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 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 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 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)
