def test_default_cols(self):
"""hanningsmooth: Default datacolumn=all and MMS output"""
self.createMMS(self.msfile, column="all")
self.outputms = "hannall.ms"
hanningsmooth(vis=self.testmms, outputvis=self.outputms)
self.assertTrue(ParallelDataHelper.isParallelMS(self.outputms), "Output should be an MMS")
# Should have all scratch columns in output
cd = th.getColDesc(self.outputms, "DATA")
self.assertGreater(len(cd), 0, "DATA column does not exist")
cc = th.getColDesc(self.outputms, "CORRECTED_DATA")
self.assertGreater(len(cc), 0, "CORRECTED_DATA does not exist")
# Now repeat the above steps but create an output MS by setting keepmms=False
os.system("rm -rf " + self.outputms)
hanningsmooth(vis=self.testmms, outputvis=self.outputms, keepmms=False)
self.assertFalse(ParallelDataHelper.isParallelMS(self.outputms), "Output should be a normal MS")
# Should have all scratch columns in output
cd = th.getColDesc(self.outputms, "DATA")
self.assertGreater(len(cd), 0, "DATA column does not exist")
cc = th.getColDesc(self.outputms, "CORRECTED_DATA")
self.assertGreater(len(cc), 0, "CORRECTED_DATA does not exist")
def test_default_cols(self):
'''hanningsmooth: Default datacolumn=all and MMS output'''
self.createMMS(self.msfile, column='all')
self.outputms = 'hannall.ms'
hanningsmooth(vis=self.testmms, outputvis=self.outputms)
self.assertTrue(ParallelDataHelper.isParallelMS(self.outputms),
'Output should be an MMS')
# Should have all scratch columns in output
cd = th.getColDesc(self.outputms, 'DATA')
self.assertGreater(len(cd), 0, 'DATA column does not exist')
cc = th.getColDesc(self.outputms, 'CORRECTED_DATA')
self.assertGreater(len(cc), 0, 'CORRECTED_DATA does not exist')
# Now repeat the above steps but create an output MS by setting keepmms=False
os.system('rm -rf ' + self.outputms)
hanningsmooth(vis=self.testmms, outputvis=self.outputms, keepmms=False)
self.assertFalse(ParallelDataHelper.isParallelMS(self.outputms),
'Output should be a normal MS')
# Should have all scratch columns in output
cd = th.getColDesc(self.outputms, 'DATA')
self.assertGreater(len(cd), 0, 'DATA column does not exist')
cc = th.getColDesc(self.outputms, 'CORRECTED_DATA')
self.assertGreater(len(cc), 0, 'CORRECTED_DATA does not exist')
def test2(self):
'''hanningsmooth - Test 2: Check that output MS is created'''
self.outputms = 'hann2.ms'
hanningsmooth(vis=self.msfile,
outputvis=self.outputms,
datacolumn='corrected')
# Smoothed data should be saved in DATA column of outupt MS
self.assertTrue(os.path.exists(self.outputms))
def test1(self):
"""hanningsmooth - Test 1: Wrong input MS should raise an exception"""
msfile = 'badmsfile'
self.outputms = 'none.ms'
try:
hanningsmooth(vis=msfile)
except exceptions.RuntimeError, instance:
print 'Expected error: %s' % instance
def test1(self):
"""hanningsmooth - Test 1: Wrong input MS should raise an exception"""
msfile = "badmsfile"
self.outputms = "none.ms"
try:
hanningsmooth(vis=msfile)
except exceptions.RuntimeError, instance:
print "Expected error: %s" % instance
def test_corrected_col(self):
'''hanningsmooth: Apply smoothing in CORRECTED column'''
self.outputms = 'hanncorr.ms'
# check correct flagging before (just for one row as a sample)
flag_col = th.getVarCol(self.msfile, 'FLAG')
self.assertTrue(flag_col['r1'][0][0] == [False])
self.assertTrue(flag_col['r1'][0][1] == [False])
self.assertTrue(flag_col['r1'][0][3838] == [False])
self.assertTrue(flag_col['r1'][0][3839] == [False])
# input column
data_col = th.getVarCol(self.msfile, 'CORRECTED_DATA')
hanningsmooth(vis=self.msfile,
outputvis=self.outputms,
datacolumn='corrected')
# output smoothed column
corr_col = th.getVarCol(self.outputms, 'DATA')
nrows = len(corr_col)
# check correct flagging after (just for one row as a sample)
flag_col = th.getVarCol(self.outputms, 'FLAG')
self.assertTrue(flag_col['r1'][0][0] == [True])
self.assertTrue(flag_col['r1'][0][1] == [False])
self.assertTrue(flag_col['r1'][0][3838] == [False])
self.assertTrue(flag_col['r1'][0][3839] == [True])
# Loop over every 2nd row,pol and get the data for each channel
max = 1e-04
for i in range(1, nrows, 2):
row = 'r%s' % i
# polarization is 0-1
for pol in range(0, 2):
# array's channels is 0-3840
for chan in range(1, 3839):
# channels must start from second and end before the last
data = data_col[row][pol][chan]
dataB = data_col[row][pol][chan - 1]
dataA = data_col[row][pol][chan + 1]
Smoothed = th.calculateHanning(dataB, data, dataA)
CorData = corr_col[row][pol][chan]
# Check the difference
self.assertTrue(
abs(CorData - Smoothed) < max,
'CorData=%s Smoothed=%s in row=%s pol=%s chan=%s' %
(CorData, Smoothed, row, pol, chan))
def test_corrected_col(self):
"""hanningsmooth: Apply smoothing in CORRECTED column"""
self.outputms = "hanncorr.ms"
# check correct flagging before (just for one row as a sample)
flag_col = th.getVarCol(self.msfile, "FLAG")
self.assertTrue(flag_col["r1"][0][0] == [False])
self.assertTrue(flag_col["r1"][0][1] == [False])
self.assertTrue(flag_col["r1"][0][3838] == [False])
self.assertTrue(flag_col["r1"][0][3839] == [False])
# input column
data_col = th.getVarCol(self.msfile, "CORRECTED_DATA")
hanningsmooth(vis=self.msfile, outputvis=self.outputms, datacolumn="corrected")
# output smoothed column
corr_col = th.getVarCol(self.outputms, "DATA")
nrows = len(corr_col)
# check correct flagging after (just for one row as a sample)
flag_col = th.getVarCol(self.outputms, "FLAG")
self.assertTrue(flag_col["r1"][0][0] == [True])
self.assertTrue(flag_col["r1"][0][1] == [False])
self.assertTrue(flag_col["r1"][0][3838] == [False])
self.assertTrue(flag_col["r1"][0][3839] == [True])
# Loop over every 2nd row,pol and get the data for each channel
max = 1e-04
for i in range(1, nrows, 2):
row = "r%s" % i
# polarization is 0-1
for pol in range(0, 2):
# array's channels is 0-3840
for chan in range(1, 3839):
# channels must start from second and end before the last
data = data_col[row][pol][chan]
dataB = data_col[row][pol][chan - 1]
dataA = data_col[row][pol][chan + 1]
Smoothed = th.calculateHanning(dataB, data, dataA)
CorData = corr_col[row][pol][chan]
# Check the difference
self.assertTrue(
abs(CorData - Smoothed) < max,
"CorData=%s Smoothed=%s in row=%s pol=%s chan=%s" % (CorData, Smoothed, row, pol, chan),
)
def test3(self):
'''hanningsmooth - Test 3: Check theoretical and calculated values on non-existing CORRECTED column'''
self.outputms = 'hann3.ms'
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.msfile, 'FLAG')
self.assertTrue(flag_col['r1'][0][0] == [False])
self.assertTrue(flag_col['r1'][0][1] == [False])
self.assertTrue(flag_col['r1'][0][61] == [False])
self.assertTrue(flag_col['r1'][0][62] == [False])
# It should fall-back and use the input DATA column
hanningsmooth(vis=self.msfile,
outputvis=self.outputms,
datacolumn='corrected')
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.outputms, 'FLAG')
self.assertTrue(flag_col['r1'][0][0] == [True])
self.assertTrue(flag_col['r1'][0][1] == [False])
self.assertTrue(flag_col['r1'][0][61] == [False])
self.assertTrue(flag_col['r1'][0][62] == [True])
data_col = th.getVarCol(self.msfile, 'DATA')
corr_col = th.getVarCol(self.outputms, 'DATA')
nrows = len(corr_col)
# Loop over every 2nd row,pol and get the data for each channel
max = 1e-05
for i in range(1, nrows, 2):
row = 'r%s' % i
# polarization is 0-1
for pol in range(0, 2):
# array's channels is 0-63
for chan in range(1, 62):
# channels must start from second and end before the last
data = data_col[row][pol][chan]
dataB = data_col[row][pol][chan - 1]
dataA = data_col[row][pol][chan + 1]
Smoothed = th.calculateHanning(dataB, data, dataA)
CorData = corr_col[row][pol][chan]
# Check the difference
self.assertTrue(abs(CorData - Smoothed) < max)
def test6(self):
"""hanningsmooth - Test 6: Flagging should be correct with datacolumn==ALL"""
self.outputms = "hann6.ms"
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.msfile, "FLAG")
self.assertTrue(flag_col["r1"][0][0] == [False])
self.assertTrue(flag_col["r1"][0][1] == [False])
self.assertTrue(flag_col["r1"][0][61] == [False])
self.assertTrue(flag_col["r1"][0][62] == [False])
hanningsmooth(vis=self.msfile, outputvis=self.outputms, datacolumn="all")
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.outputms, "FLAG")
self.assertTrue(flag_col["r1"][0][0] == [True])
self.assertTrue(flag_col["r1"][0][1] == [False])
self.assertTrue(flag_col["r1"][0][61] == [False])
self.assertTrue(flag_col["r1"][0][62] == [True])
def test3(self):
"""hanningsmooth - Test 3: Check theoretical and calculated values on non-existing CORRECTED column"""
self.outputms = "hann3.ms"
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.msfile, "FLAG")
self.assertTrue(flag_col["r1"][0][0] == [False])
self.assertTrue(flag_col["r1"][0][1] == [False])
self.assertTrue(flag_col["r1"][0][61] == [False])
self.assertTrue(flag_col["r1"][0][62] == [False])
# It should fall-back and use the input DATA column
hanningsmooth(vis=self.msfile, outputvis=self.outputms, datacolumn="corrected")
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.outputms, "FLAG")
self.assertTrue(flag_col["r1"][0][0] == [True])
self.assertTrue(flag_col["r1"][0][1] == [False])
self.assertTrue(flag_col["r1"][0][61] == [False])
self.assertTrue(flag_col["r1"][0][62] == [True])
data_col = th.getVarCol(self.msfile, "DATA")
corr_col = th.getVarCol(self.outputms, "DATA")
nrows = len(corr_col)
# Loop over every 2nd row,pol and get the data for each channel
max = 1e-05
for i in range(1, nrows, 2):
row = "r%s" % i
# polarization is 0-1
for pol in range(0, 2):
# array's channels is 0-63
for chan in range(1, 62):
# channels must start from second and end before the last
data = data_col[row][pol][chan]
dataB = data_col[row][pol][chan - 1]
dataA = data_col[row][pol][chan + 1]
Smoothed = th.calculateHanning(dataB, data, dataA)
CorData = corr_col[row][pol][chan]
# Check the difference
self.assertTrue(abs(CorData - Smoothed) < max)
def test6(self):
'''hanningsmooth - Test 6: Flagging should be correct with datacolumn==ALL'''
self.outputms = 'hann6.ms'
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.msfile, 'FLAG')
self.assertTrue(flag_col['r1'][0][0] == [False])
self.assertTrue(flag_col['r1'][0][1] == [False])
self.assertTrue(flag_col['r1'][0][61] == [False])
self.assertTrue(flag_col['r1'][0][62] == [False])
hanningsmooth(vis=self.msfile,
outputvis=self.outputms,
datacolumn='all')
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.outputms, 'FLAG')
self.assertTrue(flag_col['r1'][0][0] == [True])
self.assertTrue(flag_col['r1'][0][1] == [False])
self.assertTrue(flag_col['r1'][0][61] == [False])
self.assertTrue(flag_col['r1'][0][62] == [True])
def test4(self):
'''hanningsmooth - Test 4: Theoretical and calculated values should be the same for MMS-case'''
# Split the input to decrease the running time
split(self.msfile,
outputvis='splithan.ms',
scan='1,2',
datacolumn='data')
self.msfile = 'splithan.ms'
# create a test MMS. It creates self.testmms
self.createMMS(self.msfile)
self.outputms = 'hann4.mms'
# check correct flagging (just for one row as a sample)
mslocal = mstool()
mslocal.open(self.msfile)
mslocal.sort('sorted.ms', [
'OBSERVATION_ID', 'ARRAY_ID', 'SCAN_NUMBER', 'FIELD_ID',
'DATA_DESC_ID', 'ANTENNA1', 'ANTENNA2', 'TIME'
])
mslocal.close()
self.msfile = 'sorted.ms'
flag_col = th.getVarCol(self.msfile, 'FLAG')
self.assertTrue(flag_col['r1'][0][0] == [False])
self.assertTrue(flag_col['r1'][0][1] == [False])
self.assertTrue(flag_col['r1'][0][61] == [False])
self.assertTrue(flag_col['r1'][0][62] == [False])
data_col = th.getVarCol(self.msfile, 'DATA')
hanningsmooth(vis=self.testmms,
outputvis=self.outputms,
datacolumn='data',
keepmms=True)
self.assertTrue(ParallelDataHelper.isParallelMS(self.outputms),
'Output should be an MMS')
# Sort the MMS
mslocal.open(self.outputms)
mslocal.sort('sorted.mms', [
'OBSERVATION_ID', 'ARRAY_ID', 'SCAN_NUMBER', 'FIELD_ID',
'DATA_DESC_ID', 'ANTENNA1', 'ANTENNA2', 'TIME'
])
mslocal.close()
self.outputms = 'sorted.mms'
corr_col = th.getVarCol(self.outputms, 'DATA')
nrows = len(corr_col)
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.outputms, 'FLAG')
self.assertTrue(flag_col['r1'][0][0] == [True])
self.assertTrue(flag_col['r1'][0][1] == [False])
self.assertTrue(flag_col['r1'][0][61] == [False])
self.assertTrue(flag_col['r1'][0][62] == [True])
# Loop over every 2nd row,pol and get the data for each channel
max = 1e-05
for i in range(1, nrows, 2):
row = 'r%s' % i
# polarization is 0-1
for pol in range(0, 2):
# array's channels is 0-63
for chan in range(1, 62):
# channels must start from second and end before the last
data = data_col[row][pol][chan]
dataB = data_col[row][pol][chan - 1]
dataA = data_col[row][pol][chan + 1]
Smoothed = th.calculateHanning(dataB, data, dataA)
CorData = corr_col[row][pol][chan]
# Check the difference
self.assertTrue(abs(CorData - Smoothed) < max)
def test2(self):
"""hanningsmooth - Test 2: Check that output MS is created"""
self.outputms = "hann2.ms"
hanningsmooth(vis=self.msfile, outputvis=self.outputms, datacolumn="corrected")
# Smoothed data should be saved in DATA column of outupt MS
self.assertTrue(os.path.exists(self.outputms))
def test4(self):
"""hanningsmooth - Test 4: Theoretical and calculated values should be the same for MMS-case"""
# Split the input to decrease the running time
split(self.msfile, outputvis="splithan.ms", scan="1,2", datacolumn="data")
self.msfile = "splithan.ms"
# create a test MMS. It creates self.testmms
self.createMMS(self.msfile)
self.outputms = "hann4.mms"
# check correct flagging (just for one row as a sample)
mslocal = mstool()
mslocal.open(self.msfile)
mslocal.sort(
"sorted.ms",
["OBSERVATION_ID", "ARRAY_ID", "SCAN_NUMBER", "FIELD_ID", "DATA_DESC_ID", "ANTENNA1", "ANTENNA2", "TIME"],
)
mslocal.close()
self.msfile = "sorted.ms"
flag_col = th.getVarCol(self.msfile, "FLAG")
self.assertTrue(flag_col["r1"][0][0] == [False])
self.assertTrue(flag_col["r1"][0][1] == [False])
self.assertTrue(flag_col["r1"][0][61] == [False])
self.assertTrue(flag_col["r1"][0][62] == [False])
data_col = th.getVarCol(self.msfile, "DATA")
hanningsmooth(vis=self.testmms, outputvis=self.outputms, datacolumn="data", keepmms=True)
self.assertTrue(ParallelDataHelper.isParallelMS(self.outputms), "Output should be an MMS")
# Sort the MMS
mslocal.open(self.outputms)
mslocal.sort(
"sorted.mms",
["OBSERVATION_ID", "ARRAY_ID", "SCAN_NUMBER", "FIELD_ID", "DATA_DESC_ID", "ANTENNA1", "ANTENNA2", "TIME"],
)
mslocal.close()
self.outputms = "sorted.mms"
corr_col = th.getVarCol(self.outputms, "DATA")
nrows = len(corr_col)
# check correct flagging (just for one row as a sample)
flag_col = th.getVarCol(self.outputms, "FLAG")
self.assertTrue(flag_col["r1"][0][0] == [True])
self.assertTrue(flag_col["r1"][0][1] == [False])
self.assertTrue(flag_col["r1"][0][61] == [False])
self.assertTrue(flag_col["r1"][0][62] == [True])
# Loop over every 2nd row,pol and get the data for each channel
max = 1e-05
for i in range(1, nrows, 2):
row = "r%s" % i
# polarization is 0-1
for pol in range(0, 2):
# array's channels is 0-63
for chan in range(1, 62):
# channels must start from second and end before the last
data = data_col[row][pol][chan]
dataB = data_col[row][pol][chan - 1]
dataA = data_col[row][pol][chan + 1]
Smoothed = th.calculateHanning(dataB, data, dataA)
CorData = corr_col[row][pol][chan]
# Check the difference
self.assertTrue(abs(CorData - Smoothed) < max)