo.bits_per_sample/8.0 * \
self.num_channels_per_record
self.num_samples_per_record = self.specinfo.spectra_per_subint
self.header_version = float(self.specinfo.header_version)
def __init__(self, fitsfns):
"""PSR fits Header object constructor.
"""
from formats import psrfits
super(PsrfitsData, self).__init__(fitsfns)
# Read information from files
self.specinfo = psrfits.SpectraInfo(self.fns)
self.original_file = os.path.split(sorted(self.specinfo.filenames)[0])[-1]
self.project_id = self.specinfo.project_id
self.observers = self.specinfo.observer
self.source_name = self.specinfo.source
self.center_freq = self.specinfo.fctr
self.num_channels_per_record = self.specinfo.num_channels
self.channel_bandwidth = self.specinfo.df*1000.0 # In kHz
self.sample_time = self.specinfo.dt*1e6 # In microseconds
self.sum_id = int(self.specinfo.summed_polns)
self.timestamp_mjd = self.specinfo.start_MJD[0]
self.start_lst = self.specinfo.start_lst
self.orig_start_az = self.specinfo.azimuth
self.orig_start_za = self.specinfo.zenith_ang
self.orig_ra_deg = self.specinfo.ra2000
self.orig_dec_deg = self.specinfo.dec2000
self.orig_right_ascension = float(protractor.convert(self.orig_ra_deg, \
'deg', 'hmsstr')[0].replace(':', ''))
self.orig_declination = float(protractor.convert(self.orig_dec_deg, \
'deg', 'dmsstr')[0].replace(':', ''))
l, b = sextant.equatorial_to_galactic(self.orig_ra_deg, self.orig_dec_deg, \
'deg', 'deg', J2000=True)
self.orig_galactic_longitude = float(l)
self.orig_galactic_latitude = float(b)
self.file_size = int(sum([os.path.getsize(fn) for fn in fitsfns]))
self.observation_time = self.specinfo.T
self.num_samples = self.specinfo.N
self.data_size = self.num_samples * \
self.specinfo.bits_per_sample/8.0 * \
self.num_channels_per_record
self.num_samples_per_record = self.specinfo.spectra_per_subint
self.header_version = float(self.specinfo.header_version)
def __init__(self, wappfns, beamnum):
"""WAPP Data object constructor.
"""
super(WappData, self).__init__(wappfns)
# Open wapp files, sort by offset since start of observation
cmp_offset = lambda w1,w2: cmp(w1.header['timeoff'], w2.header['timeoff'])
self.wapps = sorted([wapp.wapp(fn) for fn in wappfns], cmp=cmp_offset)
w0 = self.wapps[0]
# Check WAPP files are from the same observation
if False in [w0.header['src_name'] == w.header['src_name'] \
for w in self.wapps]:
raise ValueError("Source name is not consistent in all files.")
if False in [w0.header['obs_date'] == w.header['obs_date'] \
for w in self.wapps]:
raise ValueError("Observation date is not consistent in all files.")
if False in [w0.header['start_time'] == w.header['start_time'] \
for w in self.wapps]:
raise ValueError("Start time is not consistent in all files.")
# Divide number of samples by 2 because beams are multiplexed
# First entry is 0 because first file is start of observation
sampoffset = np.cumsum([0]+[w.number_of_samples/2 for w in self.wapps])
if False in [w.header['timeoff']==samps for (w,samps) in \
zip(self.wapps, sampoffset)]:
raise ValueError("Offset since start of observation not consistent.")
self.original_file = os.path.split(w0.filename)[-1]
matchdict = self.fnmatch(self.original_file).groupdict()
if 'beam' in matchdict:
self.beam_id = int(matchdict['beam'])
else:
self.beam_id = beamnum
self.project_id = w0.header['project_id']
self.observers = w0.header['observers']
self.start_ast = w0.header['start_ast']
self.start_lst = w0.header['start_lst']
self.source_name = w0.header['src_name']
self.center_freq = w0.header['cent_freq']
self.num_channels_per_record = w0.header['num_lags']
# ALFA band is inverted
self.channel_bandwidth = -abs(w0.header['bandwidth'] / \
float(self.num_channels_per_record))
self.num_ifs = w0.header['nifs']
self.sample_time = w0.header['samp_time'] # in micro seconds
self.sum_id = w0.header['sum']
# Compute timestamp_mjd
date = date_re.match(w0.header['obs_date']).groupdict()
time = time_re.match(w0.header['start_time']).groupdict()
dayfrac = (int(time['hour']) + \
(int(time['min']) + \
(int(time['sec']) / 60.0)) / 60.0) / 24.0
day = calendar.date_to_MJD(int(date['year']), int(date['month']), \
int(date['day']))
self.timestamp_mjd = day + dayfrac
# Combine obs_name
scan = matchdict()['scan']
self.obs_name = '.'.join([self.project_id, self.source_name, \
str(int(self.timestamp_mjd)), \
scan])
# Get beam positions
self.beam_id = beamnum
if beamnum == 7:
b = 6
else:
b = beamnum
self.orig_start_az = w0.header['alfa_az'][b]
if w0.header['start_az'] > 360.0 and self.orig_start_az < 360.0:
self.orig_start_az += 360.0
self.orig_start_za = w0.header['alfa_za'][b]
self.orig_ra_deg = w0.header['alfa_raj'][b]*15.0
self.orig_dec_deg = w0.header['alfa_decj'][b]
self.orig_right_ascension = float(protractor.convert(self.orig_ra_deg, \
'deg', 'hmsstr')[0].replace(':', ''))
self.orig_declination = float(protractor.convert(self.orig_dec_deg, \
'deg', 'dmsstr')[0].replace(':', ''))
l, b = sextant.equatorial_to_galactic(self.orig_ra_deg, self.orig_dec_deg, \
'deg', 'deg', J2000=True)
self.orig_galactic_longitude = float(l)
self.orig_galactic_latitude = float(b)
self.get_correct_positions()
def __init__(self, filenames):
self.filenames = filenames
self.num_files = len(filenames)
self.N = 0
self.user_poln = 0
self.default_poln = 0
# Initialise a few arrays
self.start_MJD = np.empty(self.num_files)
self.num_subint = np.empty(self.num_files)
self.start_subint = np.empty(self.num_files)
self.start_spec = np.empty(self.num_files)
self.num_pad = np.empty(self.num_files)
self.num_spec = np.empty(self.num_files)
# The following should default to False
self.need_scale = False
self.need_offset = False
self.need_weight = False
self.need_flipband = False
for ii, fn in enumerate(filenames):
if not is_PSRFITS(fn):
raise ValueError("File '%s' does not appear to be PSRFITS!" % fn)
# Open the PSRFITS file
hdus = pyfits.open(fn, mode='readonly')
if ii==0:
self.hdu_names = [hdu.name for hdu in hdus]
primary = hdus['PRIMARY'].header
if 'TELESCOP' not in primary.keys():
telescope = ""
else:
telescope = primary['TELESCOP']
# Quick fix for MockSpec data...
if telescope == "ARECIBO 305m":
telescope = "Arecibo"
if ii == 0:
self.telescope = telescope
else:
if telescope != self.telescope[0]:
warnings.warn("'TELESCOP' values don't match for files 0 and %d!" % ii)
self.observer = primary['OBSERVER']
self.source = primary['SRC_NAME']
self.frontend = primary['FRONTEND']
self.backend = primary['BACKEND']
self.project_id = primary['PROJID']
self.date_obs = primary['DATE-OBS']
self.poln_type = primary['FD_POLN']
self.ra_str = primary['RA']
self.dec_str = primary['DEC']
self.fctr = primary['OBSFREQ']
self.orig_num_chan = primary['OBSNCHAN']
self.orig_df = primary['OBSBW']
self.beam_FWHM = primary['BMIN']
# CHAN_DM card is not in earlier versions of PSRFITS
if 'CHAN_DM' not in primary.keys():
self.chan_dm = 0.0
else:
self.chan_dm = primary['CHAN_DM']
self.start_MJD[ii] = primary['STT_IMJD'] + (primary['STT_SMJD'] + \
primary['STT_OFFS'])/psr_utils.SECPERDAY
# Are we tracking
track = (primary['TRK_MODE'] == "TRACK")
if ii==0:
self.tracking = track
else:
if track != self.tracking:
warnings.warn("'TRK_MODE' values don't match for files 0 and %d" % ii)
# Now switch to the subint HDU header
subint = hdus['SUBINT'].header
self.dt = subint['TBIN']
self.num_channels = subint['NCHAN']
self.num_polns = subint['NPOL']
# PRESTO's 'psrfits.c' has some settings based on environ variables
envval = os.getenv("PSRFITS_POLN")
if envval is not None:
ival = int(envval)
if ((ival > -1) and (ival < self.num_polns)):
print "Using polarisation %d (from 0-%d) from PSRFITS_POLN." % \
(ival, self.num_polns-1)
self.default_poln = ival
self.user_poln = 1
self.poln_order = subint['POL_TYPE']
if subint['NCHNOFFS'] > 0:
warnings.warn("first freq channel is not 0 in file %d" % ii)
self.spectra_per_subint = subint['NSBLK']
self.bits_per_sample = subint['NBITS']
self.num_subint[ii] = subint['NAXIS2']
self.start_subint[ii] = subint['NSUBOFFS']
self.time_per_subint = self.dt * self.spectra_per_subint
# This is the MJD offset based on the starting subint number
MJDf = (self.time_per_subint * self.start_subint[ii])/psr_utils.SECPERDAY
# The start_MJD values should always be correct
self.start_MJD[ii] += MJDf
# Compute the starting spectra from the times
MJDf = self.start_MJD[ii] - self.start_MJD[0]
if MJDf < 0.0:
raise ValueError("File %d seems to be from before file 0!" % ii)
self.start_spec[ii] = (MJDf * psr_utils.SECPERDAY / self.dt + 0.5)
# Now pull stuff from the columns
subint_hdu = hdus['SUBINT']
# Identify the OFFS_SUB column number
if 'OFFS_SUB' not in subint_hdu.columns.names:
warnings.warn("Can't find the 'OFFS_SUB' column!")
else:
colnum = subint_hdu.columns.names.index('OFFS_SUB')
if ii==0:
self.offs_sub_col = colnum
elif self.offs_sub_col != colnum:
warnings.warn("'OFFS_SUB' column changes between files 0 and %d!" % ii)
# Identify the data column and the data type
if 'DATA' not in subint_hdu.columns.names:
warnings.warn("Can't find the 'DATA' column!")
else:
colnum = subint_hdu.columns.names.index('DATA')
if ii==0:
self.data_col = colnum
self.FITS_typecode = subint_hdu.columns[self.data_col].format[-1]
elif self.data_col != colnum:
warnings.warn("'DATA' column changes between files 0 and %d!" % ii)
# Telescope azimuth
if 'TEL_AZ' not in subint_hdu.columns.names:
self.azimuth = 0.0
else:
colnum = subint_hdu.columns.names.index('TEL_AZ')
if ii==0:
self.tel_az_col = colnum
self.azimuth = subint_hdu.data[0]['TEL_AZ']
# Telescope zenith angle
if 'TEL_ZEN' not in subint_hdu.columns.names:
self.zenith_ang = 0.0
else:
colnum = subint_hdu.columns.names.index('TEL_ZEN')
if ii==0:
self.tel_zen_col = colnum
self.zenith_ang = subint_hdu.data[0]['TEL_ZEN']
# Observing frequencies
if 'DAT_FREQ' not in subint_hdu.columns.names:
warnings.warn("Can't find the channel freq column, 'DAT_FREQ'!")
else:
colnum = subint_hdu.columns.names.index('DAT_FREQ')
freqs = subint_hdu.data[0]['DAT_FREQ']
if ii==0:
self.freqs_col = colnum
self.df = freqs[1]-freqs[0]
self.lo_freq = freqs[0]
self.hi_freq = freqs[-1]
# Now check that the channel spacing is the same throughout
ftmp = freqs[1:] - freqs[:-1]
if np.any((ftmp - self.df)) > 1e-7:
warnings.warn("Channel spacing changes in file %d!" % ii)
else:
ftmp = np.abs(self.df - (freqs[1]-freqs[0]))
if ftmp > 1e-7:
warnings.warn("Channel spacing between files 0 and %d!" % ii)
ftmp = np.abs(self.lo_freq-freqs[0])
if ftmp > 1e-7:
warnings.warn("Low channel changes between files 0 and %d!" % ii)
ftmp = np.abs(self.hi_freq-freqs[-1])
if ftmp > 1e-7:
warnings.warn("High channel changes between files 0 and %d!" % ii)
# Data weights
if 'DAT_WTS' not in subint_hdu.columns.names:
warnings.warn("Can't find the channel weights column, 'DAT_WTS'!")
else:
colnum = subint_hdu.columns.names.index('DAT_WTS')
if ii==0:
self.dat_wts_col = colnum
elif self.dat_wts_col != colnum:
warnings.warn("'DAT_WTS column changes between files 0 and %d!" % ii)
if np.any(subint_hdu.data[0]['DAT_WTS'] != 1.0):
self.need_weight = True
# Data offsets
if 'DAT_OFFS' not in subint_hdu.columns.names:
warnings.warn("Can't find the channel offsets column, 'DAT_OFFS'!")
else:
colnum = subint_hdu.columns.names.index('DAT_OFFS')
if ii==0:
self.dat_offs_col = colnum
elif self.dat_offs_col != colnum:
warnings.warn("'DAT_OFFS column changes between files 0 and %d!" % ii)
if np.any(subint_hdu.data[0]['DAT_OFFS'] != 0.0):
self.need_offset = True
# Data scalings
if 'DAT_SCL' not in subint_hdu.columns.names:
warnings.warn("Can't find the channel scalings column, 'DAT_SCL'!")
else:
colnum = subint_hdu.columns.names.index('DAT_SCL')
if ii==0:
self.dat_scl_col = colnum
elif self.dat_scl_col != colnum:
warnings.warn("'DAT_SCL' column changes between files 0 and %d!" % ii)
if np.any(subint_hdu.data[0]['DAT_SCL'] != 1.0):
self.need_scale = True
# Comute the samples per file and the amount of padding
# that the _previous_ file has
self.num_pad[ii] = 0
self.num_spec[ii] = self.spectra_per_subint * self.num_subint[ii]
if ii>0:
if self.start_spec[ii] > self.N: # Need padding
self.num_pad[ii-1] = self.start_spec[ii] - self.N
self.N += self.num_pad[ii-1]
self.N += self.num_spec[ii]
# Finished looping through PSRFITS files. Finalise a few things.
# Convert the position strings into degrees
self.ra2000 = protractor.convert(self.ra_str, 'hmsstr', 'deg')
self.dec2000 = protractor.convert(self.dec_str, 'dmsstr', 'deg')
# Are the polarisations summed?
if (self.poln_order=="AA+BB") or (self.poln_order=="INTEN"):
self.summed_polns = True
else:
self.summed_polns = False
# Calculate some others
self.T = self.N * self.dt
self.orig_df /= float(self.orig_num_chan)
self.samples_per_spectra = self.num_polns * self.num_channels
# Note: the following is the number of bytes that will be in
# the returned array.
if self.bits_per_sample < 8:
self.bytes_per_spectra = self.samples_per_spectra
else:
self.bytes_per_spectra = (self.bits_per_sample * self.samples_per_spectra)/8
self.samples_per_subint = self.samples_per_spectra * self.spectra_per_subint
self.bytes_per_subint = self.bytes_per_spectra * self.spectra_per_subint
# Flip the band?
if self.hi_freq < self.lo_freq:
tmp = self.hi_freq
self.hi_freq = self.lo_freq
self.lo_freq = tmp
self.df *= -1.0
self.need_flipband = True
# Compute the bandwidth
self.BW = self.num_channels * self.df
self.mjd = int(self.start_MJD[0])
self.secs = (self.start_MJD[0] % 1)*psr_utils.SECPERDAY
def __init__(self, filenames, verbose=False):
self.filenames = filenames
self.num_files = len(filenames)
self.N = 0
self.user_poln = 0
self.default_poln = 0
# Initialise a few arrays
self.start_MJD = np.empty(self.num_files)
self.num_subint = np.empty(self.num_files)
self.start_subint = np.empty(self.num_files)
self.start_spec = np.empty(self.num_files)
self.num_pad = np.empty(self.num_files)
self.num_spec = np.empty(self.num_files)
# The following should default to False
self.need_scale = False
self.need_offset = False
self.need_weight = False
self.need_flipband = False
for ii, fn in enumerate(filenames):
if verbose:
print "Reading '%s'" % fn
if not is_PSRFITS(fn):
raise ValueError("File '%s' does not appear to be PSRFITS!" %
fn)
# Open the PSRFITS file
hdus = pyfits.open(fn, mode='readonly', checksum=False)
self.hdus = hdus
if ii == 0:
self.hdu_names = [hdu.name for hdu in hdus]
primary = hdus['PRIMARY'].header
if primary.has_key('IBEAM'):
self.beam_id = primary['IBEAM']
elif hdus[1].header.has_key('BEAM'):
self.beam_id = hdus[1].header['BEAM']
else:
self.beam_id = None
if primary.has_key('TELESCOP'):
telescope = primary['TELESCOP']
# Quick fix for MockSpec data...
if telescope == "ARECIBO 305m":
telescope = "Arecibo"
else:
telescope = ""
if ii == 0:
self.telescope = telescope
else:
if telescope != self.telescope[0]:
warnings.warn(
"'TELESCOP' values don't match for files 0 and %d!" %
ii)
self.observer = primary['OBSERVER']
self.source = primary['SRC_NAME']
self.frontend = primary['FRONTEND']
self.backend = primary['BACKEND']
self.project_id = primary['PROJID']
self.date_obs = primary['DATE-OBS']
self.poln_type = primary['FD_POLN']
self.ra_str = primary['RA']
self.dec_str = primary['DEC']
self.fctr = primary['OBSFREQ']
self.orig_num_chan = primary['OBSNCHAN']
self.orig_df = primary['OBSBW']
self.beam_FWHM = primary['BMIN']
# CHAN_DM card is not in earlier versions of PSRFITS
if primary.has_key('CHAN_DM'):
self.chan_dm = primary['CHAN_DM']
else:
self.chan_dm = 0.0
self.start_MJD[ii] = primary['STT_IMJD'] + (primary['STT_SMJD'] + \
primary['STT_OFFS'])/psr_utils.SECPERDAY
# Are we tracking
track = (primary['TRK_MODE'] == "TRACK")
if ii == 0:
self.tracking = track
else:
if track != self.tracking:
warnings.warn(
"'TRK_MODE' values don't match for files 0 and %d" %
ii)
# Now switch to the subint HDU header
subint = hdus['SUBINT'].header
self.dt = subint['TBIN']
self.num_channels = subint['NCHAN']
self.num_polns = subint['NPOL']
# PRESTO's 'psrfits.c' has some settings based on environ variables
envval = os.getenv("PSRFITS_POLN")
if envval is not None:
ival = int(envval)
if ((ival > -1) and (ival < self.num_polns)):
print "Using polarisation %d (from 0-%d) from PSRFITS_POLN." % \
(ival, self.num_polns-1)
self.default_poln = ival
self.user_poln = 1
self.poln_order = subint['POL_TYPE']
if subint['NCHNOFFS'] > 0:
warnings.warn("first freq channel is not 0 in file %d" % ii)
self.spectra_per_subint = subint['NSBLK']
self.bits_per_sample = subint['NBITS']
self.num_subint[ii] = subint['NAXIS2']
self.start_subint[ii] = subint['NSUBOFFS']
self.time_per_subint = self.dt * self.spectra_per_subint
# Now pull stuff from the columns
subint_hdu = hdus['SUBINT']
# The following is a hack to read in only the first row
# from the fits file
subint_hdu.columns._shape = 1
# Identify the OFFS_SUB column number
if 'OFFS_SUB' not in subint_hdu.columns.names:
warnings.warn("Can't find the 'OFFS_SUB' column!")
else:
colnum = subint_hdu.columns.names.index('OFFS_SUB')
if ii == 0:
self.offs_sub_col = colnum
elif self.offs_sub_col != colnum:
warnings.warn(
"'OFFS_SUB' column changes between files 0 and %d!" %
ii)
# Read the OFFS_SUB column value for the 1st row
offs_sub = subint_hdu.data[0]['OFFS_SUB']
numrows = int((offs_sub - 0.5 * self.time_per_subint) / \
self.time_per_subint + 1e-7)
# Check to see if any rows have been deleted or are missing
if numrows > self.start_subint[ii]:
warnings.warn("Warning: NSUBOFFS reports %d previous rows\n" \
" but OFFS_SUB implies %s. Using OFFS_SUB.\n" \
" Will likely be able to correct for this.\n" % \
(self.start_subint[ii], numrows))
self.start_subint[ii] = numrows
# This is the MJD offset based on the starting subint number
MJDf = (self.time_per_subint *
self.start_subint[ii]) / psr_utils.SECPERDAY
# The start_MJD values should always be correct
self.start_MJD[ii] += MJDf
# Compute the starting spectra from the times
MJDf = self.start_MJD[ii] - self.start_MJD[0]
if MJDf < 0.0:
raise ValueError("File %d seems to be from before file 0!" %
ii)
self.start_spec[ii] = (MJDf * psr_utils.SECPERDAY / self.dt + 0.5)
# Identify the data column and the data type
if 'DATA' not in subint_hdu.columns.names:
warnings.warn("Can't find the 'DATA' column!")
self.FITS_typecode = 0
self.data_col = 0
else:
colnum = subint_hdu.columns.names.index('DATA')
if ii == 0:
self.data_col = colnum
self.FITS_typecode = subint_hdu.columns[
self.data_col].format[-1]
elif self.data_col != colnum:
warnings.warn(
"'DATA' column changes between files 0 and %d!" % ii)
# Telescope azimuth
if 'TEL_AZ' not in subint_hdu.columns.names:
self.azimuth = 0.0
else:
colnum = subint_hdu.columns.names.index('TEL_AZ')
if ii == 0:
self.tel_az_col = colnum
self.azimuth = subint_hdu.data[0]['TEL_AZ']
# Telescope zenith angle
if 'TEL_ZEN' not in subint_hdu.columns.names:
self.zenith_ang = 0.0
else:
colnum = subint_hdu.columns.names.index('TEL_ZEN')
if ii == 0:
self.tel_zen_col = colnum
self.zenith_ang = subint_hdu.data[0]['TEL_ZEN']
# Observing frequencies
if 'DAT_FREQ' not in subint_hdu.columns.names:
warnings.warn(
"Can't find the channel freq column, 'DAT_FREQ'!")
else:
colnum = subint_hdu.columns.names.index('DAT_FREQ')
freqs = subint_hdu.data[0]['DAT_FREQ']
if ii == 0:
self.freqs_col = colnum
self.df = freqs[1] - freqs[0]
self.lo_freq = freqs[0]
self.hi_freq = freqs[-1]
# Now check that the channel spacing is the same throughout
ftmp = freqs[1:] - freqs[:-1]
if np.any((ftmp - self.df)) > 1e-7:
warnings.warn("Channel spacing changes in file %d!" %
ii)
else:
ftmp = np.abs(self.df - (freqs[1] - freqs[0]))
if ftmp > 1e-7:
warnings.warn(
"Channel spacing between files 0 and %d!" % ii)
ftmp = np.abs(self.lo_freq - freqs[0])
if ftmp > 1e-7:
warnings.warn(
"Low channel changes between files 0 and %d!" % ii)
ftmp = np.abs(self.hi_freq - freqs[-1])
if ftmp > 1e-7:
warnings.warn(
"High channel changes between files 0 and %d!" %
ii)
# Data weights
if 'DAT_WTS' not in subint_hdu.columns.names:
warnings.warn(
"Can't find the channel weights column, 'DAT_WTS'!")
else:
colnum = subint_hdu.columns.names.index('DAT_WTS')
if ii == 0:
self.dat_wts_col = colnum
elif self.dat_wts_col != colnum:
warnings.warn(
"'DAT_WTS column changes between files 0 and %d!" % ii)
if np.any(subint_hdu.data[0]['DAT_WTS'] != 1.0):
self.need_weight = True
# Data offsets
if 'DAT_OFFS' not in subint_hdu.columns.names:
warnings.warn(
"Can't find the channel offsets column, 'DAT_OFFS'!")
else:
colnum = subint_hdu.columns.names.index('DAT_OFFS')
if ii == 0:
self.dat_offs_col = colnum
elif self.dat_offs_col != colnum:
warnings.warn(
"'DAT_OFFS column changes between files 0 and %d!" %
ii)
if np.any(subint_hdu.data[0]['DAT_OFFS'] != 0.0):
self.need_offset = True
# Data scalings
if 'DAT_SCL' not in subint_hdu.columns.names:
warnings.warn(
"Can't find the channel scalings column, 'DAT_SCL'!")
else:
colnum = subint_hdu.columns.names.index('DAT_SCL')
if ii == 0:
self.dat_scl_col = colnum
elif self.dat_scl_col != colnum:
warnings.warn(
"'DAT_SCL' column changes between files 0 and %d!" %
ii)
if np.any(subint_hdu.data[0]['DAT_SCL'] != 1.0):
self.need_scale = True
# Comute the samples per file and the amount of padding
# that the _previous_ file has
self.num_pad[ii] = 0
self.num_spec[ii] = self.spectra_per_subint * self.num_subint[ii]
if ii > 0:
if self.start_spec[ii] > self.N: # Need padding
self.num_pad[ii - 1] = self.start_spec[ii] - self.N
self.N += self.num_pad[ii - 1]
self.N += self.num_spec[ii]
# Finished looping through PSRFITS files. Finalise a few things.
# Convert the position strings into degrees
self.ra2000 = protractor.convert(self.ra_str, 'hmsstr', 'deg')
self.dec2000 = protractor.convert(self.dec_str, 'dmsstr', 'deg')
# Are the polarisations summed?
if (self.poln_order == "AA+BB") or (self.poln_order == "INTEN"):
self.summed_polns = True
else:
self.summed_polns = False
# Calculate some others
self.T = self.N * self.dt
self.orig_df /= float(self.orig_num_chan)
self.samples_per_spectra = self.num_polns * self.num_channels
# Note: the following is the number of bytes that will be in
# the returned array.
if self.bits_per_sample < 8:
self.bytes_per_spectra = self.samples_per_spectra
else:
self.bytes_per_spectra = (self.bits_per_sample *
self.samples_per_spectra) / 8
self.samples_per_subint = self.samples_per_spectra * self.spectra_per_subint
self.bytes_per_subint = self.bytes_per_spectra * self.spectra_per_subint
# Flip the band?
if self.hi_freq < self.lo_freq:
tmp = self.hi_freq
self.hi_freq = self.lo_freq
self.lo_freq = tmp
self.df *= -1.0
self.need_flipband = True
# Compute the bandwidth
self.BW = self.num_channels * self.df
# A few extras
self.start_lst = primary['STT_LST']
# Close the psrfits file
hdus.close()
def __init__(self, wappfns, beamnum):
"""WAPP Data object constructor.
"""
super(WappData, self).__init__(wappfns)
# Open wapp files, sort by offset since start of observation
cmp_offset = lambda w1, w2: cmp(w1.header['timeoff'], w2.header[
'timeoff'])
self.wapps = sorted([wapp.wapp(fn) for fn in wappfns], cmp=cmp_offset)
w0 = self.wapps[0]
# Check WAPP files are from the same observation
if False in [w0.header['src_name'] == w.header['src_name'] \
for w in self.wapps]:
raise ValueError("Source name is not consistent in all files.")
if False in [w0.header['obs_date'] == w.header['obs_date'] \
for w in self.wapps]:
raise ValueError(
"Observation date is not consistent in all files.")
if False in [w0.header['start_time'] == w.header['start_time'] \
for w in self.wapps]:
raise ValueError("Start time is not consistent in all files.")
# Divide number of samples by 2 because beams are multiplexed
# First entry is 0 because first file is start of observation
sampoffset = np.cumsum([0] +
[w.number_of_samples / 2 for w in self.wapps])
if False in [w.header['timeoff']==samps for (w,samps) in \
zip(self.wapps, sampoffset)]:
raise ValueError(
"Offset since start of observation not consistent.")
self.original_file = os.path.split(w0.filename)[-1]
matchdict = self.fnmatch(self.original_file).groupdict()
if 'beam' in matchdict:
self.beam_id = int(matchdict['beam'])
else:
self.beam_id = beamnum
self.project_id = w0.header['project_id']
self.observers = w0.header['observers']
self.start_ast = w0.header['start_ast']
self.start_lst = w0.header['start_lst']
self.source_name = w0.header['src_name']
self.center_freq = w0.header['cent_freq']
self.num_channels_per_record = w0.header['num_lags']
# ALFA band is inverted
self.channel_bandwidth = -abs(w0.header['bandwidth'] / \
float(self.num_channels_per_record))
self.num_ifs = w0.header['nifs']
self.sample_time = w0.header['samp_time'] # in micro seconds
self.sum_id = w0.header['sum']
# Compute timestamp_mjd
date = date_re.match(w0.header['obs_date']).groupdict()
time = time_re.match(w0.header['start_time']).groupdict()
dayfrac = (int(time['hour']) + \
(int(time['min']) + \
(int(time['sec']) / 60.0)) / 60.0) / 24.0
day = calendar.date_to_MJD(int(date['year']), int(date['month']), \
int(date['day']))
self.timestamp_mjd = day + dayfrac
# Combine obs_name
scan = matchdict()['scan']
self.obs_name = '.'.join([self.project_id, self.source_name, \
str(int(self.timestamp_mjd)), \
scan])
# Get beam positions
self.beam_id = beamnum
if beamnum == 7:
b = 6
else:
b = beamnum
self.orig_start_az = w0.header['alfa_az'][b]
if w0.header['start_az'] > 360.0 and self.orig_start_az < 360.0:
self.orig_start_az += 360.0
self.orig_start_za = w0.header['alfa_za'][b]
self.orig_ra_deg = w0.header['alfa_raj'][b] * 15.0
self.orig_dec_deg = w0.header['alfa_decj'][b]
self.orig_right_ascension = float(protractor.convert(self.orig_ra_deg, \
'deg', 'hmsstr')[0].replace(':', ''))
self.orig_declination = float(protractor.convert(self.orig_dec_deg, \
'deg', 'dmsstr')[0].replace(':', ''))
l, b = sextant.equatorial_to_galactic(self.orig_ra_deg, self.orig_dec_deg, \
'deg', 'deg', J2000=True)
self.orig_galactic_longitude = float(l)
self.orig_galactic_latitude = float(b)
self.get_correct_positions()
def __init__(self, filenames, verbose=False):
self.filenames = filenames
self.num_files = len(filenames)
self.N = 0
self.user_poln = 0
self.default_poln = 0
# Initialise a few arrays
self.start_MJD = np.empty(self.num_files)
self.num_subint = np.empty(self.num_files)
self.start_subint = np.empty(self.num_files)
self.start_spec = np.empty(self.num_files)
self.num_pad = np.empty(self.num_files)
self.num_spec = np.empty(self.num_files)
# The following should default to False
self.need_scale = False
self.need_offset = False
self.need_weight = False
self.need_flipband = False
for ii, fn in enumerate(filenames):
if verbose:
print "Reading '%s'" % fn
if not is_PSRFITS(fn):
raise ValueError("File '%s' does not appear to be PSRFITS!" % fn)
# Open the PSRFITS file
hdus = pyfits.open(fn, mode="readonly", checksum=False)
self.hdus = hdus
if ii == 0:
self.hdu_names = [hdu.name for hdu in hdus]
primary = hdus["PRIMARY"].header
if primary.has_key("IBEAM"):
self.beam_id = primary["IBEAM"]
elif hdus[1].header.has_key("BEAM"):
self.beam_id = hdus[1].header["BEAM"]
else:
self.beam_id = None
if primary.has_key("TELESCOP"):
telescope = primary["TELESCOP"]
# Quick fix for MockSpec data...
if telescope == "ARECIBO 305m":
telescope = "Arecibo"
else:
telescope = ""
if ii == 0:
self.telescope = telescope
else:
if telescope != self.telescope[0]:
warnings.warn("'TELESCOP' values don't match for files 0 and %d!" % ii)
self.observer = primary["OBSERVER"]
self.source = primary["SRC_NAME"]
self.frontend = primary["FRONTEND"]
self.backend = primary["BACKEND"]
self.project_id = primary["PROJID"]
self.date_obs = primary["DATE-OBS"]
self.poln_type = primary["FD_POLN"]
self.ra_str = primary["RA"]
self.dec_str = primary["DEC"]
self.fctr = primary["OBSFREQ"]
self.orig_num_chan = primary["OBSNCHAN"]
self.orig_df = primary["OBSBW"]
self.beam_FWHM = primary["BMIN"]
# CHAN_DM card is not in earlier versions of PSRFITS
if primary.has_key("CHAN_DM"):
self.chan_dm = primary["CHAN_DM"]
else:
self.chan_dm = 0.0
self.start_MJD[ii] = primary["STT_IMJD"] + (primary["STT_SMJD"] + primary["STT_OFFS"]) / psr_utils.SECPERDAY
# Are we tracking
track = primary["TRK_MODE"] == "TRACK"
if ii == 0:
self.tracking = track
else:
if track != self.tracking:
warnings.warn("'TRK_MODE' values don't match for files 0 and %d" % ii)
# Now switch to the subint HDU header
subint = hdus["SUBINT"].header
self.dt = subint["TBIN"]
self.num_channels = subint["NCHAN"]
self.num_polns = subint["NPOL"]
# PRESTO's 'psrfits.c' has some settings based on environ variables
envval = os.getenv("PSRFITS_POLN")
if envval is not None:
ival = int(envval)
if (ival > -1) and (ival < self.num_polns):
print "Using polarisation %d (from 0-%d) from PSRFITS_POLN." % (ival, self.num_polns - 1)
self.default_poln = ival
self.user_poln = 1
self.poln_order = subint["POL_TYPE"]
if subint["NCHNOFFS"] > 0:
warnings.warn("first freq channel is not 0 in file %d" % ii)
self.spectra_per_subint = subint["NSBLK"]
self.bits_per_sample = subint["NBITS"]
self.num_subint[ii] = subint["NAXIS2"]
self.start_subint[ii] = subint["NSUBOFFS"]
self.time_per_subint = self.dt * self.spectra_per_subint
# Now pull stuff from the columns
subint_hdu = hdus["SUBINT"]
# The following is a hack to read in only the first row
# from the fits file
subint_hdu.columns._shape = 1
# Identify the OFFS_SUB column number
if "OFFS_SUB" not in subint_hdu.columns.names:
warnings.warn("Can't find the 'OFFS_SUB' column!")
else:
colnum = subint_hdu.columns.names.index("OFFS_SUB")
if ii == 0:
self.offs_sub_col = colnum
elif self.offs_sub_col != colnum:
warnings.warn("'OFFS_SUB' column changes between files 0 and %d!" % ii)
# Read the OFFS_SUB column value for the 1st row
offs_sub = subint_hdu.data[0]["OFFS_SUB"]
numrows = int((offs_sub - 0.5 * self.time_per_subint) / self.time_per_subint + 1e-7)
# Check to see if any rows have been deleted or are missing
if numrows > self.start_subint[ii]:
warnings.warn(
"Warning: NSUBOFFS reports %d previous rows\n"
" but OFFS_SUB implies %s. Using OFFS_SUB.\n"
" Will likely be able to correct for this.\n" % (self.start_subint[ii], numrows)
)
self.start_subint[ii] = numrows
# This is the MJD offset based on the starting subint number
MJDf = (self.time_per_subint * self.start_subint[ii]) / psr_utils.SECPERDAY
# The start_MJD values should always be correct
self.start_MJD[ii] += MJDf
# Compute the starting spectra from the times
MJDf = self.start_MJD[ii] - self.start_MJD[0]
if MJDf < 0.0:
raise ValueError("File %d seems to be from before file 0!" % ii)
self.start_spec[ii] = MJDf * psr_utils.SECPERDAY / self.dt + 0.5
# Identify the data column and the data type
if "DATA" not in subint_hdu.columns.names:
warnings.warn("Can't find the 'DATA' column!")
self.FITS_typecode = 0
self.data_col = 0
else:
colnum = subint_hdu.columns.names.index("DATA")
if ii == 0:
self.data_col = colnum
self.FITS_typecode = subint_hdu.columns[self.data_col].format[-1]
elif self.data_col != colnum:
warnings.warn("'DATA' column changes between files 0 and %d!" % ii)
# Telescope azimuth
if "TEL_AZ" not in subint_hdu.columns.names:
self.azimuth = 0.0
else:
colnum = subint_hdu.columns.names.index("TEL_AZ")
if ii == 0:
self.tel_az_col = colnum
self.azimuth = subint_hdu.data[0]["TEL_AZ"]
# Telescope zenith angle
if "TEL_ZEN" not in subint_hdu.columns.names:
self.zenith_ang = 0.0
else:
colnum = subint_hdu.columns.names.index("TEL_ZEN")
if ii == 0:
self.tel_zen_col = colnum
self.zenith_ang = subint_hdu.data[0]["TEL_ZEN"]
# Observing frequencies
if "DAT_FREQ" not in subint_hdu.columns.names:
warnings.warn("Can't find the channel freq column, 'DAT_FREQ'!")
else:
colnum = subint_hdu.columns.names.index("DAT_FREQ")
freqs = subint_hdu.data[0]["DAT_FREQ"]
if ii == 0:
self.freqs_col = colnum
self.df = freqs[1] - freqs[0]
self.lo_freq = freqs[0]
self.hi_freq = freqs[-1]
# Now check that the channel spacing is the same throughout
ftmp = freqs[1:] - freqs[:-1]
if np.any((ftmp - self.df)) > 1e-7:
warnings.warn("Channel spacing changes in file %d!" % ii)
else:
ftmp = np.abs(self.df - (freqs[1] - freqs[0]))
if ftmp > 1e-7:
warnings.warn("Channel spacing between files 0 and %d!" % ii)
ftmp = np.abs(self.lo_freq - freqs[0])
if ftmp > 1e-7:
warnings.warn("Low channel changes between files 0 and %d!" % ii)
ftmp = np.abs(self.hi_freq - freqs[-1])
if ftmp > 1e-7:
warnings.warn("High channel changes between files 0 and %d!" % ii)
# Data weights
if "DAT_WTS" not in subint_hdu.columns.names:
warnings.warn("Can't find the channel weights column, 'DAT_WTS'!")
else:
colnum = subint_hdu.columns.names.index("DAT_WTS")
if ii == 0:
self.dat_wts_col = colnum
elif self.dat_wts_col != colnum:
warnings.warn("'DAT_WTS column changes between files 0 and %d!" % ii)
if np.any(subint_hdu.data[0]["DAT_WTS"] != 1.0):
self.need_weight = True
# Data offsets
if "DAT_OFFS" not in subint_hdu.columns.names:
warnings.warn("Can't find the channel offsets column, 'DAT_OFFS'!")
else:
colnum = subint_hdu.columns.names.index("DAT_OFFS")
if ii == 0:
self.dat_offs_col = colnum
elif self.dat_offs_col != colnum:
warnings.warn("'DAT_OFFS column changes between files 0 and %d!" % ii)
if np.any(subint_hdu.data[0]["DAT_OFFS"] != 0.0):
self.need_offset = True
# Data scalings
if "DAT_SCL" not in subint_hdu.columns.names:
warnings.warn("Can't find the channel scalings column, 'DAT_SCL'!")
else:
colnum = subint_hdu.columns.names.index("DAT_SCL")
if ii == 0:
self.dat_scl_col = colnum
elif self.dat_scl_col != colnum:
warnings.warn("'DAT_SCL' column changes between files 0 and %d!" % ii)
if np.any(subint_hdu.data[0]["DAT_SCL"] != 1.0):
self.need_scale = True
# Comute the samples per file and the amount of padding
# that the _previous_ file has
self.num_pad[ii] = 0
self.num_spec[ii] = self.spectra_per_subint * self.num_subint[ii]
if ii > 0:
if self.start_spec[ii] > self.N: # Need padding
self.num_pad[ii - 1] = self.start_spec[ii] - self.N
self.N += self.num_pad[ii - 1]
self.N += self.num_spec[ii]
# Finished looping through PSRFITS files. Finalise a few things.
# Convert the position strings into degrees
self.ra2000 = protractor.convert(self.ra_str, "hmsstr", "deg")
self.dec2000 = protractor.convert(self.dec_str, "dmsstr", "deg")
# Are the polarisations summed?
if (self.poln_order == "AA+BB") or (self.poln_order == "INTEN"):
self.summed_polns = True
else:
self.summed_polns = False
# Calculate some others
self.T = self.N * self.dt
self.orig_df /= float(self.orig_num_chan)
self.samples_per_spectra = self.num_polns * self.num_channels
# Note: the following is the number of bytes that will be in
# the returned array.
if self.bits_per_sample < 8:
self.bytes_per_spectra = self.samples_per_spectra
else:
self.bytes_per_spectra = (self.bits_per_sample * self.samples_per_spectra) / 8
self.samples_per_subint = self.samples_per_spectra * self.spectra_per_subint
self.bytes_per_subint = self.bytes_per_spectra * self.spectra_per_subint
# Flip the band?
if self.hi_freq < self.lo_freq:
tmp = self.hi_freq
self.hi_freq = self.lo_freq
self.lo_freq = tmp
self.df *= -1.0
self.need_flipband = True
# Compute the bandwidth
self.BW = self.num_channels * self.df
# A few extras
self.start_lst = primary["STT_LST"]
# Close the psrfits file
hdus.close()
