def make_imaging_weight_column(ms):
t = pt.table(ms, readonly=False, ack=False)
cnames = t.colnames()
try:
cdesc = t.getcoldesc('DATA')
except:
raise ValueError('Column DATA does not exist')
# Determine if the DATA storage specification is tiled.
hasTiled = False
try:
dminfo = t.getdminfo("DATA")
if dminfo['TYPE'][:5] == 'Tiled':
hasTiled = True
except:
hasTiled = False
# Use TiledShapeStMan if needed.
if not hasTiled:
dminfo = {
'TYPE': 'TiledShapeStMan',
'SPEC': {
'DEFAULTTILESHAPE': [4, 32, 128]
}
}
if 'IMAGING_WEIGHT' in cnames:
six.print_("Column IMAGING_WEIGHT not added; it already exists")
else:
# Add IMAGING_WEIGHT which is 1-dim and has type float.
# It needs a shape, otherwise the CASA imager complains.
shp = []
if 'shape' in cdesc:
shp = cdesc['shape']
if len(shp) > 0:
shp = [shp[0]] # use nchan from shape
else:
shp = [t.getcell('DATA', 0).shape[0]] # use nchan from actual data
cd = makearrcoldesc('IMAGING_WEIGHT',
0,
ndim=1,
shape=shp,
valuetype='float')
dminfo = {
'TYPE': 'TiledShapeStMan',
'SPEC': {
'DEFAULTTILESHAPE': [32, 128]
}
}
dminfo['NAME'] = 'imagingweight'
t.addcols(maketabdesc(cd), dminfo)
print "added column IMAGING_WEIGHT"
t.flush()
t.close()
return
def addDerivedMSCal(msname):
""" Add the derived columns like HA to an MS or CalTable.
It adds the columns HA, HA1, HA2, PA1, PA2, LAST, LAST1, LAST2, AZEL1,
AZEL2, and UVW_J2000.
They are all bound to the DerivedMSCal virtual data manager.
It fails if one of the columns already exists.
"""
# Open the MS
t = table(msname, readonly=False, ack=False)
colnames = t.colnames()
# Check that the columns needed by DerivedMSCal are present.
# Note that ANTENNA2 and FEED2 are not required.
for col in ["TIME", "ANTENNA1", "FIELD_ID", "FEED1"]:
if col not in colnames:
raise ValueError("Columns " + colnames +
" should be present in table " + msname)
scols1 = ['HA', 'HA1', 'HA2', 'PA1', 'PA2']
scols2 = ['LAST', 'LAST1', 'LAST2']
acols1 = ['AZEL1', 'AZEL2']
acols2 = ['UVW_J2000']
descs = []
# Define the columns and their units.
for col in scols1:
descs.append(
makescacoldesc(col, 0., keywords={"QuantumUnits": ["rad"]}))
for col in scols2:
descs.append(makescacoldesc(col, 0., keywords={"QuantumUnits": ["d"]}))
for col in acols1:
descs.append(
makearrcoldesc(col, 0., keywords={"QuantumUnits": ["rad", "rad"]}))
for col in acols2:
descs.append(
makearrcoldesc(col,
0.,
keywords={
"QuantumUnits": ["m", "m", "m"],
"MEASINFO": {
"Ref": "J2000",
"type": "uvw"
}
}))
# Add all columns using DerivedMSCal as data manager.
dminfo = {"TYPE": "DerivedMSCal", "NAME": "", "SPEC": {}}
t.addcols(maketabdesc(descs), dminfo)
# Flush the table to make sure it is written.
t.flush()
def make_imaging_weight_column(ms):
t = pt.table(ms, readonly=False, ack=False)
cnames = t.colnames()
try:
cdesc = t.getcoldesc('DATA')
except:
raise ValueError('Column DATA does not exist')
# Determine if the DATA storage specification is tiled.
hasTiled = False
try:
dminfo = t.getdminfo("DATA")
if dminfo['TYPE'][:5] == 'Tiled':
hasTiled = True
except:
hasTiled = False
# Use TiledShapeStMan if needed.
if not hasTiled:
dminfo = {'TYPE': 'TiledShapeStMan',
'SPEC': {'DEFAULTTILESHAPE': [4, 32, 128]}}
if 'IMAGING_WEIGHT' in cnames:
six.print_("Column IMAGING_WEIGHT not added; it already exists")
else:
# Add IMAGING_WEIGHT which is 1-dim and has type float.
# It needs a shape, otherwise the CASA imager complains.
shp = []
if 'shape' in cdesc:
shp = cdesc['shape']
if len(shp) > 0:
shp = [shp[0]] # use nchan from shape
else:
shp = [t.getcell('DATA', 0).shape[0]] # use nchan from actual data
cd = makearrcoldesc('IMAGING_WEIGHT', 0, ndim=1, shape=shp,
valuetype='float')
dminfo = {'TYPE': 'TiledShapeStMan',
'SPEC': {'DEFAULTTILESHAPE': [32, 128]}}
dminfo['NAME'] = 'imagingweight'
t.addcols(maketabdesc(cd), dminfo)
print "added column IMAGING_WEIGHT"
t.flush()
t.close()
return
def addDerivedMSCal(msname):
""" Add the derived columns like HA to an MS or CalTable.
It adds the columns HA, HA1, HA2, PA1, PA2, LAST, LAST1, LAST2, AZEL1,
AZEL2, and UVW_J2000.
They are all bound to the DerivedMSCal virtual data manager.
It fails if one of the columns already exists.
"""
# Open the MS
t = table(msname, readonly=False, ack=False)
colnames = t.colnames()
# Check that the columns needed by DerivedMSCal are present.
# Note that ANTENNA2 and FEED2 are not required.
for col in ["TIME", "ANTENNA1", "FIELD_ID", "FEED1"]:
if col not in colnames:
raise ValueError("Columns " + colnames +
" should be present in table " + msname)
scols1 = ['HA', 'HA1', 'HA2', 'PA1', 'PA2']
scols2 = ['LAST', 'LAST1', 'LAST2']
acols1 = ['AZEL1', 'AZEL2']
acols2 = ['UVW_J2000']
descs = []
# Define the columns and their units.
for col in scols1:
descs.append(makescacoldesc(col, 0.,
keywords={"QuantumUnits": ["rad"]}))
for col in scols2:
descs.append(makescacoldesc(col, 0.,
keywords={"QuantumUnits": ["d"]}))
for col in acols1:
descs.append(makearrcoldesc(col, 0.,
keywords={"QuantumUnits": ["rad", "rad"]}))
for col in acols2:
descs.append(makearrcoldesc(col, 0.,
keywords={"QuantumUnits": ["m", "m", "m"],
"MEASINFO": {"Ref": "J2000",
"type": "uvw"}}))
# Add all columns using DerivedMSCal as data manager.
dminfo = {"TYPE": "DerivedMSCal", "NAME": "", "SPEC": {}}
t.addcols(maketabdesc(descs), dminfo)
# Flush the table to make sure it is written.
t.flush()
def addImagingColumns(msname, ack=True):
""" Add the columns to an MS needed for the casa imager.
It adds the columns MODEL_DATA, CORRECTED_DATA, and IMAGING_WEIGHT.
It also sets the CHANNEL_SELECTION keyword needed for the older casa
imagers.
A column is not added if already existing.
"""
# numpy is needed
import numpy as np
# Open the MS
t = table(msname, readonly=False, ack=False)
cnames = t.colnames()
# Get the description of the DATA column.
try:
cdesc = t.getcoldesc('DATA')
except:
raise ValueError('Column DATA does not exist')
# Determine if the DATA storage specification is tiled.
hasTiled = False
try:
dminfo = t.getdminfo("DATA")
if dminfo['TYPE'][:5] == 'Tiled':
hasTiled = True
except:
hasTiled = False
# Use TiledShapeStMan if needed.
if not hasTiled:
dminfo = {'TYPE': 'TiledShapeStMan',
'SPEC': {'DEFAULTTILESHAPE': [4, 32, 128]}}
# Add the columns(if not existing). Use the description of the DATA column.
if 'MODEL_DATA' in cnames:
six.print_("Column MODEL_DATA not added; it already exists")
else:
dminfo['NAME'] = 'modeldata'
cdesc['comment'] = 'The model data column'
t.addcols(maketabdesc(makecoldesc('MODEL_DATA', cdesc)), dminfo)
if ack:
six.print_("added column MODEL_DATA")
if 'CORRECTED_DATA' in cnames:
six.print_("Column CORRECTED_DATA not added; it already exists")
else:
dminfo['NAME'] = 'correcteddata'
cdesc['comment'] = 'The corrected data column'
t.addcols(maketabdesc(makecoldesc('CORRECTED_DATA', cdesc)), dminfo)
if ack:
six.print_("'added column CORRECTED_DATA")
if 'IMAGING_WEIGHT' in cnames:
six.print_("Column IMAGING_WEIGHT not added; it already exists")
else:
# Add IMAGING_WEIGHT which is 1-dim and has type float.
# It needs a shape, otherwise the CASA imager complains.
shp = []
if 'shape' in cdesc:
shp = cdesc['shape']
if len(shp) > 0:
shp = [shp[0]] # use nchan from shape
else:
shp = [t.getcell('DATA', 0).shape[0]] # use nchan from actual data
cd = makearrcoldesc('IMAGING_WEIGHT', 0, ndim=1, shape=shp,
valuetype='float')
dminfo = {'TYPE': 'TiledShapeStMan',
'SPEC': {'DEFAULTTILESHAPE': [32, 128]}}
dminfo['NAME'] = 'imagingweight'
t.addcols(maketabdesc(cd), dminfo)
if ack:
six.print_("added column IMAGING_WEIGHT")
# Add or overwrite keyword CHANNEL_SELECTION.
if 'CHANNEL_SELECTION' in t.colkeywordnames('MODEL_DATA'):
t.removecolkeyword('MODEL_DATA', 'CHANNEL_SELECTION')
# Define the CHANNEL_SELECTION keyword containing the channels of
# all spectral windows.
tspw = table(t.getkeyword('SPECTRAL_WINDOW'), ack=False)
nchans = tspw.getcol('NUM_CHAN')
chans = [[0, nch] for nch in nchans]
t.putcolkeyword('MODEL_DATA', 'CHANNEL_SELECTION', np.int32(chans))
if ack:
six.print_("defined keyword CHANNEL_SELECTION in column MODEL_DATA")
# Flush the table to make sure it is written.
t.flush()
def addImagingColumns(msname, ack=True):
""" Add the columns to an MS needed for the casa imager.
It adds the columns MODEL_DATA, CORRECTED_DATA, and IMAGING_WEIGHT.
It also sets the CHANNEL_SELECTION keyword needed for the older casa
imagers.
A column is not added if already existing.
"""
# numpy is needed
import numpy as np
# Open the MS
t = table(msname, readonly=False, ack=False)
cnames = t.colnames()
# Get the description of the DATA column.
try:
cdesc = t.getcoldesc('DATA')
except:
raise ValueError('Column DATA does not exist')
# Determine if the DATA storage specification is tiled.
hasTiled = False
try:
dminfo = t.getdminfo("DATA")
if dminfo['TYPE'][:5] == 'Tiled':
hasTiled = True
except:
hasTiled = False
# Use TiledShapeStMan if needed.
if not hasTiled:
dminfo = {'TYPE': 'TiledShapeStMan',
'SPEC': {'DEFAULTTILESHAPE': [4, 32, 128]}}
# Add the columns(if not existing). Use the description of the DATA column.
if 'MODEL_DATA' in cnames:
six.print_("Column MODEL_DATA not added; it already exists")
else:
dminfo['NAME'] = 'modeldata'
cdesc['comment'] = 'The model data column'
t.addcols(maketabdesc(makecoldesc('MODEL_DATA', cdesc)), dminfo)
if ack:
six.print_("added column MODEL_DATA")
if 'CORRECTED_DATA' in cnames:
six.print_("Column CORRECTED_DATA not added; it already exists")
else:
dminfo['NAME'] = 'correcteddata'
cdesc['comment'] = 'The corrected data column'
t.addcols(maketabdesc(makecoldesc('CORRECTED_DATA', cdesc)), dminfo)
if ack:
six.print_("'added column CORRECTED_DATA")
if 'IMAGING_WEIGHT' in cnames:
six.print_("Column IMAGING_WEIGHT not added; it already exists")
else:
# Add IMAGING_WEIGHT which is 1-dim and has type float.
# It needs a shape, otherwise the CASA imager complains.
shp = []
if 'shape' in cdesc:
shp = cdesc['shape']
if len(shp) > 0:
shp = [shp[0]] # use nchan from shape
else:
shp = [t.getcell('DATA', 0).shape[0]] # use nchan from actual data
cd = makearrcoldesc('IMAGING_WEIGHT', 0, ndim=1, shape=shp,
valuetype='float')
dminfo = {'TYPE': 'TiledShapeStMan',
'SPEC': {'DEFAULTTILESHAPE': [32, 128]}}
dminfo['NAME'] = 'imagingweight'
t.addcols(maketabdesc(cd), dminfo)
if ack:
six.print_("added column IMAGING_WEIGHT")
# Add or overwrite keyword CHANNEL_SELECTION.
if 'CHANNEL_SELECTION' in t.colkeywordnames('MODEL_DATA'):
t.removecolkeyword('MODEL_DATA', 'CHANNEL_SELECTION')
# Define the CHANNEL_SELECTION keyword containing the channels of
# all spectral windows.
tspw = table(t.getkeyword('SPECTRAL_WINDOW'), ack=False)
nchans = tspw.getcol('NUM_CHAN')
chans = [[0, nch] for nch in nchans]
t.putcolkeyword('MODEL_DATA', 'CHANNEL_SELECTION', np.int32(chans))
if ack:
six.print_("defined keyword CHANNEL_SELECTION in column MODEL_DATA")
# Flush the table to make sure it is written.
t.flush()
def _write_observation_table(filename, config):
"""
Write the observation table.
"""
station = config.station
nant = config.nant
nbl = config.nbl
tint = config.tint
freq = config.freq
nchan = config.nchan
pols = config.pols
npol = config.npol
nint = config.nint
# Observation
col1 = tableutil.makearrcoldesc('TIME_RANGE',
0.0,
1,
comment='Start and end of observation',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
col2 = tableutil.makearrcoldesc('LOG', 'none', 1, comment='Observing log')
col3 = tableutil.makearrcoldesc('SCHEDULE',
'none',
1,
comment='Observing schedule')
col4 = tableutil.makescacoldesc('FLAG_ROW', False, comment='Row flag')
col5 = tableutil.makescacoldesc('OBSERVER',
station.name,
comment='Name of observer(s)')
col6 = tableutil.makescacoldesc('PROJECT',
station.name,
comment='Project identification string')
col7 = tableutil.makescacoldesc(
'RELEASE_DATE',
0.0,
comment='Release date when data becomes public',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
col8 = tableutil.makescacoldesc('SCHEDULE_TYPE',
'all-sky',
comment='Observing schedule type')
col9 = tableutil.makescacoldesc('TELESCOPE_NAME',
station.name,
comment='Telescope Name (e.g. WSRT, VLBA)')
desc = tableutil.maketabdesc(
[col1, col2, col3, col4, col5, col6, col7, col8, col9])
tb = table("%s/OBSERVATION" % filename, desc, nrow=nint, ack=False)
tb.putcol('TIME_RANGE', numpy.zeros((nint, 2)), 0, nint)
tb.putcol('LOG', numpy.array([
[
'Not provided',
],
] * nint, dtype='S'), 0, nint)
tb.putcol('SCHEDULE', numpy.array([
[
'Not provided',
],
] * nint, dtype='S'), 0, nint)
tb.putcol('FLAG_ROW', [
False,
] * nint, 0, nint)
tb.putcol('OBSERVER', [
os.path.basename(__file__),
] * nint, 0, nint)
tb.putcol('PROJECT', [
station.name + ' all-sky',
] * nint, 0, nint)
tb.putcol('RELEASE_DATE', [
0.0,
] * nint, 0, nint)
tb.putcol('SCHEDULE_TYPE', [
'all-sky',
] * nint, 0, nint)
tb.putcol('TELESCOPE_NAME', [
station.name,
] * nint, 0, nint)
tb.flush()
tb.close()
# Source
col1 = tableutil.makearrcoldesc('DIRECTION',
0.0,
2,
comment='Direction (e.g. RA, DEC).',
keywords={
'QuantumUnits': ['rad', 'rad'],
'MEASINFO': {
'type': 'direction',
'Ref': 'J2000'
}
})
col2 = tableutil.makearrcoldesc('PROPER_MOTION',
0.0,
2,
comment='Proper motion',
keywords={'QuantumUnits': [
'rad/s',
]})
col3 = tableutil.makescacoldesc(
'CALIBRATION_GROUP',
0,
comment='Number of grouping for calibration purpose.')
col4 = tableutil.makescacoldesc(
'CODE',
"none",
comment='Special characteristics of source, e.g. Bandpass calibrator')
col5 = tableutil.makescacoldesc(
'INTERVAL',
0.0,
comment='Interval of time for which this set of parameters is accurate',
keywords={'QuantumUnits': [
's',
]})
col6 = tableutil.makescacoldesc(
'NAME', "none", comment='Name of source as given during observations')
col7 = tableutil.makescacoldesc('NUM_LINES',
0,
comment='Number of spectral lines')
col8 = tableutil.makescacoldesc('SOURCE_ID', 0, comment='Source id')
col9 = tableutil.makescacoldesc(
'SPECTRAL_WINDOW_ID', -1, comment='ID for this spectral window setup')
col10 = tableutil.makescacoldesc(
'TIME',
0.0,
comment=
'Midpoint of time for which this set of parameters is accurate.',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
col11 = tableutil.makearrcoldesc('TRANSITION',
'none',
1,
comment='Line Transition name')
col12 = tableutil.makearrcoldesc('REST_FREQUENCY',
1.0,
1,
comment='Line rest frequency',
keywords={
'QuantumUnits': [
'Hz',
],
'MEASINFO': {
'type': 'frequency',
'Ref': 'LSRK'
}
})
col13 = tableutil.makearrcoldesc('SYSVEL',
1.0,
1,
comment='Systemic velocity at reference',
keywords={
'QuantumUnits': [
'm/s',
],
'MEASINFO': {
'type': 'radialvelocity',
'Ref': 'LSRK'
}
})
desc = tableutil.maketabdesc([
col1, col2, col3, col4, col5, col6, col7, col8, col9, col10, col11,
col12, col13
])
tb = table("%s/SOURCE" % filename, desc, nrow=nint, ack=False)
tb.putcol('DIRECTION', numpy.zeros((nint, 1, 2)), 0, nint)
tb.putcol('PROPER_MOTION', numpy.zeros((nint, 1, 2)), 0, nint)
tb.putcol('CALIBRATION_GROUP', [
0,
] * nint, 0, nint)
tb.putcol('CODE', [
'none',
] * nint, 0, nint)
tb.putcol('INTERVAL', [
tint,
] * nint, 0, nint)
tb.putcol('NAME', [
'zenith',
] * nint, 0, nint)
tb.putcol('NUM_LINES', [
0,
] * nint, 0, nint)
tb.putcol('SOURCE_ID', [
0,
] * nint, 0, nint)
tb.putcol('SPECTRAL_WINDOW_ID', [
-1,
] * nint, 0, nint)
tb.putcol('TIME', [
0.0,
] * nint, 0, nint)
#tb.putcol('TRANSITION', []*nint, 0, nint)
#tb.putcol('REST_FREQUENCY', []*nint, 0, nint)
#tb.putcol('SYSVEL', []*nint, 0, nint)
tb.flush()
tb.close()
# Field
col1 = tableutil.makearrcoldesc(
'DELAY_DIR',
0.0,
2,
comment=
'Direction of delay center (e.g. RA, DEC)as polynomial in time.',
keywords={
'QuantumUnits': ['rad', 'rad'],
'MEASINFO': {
'type': 'direction',
'Ref': 'J2000'
}
})
col2 = tableutil.makearrcoldesc(
'PHASE_DIR',
0.0,
2,
comment='Direction of phase center (e.g. RA, DEC).',
keywords={
'QuantumUnits': ['rad', 'rad'],
'MEASINFO': {
'type': 'direction',
'Ref': 'J2000'
}
})
col3 = tableutil.makearrcoldesc(
'REFERENCE_DIR',
0.0,
2,
comment=
'Direction of REFERENCE center (e.g. RA, DEC).as polynomial in time.',
keywords={
'QuantumUnits': ['rad', 'rad'],
'MEASINFO': {
'type': 'direction',
'Ref': 'J2000'
}
})
col4 = tableutil.makescacoldesc(
'CODE',
"none",
comment='Special characteristics of field, e.g. Bandpass calibrator')
col5 = tableutil.makescacoldesc('FLAG_ROW', False, comment='Row Flag')
col6 = tableutil.makescacoldesc('NAME',
"none",
comment='Name of this field')
col7 = tableutil.makescacoldesc('NUM_POLY',
0,
comment='Polynomial order of _DIR columns')
col8 = tableutil.makescacoldesc('SOURCE_ID', 0, comment='Source id')
col9 = tableutil.makescacoldesc(
'TIME',
0.0,
comment='Time origin for direction and rate',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
desc = tableutil.maketabdesc(
[col1, col2, col3, col4, col5, col6, col7, col8, col9])
tb = table("%s/FIELD" % filename, desc, nrow=nint, ack=False)
tb.putcol('DELAY_DIR', numpy.zeros((nint, 1, 2)), 0, nint)
tb.putcol('PHASE_DIR', numpy.zeros((nint, 1, 2)), 0, nint)
tb.putcol('REFERENCE_DIR', numpy.zeros((nint, 1, 2)), 0, nint)
tb.putcol('CODE', [
'none',
] * nint, 0, nint)
tb.putcol('FLAG_ROW', [
False,
] * nint, 0, nint)
tb.putcol('NAME', [
'zenith',
] * nint, 0, nint)
tb.putcol('NUM_POLY', [
0,
] * nint, 0, nint)
tb.putcol('SOURCE_ID', list(range(nint)), 0, nint)
tb.putcol('TIME', [
0.0,
] * nint, 0, nint)
tb.flush()
tb.close()
def _write_polarization_table(filename, config):
"""
Write the polarization table.
"""
station = config.station
nant = config.nant
nbl = config.nbl
tint = config.tint
freq = config.freq
nchan = config.nchan
pols = config.pols
npol = config.npol
nint = config.nint
# Polarization
stks = numpy.array([STOKES_CODES[p] for p in pols])
prds = numpy.zeros((2, npol), dtype=numpy.int32)
for i in range(stks.size):
stk = stks[i]
if stk > 4:
prds[0, i] = ((stk - 1) % 4) / 2
prds[1, i] = ((stk - 1) % 4) % 2
else:
prds[0, i] = 1
prds[1, i] = 1
col1 = tableutil.makearrcoldesc(
'CORR_TYPE',
0,
1,
comment=
'The polarization type for each correlation product, as a Stokes enum.'
)
col2 = tableutil.makearrcoldesc(
'CORR_PRODUCT',
0,
2,
comment='Indices describing receptors of feed going into correlation')
col3 = tableutil.makescacoldesc('FLAG_ROW', False, comment='flag')
col4 = tableutil.makescacoldesc('NUM_CORR',
npol,
comment='Number of correlation products')
desc = tableutil.maketabdesc([col1, col2, col3, col4])
tb = table("%s/POLARIZATION" % filename, desc, nrow=1, ack=False)
tb.putcell('CORR_TYPE', 0, stks)
tb.putcell('CORR_PRODUCT', 0, prds.T)
tb.putcell('FLAG_ROW', 0, False)
tb.putcell('NUM_CORR', 0, npol)
tb.flush()
tb.close()
# Feed
col1 = tableutil.makearrcoldesc(
'POSITION',
0.0,
1,
comment='Position of feed relative to feed reference position',
keywords={
'QuantumUnits': ['m', 'm', 'm'],
'MEASINFO': {
'type': 'position',
'Ref': 'ITRF'
}
})
col2 = tableutil.makearrcoldesc(
'BEAM_OFFSET',
0.0,
2,
comment='Beam position offset (on sky but in antennareference frame)',
keywords={
'QuantumUnits': ['rad', 'rad'],
'MEASINFO': {
'type': 'direction',
'Ref': 'J2000'
}
})
col3 = tableutil.makearrcoldesc(
'POLARIZATION_TYPE',
'X',
1,
comment='Type of polarization to which a given RECEPTOR responds')
col4 = tableutil.makearrcoldesc(
'POL_RESPONSE',
1j,
2,
valuetype='complex',
comment='D-matrix i.e. leakage between two receptors')
col5 = tableutil.makearrcoldesc(
'RECEPTOR_ANGLE',
0.0,
1,
comment='The reference angle for polarization',
keywords={'QuantumUnits': [
'rad',
]})
col6 = tableutil.makescacoldesc('ANTENNA_ID',
0,
comment='ID of antenna in this array')
col7 = tableutil.makescacoldesc('BEAM_ID', -1, comment='Id for BEAM model')
col8 = tableutil.makescacoldesc('FEED_ID', 0, comment='Feed id')
col9 = tableutil.makescacoldesc(
'INTERVAL',
0.0,
comment='Interval for which this set of parameters is accurate',
keywords={'QuantumUnits': [
's',
]})
col10 = tableutil.makescacoldesc(
'NUM_RECEPTORS',
2,
comment='Number of receptors on this feed (probably 1 or 2)')
col11 = tableutil.makescacoldesc(
'SPECTRAL_WINDOW_ID', -1, comment='ID for this spectral window setup')
col12 = tableutil.makescacoldesc(
'TIME',
0.0,
comment='Midpoint of time for which this set of parameters is accurate',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
desc = tableutil.maketabdesc([
col1, col2, col3, col4, col5, col6, col7, col8, col9, col10, col11,
col12
])
tb = table("%s/FEED" % filename, desc, nrow=nant, ack=False)
presp = numpy.zeros((nant, 2, 2), dtype=numpy.complex64)
if stks[0] > 8:
ptype = [['X', 'Y'] for i in range(nant)]
presp[:, 0, 0] = 1.0
presp[:, 0, 1] = 0.0
presp[:, 1, 0] = 0.0
presp[:, 1, 1] = 1.0
elif stks[0] > 4:
ptype = [['R', 'L'] for i in range(nant)]
presp[:, 0, 0] = 1.0
presp[:, 0, 1] = -1.0j
presp[:, 1, 0] = 1.0j
presp[:, 1, 1] = 1.0
else:
ptype = [['X', 'Y'] for i in range(nant)]
presp[:, 0, 0] = 1.0
presp[:, 0, 1] = 0.0
presp[:, 1, 0] = 0.0
presp[:, 1, 1] = 1.0
tb.putcol('POSITION', numpy.zeros((nant, 3)), 0, nant)
tb.putcol('BEAM_OFFSET', numpy.zeros((nant, 2, 2)), 0, nant)
tb.putcol('POLARIZATION_TYPE', numpy.array(ptype, dtype='S'), 0, nant)
tb.putcol('POL_RESPONSE', presp, 0, nant)
tb.putcol('RECEPTOR_ANGLE', numpy.zeros((nant, 2)), 0, nant)
tb.putcol('ANTENNA_ID', list(range(nant)), 0, nant)
tb.putcol('BEAM_ID', [
-1,
] * nant, 0, nant)
tb.putcol('FEED_ID', [
0,
] * nant, 0, nant)
tb.putcol('INTERVAL', [
tint,
] * nant, 0, nant)
tb.putcol('NUM_RECEPTORS', [
2,
] * nant, 0, nant)
tb.putcol('SPECTRAL_WINDOW_ID', [
-1,
] * nant, 0, nant)
tb.putcol('TIME', [
0.0,
] * nant, 0, nant)
tb.flush()
tb.close()
def _write_antenna_table(filename, config):
"""
Write the antenna table.
"""
station = config.station
nant = config.nant
nbl = config.nbl
tint = config.tint
freq = config.freq
nchan = config.nchan
pols = config.pols
npol = config.npol
nint = config.nint
col1 = tableutil.makearrcoldesc(
'OFFSET',
0.0,
1,
comment='Axes offset of mount to FEED REFERENCE point',
keywords={
'QuantumUnits': ['m', 'm', 'm'],
'MEASINFO': {
'type': 'position',
'Ref': 'ITRF'
}
})
col2 = tableutil.makearrcoldesc(
'POSITION',
0.0,
1,
comment='Antenna X,Y,Z phase reference position',
keywords={
'QuantumUnits': ['m', 'm', 'm'],
'MEASINFO': {
'type': 'position',
'Ref': 'ITRF'
}
})
col3 = tableutil.makescacoldesc('TYPE',
"ground-based",
comment='Antenna type (e.g. SPACE-BASED)')
col4 = tableutil.makescacoldesc('DISH_DIAMETER',
2.0,
comment='Physical diameter of dish',
keywords={'QuantumUnits': [
'm',
]})
col5 = tableutil.makescacoldesc('FLAG_ROW',
False,
comment='Flag for this row')
col6 = tableutil.makescacoldesc(
'MOUNT', "alt-az", comment='Mount type e.g. alt-az, equatorial, etc.')
col7 = tableutil.makescacoldesc('NAME',
"none",
comment='Antenna name, e.g. VLA22, CA03')
col8 = tableutil.makescacoldesc('STATION',
station.name,
comment='Station (antenna pad) name')
desc = tableutil.maketabdesc(
[col1, col2, col3, col4, col5, col6, col7, col8])
tb = table("%s/ANTENNA" % filename, desc, nrow=nant, ack=False)
tb.putcol('OFFSET', numpy.zeros((nant, 3)), 0, nant)
tb.putcol('TYPE', ['GROUND-BASED,'] * nant, 0, nant)
tb.putcol('DISH_DIAMETER', [
2.0,
] * nant, 0, nant)
tb.putcol('FLAG_ROW', [
False,
] * nant, 0, nant)
tb.putcol('MOUNT', [
'ALT-AZ',
] * nant, 0, nant)
tb.putcol('NAME', ['LWA%03i' % ant.id for ant in station.antennas], 0,
nant)
tb.putcol('STATION', [
station.name,
] * nant, 0, nant)
for i, ant in enumerate(station.antennas):
#tb.putcell('OFFSET', i, [0.0, 0.0, 0.0])
tb.putcell('POSITION', i, ant.ecef)
#tb.putcell('TYPE', i, 'GROUND-BASED')
#tb.putcell('DISH_DIAMETER', i, 2.0)
#tb.putcell('FLAG_ROW', i, False)
#tb.putcell('MOUNT', i, 'ALT-AZ')
#tb.putcell('NAME', i, ant.get_name())
#tb.putcell('STATION', i, station.name)
tb.flush()
tb.close()
def _write_main_table(filename, config):
"""
Write the main data table.
"""
station = config.station
nant = config.nant
nbl = config.nbl
tint = config.tint
freq = config.freq
nchan = config.nchan
pols = config.pols
npol = config.npol
nint = config.nint
col1 = tableutil.makearrcoldesc(
'UVW',
0.0,
1,
comment='Vector with uvw coordinates (in meters)',
keywords={
'QuantumUnits': ['m', 'm', 'm'],
'MEASINFO': {
'type': 'uvw',
'Ref': 'ITRF'
}
})
col2 = tableutil.makearrcoldesc(
'FLAG',
False,
2,
comment='The data flags, array of bools with same shape as data')
col3 = tableutil.makearrcoldesc(
'FLAG_CATEGORY',
False,
3,
comment='The flag category, NUM_CAT flags for each datum',
keywords={'CATEGORY': [
'',
]})
col4 = tableutil.makearrcoldesc(
'WEIGHT',
1.0,
1,
valuetype='float',
comment='Weight for each polarization spectrum')
col5 = tableutil.makearrcoldesc(
'SIGMA',
9999.,
1,
valuetype='float',
comment='Estimated rms noise for channel with unity bandpass response')
col6 = tableutil.makescacoldesc(
'ANTENNA1', 0, comment='ID of first antenna in interferometer')
col7 = tableutil.makescacoldesc(
'ANTENNA2', 0, comment='ID of second antenna in interferometer')
col8 = tableutil.makescacoldesc('ARRAY_ID',
0,
comment='ID of array or subarray')
col9 = tableutil.makescacoldesc('DATA_DESC_ID',
0,
comment='The data description table index')
col10 = tableutil.makescacoldesc('EXPOSURE',
0.0,
comment='he effective integration time',
keywords={'QuantumUnits': [
's',
]})
col11 = tableutil.makescacoldesc('FEED1',
0,
comment='The feed index for ANTENNA1')
col12 = tableutil.makescacoldesc('FEED2',
0,
comment='The feed index for ANTENNA2')
col13 = tableutil.makescacoldesc('FIELD_ID',
0,
comment='Unique id for this pointing')
col14 = tableutil.makescacoldesc(
'FLAG_ROW',
False,
comment='Row flag - flag all data in this row if True')
col15 = tableutil.makescacoldesc('INTERVAL',
0.0,
comment='The sampling interval',
keywords={'QuantumUnits': [
's',
]})
col16 = tableutil.makescacoldesc(
'OBSERVATION_ID',
0,
comment='ID for this observation, index in OBSERVATION table')
col17 = tableutil.makescacoldesc(
'PROCESSOR_ID',
-1,
comment='Id for backend processor, index in PROCESSOR table')
col18 = tableutil.makescacoldesc(
'SCAN_NUMBER', 1, comment='Sequential scan number from on-line system')
col19 = tableutil.makescacoldesc('STATE_ID',
-1,
comment='ID for this observing state')
col20 = tableutil.makescacoldesc('TIME',
0.0,
comment='Modified Julian Day',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
col21 = tableutil.makescacoldesc('TIME_CENTROID',
0.0,
comment='Modified Julian Day',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
col22 = tableutil.makearrcoldesc("DATA",
0j,
2,
valuetype='complex',
comment='The data column')
desc = tableutil.maketabdesc([
col1, col2, col3, col4, col5, col6, col7, col8, col9, col10, col11,
col12, col13, col14, col15, col16, col17, col18, col19, col20, col21,
col22
])
tb = table("%s" % filename, desc, nrow=nint * nbl, ack=False)
fg = numpy.zeros((nint * nbl, npol, nchan), dtype=numpy.bool)
fc = numpy.zeros((nint * nbl, npol, nchan, 1), dtype=numpy.bool)
uv = numpy.zeros((nint * nbl, 3), dtype=numpy.float64)
a1 = numpy.zeros((nint * nbl, ), dtype=numpy.int32)
a2 = numpy.zeros((nint * nbl, ), dtype=numpy.int32)
vs = numpy.zeros((nint * nbl, npol, nchan), dtype=numpy.complex64)
wg = numpy.ones((nint * nbl, npol))
sg = numpy.ones((nint * nbl, npol)) * 9999
k = 0
base_uvw = get_zenith_uvw(station,
LWATime.now()) # Kind of an interesting choice
for t in range(nint):
uv[t * nbl:(t + 1) * nbl, :] = base_uvw
for i in range(nant):
for j in range(i, nant):
a1[k] = i
a2[k] = j
k += 1
tb.putcol('UVW', uv, 0, nint * nbl)
tb.putcol('FLAG', fg.transpose(0, 2, 1), 0, nint * nbl)
tb.putcol('FLAG_CATEGORY', fc.transpose(0, 3, 2, 1), 0, nint * nbl)
tb.putcol('WEIGHT', wg, 0, nint * nbl)
tb.putcol('SIGMA', sg, 0, nint * nbl)
tb.putcol('ANTENNA1', a1, 0, nint * nbl)
tb.putcol('ANTENNA2', a2, 0, nint * nbl)
tb.putcol('ARRAY_ID', [
0,
] * nint * nbl, 0, nint * nbl)
tb.putcol('DATA_DESC_ID', [
0,
] * nint * nbl, 0, nint * nbl)
tb.putcol('EXPOSURE', [
tint,
] * nint * nbl, 0, nint * nbl)
tb.putcol('FEED1', [
0,
] * nint * nbl, 0, nint * nbl)
tb.putcol('FEED2', [
0,
] * nint * nbl, 0, nint * nbl)
tb.putcol('FIELD_ID', [i for i in range(nint) for j in range(nbl)], 0,
nint * nbl)
tb.putcol('FLAG_ROW', [
False,
] * nint * nbl, 0, nint * nbl)
tb.putcol('INTERVAL', [
tint,
] * nint * nbl, 0, nint * nbl)
tb.putcol('OBSERVATION_ID', [i for i in range(nint) for j in range(nbl)],
0, nint * nbl)
tb.putcol('PROCESSOR_ID', [
-1,
] * nint * nbl, 0, nint * nbl)
tb.putcol('SCAN_NUMBER', [i + 1 for i in range(nint) for j in range(nbl)],
0, nint * nbl)
tb.putcol('STATE_ID', [
-1,
] * nint * nbl, 0, nint * nbl)
tb.putcol('TIME', [
0.0,
] * nint * nbl, 0, nint * nbl)
tb.putcol('TIME_CENTROID', [
0.0,
] * nint * nbl, 0, nint * nbl)
tb.putcol('DATA', vs.transpose(0, 2, 1), 0, nint * nbl)
tb.flush()
tb.close()
# Data description
col1 = tableutil.makescacoldesc('FLAG_ROW', False, comment='Flag this row')
col2 = tableutil.makescacoldesc('POLARIZATION_ID',
0,
comment='Pointer to polarization table')
col3 = tableutil.makescacoldesc('SPECTRAL_WINDOW_ID',
0,
comment='Pointer to spectralwindow table')
desc = tableutil.maketabdesc([col1, col2, col3])
tb = table("%s/DATA_DESCRIPTION" % filename, desc, nrow=nint, ack=False)
tb.putcol('FLAG_ROW', [
0,
] * nint, 0, nint)
tb.putcol('POLARIZATION_ID', [
0,
] * nint, 0, nint)
tb.putcol('SPECTRAL_WINDOW_ID', [
0,
] * nint, 0, nint)
tb.flush()
tb.close()
def _write_misc_required_tables(filename, config):
station = config.station
nant = config.nant
nbl = config.nbl
tint = config.tint
freq = config.freq
nchan = config.nchan
pols = config.pols
npol = config.npol
nint = config.nint
# Flag command
col1 = tableutil.makescacoldesc(
'TIME',
0.0,
comment='Midpoint of interval for which this flag is valid',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
col2 = tableutil.makescacoldesc(
'INTERVAL',
0.0,
comment='Time interval for which this flag is valid',
keywords={'QuantumUnits': [
's',
]})
col3 = tableutil.makescacoldesc('TYPE',
'flag',
comment='Type of flag (FLAG or UNFLAG)')
col4 = tableutil.makescacoldesc('REASON', 'reason', comment='Flag reason')
col5 = tableutil.makescacoldesc('LEVEL',
0,
comment='Flag level - revision level')
col6 = tableutil.makescacoldesc('SEVERITY',
0,
comment='Severity code (0-10)')
col7 = tableutil.makescacoldesc(
'APPLIED',
False,
comment='True if flag has been applied to main table')
col8 = tableutil.makescacoldesc('COMMAND',
'command',
comment='Flagging command')
desc = tableutil.maketabdesc(
[col1, col2, col3, col4, col5, col6, col7, col8])
tb = table("%s/FLAG_CMD" % filename, desc, nrow=0, ack=False)
tb.flush()
tb.close()
# History
col1 = tableutil.makescacoldesc('TIME',
0.0,
comment='Timestamp of message',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
col2 = tableutil.makescacoldesc(
'OBSERVATION_ID',
0,
comment='Observation id (index in OBSERVATION table)')
col3 = tableutil.makescacoldesc('MESSAGE',
'message',
comment='Log message')
col4 = tableutil.makescacoldesc('PRIORITY',
'NORMAL',
comment='Message priority')
col5 = tableutil.makescacoldesc(
'ORIGIN',
'origin',
comment='(Source code) origin from which message originated')
col6 = tableutil.makescacoldesc('OBJECT_ID',
0,
comment='Originating ObjectID')
col7 = tableutil.makescacoldesc('APPLICATION',
'application',
comment='Application name')
col8 = tableutil.makearrcoldesc('CLI_COMMAND',
'command',
1,
comment='CLI command sequence')
col9 = tableutil.makearrcoldesc('APP_PARAMS',
'params',
1,
comment='Application parameters')
desc = tableutil.maketabdesc(
[col1, col2, col3, col4, col5, col6, col7, col8, col9])
tb = table("%s/HISTORY" % filename, desc, nrow=0, ack=False)
tb.flush()
tb.close()
# POINTING
col1 = tableutil.makescacoldesc('ANTENNA_ID', 0, comment='Antenna Id')
col2 = tableutil.makescacoldesc('TIME',
0.0,
comment='Time interval midpoint',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
col3 = tableutil.makescacoldesc('INTERVAL',
0.0,
comment='Time interval',
keywords={'QuantumUnits': [
's',
]})
col4 = tableutil.makescacoldesc('NAME',
'name',
comment='Pointing position name')
col5 = tableutil.makescacoldesc('NUM_POLY', 0, comment='Series order')
col6 = tableutil.makescacoldesc('TIME_ORIGIN',
0.0,
comment='Time origin for direction',
keywords={
'QuantumUnits': [
's',
],
'MEASINFO': {
'type': 'epoch',
'Ref': 'UTC'
}
})
col7 = tableutil.makearrcoldesc(
'DIRECTION',
0.0,
2,
comment='Antenna pointing direction as polynomial in time',
keywords={
'QuantumUnits': ['rad', 'rad'],
'MEASINFO': {
'type': 'direction',
'Ref': 'J2000'
}
})
col8 = tableutil.makearrcoldesc(
'TARGET',
0.0,
2,
comment='target direction as polynomial in time',
keywords={
'QuantumUnits': ['rad', 'rad'],
'MEASINFO': {
'type': 'direction',
'Ref': 'J2000'
}
})
col9 = tableutil.makescacoldesc(
'TRACKING', True, comment='Tracking flag - True if on position')
desc = tableutil.maketabdesc(
[col1, col2, col3, col4, col5, col6, col7, col8, col9])
tb = table("%s/POINTING" % filename, desc, nrow=0, ack=False)
tb.flush()
tb.close()
# Processor
col1 = tableutil.makescacoldesc('TYPE', 'type', comment='Processor type')
col2 = tableutil.makescacoldesc('SUB_TYPE',
'subtype',
comment='Processor sub type')
col3 = tableutil.makescacoldesc('TYPE_ID', 0, comment='Processor type id')
col4 = tableutil.makescacoldesc('MODE_ID', 0, comment='Processor mode id')
col5 = tableutil.makescacoldesc('FLAG_ROW', False, comment='flag')
desc = tableutil.maketabdesc([col1, col2, col3, col4, col5])
tb = table("%s/PROCESSOR" % filename, desc, nrow=0, ack=False)
tb.flush()
tb.close()
# State
col1 = tableutil.makescacoldesc('SIG',
True,
comment='True for a source observation')
col2 = tableutil.makescacoldesc('REF',
False,
comment='True for a reference observation')
col3 = tableutil.makescacoldesc('CAL',
0.0,
comment='Noise calibration temperature',
keywords={'QuantumUnits': [
'K',
]})
col4 = tableutil.makescacoldesc('LOAD',
0.0,
comment='Load temperature',
keywords={'QuantumUnits': [
'K',
]})
col5 = tableutil.makescacoldesc(
'SUB_SCAN', 0, comment='Sub scan number, relative to scan number')
col6 = tableutil.makescacoldesc(
'OBS_MODE', 'mode', comment='Observing mode, e.g., OFF_SPECTRUM')
col7 = tableutil.makescacoldesc('FLAG_ROW', False, comment='Row flag')
desc = tableutil.maketabdesc([col1, col2, col3, col4, col5, col6, col7])
tb = table("%s/STATE" % filename, desc, nrow=0, ack=False)
tb.flush()
tb.close()
def _write_spectralwindow_table(filename, config):
"""
Write the spectral window table.
"""
station = config.station
nant = config.nant
nbl = config.nbl
tint = config.tint
freq = config.freq
nchan = config.nchan
chan_bw = config.chan_bw
pols = config.pols
npol = config.npol
nint = config.nint
# Spectral Window
col1 = tableutil.makescacoldesc('MEAS_FREQ_REF',
0,
comment='Frequency Measure reference')
col2 = tableutil.makearrcoldesc(
'CHAN_FREQ',
0.0,
1,
comment='Center frequencies for each channel in the data matrix',
keywords={
'QuantumUnits': [
'Hz',
],
'MEASINFO': {
'type':
'frequency',
'VarRefCol':
'MEAS_FREQ_REF',
'TabRefTypes': [
'REST', 'LSRK', 'LSRD', 'BARY', 'GEO', 'TOPO', 'GALACTO',
'LGROUP', 'CMB', 'Undefined'
],
'TabRefCodes':
numpy.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 64],
dtype=numpy.uint32)
}
})
col3 = tableutil.makescacoldesc(
'REF_FREQUENCY',
freq[0],
comment='The reference frequency',
keywords={
'QuantumUnits': [
'Hz',
],
'MEASINFO': {
'type':
'frequency',
'VarRefCol':
'MEAS_FREQ_REF',
'TabRefTypes': [
'REST', 'LSRK', 'LSRD', 'BARY', 'GEO', 'TOPO', 'GALACTO',
'LGROUP', 'CMB', 'Undefined'
],
'TabRefCodes':
numpy.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 64],
dtype=numpy.uint32)
}
})
col4 = tableutil.makearrcoldesc('CHAN_WIDTH',
0.0,
1,
comment='Channel width for each channel',
keywords={'QuantumUnits': [
'Hz',
]})
col5 = tableutil.makearrcoldesc(
'EFFECTIVE_BW',
0.0,
1,
comment='Effective noise bandwidth of each channel',
keywords={'QuantumUnits': [
'Hz',
]})
col6 = tableutil.makearrcoldesc(
'RESOLUTION',
0.0,
1,
comment='The effective noise bandwidth for each channel',
keywords={'QuantumUnits': [
'Hz',
]})
col7 = tableutil.makescacoldesc('FLAG_ROW', False, comment='flag')
col8 = tableutil.makescacoldesc('FREQ_GROUP', 1, comment='Frequency group')
col9 = tableutil.makescacoldesc('FREQ_GROUP_NAME',
"group1",
comment='Frequency group name')
col10 = tableutil.makescacoldesc('IF_CONV_CHAIN',
0,
comment='The IF conversion chain number')
col11 = tableutil.makescacoldesc('NAME',
"%i channels" % nchan,
comment='Spectral window name')
col12 = tableutil.makescacoldesc('NET_SIDEBAND', 0, comment='Net sideband')
col13 = tableutil.makescacoldesc('NUM_CHAN',
0,
comment='Number of spectral channels')
col14 = tableutil.makescacoldesc(
'TOTAL_BANDWIDTH',
0.0,
comment='The total bandwidth for this window',
keywords={'QuantumUnits': [
'Hz',
]})
desc = tableutil.maketabdesc([
col1, col2, col3, col4, col5, col6, col7, col8, col9, col10, col11,
col12, col13, col14
])
tb = table("%s/SPECTRAL_WINDOW" % filename, desc, nrow=1, ack=False)
tb.putcell('MEAS_FREQ_REF', 0, 0)
tb.putcell('CHAN_FREQ', 0, freq)
tb.putcell('REF_FREQUENCY', 0, freq[0])
tb.putcell('CHAN_WIDTH', 0, [
chan_bw,
] * nchan)
tb.putcell('EFFECTIVE_BW', 0, [
chan_bw,
] * nchan)
tb.putcell('RESOLUTION', 0, [
chan_bw,
] * nchan)
tb.putcell('FLAG_ROW', 0, False)
tb.putcell('FREQ_GROUP', 0, 1)
tb.putcell('FREQ_GROUP_NAME', 0, 'group%i' % 1)
tb.putcell('IF_CONV_CHAIN', 0, 0)
tb.putcell('NAME', 0, "IF %i, %i channels" % (1, nchan))
tb.putcell('NET_SIDEBAND', 0, 0)
tb.putcell('NUM_CHAN', 0, nchan)
tb.putcell('TOTAL_BANDWIDTH', 0, nchan * chan_bw)
tb.flush()
tb.close()