def updateObsTable(image, msName, minbl, maxbl, aswvl, usedCounts, visCounts,
minTime, maxTime, totTime):
obstab = pt.table(image.name() + "/LOFAR_OBSERVATION",
readonly=False,
ack=False)
oritab = pt.table(image.name() + "/LOFAR_ORIGIN", ack=False)
minfreq = pt.taql("calc min([select FREQUENCY_MIN from '" + oritab.name() +
"'])")
maxfreq = pt.taql("calc max([select FREQUENCY_MAX from '" + oritab.name() +
"'])")
obstab.putcell("OBSERVATION_FREQUENCY_MIN", 0, minfreq[0])
obstab.putcell("OBSERVATION_FREQUENCY_MAX", 0, maxfreq[0])
obstab.putcell("OBSERVATION_FREQUENCY_CENTER", 0,
(minfreq[0] + maxfreq[0]) / 2)
obstab.putcell("OBSERVATION_INTEGRATION_TIME", 0, totTime)
obstab.putcell("OBSERVATION_START", 0, minTime)
obstab.putcell("OBSERVATION_END", 0, maxTime)
obstab.putcell("TIME_RANGE", 0, (minTime, maxTime))
obstab.putcell("FILENAME", 0, os.path.basename(image.name()))
obstab.putcell("FILETYPE", 0, "sky")
pt.taql("update '" + obstab.name() + "' set FILEDATE = mjd(date()), " +
"RELEASE_DATE = mjd(date()+365)")
# Determine minimum and maximum baseline length
# If needed, convert from wavelengths to meters.
mstab = pt.table(msName, ack=False)
if aswvl:
minbl *= 2.99792e8 / maxfreq[0]
maxbl *= 2.99792e8 / minfreq[0]
if minbl <= 0:
mbl = pt.taql("calc sqrt(min([select sumsqr(UVW[:2]) from " + msName +
"]))")
minbl = max(mbl[0], abs(minbl))
if maxbl <= 0:
mbl = pt.taql("calc sqrt(max([select sumsqr(UVW[:2]) from " + msName +
"]))")
if maxbl == 0:
maxbl = mbl[0]
else:
maxbl = min(mbl[0], abs(maxbl))
mstab.close()
# Add and fill a few extra columns.
col1 = pt.makescacoldesc("MIN_BASELINE_LENGTH", 0, valuetype='double')
col2 = pt.makescacoldesc("MAX_BASELINE_LENGTH", 0, valuetype='double')
col3 = pt.makearrcoldesc("NVIS_USED", 0, valuetype='int')
col4 = pt.makearrcoldesc("NVIS_TOTAL", 0, valuetype='int')
obstab.addcols(pt.maketabdesc([col1, col2, col3, col4]))
obstab.putcolkeyword("MIN_BASELINE_LENGTH", "QuantumUnits", ["m"])
obstab.putcolkeyword("MAX_BASELINE_LENGTH", "QuantumUnits", ["m"])
obstab.putcell("MIN_BASELINE_LENGTH", 0, minbl)
obstab.putcell("MAX_BASELINE_LENGTH", 0, maxbl)
# Get sum for all MSs.
tusedCounts = usedCounts.sum(axis=0)
tvisCounts = visCounts.sum(axis=0)
obstab.putcell("NVIS_USED", 0, tusedCounts)
obstab.putcell("NVIS_TOTAL", 0, tvisCounts)
obstab.close()
oritab.close()
print "Updated subtable LOFAR_OBSERVATION"
def updateObsTable (image, msName, minbl, maxbl, aswvl,
usedCounts, visCounts, minTime, maxTime, totTime):
obstab = pt.table (image.name() + "/LOFAR_OBSERVATION", readonly=False,
ack=False)
oritab = pt.table (image.name() + "/LOFAR_ORIGIN", ack=False)
minfreq = pt.taql ("calc min([select FREQUENCY_MIN from '" +
oritab.name() + "'])")
maxfreq = pt.taql ("calc max([select FREQUENCY_MAX from '" +
oritab.name() + "'])")
obstab.putcell ("OBSERVATION_FREQUENCY_MIN", 0, minfreq[0]);
obstab.putcell ("OBSERVATION_FREQUENCY_MAX", 0, maxfreq[0]);
obstab.putcell ("OBSERVATION_FREQUENCY_CENTER", 0, (minfreq[0]+maxfreq[0])/2);
obstab.putcell ("OBSERVATION_INTEGRATION_TIME", 0, totTime);
obstab.putcell ("OBSERVATION_START", 0, minTime);
obstab.putcell ("OBSERVATION_END", 0, maxTime);
obstab.putcell ("TIME_RANGE", 0, (minTime, maxTime));
obstab.putcell ("FILENAME", 0, os.path.basename(image.name()))
obstab.putcell ("FILETYPE", 0, "sky")
pt.taql ("update '" + obstab.name() + "' set FILEDATE = mjd(date()), " +
"RELEASE_DATE = mjd(date()+365)")
# Determine minimum and maximum baseline length
# If needed, convert from wavelengths to meters.
mstab = pt.table(msName, ack=False)
if aswvl:
minbl *= 2.99792e8 / maxfreq[0]
maxbl *= 2.99792e8 / minfreq[0]
if minbl <= 0:
mbl = pt.taql ("calc sqrt(min([select sumsqr(UVW[:2]) from " + msName + "]))")
minbl = max(mbl[0], abs(minbl))
if maxbl <= 0:
mbl = pt.taql ("calc sqrt(max([select sumsqr(UVW[:2]) from " + msName + "]))")
if maxbl == 0:
maxbl = mbl[0]
else:
maxbl = min(mbl[0], abs(maxbl))
mstab.close()
# Add and fill a few extra columns.
col1 = pt.makescacoldesc ("MIN_BASELINE_LENGTH", 0, valuetype='double')
col2 = pt.makescacoldesc ("MAX_BASELINE_LENGTH", 0, valuetype='double')
col3 = pt.makearrcoldesc ("NVIS_USED", 0, valuetype='int')
col4 = pt.makearrcoldesc ("NVIS_TOTAL", 0, valuetype='int')
obstab.addcols (pt.maketabdesc ([col1, col2, col3, col4]))
obstab.putcolkeyword ("MIN_BASELINE_LENGTH", "QuantumUnits", ["m"])
obstab.putcolkeyword ("MAX_BASELINE_LENGTH", "QuantumUnits", ["m"])
obstab.putcell ("MIN_BASELINE_LENGTH", 0, minbl)
obstab.putcell ("MAX_BASELINE_LENGTH", 0, maxbl)
# Get sum for all MSs.
tusedCounts = usedCounts.sum (axis=0)
tvisCounts = visCounts.sum (axis=0)
obstab.putcell ("NVIS_USED", 0, tusedCounts)
obstab.putcell ("NVIS_TOTAL", 0, tvisCounts)
obstab.close()
oritab.close()
print "Updated subtable LOFAR_OBSERVATION"
def main(options):
ms = options.ms
if ms == '':
print 'Error: you have to specify an input MS, use -h for help'
return
cols = options.cols
incol = options.incol
t = pt.table(ms, readonly=False, ack=False)
for col in cols.split(','):
if col not in t.colnames():
logging.info('Adding the output column '+col+' to '+ms+'.')
if incol == '':
incol = 'DATA'
update = False
else:
update = True
coldmi = t.getdminfo(incol)
coldmi['NAME'] = col
t.addcols(pt.maketabdesc(pt.makearrcoldesc(col, 0., valuetype=t.col(incol).datatype(), shape=numpy.array(t.getcell(incol,0)).shape)), coldmi)
if update:
logging.warning('Setting '+col+' = '+incol+'.')
t.putcol(col, t.getcol(incol))
else:
logging.warning('Column '+col+' already exists.')
t.close()
def main(options):
inms = options.inms
if inms == '':
print 'Error: you have to specify an input MS, use -h for help'
return
outcol = options.outcol
t = pt.table(inms, readonly=False, ack=True)
if outcol not in t.colnames():
print 'Adding the output column', outcol, 'to', inms
coldmi = t.getdminfo('DATA')
coldmi['NAME'] = outcol
t.addcols(
pt.maketabdesc(
pt.makearrcoldesc(outcol,
0.,
valuetype='complex',
shape=numpy.array(t.getcell('DATA',
0)).shape)),
coldmi)
data = t.getcol('DATA')
t.putcol(outcol, data)
else:
print outcol, 'column already exist'
def main(options):
cI = numpy.complex(0.,1.)
inms = options.inms
if inms == '':
print 'Error: you have to specify an input MS, use -h for help'
return
column = options.column
outcol = options.outcol
t = pt.table(inms, readonly=False, ack=True)
if outcol not in t.colnames():
print 'Adding output column',outcol,'to',inms
coldmi = t.getdminfo(column)
coldmi['NAME'] = outcol
t.addcols(pt.maketabdesc(pt.makearrcoldesc(outcol, 0., valuetype='complex', shape=numpy.array(t.getcell(column,0)).shape)), coldmi)
print 'Reading input column'
data = t.getcol(column)
print 'Computing output column'
outdata = numpy.transpose(numpy.array([
data[:,:,0]-cI*data[:,:,1]+cI*data[:,:,2]+data[:,:,3],
data[:,:,0]+cI*data[:,:,1]+cI*data[:,:,2]-data[:,:,3],
data[:,:,0]-cI*data[:,:,1]-cI*data[:,:,2]-data[:,:,3],
data[:,:,0]+cI*data[:,:,1]-cI*data[:,:,2]+data[:,:,3]]),
(1,2,0))
print 'Finishing up'
t.putcol(outcol, outdata)
def create_ms(msname, input_fits, ms_dict):
""" create empty MS """
x.sh(return_simms_string(msname, input_fits, **ms_dict))
# set STATION names to same as NAME col
antt = pt.table(os.path.join(msname, 'ANTENNA'), readonly=False, ack=False)
antt.putcol('STATION', antt.getcol('NAME'))
antt.close()
# set FIELD name to input filename (minus extension)
fieldtab = pt.table(os.path.join(msname, 'FIELD'),
readonly=False,
ack=False)
fieldtab.putcol('NAME', input_fits.split('/')[-1].split('.')[0])
fieldtab.close()
# set SOURCE name to input filename (minus extension)
srctab = pt.table(os.path.join(msname, 'SOURCE'),
readonly=False,
ack=False)
srctab.putcol('NAME', input_fits.split('/')[-1].split('.')[0])
srctab.close()
# set SPW name to input filename (minus extension)
spwtab = pt.table(os.path.join(msname, 'SPECTRAL_WINDOW'),
readonly=False,
ack=False)
spwtab.putcol('NAME', input_fits.split('/')[-1].split('.')[0])
spwtab.close()
# INI: Add WEIGHT_SPECTRUM and SIGMA_SPECTRUM columns to the MS
tab = pt.table(msname, readonly=False)
data = tab.getcol('DATA')
tab.addcols(
pt.makearrcoldesc('SIGMA_SPECTRUM',
value=1.0,
shape=[data.shape[1], data.shape[2]],
valuetype='float'))
tab.addcols(
pt.makearrcoldesc('WEIGHT_SPECTRUM',
value=1.0,
shape=[data.shape[1], data.shape[2]],
valuetype='float'))
tab.close()
info('Measurement Set %s created ' % msname)
def addcol(ms, incol, outcol):
if outcol not in ms.colnames():
logging.info('Adding column: '+outcol)
coldmi = ms.getdminfo(incol)
coldmi['NAME'] = outcol
datatype = ms.col(incol).datatype()
ms.addcols(pt.maketabdesc(pt.makearrcoldesc(outcol, 0., valuetype=datatype, shape=np.array(ms.getcell(incol,0)).shape)), coldmi)
if outcol != incol:
# copy columns val
logging.info('Set '+outcol+'='+incol)
ms.putcol(outcol, ms.getcol(incol))
def addcol(msname='$MS',colname=None,shape=None,
data_desc_type='array',valuetype=None,init_with=0,**kw):
""" add column to MS
msanme : MS to add colmn to
colname : column name
shape : shape
valuetype : data type
data_desc_type : 'scalar' for scalar elements and array for 'array' elements
init_with : value to initialise the column with
"""
msname, colname = interpolate_locals('msname colname')
tab = pyrap.tables.table(msname,readonly=False)
try:
tab.getcol(colname)
info('Column already exists')
except RuntimeError:
info('Attempting to add %s column to %s'%(colname,msname))
from pyrap.tables import maketabdesc
valuetype = valuetype or 'complex'
if shape is None:
dshape = list(tab.getcol('DATA').shape)
shape = dshape[1:]
if data_desc_type=='array':
from pyrap.tables import makearrcoldesc
coldmi = tab.getdminfo('DATA') # God forbid this (or the TIME) column doesn't exist
coldmi['NAME'] = colname.lower()
tab.addcols(maketabdesc(makearrcoldesc(colname,init_with,shape=shape,valuetype=valuetype)),coldmi)
elif data_desc_type=='scalar':
from pyrap.tables import makescacoldesc
coldmi = tab.getdminfo('TIME')
coldmi['NAME'] = colname.lower()
tab.addcols(maketabdesc(makescacoldesc(colname,init_with,valuetype=valuetype)),coldmi)
info('Column added successfuly.')
if init_with:
nrows = dshape[0]
rowchunk = nrows//10 if nrows > 1000 else nrows
for row0 in range(0,nrows,rowchunk):
nr = min(rowchunk,nrows-row0)
dshape[0] = nr
tab.putcol(colname,numpy.ones(dshape,dtype=valuetype)*init_with,row0,nr)
tab.close()
def main(options):
inms = options.inms
if inms == '':
print 'Error: you have to specify an input MS, use -h for help'
return
outcol = options.outcol
t = pt.table(inms, readonly=False, ack=True)
if outcol not in t.colnames():
print 'Adding the output column',outcol,'to',inms
coldmi = t.getdminfo('WEIGHT_SPECTRUM')
coldmi['NAME'] = outcol
t.addcols(pt.maketabdesc(pt.makearrcoldesc(outcol, 0., valuetype='float', shape=numpy.array(t.getcell('WEIGHT_SPECTRUM',0)).shape)), coldmi)
data = t.getcol('WEIGHT_SPECTRUM')
t.putcol(outcol, data)
else:
print outcol, 'column already exist'
def export_ms(hdf_file, ms_file, verbosity=1):
""" Convert an HDF file to MS
:param hdf_file: Input HDF-MS filename
:param ms_file: Output MS filename
TODO: Get this working properly.
"""
pp = PrintLog(verbosity=verbosity)
hdul = IdiHdulist(verbosity=1)
hdul.read_hdf("testms.h5")
main_hdu = hdul["MAIN"]
vdict = {
'float32': 'float',
'float64': 'double',
'complex64': 'complex',
'complex128': 'dcomplex',
'int32': 'int',
'uint32': 'uint',
'str': 'string',
'bool': 'bool'
}
col_descs = []
for col, cdata in main_hdu.data.items():
col = str(col)
pp.pp("%16s %s %s" % (col, cdata.shape, cdata.dtype))
if cdata.ndim == 1:
vt = vdict[str(cdata.dtype)]
cdesc = pt.makescacoldesc(col, cdata[0], valuetype=vt)
else:
cdesc = pt.makearrcoldesc(col, cdata[0], valuetype=vt)
col_descs.append(cdesc)
tdesc = pt.maketabdesc(col_descs)
t = pt.table("table.ms", tdesc, nrow=main_hdu.n_rows)
def main(options):
cI = numpy.complex(0., 1.)
inms = options.inms
if inms == '':
print 'Error: you have to specify an input MS, use -h for help'
return
column = options.column
outcol = options.outcol
t = pt.table(inms, readonly=False, ack=True)
if outcol not in t.colnames():
print 'Adding output column', outcol, 'to', inms
coldmi = t.getdminfo(column)
coldmi['NAME'] = outcol
t.addcols(
pt.maketabdesc(
pt.makearrcoldesc(outcol,
0.,
valuetype='complex',
shape=numpy.array(t.getcell(column,
0)).shape)),
coldmi)
print 'Reading input column'
data = t.getcol(column)
print 'Computing output column'
outdata = numpy.transpose(
numpy.array([
data[:, :, 0] - cI * data[:, :, 1] + cI * data[:, :, 2] +
data[:, :, 3], data[:, :, 0] + cI * data[:, :, 1] +
cI * data[:, :, 2] - data[:, :, 3], data[:, :, 0] -
cI * data[:, :, 1] - cI * data[:, :, 2] - data[:, :, 3],
data[:, :, 0] + cI * data[:, :, 1] - cI * data[:, :, 2] +
data[:, :, 3]
]), (1, 2, 0))
print 'Finishing up'
t.putcol(outcol, outdata)
def export_ms(hdf_file, ms_file, verbosity=1):
""" Convert an HDF file to MS
:param hdf_file: Input HDF-MS filename
:param ms_file: Output MS filename
TODO: Get this working properly.
"""
pp = PrintLog(verbosity=verbosity)
hdul = IdiHdulist(verbosity=1)
hdul.read_hdf("testms.h5")
main_hdu = hdul["MAIN"]
vdict = {'float32' : 'float',
'float64' : 'double',
'complex64' : 'complex',
'complex128' : 'dcomplex',
'int32' : 'int',
'uint32' : 'uint',
'str' : 'string',
'bool' : 'bool'
}
col_descs = []
for col, cdata in main_hdu.data.items():
col = str(col)
pp.pp("%16s %s %s" % (col, cdata.shape, cdata.dtype))
if cdata.ndim == 1:
vt = vdict[str(cdata.dtype)]
cdesc = pt.makescacoldesc(col, cdata[0], valuetype=vt)
else:
cdesc = pt.makearrcoldesc(col, cdata[0], valuetype=vt)
col_descs.append(cdesc)
tdesc = pt.maketabdesc(col_descs)
t = pt.table("table.ms", tdesc, nrow=main_hdu.n_rows)
def addcol(msname,
colname=None,
shape=None,
data_desc_type='array',
valuetype=None,
init_with=None,
coldesc=None,
coldmi=None,
clone='DATA',
rowchunk=None,
**kw):
""" Add column to MS
msanme : MS to add colmn to
colname : column name
shape : shape
valuetype : data type
data_desc_type : 'scalar' for scalar elements and array for 'array' elements
init_with : value to initialise the column with
"""
tab = table(msname, readonly=False)
if colname in tab.colnames():
print('Column already exists')
return 'exists'
print('Attempting to add %s column to %s' % (colname, msname))
valuetype = valuetype or 'complex'
if coldesc:
data_desc = coldesc
shape = coldesc['shape']
elif shape:
data_desc = maketabdesc(
makearrcoldesc(colname,
init_with,
shape=shape,
valuetype=valuetype))
elif valuetype == 'scalar':
data_desc = maketabdesc(
makearrcoldesc(colname, init_with, valuetype=valuetype))
elif clone:
element = tab.getcell(clone, 0)
try:
shape = element.shape
data_desc = maketabdesc(
makearrcoldesc(colname,
element.flatten()[0],
shape=shape,
valuetype=valuetype))
except AttributeError:
shape = []
data_desc = maketabdesc(
makearrcoldesc(colname, element, valuetype=valuetype))
colinfo = [data_desc, coldmi] if coldmi else [data_desc]
tab.addcols(*colinfo)
print('Column added successfuly.')
if init_with is None:
tab.close()
return 'added'
else:
spwids = set(tab.getcol('DATA_DESC_ID'))
for spw in spwids:
print('Initialising {0:s} column with {1}. DDID is {2:d}'.format(
colname, init_with, spw))
tab_spw = tab.query('DATA_DESC_ID=={0:d}'.format(spw))
nrows = tab_spw.nrows()
rowchunk = rowchunk or nrows / 10
dshape = [0] + [a for a in shape]
for row0 in range(0, nrows, rowchunk):
nr = min(rowchunk, nrows - row0)
dshape[0] = nr
print("Wrtiting to column %s (rows %d to %d)" %
(colname, row0, row0 + nr - 1))
tab_spw.putcol(
colname,
numpy.ones(dshape, dtype=type(init_with)) * init_with,
row0, nr)
tab_spw.close()
tab.close()
return 'added'
def main(options):
cI = numpy.complex(0., 1.)
inms = options.inms
if inms == '':
print 'Error: you have to specify an input MS, use -h for help'
return
column = options.column
outcol = options.outcol
t = pt.table(inms, readonly=False, ack=True)
if options.back:
lincol = options.lincol
if lincol not in t.colnames():
print 'Adding the output linear polarization column', lincol, 'to', inms
coldmi = t.getdminfo(column)
coldmi['NAME'] = lincol
t.addcols(
pt.maketabdesc(
pt.makearrcoldesc(lincol,
0.,
valuetype='complex',
shape=numpy.array(t.getcell(column,
0)).shape)),
coldmi)
### RVW EDIT 2012
print 'Reading the input column (circular)', column
if column not in t.colnames():
print 'Error: Input column does not exist'
return
### RVW EDIT 2012 Input column with the -c switch
cirdata = t.getcol(column)
#cirdata = t.getcol(outcol)
#print 'SHAPE ARRAY', numpy.shape(cirdata)
print 'Computing the linear polarization terms...'
lindata = numpy.transpose(
numpy.array([
0.5 * (cirdata[:, :, 0] + cirdata[:, :, 1] + cirdata[:, :, 2] +
cirdata[:, :, 3]),
0.5 * (cI * cirdata[:, :, 0] - cI * cirdata[:, :, 1] +
cI * cirdata[:, :, 2] - cI * cirdata[:, :, 3]),
0.5 * (-cI * cirdata[:, :, 0] - cI * cirdata[:, :, 1] +
cI * cirdata[:, :, 2] + cI * cirdata[:, :, 3]),
0.5 * (cirdata[:, :, 0] - cirdata[:, :, 1] - cirdata[:, :, 2] +
cirdata[:, :, 3])
]), (1, 2, 0))
print 'Finishing up...'
t.putcol(lincol, lindata)
else:
if outcol not in t.colnames():
print 'Adding the output column', outcol, 'to', inms
coldmi = t.getdminfo(column)
coldmi['NAME'] = outcol
t.addcols(
pt.maketabdesc(
pt.makearrcoldesc(outcol,
0.,
valuetype='complex',
shape=numpy.array(t.getcell(column,
0)).shape)),
coldmi)
print 'Reading the input column (linear)', column
data = t.getcol(column)
print 'Computing the output column'
outdata = numpy.transpose(
numpy.array([
0.5 * (data[:, :, 0] - cI * data[:, :, 1] +
cI * data[:, :, 2] + data[:, :, 3]),
0.5 * (data[:, :, 0] + cI * data[:, :, 1] +
cI * data[:, :, 2] - data[:, :, 3]),
0.5 * (data[:, :, 0] - cI * data[:, :, 1] -
cI * data[:, :, 2] - data[:, :, 3]),
0.5 * (data[:, :, 0] + cI * data[:, :, 1] -
cI * data[:, :, 2] + data[:, :, 3])
]), (1, 2, 0))
print 'Finishing up...'
t.putcol(outcol, outdata)
if options.poltable:
print 'Updating the POLARIZATION table...'
tp = pt.table(inms + '/POLARIZATION', readonly=False, ack=True)
### RVW EDIT 2012
if options.back:
tp.putcol('CORR_TYPE',
numpy.array([[9, 10, 11, 12]],
dtype=numpy.int32)) # FROM CIRC-->LIN
else:
tp.putcol('CORR_TYPE',
numpy.array([[5, 6, 7, 8]],
dtype=numpy.int32)) # FROM LIN-->CIRC
c1 = c + (3 * d * k)
d1 = d
print "Adding %s\t%d\t%3.2f\t%3.2f\t%.4f\t%.4f\t%.4f\t%.4f" % \
(name, epoch, ra, decl, a1, b1, c1, d1)
# append to standards table
fc.addrows()
fc.putcell("Name", fc.nrows() - 1, name)
fc.putcell("RA_J2000", fc.nrows() - 1, ra)
fc.putcell("Dec_J2000", fc.nrows() - 1, decl)
fc.putcell("AltNames", fc.nrows() - 1, np.array([[name]]))
coeffs = tbls.makearrcoldesc(name + "_coeffs",
None,
ndim=1,
shape=[4],
valuetype="float")
coefferrs = tbls.makearrcoldesc(name + "_coefferrs",
None,
ndim=1,
shape=[4],
valuetype="float")
pb.addcols(coeffs)
pb.addcols(coefferrs)
pb.putcol(
name + "_coeffs",
np.tile(np.array([a1, b1, c1, d1], dtype=np.float32),
(pb.nrows(), 1)))
pb.putcol(
name + "_coefferrs",
def main(options):
cI = numpy.complex(0.,1.)
inms = options.inms
if inms == '':
print 'Error: you have to specify an input MS, use -h for help'
return
column = options.column
outcol = options.outcol
t = pt.table(inms, readonly=False, ack=True)
if options.back:
lincol = options.lincol
if lincol not in t.colnames():
print 'Adding the output linear polarization column',lincol,'to',inms
coldmi = t.getdminfo(column)
coldmi['NAME'] = lincol
t.addcols(pt.maketabdesc(pt.makearrcoldesc(lincol, 0., valuetype='complex', shape=numpy.array(t.getcell(column,0)).shape)), coldmi)
### RVW EDIT 2012
print 'Reading the input column (circular)', column
if column not in t.colnames():
print 'Error: Input column does not exist'
return
### RVW EDIT 2012 Input column with the -c switch
cirdata = t.getcol(column)
#cirdata = t.getcol(outcol)
#print 'SHAPE ARRAY', numpy.shape(cirdata)
print 'Computing the linear polarization terms...'
lindata = numpy.transpose(numpy.array([
0.5*(cirdata[:,:,0]+cirdata[:,:,1]+cirdata[:,:,2]+cirdata[:,:,3]),
0.5*(cI*cirdata[:,:,0]-cI*cirdata[:,:,1]+cI*cirdata[:,:,2]-cI*cirdata[:,:,3]),
0.5*(-cI*cirdata[:,:,0]-cI*cirdata[:,:,1]+cI*cirdata[:,:,2]+cI*cirdata[:,:,3]),
0.5*(cirdata[:,:,0]-cirdata[:,:,1]-cirdata[:,:,2]+cirdata[:,:,3])]),
(1,2,0))
print 'Finishing up...'
t.putcol(lincol, lindata)
else:
if outcol not in t.colnames():
print 'Adding the output column',outcol,'to',inms
coldmi = t.getdminfo(column)
coldmi['NAME'] = outcol
t.addcols(pt.maketabdesc(pt.makearrcoldesc(outcol, 0., valuetype='complex', shape=numpy.array(t.getcell(column,0)).shape)), coldmi)
print 'Reading the input column (linear)', column
data = t.getcol(column)
print 'Computing the output column'
outdata = numpy.transpose(numpy.array([
0.5*(data[:,:,0]-cI*data[:,:,1]+cI*data[:,:,2]+data[:,:,3]),
0.5*(data[:,:,0]+cI*data[:,:,1]+cI*data[:,:,2]-data[:,:,3]),
0.5*(data[:,:,0]-cI*data[:,:,1]-cI*data[:,:,2]-data[:,:,3]),
0.5*(data[:,:,0]+cI*data[:,:,1]-cI*data[:,:,2]+data[:,:,3])]),
(1,2,0))
print 'Finishing up...'
t.putcol(outcol, outdata)
if options.poltable:
print 'Updating the POLARIZATION table...'
tp = pt.table(inms+'/POLARIZATION',readonly=False,ack=True)
### RVW EDIT 2012
if options.back:
tp.putcol('CORR_TYPE',numpy.array([[9,10,11,12]],dtype=numpy.int32)) # FROM CIRC-->LIN
else:
tp.putcol('CORR_TYPE',numpy.array([[5,6,7,8]],dtype=numpy.int32)) # FROM LIN-->CIRC
