def test_compare_headers():
uvf = LedaFits('data/test_lalc.fitsidi')
lalc = LedaFits()
lalc.filename = 'data/test_lalc.LA'
lalc.readLfile(n_ant=256, n_chans=109)
ok_count = 0
# Check all header values
h1("Testing header keywords")
h2("Common")
ok_count += compare_dicts(uvf.h_common, lalc.h_common)
h2("Parameters")
ok_count += compare_dicts(uvf.h_params, lalc.h_params)
h2("Antenna")
ok_count += compare_dicts(uvf.h_antenna, lalc.h_antenna)
h2("Array Geometry")
ok_count += compare_dicts(uvf.h_array_geometry, lalc.h_array_geometry)
h2("Frequency")
ok_count += compare_dicts(uvf.h_frequency, lalc.h_frequency)
h2("Source")
ok_count += compare_dicts(uvf.h_source, lalc.h_source)
h2("UV DATA")
ok_count += compare_dicts(uvf.h_uv_data, lalc.h_uv_data)
assert ok_count == 7
def test_hdf():
idi = LedaFits('data/test_lalc.fitsidi')
idi.exportHdf5('data/test_lalc.hdf')
hdf = LedaFits('data/test_lalc.hdf')
ok_count = 0
# Check all header values
h1("Testing header keywords")
h2("Common")
ok_count += compare_dicts(idi.h_common, hdf.h_common)
h2("Params")
ok_count += compare_dicts(idi.h_params, hdf.h_params)
h2("Antenna")
ok_count += compare_dicts(idi.h_antenna, hdf.h_antenna)
h2("Array Geometry")
ok_count += compare_dicts(idi.h_array_geometry, hdf.h_array_geometry)
h2("Frequency")
ok_count += compare_dicts(idi.h_frequency, hdf.h_frequency)
h2("Source")
ok_count += compare_dicts(idi.h_source, hdf.h_source)
h2("UV DATA")
ok_count += compare_dicts(idi.h_uv_data, hdf.h_uv_data)
h1("Testing data tables")
h2("Antenna")
ok_count += compare_dicts(idi.d_antenna, hdf.d_antenna)
h2("Array Geometry")
ok_count += compare_dicts(idi.d_array_geometry, hdf.d_array_geometry)
h2("Frequency")
ok_count += compare_dicts(idi.d_frequency, hdf.d_frequency)
h2("Source")
ok_count += compare_dicts(idi.d_source, hdf.d_source)
h2("UV DATA")
ok_count += compare_dicts(idi.d_uv_data, hdf.d_uv_data)
assert ok_count == 12
print "PASS: All header and table data match"
try:
assert str(hdf.__repr__()) == str(idi.__repr__())
print "PASS: __repr__ match"
except:
print "ERROR: __repr__ do not match"
print str(hdf.__repr__())
print str(idi.__repr__())
print hdf.h_uv_data
print idi.h_uv_data
print hdf.h_array_geometry
print idi.h_array_geometry
raise
def test_lalc():
""" Check that LA->interfits->LA->interfits creates identical data. """
lalc = LedaFits()
lalc.filename = 'data/test_lalc.LA'
lalc.readLfile(n_ant=256, n_chans=109)
lalc.exportFitsidi('data/test_lalc_direct.fitsidi')
uvf = LedaFits('data/test_lalc_direct.fitsidi')
ok_count = 0
# Check all header values
h1("Testing header keywords")
h2("Common")
ok_count += compare_dicts(uvf.h_common, lalc.h_common)
h2("Parameters")
ok_count += compare_dicts(uvf.h_params, lalc.h_params)
h2("Antenna")
ok_count += compare_dicts(uvf.h_antenna, lalc.h_antenna)
h2("Array Geometry")
ok_count += compare_dicts(uvf.h_array_geometry, lalc.h_array_geometry)
h2("Frequency")
ok_count += compare_dicts(uvf.h_frequency, lalc.h_frequency)
h2("Source")
ok_count += compare_dicts(uvf.h_source, lalc.h_source)
h2("UV DATA")
ok_count += compare_dicts(uvf.h_uv_data, lalc.h_uv_data)
h1("Testing data tables")
h2("Antenna")
ok_count += compare_dicts(uvf.d_antenna, lalc.d_antenna)
h2("Array Geometry")
ok_count += compare_dicts(uvf.d_array_geometry, lalc.d_array_geometry)
h2("Frequency")
ok_count += compare_dicts(uvf.d_frequency, lalc.d_frequency)
h2("Source")
ok_count += compare_dicts(uvf.d_source, lalc.d_source)
assert ok_count == 11
try:
assert repr(lalc) == repr(uvf)
except AssertionError:
print "ERROR: __repr__ outputs do not match"
print repr(uvf)
print repr(lalc)
os.remove('data/test_lalc_direct.fitsidi')
def main(args):
# Parse the command line
config = parseConfig(args)
filenames = config['args']
# Inspect the files to try and figure out what is what
metadataList = []
for filename in filenames:
uvw = LedaFits(verbose=False)
metadataList.append( (filename, uvw.inspectFile(filename)) )
# Group the files by start time and save the filenames and frequency ranges
groups = []
for filename,metadata in metadataList:
tStart = metadata['tstart']
chanBW = metadata['chanbw']
freqStart = metadata['reffreq'] + (1 - metadata['refpixel'])*chanBW
freqStop = metadata['reffreq'] + (metadata['nchan'] - metadata['refpixel'])*chanBW
## See if this file represents the start of a new group or not
new = True
for group in groups:
if tStart == group[0]:
new = False
group[1].append(filename)
group[2].append((freqStart,freqStop,chanBW))
break
## A new group has been found
if new:
group = [tStart, [filename,], [(freqStart,freqStop,chanBW),]]
groups.append(group)
# Report
print "Got %i files with groupings:" % len(filenames)
validity = []
for i,group in enumerate(groups):
## Sort the group by frequency
freqs = []
for start,stop,cbw in group[2]:
freqs.append(start)
freqOrder = [j[0] for j in sorted(enumerate(freqs), key=lambda x:x[1])]
group[1] = [group[1][j] for j in freqOrder]
group[2] = [group[2][j] for j in freqOrder]
## Report and validate
print " Group #%i" % (i+1,)
print " -> start time %s (%.2f)" % (datetime.utcfromtimestamp(group[0]), group[0])
valid = True
for j,(name,(start,stop,chanBW)) in enumerate(zip(group[1], group[2])):
### Check for frequency continuity
try:
freqDiff = start - oldStop
except NameError:
freqDiff = chanBW
oldStop = stop
if freqDiff != chanBW:
valid = False
### Report on this file
print " %i: %s from %.2f to %.2f MHz" % (j+1, os.path.basename(name), start/1e6, stop/1e6)
validity.append(valid)
print " -> valid set? %s" % valid
## Reset the validity between groups
del oldStop
print " "
# Combine
for i,(valid,group) in enumerate(zip(validity,groups)):
print "Combining group #%i..." % (i+1,)
## Jump over invalid groups
if not valid:
print " -> invalid, skipping"
continue
## Read in the files
uvws = []
for filename in group[1]:
uvws.append( LedaFits(filename, verbose=False) )
## Build the output name
obsDate = datetime.strptime(uvws[0].date_obs, "%Y-%m-%dT%H:%M:%S")
if len(group[1]) > 1:
outname = "%s_%s_%s_comb%i.FITS_" % (uvws[0].instrument, uvws[0].telescope, obsDate.strftime("%Y%m%d%H%M%S"), len(uvws))
else:
obsFreq = int((uvws[0].formatFreqs()).mean() / 1e6)
outname = "%s_%s_%s_%iMHz.FITS_" % (uvws[0].instrument, uvws[0].telescope, obsDate.strftime("%Y%m%d%H%M%S"), obsFreq)
print " -> group file basename will be '%s*'" % outname
## Make a note of lowest frequency value
freq_min = numpy.min(uvws[0].formatFreqs())
## Concatenate together the various FLUX sets
if len(uvws) > 1:
timeBL = uvws[0].d_uv_data["FLUX"].shape[0]
freqPolComp = uvws[0].d_uv_data["FLUX"].shape[1]
new_uv_data = numpy.zeros((timeBL, freqPolComp*len(group[1])), dtype=uvws[0].d_uv_data["FLUX"].dtype)
for i,uvw in enumerate(uvws):
new_uv_data[:,i*freqPolComp:(i+1)*freqPolComp] = 1.0*uvw.d_uv_data["FLUX"]
uvws[0].d_uv_data["FLUX"] = new_uv_data
## Overwrite frequency axis keywords so that we can export UV_DATA table correctly
uvws[0].h_common["REF_FREQ"] = freq_min
uvws[0].h_common["REF_PIXL"] = 1
uvws[0].h_common["NO_CHAN"] *= len(group[1])
uvws[0].h_params["NCHAN"] = uvws[0].h_common["NO_CHAN"]
uvws[0].d_frequency["TOTAL_BANDWIDTH"] *= len(group[1])
## Remove the other LedaFits instances since we only need the first one now
while len(uvws) > 1:
del uvws[-1]
## Add in the UVW coordinates
uvws[0].generateUVW(src='ZEN', use_stored=False, update_src=True)
if config['applyPhasing']:
## Apply the cable delays
uvws[0].apply_cable_delays()
## Phase to zenith
uvws[0].phase_to_src(src='ZEN')
else:
## Update the outname to reflect the fact that no phasing as been applied
outname = "%sNoPhasing_" % outname
## Save
if config['fullRes']:
### Extract all possible baselines
bls = getAllBaselines(uvws[0])
uvws[0].select_baselines(bls)
### Verify
uvws[0].verify()
### Save as FITS IDI
uvws[0].exportFitsidi(outname+'1')
### Cleanup the associated XML file
try:
xmlname = outname+'1.xml'
os.unlink(xmlname)
except OSError:
pass
if config['totalPower']:
### Extract the total power at full resolution
bls = getTotalPowerBaselines(uvws[0])
uvws[0].select_baselines(bls)
### Verify
uvws[0].verify()
### Save as FITS IDI
uvws[0].exportFitsidi(outname+'TP')
### Cleanup the associated XML file
try:
xmlname = outname+'TP.xml'
os.unlink(xmlname)
except OSError:
pass
if config['switching']:
### Extract the switching baselines at full resolution
bls = getSwitchingBaselines(uvws[0])
uvws[0].select_baselines(bls)
### Verify
uvws[0].verify()
### Save as FITS IDI
uvws[0].exportFitsidi(outname+'SW')
### Cleanup the associated XML file
try:
xmlname = outname+'SW.xml'
os.unlink(xmlname)
except OSError:
pass
if config['average']:
### Extract the static baselines
bls = getStaticBaselines(uvws[0])
uvws[0].select_baselines(bls)
### Decimate within a try...expect block to deal with bad decimation parameters
try:
uvws[0].average_time_frequency(config['tDecim'], config['sDecim'], mode='nearest')
except ValueError, e:
print "ERROR: %s, skipping" % str(e)
continue
### Verify
uvws[0].verify()
### Save as FITS IDI
uvws[0].exportFitsidi(outname+'AV')
### Cleanup the associated XML file
try:
xmlname = outname+'AV.xml'
os.unlink(xmlname)
except OSError:
pass
## Cleanup
del uvws[0]
gc.collect()
def test_compare_flux():
uvf = LedaFits('data/test_lalc.fitsidi')
lalc = LedaFits()
lalc.filename = 'data/test_lalc.LA'
lalc.readLfile(n_ant=256, n_chans=109)
lalc_flux = lalc.d_uv_data['FLUX']
uvf_flux = uvf.d_uv_data['FLUX']
lalc_bls = lalc.d_uv_data['BASELINE']
uvf_bls = uvf.d_uv_data['BASELINE']
assert np.allclose(lalc_bls, uvf_bls)
print "PASS: BASELINE IDS MATCH"
assert lalc_flux.shape == uvf_flux.shape
print "PASS: FLUX SHAPE MATCH"
print lalc_flux.shape
print uvf_flux.shape
try:
assert lalc_flux.dtype == uvf_flux.dtype
print "PASS: FLUX DTYPE MATCH"
except AssertionError:
print "ERROR: DTYPES DO NOT MATCH"
print lalc_flux.dtype, uvf_flux.dtype
print "Testing flux data..."
for row in range(0, lalc_flux.shape[0]):
if not row % 1000:
print "\t %i of %i"%(row, lalc_flux.shape[0])
try:
xxl = lalc_flux[row][::8]**2 + lalc_flux[row][1::8]**2
yyl = lalc_flux[row][2::8]**2 + lalc_flux[row][3::8]**2
xyl = lalc_flux[row][4::8]**2 + lalc_flux[row][5::8]**2
yxl = lalc_flux[row][6::8]**2 + lalc_flux[row][7::8]**2
xxu = uvf_flux[row][::8]**2 + uvf_flux[row][1::8]**2
yyu = uvf_flux[row][2::8]**2 + uvf_flux[row][3::8]**2
xyu = uvf_flux[row][4::8]**2 + uvf_flux[row][5::8]**2
yxu = uvf_flux[row][6::8]**2 + uvf_flux[row][7::8]**2
assert np.allclose(xxl, xxu)
assert np.allclose(yyl, yyu)
assert np.allclose(xyl, xyu)
assert np.allclose(yxl, yxu)
except AssertionError:
print "ERROR: Flux values do not agree"
print uvf_flux[row, 0:10]
print lalc_flux[row, 0:10]
raise
print "PASS: FLUX DATA MATCH"
print "Testing stokes generator..."
xxl, yyl, xyl, yxl = lalc.formatStokes()
xxu, yyu, xyu, yxu = uvf.formatStokes()
try:
assert np.allclose(np.abs(xxl), np.abs(xxu))
assert np.allclose(np.abs(yyl), np.abs(yyu))
assert np.allclose(np.abs(xyl), np.abs(xyu))
assert np.allclose(np.abs(yxl), np.abs(yxu))
except AssertionError:
print "ERROR: Flux values do not agree"
raise
print "PASS: FLUX DATA STOKES FORMAT"
def main(args):
filenames = args
# Inspect the files to try and figure out what is what
metadataList = []
for filename in filenames:
uvw = LedaFits()
metadataList.append( (filename, uvw.inspectFile(filename)) )
# Group the files by start time and save the filenames and frequency ranges
groups = []
for filename,metadata in metadataList:
tStart = metadata['tstart']
chanBW = metadata['chanbw']
freqStart = metadata['reffreq'] + (1 - metadata['refpixel'])*chanBW
freqStop = metadata['reffreq'] + (metadata['nchan'] - metadata['refpixel'])*chanBW
## See if this file represents the start of a new group or not
new = True
for group in groups:
if tStart == group[0]:
new = False
group[1].append(filename)
group[2].append((freqStart,freqStop,chanBW))
break
## A new group has been found
if new:
group = [tStart, [filename,], [(freqStart,freqStop,chanBW),]]
groups.append(group)
# Report
print "Got %i files with groupings:" % len(filenames)
validity = []
for i,group in enumerate(groups):
## Sort the group by frequency
freqs = []
for start,stop,cbw in group[2]:
freqs.append(start)
freqOrder = [j[0] for j in sorted(enumerate(freqs), key=lambda x:x[1])]
group[1] = [group[1][j] for j in freqOrder]
group[2] = [group[2][j] for j in freqOrder]
## Report and validate
print " Group #%i" % (i+1,)
print " -> start time %s (%.2f)" % (datetime.utcfromtimestamp(group[0]), group[0])
valid = True
for j,(name,(start,stop,chanBW)) in enumerate(zip(group[1], group[2])):
### Check for frequency continuity
try:
freqDiff = start - oldStop
except NameError:
freqDiff = chanBW
oldStop = stop
if freqDiff != chanBW:
valid = False
### Report on this file
print " %i: %s from %.2f to %.2f MHz" % (j+1, os.path.basename(name), start/1e6, stop/1e6)
validity.append(valid)
print " -> valid set? %s" % valid
## Reset the validity between groups
del oldStop
print " "
# Combine
for i,(valid,group) in enumerate(zip(validity,groups)):
print "Combining group #%i..." % (i+1,)
## Jump over invalid groups
if not valid:
print " -> invalid, skipping"
continue
## Read in the files
uvws = []
for filename in group[1]:
uvws.append( LedaFits(filename) )
## Make a note of lowest frequency value
freq_min = numpy.min(uvws[0].formatFreqs())
## Concatenate together the various FLUX sets
if len(uvws) > 1:
timeBL = uvws[0].d_uv_data["FLUX"].shape[0]
freqPolComp = uvws[0].d_uv_data["FLUX"].shape[1]
new_uv_data = numpy.zeros((timeBL, freqPolComp*len(group[1])), dtype=uvws[0].d_uv_data["FLUX"].dtype)
for i,uvw in enumerate(uvws):
new_uv_data[:,i*freqPolComp:(i+1)*freqPolComp] = 1.0*uvw.d_uv_data["FLUX"]
uvws[0].d_uv_data["FLUX"] = new_uv_data
## Overwrite frequency axis keywords so that we can export UV_DATA table correctly
uvws[0].h_common["REF_FREQ"] = freq_min
uvws[0].h_common["REF_PIXL"] = 1
uvws[0].h_common["NO_CHAN"] *= len(group[1])
uvws[0].h_params["NCHAN"] = uvws[0].h_common["NO_CHAN"]
uvws[0].d_frequency["TOTAL_BANDWIDTH"] *= len(group[1])
## Remove the other LedaFits instances since we only need the first one now
while len(uvws) > 1:
del uvws[-1]
## Load in the current antenna mapping to associate antenna IDs with stand names
ant_ids = uvws[0].d_array_geometry['NOSTA']
ant_nms = [int(_annameRE.match(nm).group('id')) for nm in uvws[0].d_array_geometry['ANNAME']]
## Figure out which antenna ID each switching outrigger is
### Stand numbers for the switching outriggers
outriggers = [35, 257, 259]
ant_ids_outriggers = []
for outrigger in outriggers:
ant_ids_outriggers.append( ant_ids[ant_nms.index(outrigger)] )
## Extract
import pylab
pols = uvws[0].stokes_axis
freqs = uvws[0].formatFreqs()
for stand,ant_id in zip(outriggers, ant_ids_outriggers):
print " -> Extracting data for Stand #%i..." % stand
timestamps, data = uvws[0].extractTotalPower(ant_id, timestamps=True)
tRel = timestamps - timestamps[0]
tRel *= 24*3600 # Timestamps in seconds
data = data.real # Autocorrelations should be real
### Plot mean power over time
pylab.figure()
for i in xrange(data.shape[0]):
pylab.plot(tRel, data[i,:,:].mean(axis=-1), linestyle='-', marker='o', label='%i-%s' % (stand, pols[i]))
pylab.xlabel('Time [s]')
pylab.ylabel('Mean PSD [arb.]')
pylab.legend()
pylab.draw()
### Plot the spectra
pylab.figure()
for i in xrange(data.shape[0]):
pylab.subplot(2, 2, i+1)
for j in xrange(data.shape[1]):
pylab.plot(freqs/1e6, data[i,j,:])
pylab.title("%i-%s" % (stand, pols[i]))
pylab.xlabel('Frequency [MHz]')
pylab.ylabel('PSD [arb.]')
pylab.draw()
pylab.show()
def test_lalc_json():
lalc = LedaFits()
lalc.filename = 'data/test_lalc.LA'
lalc.readLfile(n_ant=256, n_chans=109)
lalc.readJson('data/test_lalc_json/d_antenna.json')
lalc.generateUVW()
uu = lalc.d_uv_data["UU"]
vv = lalc.d_uv_data["VV"]
ww = lalc.d_uv_data["WW"]
#print uu
#print len(uu)
print "Checking data...",
try:
assert len(uu) == len(vv) == len(ww)
except:
print len(uu), len(vv), len(ww)
raise
try:
assert len(uu) == len(lalc.d_uv_data["BASELINE"])
except AssertionError:
print len(uu), len(lalc.d_uv_data["BASELINE"])
raise
try:
assert len(uu) == len(lalc.d_uv_data["FLUX"])
except:
print len(uu), len(lalc.d_uv_data["BASELINE"])
raise
print "OK"
lalc.remove_miriad_baselines()
h2("Exporting sewed data...")
lalc.exportFitsidi('data/test_lalc_uvw.fitsidi', '../config/config.xml')
def remove_miriad_lalc():
uvf = LedaFits('data/test_lalc.fitsidi')
uvf.remove_miriad_baselines()
uvf.exportFitsidi('data/test_lalc_255.fitsidi')
def test_compare_idi_lalc_json():
lalc = LedaFits()
lalc.filename = 'data/test_lalc.LA'
lalc.readLfile(n_ant=256, n_chans=109)
lalc.readJson('data/test_lalc_json/d_antenna.json')
lalc.generateUVW()