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Job: Test Tasks OSX12 did not complete

Build log

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04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 *** Subtable PROCESSOR
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column FLAG_ROW
04-Jan-2024 11:44:30 Column FLAG_ROW PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column MODE_ID
04-Jan-2024 11:44:30 Column MODE_ID PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TYPE
04-Jan-2024 11:44:30 Column TYPE PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TYPE_ID
04-Jan-2024 11:44:30 Column TYPE_ID PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column SUB_TYPE
04-Jan-2024 11:44:30 Column SUB_TYPE PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 *** Subtable SOURCE
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column DIRECTION
04-Jan-2024 11:44:30 Column DIRECTION PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column PROPER_MOTION
04-Jan-2024 11:44:30 Column PROPER_MOTION PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column CALIBRATION_GROUP
04-Jan-2024 11:44:30 Column CALIBRATION_GROUP PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column CODE
04-Jan-2024 11:44:30 Column CODE PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column INTERVAL
04-Jan-2024 11:44:30 Column INTERVAL PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column NAME
04-Jan-2024 11:44:30 Column NAME PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column NUM_LINES
04-Jan-2024 11:44:30 Column NUM_LINES PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column SOURCE_ID
04-Jan-2024 11:44:30 Column SOURCE_ID PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column SPECTRAL_WINDOW_ID
04-Jan-2024 11:44:30 Column SPECTRAL_WINDOW_ID PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TIME
04-Jan-2024 11:44:30 Column TIME PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 *** Subtable SPECTRAL_WINDOW
04-Jan-2024 11:44:30 Column CHAN_FREQ of reference.ms/SPECTRAL_WINDOW and uid___A002_X6218fb_X264.ms/SPECTRAL_WINDOW agree
04-Jan-2024 11:44:30 Column CHAN_WIDTH of reference.ms/SPECTRAL_WINDOW and uid___A002_X6218fb_X264.ms/SPECTRAL_WINDOW agree
04-Jan-2024 11:44:30 Column EFFECTIVE_BW of reference.ms/SPECTRAL_WINDOW and uid___A002_X6218fb_X264.ms/SPECTRAL_WINDOW agree
04-Jan-2024 11:44:30 Column RESOLUTION of reference.ms/SPECTRAL_WINDOW and uid___A002_X6218fb_X264.ms/SPECTRAL_WINDOW agree
04-Jan-2024 11:44:30 Column ASSOC_SPW_ID of reference.ms/SPECTRAL_WINDOW and uid___A002_X6218fb_X264.ms/SPECTRAL_WINDOW agree
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column MEAS_FREQ_REF
04-Jan-2024 11:44:30 Column MEAS_FREQ_REF PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column REF_FREQUENCY
04-Jan-2024 11:44:30 Column REF_FREQUENCY PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column FLAG_ROW
04-Jan-2024 11:44:30 Column FLAG_ROW PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column FREQ_GROUP
04-Jan-2024 11:44:30 Column FREQ_GROUP PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column FREQ_GROUP_NAME
04-Jan-2024 11:44:30 Column FREQ_GROUP_NAME PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column IF_CONV_CHAIN
04-Jan-2024 11:44:30 Column IF_CONV_CHAIN PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column NAME
04-Jan-2024 11:44:30 Column NAME PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column NET_SIDEBAND
04-Jan-2024 11:44:30 Column NET_SIDEBAND PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column NUM_CHAN
04-Jan-2024 11:44:30 Column NUM_CHAN PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TOTAL_BANDWIDTH
04-Jan-2024 11:44:30 Column TOTAL_BANDWIDTH PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column BBC_NO
04-Jan-2024 11:44:30 Column BBC_NO PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column SDM_WINDOW_FUNCTION
04-Jan-2024 11:44:30 Column SDM_WINDOW_FUNCTION PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column SDM_NUM_BIN
04-Jan-2024 11:44:30 Column SDM_NUM_BIN PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column SDM_CORR_BIT
04-Jan-2024 11:44:30 Column SDM_CORR_BIT PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 *** Subtable STATE
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column CAL
04-Jan-2024 11:44:30 Column CAL PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column FLAG_ROW
04-Jan-2024 11:44:30 Column FLAG_ROW PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column LOAD
04-Jan-2024 11:44:30 Column LOAD PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column OBS_MODE
04-Jan-2024 11:44:30 Column OBS_MODE PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column REF
04-Jan-2024 11:44:30 Column REF PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column SIG
04-Jan-2024 11:44:30 Column SIG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column SUB_SCAN
04-Jan-2024 11:44:30 Column SUB_SCAN PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 *** Subtable SYSCAL
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column ANTENNA_ID
04-Jan-2024 11:44:30 Column ANTENNA_ID PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column FEED_ID
04-Jan-2024 11:44:30 Column FEED_ID PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column INTERVAL
04-Jan-2024 11:44:30 Column INTERVAL PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column SPECTRAL_WINDOW_ID
04-Jan-2024 11:44:30 Column SPECTRAL_WINDOW_ID PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TIME
04-Jan-2024 11:44:30 Column TIME PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TCAL_SPECTRUM
04-Jan-2024 11:44:30 Column TCAL_SPECTRUM PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TRX_SPECTRUM
04-Jan-2024 11:44:30 Column TRX_SPECTRUM PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TSKY_SPECTRUM
04-Jan-2024 11:44:30 Column TSKY_SPECTRUM PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TSYS_SPECTRUM
04-Jan-2024 11:44:30 Column TSYS_SPECTRUM PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TCAL_FLAG
04-Jan-2024 11:44:30 Column TCAL_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TRX_FLAG
04-Jan-2024 11:44:30 Column TRX_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TSKY_FLAG
04-Jan-2024 11:44:30 Column TSKY_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TSYS_FLAG
04-Jan-2024 11:44:30 Column TSYS_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TANT_FLAG
04-Jan-2024 11:44:30 Column TANT_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TANT_TSYS_FLAG
04-Jan-2024 11:44:30 Column TANT_TSYS_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 *** Subtable WEATHER
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column ANTENNA_ID
04-Jan-2024 11:44:30 Column ANTENNA_ID PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column INTERVAL
04-Jan-2024 11:44:30 Column INTERVAL PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TIME
04-Jan-2024 11:44:30 Column TIME PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column PRESSURE
04-Jan-2024 11:44:30 Column PRESSURE PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column PRESSURE_FLAG
04-Jan-2024 11:44:30 Column PRESSURE_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column REL_HUMIDITY
04-Jan-2024 11:44:30 Column REL_HUMIDITY PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column REL_HUMIDITY_FLAG
04-Jan-2024 11:44:30 Column REL_HUMIDITY_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TEMPERATURE
04-Jan-2024 11:44:30 Column TEMPERATURE PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column TEMPERATURE_FLAG
04-Jan-2024 11:44:30 Column TEMPERATURE_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column DEW_POINT
04-Jan-2024 11:44:30 Column DEW_POINT PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column DEW_POINT_FLAG
04-Jan-2024 11:44:30 Column DEW_POINT_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column WIND_DIRECTION
04-Jan-2024 11:44:30 Column WIND_DIRECTION PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column WIND_DIRECTION_FLAG
04-Jan-2024 11:44:30 Column WIND_DIRECTION_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column WIND_SPEED
04-Jan-2024 11:44:30 Column WIND_SPEED PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column WIND_SPEED_FLAG
04-Jan-2024 11:44:30 Column WIND_SPEED_FLAG PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column NS_WX_STATION_ID
04-Jan-2024 11:44:30 Column NS_WX_STATION_ID PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 Testing column NS_WX_STATION_POSITION
04-Jan-2024 11:44:30 Column NS_WX_STATION_POSITION PASSED
04-Jan-2024 11:44:30 PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:30 test_task_importasdm.py::asdm_import7::test7_skiprows1
04-Jan-2024 11:44:30 Asdm-import: Test TP asdm, comparing output when duplicate DATA rows are skipped versus not-skipped, lazy and regular, with bdflagging on
04-Jan-2024 11:44:30 Skipping asdm_import7.test7_skiprows - uses stand-alone executable
04-Jan-2024 11:44:30 PASSED
04-Jan-2024 11:44:30
04-Jan-2024 11:44:38 test_task_importasdm.py::asdm_import8::test_alma_numbin
04-Jan-2024 11:44:38 test_importasdm: testing SDM columns in alma_numbin_mixed writing to alma_numbin_mixed.ms
04-Jan-2024 11:44:38 test_importasdm: testing SDM columns in alma_numbin_mixed writing to alma_numbin_mixed.numbin.ms
04-Jan-2024 11:44:38 test_importasdm: using SpectralWindow.xml.numBin for SpectralWindow.xml
04-Jan-2024 11:44:38 test_importasdm: restored original SpectralWindow.xml
04-Jan-2024 11:44:38 test_importasdm: testing SDM columns in alma_numbin_mixed writing to alma_numbin_mixed.faked.ms
04-Jan-2024 11:44:38 test_importasdm: using SpectralWindow.xml.faked for SpectralWindow.xml
04-Jan-2024 11:44:38 test_importasdm: restored original SpectralWindow.xml
04-Jan-2024 11:44:38 test_importasdm: testing SDM columns in alma_numbin_mixed writing to alma_numbin_mixed.faked.numBin.ms
04-Jan-2024 11:44:38 test_importasdm: using SpectralWindow.xml.faked.numBin for SpectralWindow.xml
04-Jan-2024 11:44:38 test_importasdm: restored original SpectralWindow.xml
04-Jan-2024 11:44:38 PASSED
04-Jan-2024 11:44:38
04-Jan-2024 11:44:54 test_task_importasdm.py::asdm_import8::test_evla_numbin
04-Jan-2024 11:44:54 test_importasdm: testing SDM columns in evla_numbin_2 writing to evla_numbin_2.ms
04-Jan-2024 11:44:54 test_importasdm: testing SDM columns in evla_numbin_2 writing to evla_numbin_2.numBin.ms
04-Jan-2024 11:44:54 test_importasdm: using SpectralWindow.xml.numBin for SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: restored original SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: testing SDM columns in evla_numbin_2 writing to evla_numbin_2.mixed.ms
04-Jan-2024 11:44:54 test_importasdm: using SpectralWindow.xml.mixed for SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: restored original SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: testing SDM columns in evla_numbin_2 writing to evla_numbin_2.bad.ms
04-Jan-2024 11:44:54 test_importasdm: using SpectralWindow.xml.bad for SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: restored original SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: testing SDM columns in evla_numbin_4 writing to evla_numbin_4.ms
04-Jan-2024 11:44:54 test_importasdm: testing SDM columns in evla_numbin_4 writing to evla_numbin_4.numBin.ms
04-Jan-2024 11:44:54 test_importasdm: using SpectralWindow.xml.numBin for SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: restored original SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: testing SDM columns in evla_numbin_4 writing to evla_numbin_4.onlyNumBin.ms
04-Jan-2024 11:44:54 test_importasdm: using SpectralWindow.xml.onlyNumBin for SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: restored original SpectralWindow.xml
04-Jan-2024 11:44:54 test_importasdm: testing SDM columns in evla_numbin_4 writing to evla_numbin_4.unknownTel.ms
04-Jan-2024 11:44:54 test_importasdm: using ExecBlock.xml.unknownTel for ExecBlock.xml
04-Jan-2024 11:44:54 test_importasdm: restored original ExecBlock.xml
04-Jan-2024 11:44:54 PASSED
04-Jan-2024 11:44:54
04-Jan-2024 11:45:07 test_task_importasdm.py::asdm_import8::test_verbose
04-Jan-2024 11:45:07 PASSED
04-Jan-2024 11:45:07
04-Jan-2024 11:45:07 - generated xml file: /Users/casaci/bamboohome/xml-data/build-dir/CASA-CPR107-TTO1P/casa6/casatestutils/nosedir/xml/test_task_importasdm/nose.xml -
04-Jan-2024 11:45:07 ================== 33 passed, 1 warning in 503.93s (0:08:23) ===================
04-Jan-2024 11:45:08 ============================= test session starts ==============================
04-Jan-2024 11:45:08 platform darwin -- Python 3.8.13, pytest-7.4.4, pluggy-1.3.0 -- /Users/casaci/bamboohome/xml-data/build-dir/CASA-CPR107-TTO1P/casa6testenv/bin/python
04-Jan-2024 11:45:08 cachedir: .pytest_cache
04-Jan-2024 11:45:08 rootdir: /Users/casaci/bamboohome/xml-data/build-dir/CASA-CPR107-TTO1P/casa6/casatestutils/nosedir/test_task_visstat
04-Jan-2024 11:45:08 configfile: pytest.ini
04-Jan-2024 11:45:12 collecting ... collected 33 items
04-Jan-2024 11:45:12
04-Jan-2024 11:45:12
04-Jan-2024 11:45:15 test_task_visstat.py::visstat_test::test_antenna
04-Jan-2024 11:45:15 test_antenna
04-Jan-2024 11:45:15 ---------------------------
04-Jan-2024 11:45:15
04-Jan-2024 11:45:15 Test the antenna selection parameter
04-Jan-2024 11:45:15
04-Jan-2024 11:45:15 Assert that selection with this parameter will return a different result than no selection.
04-Jan-2024 11:45:15 PASSED
04-Jan-2024 11:45:15
04-Jan-2024 11:45:15 2024-01-04 16:45:15        SEVERE        visstat::ms::statistics        Exception Reported: MSSelectionNullSelection : The selected table has zero rows.
04-Jan-2024 11:45:15 2024-01-04 16:45:15        SEVERE        visstat::::casa        Task visstat raised an exception of class RuntimeError with the following message: MSSelectionNullSelection : The selected table has zero rows.
04-Jan-2024 11:45:15 2024-01-04 16:45:15        SEVERE        visstat::ms::statistics        Exception Reported: MSSelectionNullSelection : The selected table has zero rows.
04-Jan-2024 11:45:15 2024-01-04 16:45:15        SEVERE        visstat::::casa        Task visstat raised an exception of class RuntimeError with the following message: MSSelectionNullSelection : The selected table has zero rows.
04-Jan-2024 11:45:15 test_task_visstat.py::visstat_test::test_array
04-Jan-2024 11:45:15 test_array
04-Jan-2024 11:45:15 -------------
04-Jan-2024 11:45:15
04-Jan-2024 11:45:15 Test the array selection parameter.
04-Jan-2024 11:45:15
04-Jan-2024 11:45:15 Assert that checking an out of range array returns a NoneType, and valid selections retrun a dictionary
04-Jan-2024 11:45:15 PASSED
04-Jan-2024 11:45:15
04-Jan-2024 11:45:24 test_task_visstat.py::visstat_test::test_axis
04-Jan-2024 11:45:24 test_axis
04-Jan-2024 11:45:24 ------------------------------
04-Jan-2024 11:45:24
04-Jan-2024 11:45:24 Test the axis parameter values.
04-Jan-2024 11:45:24 visstat should return a dict and the keys should match the provided key list.
04-Jan-2024 11:45:24
04-Jan-2024 11:45:24 This test iterates over all the possible axis values
04-Jan-2024 11:45:24 PASSED
04-Jan-2024 11:45:24
04-Jan-2024 11:45:27 test_task_visstat.py::visstat_test::test_channelSelectFlags
04-Jan-2024 11:45:27 Visstat 02: Check channel selections, useflags=True, reportingaxes='ddid',correlation=corr, datacolumn=data, axis=amp
04-Jan-2024 11:45:27 Call with spw='0:1~1', correlation=ll
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.012998353689908981, 'isMasked': True, 'isWeighted': False, 'max': 23.695859909057617, 'maxDatasetIndex': 1, 'maxIndex': 1, 'mean': 1.51201536185032, 'medabsdevmed': 0.020134394988417625, 'median': 0.027283204719424248, 'min': 0.00037757985410280526, 'minDatasetIndex': 25, 'minIndex': 195, 'npts': 21119.0, 'rms': 5.254564972098979, 'stddev': 5.032440935625601, 'sum': 31932.25242691688, 'sumOfWeights': 21119.0, 'sumsq': 583105.1578786756, 'thirdquartile': 0.20560552179813385, 'variance': 25.325461770560278}}
04-Jan-2024 11:45:27 Checking npts: 21119 vs 21119.0
04-Jan-2024 11:45:27 Call with spw='0:1~1', correlation=rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.013324417173862457, 'isMasked': True, 'isWeighted': False, 'max': 26.920883178710938, 'maxDatasetIndex': 4, 'maxIndex': 19, 'mean': 1.703732570450803, 'medabsdevmed': 0.02199349133297801, 'median': 0.028599174693226814, 'min': 0.00016617041546851397, 'minDatasetIndex': 27, 'minIndex': 173, 'npts': 21119.0, 'rms': 5.9277552741561355, 'stddev': 5.677772835275629, 'sum': 35981.12815535044, 'sumOfWeights': 21119.0, 'sumsq': 742085.3900242473, 'thirdquartile': 0.26254236698150635, 'variance': 32.237104368993855}}
04-Jan-2024 11:45:27 Checking npts: 21119 vs 21119.0
04-Jan-2024 11:45:27 Call with spw='0:1~1', correlation=ll,rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.01315868180245161, 'isMasked': True, 'isWeighted': False, 'max': 26.920883178710938, 'maxDatasetIndex': 4, 'maxIndex': 39, 'mean': 1.6078739661505588, 'medabsdevmed': 0.021032736403867602, 'median': 0.027937160804867744, 'min': 0.00016617041546851397, 'minDatasetIndex': 27, 'minIndex': 347, 'npts': 42238.0, 'rms': 5.601282694003898, 'stddev': 5.365611869664173, 'sum': 67913.38058226732, 'sumOfWeights': 42238.0, 'sumsq': 1325190.5479029168, 'thirdquartile': 0.23095539212226868, 'variance': 28.789790735881063}}
04-Jan-2024 11:45:27 Checking npts: 42238 vs 42238.0
04-Jan-2024 11:45:27 Call with spw='0:1~2', correlation=ll
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.015203726477921009, 'isMasked': True, 'isWeighted': False, 'max': 47.85862731933594, 'maxDatasetIndex': 9, 'maxIndex': 3, 'mean': 2.2685205557350705, 'medabsdevmed': 0.025584048125892878, 'median': 0.033365800976753235, 'min': 0.00037757985410280526, 'minDatasetIndex': 25, 'minIndex': 390, 'npts': 42238.0, 'rms': 8.247744697530607, 'stddev': 7.929728608521772, 'sum': 95817.77123313842, 'sumOfWeights': 42238.0, 'sumsq': 2873252.3086548215, 'thirdquartile': 0.2353196144104004, 'variance': 62.88059580480865}}
04-Jan-2024 11:45:27 Checking npts: 42238 vs 42238.0
04-Jan-2024 11:45:27 Call with spw='0:1~2', correlation=rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.015641184523701668, 'isMasked': True, 'isWeighted': False, 'max': 50.03026580810547, 'maxDatasetIndex': 30, 'maxIndex': 39, 'mean': 2.4662003717613192, 'medabsdevmed': 0.027923745336011052, 'median': 0.03566293604671955, 'min': 3.5077806387562305e-05, 'minDatasetIndex': 38, 'minIndex': 65, 'npts': 42238.0, 'rms': 8.903693383964843, 'stddev': 8.555427781728099, 'sum': 104167.37130245389, 'sumOfWeights': 42238.0, 'sumsq': 3348449.376676098, 'thirdquartile': 0.2842475175857544, 'variance': 73.19534452836497}}
04-Jan-2024 11:45:27 Checking npts: 42238 vs 42238.0
04-Jan-2024 11:45:27 Call with spw='0:1~2', correlation=ll,rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.015421337448060513, 'isMasked': True, 'isWeighted': False, 'max': 50.03026580810547, 'maxDatasetIndex': 30, 'maxIndex': 79, 'mean': 2.3673604637482013, 'medabsdevmed': 0.026692680083215237, 'median': 0.03441326133906841, 'min': 3.5077806387562305e-05, 'minDatasetIndex': 38, 'minIndex': 131, 'npts': 84476.0, 'rms': 8.581988361426047, 'stddev': 8.249056563527775, 'sum': 199985.1425355923, 'sumOfWeights': 84476.0, 'sumsq': 6221701.685330949, 'thirdquartile': 0.2572411596775055, 'variance': 68.04693418828066}}
04-Jan-2024 11:45:27 Checking npts: 84476 vs 84476.0
04-Jan-2024 11:45:27 Call with spw='0:1~4', correlation=ll
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.018262511119246483, 'isMasked': True, 'isWeighted': False, 'max': 67.18834686279297, 'maxDatasetIndex': 1, 'maxIndex': 7, 'mean': 3.2328949655030006, 'medabsdevmed': 0.03320419928058982, 'median': 0.04149508289992809, 'min': 2.2739146515959874e-05, 'minDatasetIndex': 48, 'minIndex': 851, 'npts': 84476.0, 'rms': 11.716386189704192, 'stddev': 11.261598322870743, 'sum': 273102.0351058309, 'sumOfWeights': 84476.0, 'sumsq': 11596333.532833287, 'thirdquartile': 0.27172136306762695, 'variance': 126.82359678568513}}
04-Jan-2024 11:45:27 Checking npts: 84476 vs 84476.0
04-Jan-2024 11:45:27 Call with spw='0:1~4', correlation=rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.018680663779377937, 'isMasked': True, 'isWeighted': False, 'max': 68.62496948242188, 'maxDatasetIndex': 26, 'maxIndex': 79, 'mean': 3.3996190574518157, 'medabsdevmed': 0.03522256435826421, 'median': 0.043506983667612076, 'min': 3.5077806387562305e-05, 'minDatasetIndex': 38, 'minIndex': 129, 'npts': 84476.0, 'rms': 12.239038012587871, 'stddev': 11.757477542335039, 'sum': 287186.2194972994, 'sumOfWeights': 84476.0, 'sumsq': 12654002.292281372, 'thirdquartile': 0.3134520947933197, 'variance': 138.2382781585128}}
04-Jan-2024 11:45:27 Checking npts: 84476 vs 84476.0
04-Jan-2024 11:45:27 Call with spw='0:1~4', correlation=ll,rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.01846258156001568, 'isMasked': True, 'isWeighted': False, 'max': 68.62496948242188, 'maxDatasetIndex': 26, 'maxIndex': 159, 'mean': 3.3162570114774232, 'medabsdevmed': 0.03416486969217658, 'median': 0.0424413587898016, 'min': 2.2739146515959874e-05, 'minDatasetIndex': 48, 'minIndex': 1702, 'npts': 168952.0, 'rms': 11.98056252477037, 'stddev': 11.51247594176724, 'sum': 560288.2546031302, 'sumOfWeights': 168952.0, 'sumsq': 24250335.825114865, 'thirdquartile': 0.290507972240448, 'variance': 132.5371023097695}}
04-Jan-2024 11:45:27 Checking npts: 168952 vs 168952.0
04-Jan-2024 11:45:27 Call with spw='0:1~7', correlation=ll
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.020986022427678108, 'isMasked': True, 'isWeighted': False, 'max': 70.78073120117188, 'maxDatasetIndex': 24, 'maxIndex': 13, 'mean': 3.965659174843849, 'medabsdevmed': 0.03952489420771599, 'median': 0.04782070219516754, 'min': 2.2739146515959874e-05, 'minDatasetIndex': 48, 'minIndex': 1487, 'npts': 147833.0, 'rms': 14.130246023570889, 'stddev': 13.562398173931312, 'sum': 586255.2927946859, 'sumOfWeights': 147833.0, 'sumsq': 29516906.334224183, 'thirdquartile': 0.31161126494407654, 'variance': 183.93864422825538}}
04-Jan-2024 11:45:27 Checking npts: 147833 vs 147833.0
04-Jan-2024 11:45:27 Call with spw='0:1~7', correlation=rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.02118206024169922, 'isMasked': True, 'isWeighted': False, 'max': 73.75, 'maxDatasetIndex': 12, 'maxIndex': 139, 'mean': 4.075617324934261, 'medabsdevmed': 0.040772588923573494, 'median': 0.04898509383201599, 'min': 3.5077806387562305e-05, 'minDatasetIndex': 38, 'minIndex': 225, 'npts': 147833.0, 'rms': 14.45538727219714, 'stddev': 13.868989355124057, 'sum': 602510.7359970011, 'sumOfWeights': 147833.0, 'sumsq': 30890920.713062864, 'thirdquartile': 0.35131359100341797, 'variance': 192.3488657325444}}
04-Jan-2024 11:45:27 Checking npts: 147833 vs 147833.0
04-Jan-2024 11:45:27 Call with spw='0:1~7', correlation=ll,rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.021086707711219788, 'isMasked': True, 'isWeighted': False, 'max': 73.75, 'maxDatasetIndex': 12, 'maxIndex': 279, 'mean': 4.02063824988892, 'medabsdevmed': 0.040139758959412575, 'median': 0.048403069376945496, 'min': 2.2739146515959874e-05, 'minDatasetIndex': 48, 'minIndex': 2974, 'npts': 295666.0, 'rms': 14.293741180597895, 'stddev': 13.71663739217234, 'sum': 1188766.0287916868, 'sumOfWeights': 295666.0, 'sumsq': 60407827.047287084, 'thirdquartile': 0.3312663435935974, 'variance': 188.1461413483404}}
04-Jan-2024 11:45:27 Checking npts: 295666 vs 295666.0
04-Jan-2024 11:45:27 Call with spw='0:1~13', correlation=ll
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.02359769307076931, 'isMasked': True, 'isWeighted': False, 'max': 70.78073120117188, 'maxDatasetIndex': 24, 'maxIndex': 19, 'mean': 4.57363400413573, 'medabsdevmed': 0.04534465912729502, 'median': 0.05354195833206177, 'min': 2.2739146515959874e-05, 'minDatasetIndex': 48, 'minIndex': 2759, 'npts': 274547.0, 'rms': 16.001664561308115, 'stddev': 15.33414481409489, 'sum': 1255677.4949334553, 'sumOfWeights': 274547.0, 'sumsq': 70298656.77073571, 'thirdquartile': 0.3944782316684723, 'variance': 235.1359971796332}}
04-Jan-2024 11:45:27 Checking npts: 274547 vs 274547.0
04-Jan-2024 11:45:27 Call with spw='0:1~13', correlation=rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.023458972573280334, 'isMasked': True, 'isWeighted': False, 'max': 73.75, 'maxDatasetIndex': 12, 'maxIndex': 253, 'mean': 4.598994075086256, 'medabsdevmed': 0.04547768831253052, 'median': 0.053455792367458344, 'min': 3.5077806387562305e-05, 'minDatasetIndex': 38, 'minIndex': 417, 'npts': 274547.0, 'rms': 16.050754617587547, 'stddev': 15.377803439566847, 'sum': 1262640.0263327179, 'sumOfWeights': 274547.0, 'sumsq': 70730644.13747351, 'thirdquartile': 0.4329370856285095, 'variance': 236.47683862595397}}
04-Jan-2024 11:45:27 Checking npts: 274547 vs 274547.0
04-Jan-2024 11:45:27 Call with spw='0:1~13', correlation=ll,rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.02353147603571415, 'isMasked': True, 'isWeighted': False, 'max': 73.75, 'maxDatasetIndex': 12, 'maxIndex': 507, 'mean': 4.586314039611128, 'medabsdevmed': 0.04539835639297962, 'median': 0.05349326133728027, 'min': 2.2739146515959874e-05, 'minDatasetIndex': 48, 'minIndex': 5518, 'npts': 549094.0, 'rms': 16.02622838547249, 'stddev': 15.355980894727814, 'sum': 2518317.5212661736, 'sumOfWeights': 549094.0, 'sumsq': 141029300.90821368, 'thirdquartile': 0.4128650426864624, 'variance': 235.80614923924563}}
04-Jan-2024 11:45:27 Checking npts: 549094 vs 549094.0
04-Jan-2024 11:45:27 Call with spw='0:1~62', correlation=ll
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.02503143437206745, 'isMasked': True, 'isWeighted': False, 'max': 72.1248779296875, 'maxDatasetIndex': 19, 'maxIndex': 1090, 'mean': 4.931429419886412, 'medabsdevmed': 0.047344045247882605, 'median': 0.055874770507216454, 'min': 2.2739146515959874e-05, 'minDatasetIndex': 48, 'minIndex': 13147, 'npts': 1309378.0, 'rms': 17.284456326641575, 'stddev': 16.566038874005407, 'sum': 6457105.190951668, 'sumOfWeights': 1309378.0, 'sumsq': 391179859.95315397, 'thirdquartile': 0.396679162979126, 'variance': 274.4336439750583}}
04-Jan-2024 11:45:27 Checking npts: 1309378 vs 1309378.0
04-Jan-2024 11:45:27 Call with spw='0:1~62', correlation=rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.024585282430052757, 'isMasked': True, 'isWeighted': False, 'max': 73.75, 'maxDatasetIndex': 12, 'maxIndex': 1184, 'mean': 4.892831986142966, 'medabsdevmed': 0.04655483830720186, 'median': 0.054879553616046906, 'min': 2.2130521756480448e-05, 'minDatasetIndex': 54, 'minIndex': 4277, 'npts': 1309378.0, 'rms': 17.151711039791266, 'stddev': 16.439026526444376, 'sum': 6406566.560351839, 'sumOfWeights': 1309378.0, 'sumsq': 385194380.2850013, 'thirdquartile': 0.4161178767681122, 'variance': 270.2415931371418}}
04-Jan-2024 11:45:27 Checking npts: 1309378 vs 1309378.0
04-Jan-2024 11:45:27 Call with spw='0:1~62', correlation=ll,rr
04-Jan-2024 11:45:27
04-Jan-2024 11:45:27 s2 {'DATA_DESC_ID=0': {'firstquartile': 0.02480573207139969, 'isMasked': True, 'isWeighted': False, 'max': 73.75, 'maxDatasetIndex': 12, 'maxIndex': 2369, 'mean': 4.912130703014519, 'medabsdevmed': 0.04696154408156872, 'median': 0.05538627877831459, 'min': 2.2130521756480448e-05, 'minDatasetIndex': 54, 'minIndex': 8555, 'npts': 2618756.0, 'rms': 17.21821161009346, 'stddev': 16.50266302757408, 'sum': 12863671.751303246, 'sumOfWeights': 2618756.0, 'sumsq': 776374240.2379415, 'thirdquartile': 0.40908554196357727, 'variance': 272.33788700166053}}
04-Jan-2024 11:45:27 Checking npts: 2618756 vs 2618756.0
04-Jan-2024 11:45:27 PASSED
04-Jan-2024 11:45:27
04-Jan-2024 11:45:28 test_task_visstat.py::visstat_test::test_corrLLRR
04-Jan-2024 11:45:28 Visstat 09: Test using reportingaxes=ddid, correlation=[LL,RR], datacolumn=float_data spw=[0,1,2,3]
04-Jan-2024 11:45:28 PASSED
04-Jan-2024 11:45:28
04-Jan-2024 11:45:28 test_task_visstat.py::visstat_test::test_correlation
04-Jan-2024 11:45:28 test_correlation
04-Jan-2024 11:45:28 -------------------
04-Jan-2024 11:45:28
04-Jan-2024 11:45:28 Test the correlation parameter
04-Jan-2024 11:45:28
04-Jan-2024 11:45:28 Assert that the selection with this parameter will return a different value than no selection.
04-Jan-2024 11:45:28 PASSED
04-Jan-2024 11:45:28
04-Jan-2024 11:45:29 test_task_visstat.py::visstat_test::test_datacolCorrected
04-Jan-2024 11:45:29 Visstat 07: Default values with datacolum=corrected, reportingaxis=ddid
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking firstquartile: 0.024146264419 vs 0.02414626255631447
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking isMasked: True vs True
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking isWeighted: False vs False
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking max: 73.75 vs 73.75
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking maxDatasetIndex: 12 vs 12
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking maxIndex: 2408 vs 2408
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking mean: 4.837103133618731 vs 4.837103133596972
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking medabsdevmed: 0.04501341888681054 vs 0.04501341888681054
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking median: 0.05355948396027088 vs 0.05355948396027088
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking min: 2.2130521756480448e-05 vs 2.2130521756480448e-05
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking minDatasetIndex: 54 vs 54
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking minIndex: 8692 vs 8692
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking npts: 2660994.0 vs 2660994.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking thirdquartile: 0.3291134536266327 vs 0.3291134536266327
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking rms: 17.081207832906546 vs 17.081207832904955
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking stddev: 16.382008276126726 vs 16.382008276131568
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking sum: 12871502.415939873 vs 12871502.415881826
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking sumsq: 776391995.3973862 vs 776391995.3972417
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking variance: 268.3701951590845 vs 268.37019515924317
04-Jan-2024 11:45:29 PASSED
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 test_task_visstat.py::visstat_test::test_datacolModel
04-Jan-2024 11:45:29 Visstat 03: Default values with datacolum=model, reportingaxis=ddid
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking firstquartile: 1.0 vs 1.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking isMasked: True vs True
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking isWeighted: False vs False
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking max: 1.0 vs 1.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking maxDatasetIndex: 0 vs 0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking maxIndex: 0 vs 0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking mean: 1.0 vs 1.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking medabsdevmed: 0.0 vs 0.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking median: 1.0 vs 1.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking min: 1.0 vs 1.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking minDatasetIndex: 0 vs 0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking minIndex: 0 vs 0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking npts: 2660994.0 vs 2660994.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking thirdquartile: 1.0 vs 1.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking rms: 1.0 vs 1.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking stddev: 0.0 vs 0.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking sum: 2660994.0 vs 2660994.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking sumsq: 2660994.0 vs 2660994.0
04-Jan-2024 11:45:29
04-Jan-2024 11:45:29 Checking variance: 0.0 vs 0.0
04-Jan-2024 11:45:29 PASSED
04-Jan-2024 11:45:29
04-Jan-2024 11:45:32 test_task_visstat.py::visstat_test::test_datacolMulti
04-Jan-2024 11:45:32 Visstat 08: Test when using reportingaxes='integration, datacolumn=data,corrected,model
04-Jan-2024 11:45:32 PASSED
04-Jan-2024 11:45:32
04-Jan-2024 11:45:33 test_task_visstat.py::visstat_test::test_datacolumn
04-Jan-2024 11:45:33 test_datacolumn
04-Jan-2024 11:45:33 ----------------------------
04-Jan-2024 11:45:33
04-Jan-2024 11:45:33 Check the data column parameter.
04-Jan-2024 11:45:33
04-Jan-2024 11:45:33 Iterate over possible data column inputs and check that a dictionary is created by visstat
04-Jan-2024 11:45:33 also check that all the keys that should be present are there.
04-Jan-2024 11:45:33
04-Jan-2024 11:45:33 (This last step may not be nessisary for this test)
04-Jan-2024 11:45:33 PASSED
04-Jan-2024 11:45:33
04-Jan-2024 11:45:34 test_task_visstat.py::visstat_test::test_defaultValues
04-Jan-2024 11:45:34 Visstat 01: Default values
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking firstquartile: 0.024146264419 vs 0.02414626255631447
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking isMasked: True vs True
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking isWeighted: False vs False
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking max: 73.75 vs 73.75
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking maxDatasetIndex: 12 vs 12
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking maxIndex: 2408 vs 2408
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking mean: 4.837103133618731 vs 4.837103133596972
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking medabsdevmed: 0.04501341888681054 vs 0.04501341888681054
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking median: 0.05355948396027088 vs 0.05355948396027088
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking min: 2.2130521756480448e-05 vs 2.2130521756480448e-05
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking minDatasetIndex: 54 vs 54
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking minIndex: 8692 vs 8692
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking npts: 2660994.0 vs 2660994.0
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking thirdquartile: 0.3291134536266327 vs 0.3291134536266327
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking rms: 17.081207832906546 vs 17.081207832904955
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking stddev: 16.382008276126726 vs 16.382008276131568
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking sum: 12871502.415939873 vs 12871502.415881826
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking sumsq: 776391995.3973862 vs 776391995.3972417
04-Jan-2024 11:45:34
04-Jan-2024 11:45:34 Checking variance: 268.3701951590845 vs 268.37019515924317
04-Jan-2024 11:45:34 PASSED
04-Jan-2024 11:45:34
04-Jan-2024 11:45:35 test_task_visstat.py::visstat_test::test_doquantiles
04-Jan-2024 11:45:35 test doquantiles parameter
04-Jan-2024 11:45:35 PASSED
04-Jan-2024 11:45:35
04-Jan-2024 11:45:35 test_task_visstat.py::visstat_test::test_field
04-Jan-2024 11:45:35 test_field
04-Jan-2024 11:45:35 --------------
04-Jan-2024 11:45:35
04-Jan-2024 11:45:35 Test the field selection parameter.
04-Jan-2024 11:45:35
04-Jan-2024 11:45:35 Assert that a selection using the field parameter returns a different result than no selection.
04-Jan-2024 11:45:35 PASSED
04-Jan-2024 11:45:35
04-Jan-2024 11:45:36 2024-01-04 16:45:36        WARN        visstat::::casa        DATA_DESC_ID=1 -- No valid points found
04-Jan-2024 11:45:36 test_task_visstat.py::visstat_test::test_handle_all_flagged_groups
04-Jan-2024 11:45:36 visstat 13: handle all-flagged sub-selections in reportingaxes, CAS-12857
04-Jan-2024 11:45:36 PASSED
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 test_task_visstat.py::visstat_test::test_intent
04-Jan-2024 11:45:36 test_intent
04-Jan-2024 11:45:36 -----------------
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 Test the intent parameter
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 Assert that the specified selection creates a different dict than the default values.
04-Jan-2024 11:45:36 PASSED
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 test_task_visstat.py::visstat_test::test_intentOnOff
04-Jan-2024 11:45:36 Visstat 10: Test using reportingaxes=field, datacolumn=corrected, intent=[on,off]
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on rms
04-Jan-2024 11:45:36 4.304297370622206
04-Jan-2024 11:45:36 check intent off rms
04-Jan-2024 11:45:36 4.304297370622206
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on max
04-Jan-2024 11:45:36 19.147367477416992
04-Jan-2024 11:45:36 check intent off max
04-Jan-2024 11:45:36 19.147367477416992
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on min
04-Jan-2024 11:45:36 -15.199692726135254
04-Jan-2024 11:45:36 check intent off min
04-Jan-2024 11:45:36 -15.199692726135254
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on sum
04-Jan-2024 11:45:36 35087.679596841335
04-Jan-2024 11:45:36 check intent off sum
04-Jan-2024 11:45:36 35087.679596841335
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on median
04-Jan-2024 11:45:36 4.278878211975098
04-Jan-2024 11:45:36 check intent off median
04-Jan-2024 11:45:36 4.278878211975098
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on stddev
04-Jan-2024 11:45:36 0.4260329169087803
04-Jan-2024 11:45:36 check intent off stddev
04-Jan-2024 11:45:36 0.4260329169087803
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on mean
04-Jan-2024 11:45:36 4.283164013286309
04-Jan-2024 11:45:36 check intent off mean
04-Jan-2024 11:45:36 4.283164013286309
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on rms
04-Jan-2024 11:45:36 3.9222649429916214
04-Jan-2024 11:45:36 check intent off rms
04-Jan-2024 11:45:36 3.9222649429916214
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on max
04-Jan-2024 11:45:36 5.5116047859191895
04-Jan-2024 11:45:36 check intent off max
04-Jan-2024 11:45:36 5.5116047859191895
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on min
04-Jan-2024 11:45:36 2.200864553451538
04-Jan-2024 11:45:36 check intent off min
04-Jan-2024 11:45:36 2.200864553451538
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on sum
04-Jan-2024 11:45:36 32089.27730822563
04-Jan-2024 11:45:36 check intent off sum
04-Jan-2024 11:45:36 32089.27730822563
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on median
04-Jan-2024 11:45:36 3.910185933113098
04-Jan-2024 11:45:36 check intent off median
04-Jan-2024 11:45:36 3.910185933113098
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on stddev
04-Jan-2024 11:45:36 0.20029446585363156
04-Jan-2024 11:45:36 check intent off stddev
04-Jan-2024 11:45:36 0.20029446585363156
04-Jan-2024 11:45:36
04-Jan-2024 11:45:36 check intent on mean
04-Jan-2024 11:45:36 3.917148108914265
04-Jan-2024 11:45:36 check intent off mean
04-Jan-2024 11:45:36 3.917148108914265
04-Jan-2024 11:45:36 PASSED
04-Jan-2024 11:45:36
04-Jan-2024 11:45:39 test_task_visstat.py::visstat_test::test_maxuvwdistance
04-Jan-2024 11:45:39 test_maxuvwdistance
04-Jan-2024 11:45:39 -----------------------
04-Jan-2024 11:45:39
04-Jan-2024 11:45:39 Test the maxuvwdistance parameter
04-Jan-2024 11:45:39
04-Jan-2024 11:45:39 Assert that the output is a python dict. Once again this selection seems to not change the values that are returned
04-Jan-2024 11:45:39 PASSED
04-Jan-2024 11:45:39
04-Jan-2024 11:45:39 2024-01-04 16:45:40        SEVERE        visstat::ms::statistics        Exception Reported: MSSelectionNullSelection : The selected table has zero rows.
04-Jan-2024 11:45:39 2024-01-04 16:45:40        SEVERE        visstat::::casa        Task visstat raised an exception of class RuntimeError with the following message: MSSelectionNullSelection : The selected table has zero rows.
04-Jan-2024 11:45:39 2024-01-04 16:45:40        SEVERE        visstat::ms::statistics        Exception Reported: MSSelectionNullSelection : The selected table has zero rows.
04-Jan-2024 11:45:39 2024-01-04 16:45:40        SEVERE        visstat::::casa        Task visstat raised an exception of class RuntimeError with the following message: MSSelectionNullSelection : The selected table has zero rows.
04-Jan-2024 11:45:40 test_task_visstat.py::visstat_test::test_observation
04-Jan-2024 11:45:40 test_observation
04-Jan-2024 11:45:40 -----------------------
04-Jan-2024 11:45:40
04-Jan-2024 11:45:40 Test the observation selection parameter
04-Jan-2024 11:45:40
04-Jan-2024 11:45:40 Assert that checking an out of range observation ID returns a NoneType, and valid selections return a dictionary
04-Jan-2024 11:45:40 PASSED
04-Jan-2024 11:45:40
04-Jan-2024 11:45:47 test_task_visstat.py::visstat_test::test_reportAxisField
04-Jan-2024 11:45:47 Visstat 06: Test using reportingaxes=field
04-Jan-2024 11:45:47 PASSED
04-Jan-2024 11:45:47
04-Jan-2024 11:45:48 test_task_visstat.py::visstat_test::test_reportAxisInt
04-Jan-2024 11:45:48 Visstat 05: Test using reportingaxes=integration, datacolumn=float_data
04-Jan-2024 11:45:48 rms 4.304297370622206
04-Jan-2024 11:45:48 max 19.147367477416992
04-Jan-2024 11:45:48 min -15.199692726135254
04-Jan-2024 11:45:48 sum 35087.679596841335
04-Jan-2024 11:45:48 median 4.278878211975098
04-Jan-2024 11:45:48 stddev 0.4260329169087803
04-Jan-2024 11:45:48 mean 4.283164013286309
04-Jan-2024 11:45:48 rms 4.3353846668292695
04-Jan-2024 11:45:48 max 5.960114002227783
04-Jan-2024 11:45:48 min 0.9407882690429688
04-Jan-2024 11:45:48 sum 35488.134197711945
04-Jan-2024 11:45:48 median 4.325183868408203
04-Jan-2024 11:45:48 stddev 0.1700795650207275
04-Jan-2024 11:45:48 mean 4.33204763155664
04-Jan-2024 11:45:48 rms 4.306203614057598
04-Jan-2024 11:45:48 max 6.313568592071533
04-Jan-2024 11:45:48 min 1.483452320098877
04-Jan-2024 11:45:48 sum 35238.97358107567
04-Jan-2024 11:45:48 median 4.286481618881226
04-Jan-2024 11:45:48 stddev 0.19837352702878472
04-Jan-2024 11:45:48 mean 4.301632517221148
04-Jan-2024 11:45:48 rms 4.304297370622206
04-Jan-2024 11:45:48 max 19.147367477416992
04-Jan-2024 11:45:48 min -15.199692726135254
04-Jan-2024 11:45:48 sum 35087.679596841335
04-Jan-2024 11:45:48 median 4.278878211975098
04-Jan-2024 11:45:48 stddev 0.4260329169087803
04-Jan-2024 11:45:48 mean 4.283164013286309
04-Jan-2024 11:45:48 rms 4.3353846668292695
04-Jan-2024 11:45:48 max 5.960114002227783
04-Jan-2024 11:45:48 min 0.9407882690429688
04-Jan-2024 11:45:48 sum 35488.134197711945
04-Jan-2024 11:45:48 median 4.325183868408203
04-Jan-2024 11:45:48 stddev 0.1700795650207275
04-Jan-2024 11:45:48 mean 4.33204763155664
04-Jan-2024 11:45:48 rms 4.306203614057598
04-Jan-2024 11:45:48 max 6.313568592071533
04-Jan-2024 11:45:48 min 1.483452320098877
04-Jan-2024 11:45:48 sum 35238.97358107567
04-Jan-2024 11:45:48 median 4.286481618881226
04-Jan-2024 11:45:48 stddev 0.19837352702878472
04-Jan-2024 11:45:48 mean 4.301632517221148
04-Jan-2024 11:45:48 rms 4.260218426691952
04-Jan-2024 11:45:48 max 6.594586372375488
04-Jan-2024 11:45:48 min 2.4618935585021973
04-Jan-2024 11:45:48 sum 34870.10427117348
04-Jan-2024 11:45:48 median 4.255388259887695
04-Jan-2024 11:45:48 stddev 0.17545003865511774
04-Jan-2024 11:45:48 mean 4.256604525289735
04-Jan-2024 11:45:48 rms 4.304297370622206
04-Jan-2024 11:45:48 max 19.147367477416992
04-Jan-2024 11:45:48 min -15.199692726135254
04-Jan-2024 11:45:48 sum 35087.679596841335
04-Jan-2024 11:45:48 median 4.278878211975098
04-Jan-2024 11:45:48 stddev 0.4260329169087803
04-Jan-2024 11:45:48 mean 4.283164013286309
04-Jan-2024 11:45:48 rms 4.3353846668292695
04-Jan-2024 11:45:48 max 5.960114002227783
04-Jan-2024 11:45:48 min 0.9407882690429688
04-Jan-2024 11:45:48 sum 35488.134197711945
04-Jan-2024 11:45:48 median 4.325183868408203
04-Jan-2024 11:45:48 stddev 0.1700795650207275
04-Jan-2024 11:45:48 mean 4.33204763155664
04-Jan-2024 11:45:48 rms 4.306203614057598
04-Jan-2024 11:45:48 max 6.313568592071533
04-Jan-2024 11:45:48 min 1.483452320098877
04-Jan-2024 11:45:48 sum 35238.97358107567
04-Jan-2024 11:45:48 median 4.286481618881226
04-Jan-2024 11:45:48 stddev 0.19837352702878472
04-Jan-2024 11:45:48 mean 4.301632517221148
04-Jan-2024 11:45:48 rms 4.260218426691952
04-Jan-2024 11:45:48 max 6.594586372375488
04-Jan-2024 11:45:48 min 2.4618935585021973
04-Jan-2024 11:45:48 sum 34870.10427117348
04-Jan-2024 11:45:48 median 4.255388259887695
04-Jan-2024 11:45:48 stddev 0.17545003865511774
04-Jan-2024 11:45:48 mean 4.256604525289735
04-Jan-2024 11:45:48 rms 4.304297370622206
04-Jan-2024 11:45:48 max 19.147367477416992
04-Jan-2024 11:45:48 min -15.199692726135254
04-Jan-2024 11:45:48 sum 35087.679596841335
04-Jan-2024 11:45:48 median 4.278878211975098
04-Jan-2024 11:45:48 stddev 0.4260329169087803
04-Jan-2024 11:45:48 mean 4.283164013286309
04-Jan-2024 11:45:48 rms 4.3353846668292695
04-Jan-2024 11:45:48 max 5.960114002227783
04-Jan-2024 11:45:48 min 0.9407882690429688
04-Jan-2024 11:45:48 sum 35488.134197711945
04-Jan-2024 11:45:48 median 4.325183868408203
04-Jan-2024 11:45:48 stddev 0.1700795650207275
04-Jan-2024 11:45:48 mean 4.33204763155664
04-Jan-2024 11:45:48 rms 4.306203614057598
04-Jan-2024 11:45:48 max 6.313568592071533
04-Jan-2024 11:45:48 min 1.483452320098877
04-Jan-2024 11:45:48 sum 35238.97358107567
04-Jan-2024 11:45:48 median 4.286481618881226
04-Jan-2024 11:45:48 stddev 0.19837352702878472
04-Jan-2024 11:45:48 mean 4.301632517221148
04-Jan-2024 11:45:48 rms 4.260218426691952
04-Jan-2024 11:45:48 max 6.594586372375488
04-Jan-2024 11:45:48 min 2.4618935585021973
04-Jan-2024 11:45:48 sum 34870.10427117348
04-Jan-2024 11:45:48 median 4.255388259887695
04-Jan-2024 11:45:48 stddev 0.17545003865511774
04-Jan-2024 11:45:48 mean 4.256604525289735
04-Jan-2024 11:45:48 rms 3.9222649429916214
04-Jan-2024 11:45:48 max 5.5116047859191895
04-Jan-2024 11:45:48 min 2.200864553451538
04-Jan-2024 11:45:48 sum 32089.27730822563
04-Jan-2024 11:45:48 median 3.910185933113098
04-Jan-2024 11:45:48 stddev 0.20029446585363156
04-Jan-2024 11:45:48 mean 3.917148108914265
04-Jan-2024 11:45:48 rms 3.8027938560962418
04-Jan-2024 11:45:48 max 6.305795192718506
04-Jan-2024 11:45:48 min 0.28544679284095764
04-Jan-2024 11:45:48 sum 31103.86206844449
04-Jan-2024 11:45:48 median 3.79739773273468
04-Jan-2024 11:45:48 stddev 0.2124022406509363
04-Jan-2024 11:45:48 mean 3.796858162651916
04-Jan-2024 11:45:48 rms 5.3273187281254115
04-Jan-2024 11:45:48 max 134.43093872070312
04-Jan-2024 11:45:48 min -221.74778747558594
04-Jan-2024 11:45:48 sum 32937.74573640153
04-Jan-2024 11:45:48 median 3.9856526851654053
04-Jan-2024 11:45:48 stddev 3.495085023068309
04-Jan-2024 11:45:48 mean 4.020720915088071
04-Jan-2024 11:45:48 rms 3.9222649429916214
04-Jan-2024 11:45:48 max 5.5116047859191895
04-Jan-2024 11:45:48 min 2.200864553451538
04-Jan-2024 11:45:48 sum 32089.27730822563
04-Jan-2024 11:45:48 median 3.910185933113098
04-Jan-2024 11:45:48 stddev 0.20029446585363156
04-Jan-2024 11:45:48 mean 3.917148108914265
04-Jan-2024 11:45:48 rms 3.8027938560962418
04-Jan-2024 11:45:48 max 6.305795192718506
04-Jan-2024 11:45:48 min 0.28544679284095764
04-Jan-2024 11:45:48 sum 31103.86206844449
04-Jan-2024 11:45:48 median 3.79739773273468
04-Jan-2024 11:45:48 stddev 0.2124022406509363
04-Jan-2024 11:45:48 mean 3.796858162651916
04-Jan-2024 11:45:48 rms 5.3273187281254115
04-Jan-2024 11:45:48 max 134.43093872070312
04-Jan-2024 11:45:48 min -221.74778747558594
04-Jan-2024 11:45:48 sum 32937.74573640153
04-Jan-2024 11:45:48 median 3.9856526851654053
04-Jan-2024 11:45:48 stddev 3.495085023068309
04-Jan-2024 11:45:48 mean 4.020720915088071
04-Jan-2024 11:45:48 rms 4.008290669779586
04-Jan-2024 11:45:48 max 5.441513538360596
04-Jan-2024 11:45:48 min 1.3497779369354248
04-Jan-2024 11:45:48 sum 32807.04150438309
04-Jan-2024 11:45:48 median 4.002278804779053
04-Jan-2024 11:45:48 stddev 0.16807248338680333
04-Jan-2024 11:45:48 mean 4.004765808640521
04-Jan-2024 11:45:48 rms 3.9222649429916214
04-Jan-2024 11:45:48 max 5.5116047859191895
04-Jan-2024 11:45:48 min 2.200864553451538
04-Jan-2024 11:45:48 sum 32089.27730822563
04-Jan-2024 11:45:48 median 3.910185933113098
04-Jan-2024 11:45:48 stddev 0.20029446585363156
04-Jan-2024 11:45:48 mean 3.917148108914265
04-Jan-2024 11:45:48 rms 3.8027938560962418
04-Jan-2024 11:45:48 max 6.305795192718506
04-Jan-2024 11:45:48 min 0.28544679284095764
04-Jan-2024 11:45:48 sum 31103.86206844449
04-Jan-2024 11:45:48 median 3.79739773273468
04-Jan-2024 11:45:48 stddev 0.2124022406509363
04-Jan-2024 11:45:48 mean 3.796858162651916
04-Jan-2024 11:45:48 rms 5.3273187281254115
04-Jan-2024 11:45:48 max 134.43093872070312
04-Jan-2024 11:45:48 min -221.74778747558594
04-Jan-2024 11:45:48 sum 32937.74573640153
04-Jan-2024 11:45:48 median 3.9856526851654053
04-Jan-2024 11:45:48 stddev 3.495085023068309
04-Jan-2024 11:45:48 mean 4.020720915088071
04-Jan-2024 11:45:48 rms 4.008290669779586
04-Jan-2024 11:45:48 max 5.441513538360596
04-Jan-2024 11:45:48 min 1.3497779369354248
04-Jan-2024 11:45:48 sum 32807.04150438309
04-Jan-2024 11:45:48 median 4.002278804779053
04-Jan-2024 11:45:48 stddev 0.16807248338680333
04-Jan-2024 11:45:48 mean 4.004765808640521
04-Jan-2024 11:45:48 rms 3.9222649429916214
04-Jan-2024 11:45:48 max 5.5116047859191895
04-Jan-2024 11:45:48 min 2.200864553451538
04-Jan-2024 11:45:48 sum 32089.27730822563
04-Jan-2024 11:45:48 median 3.910185933113098
04-Jan-2024 11:45:48 stddev 0.20029446585363156
04-Jan-2024 11:45:48 mean 3.917148108914265
04-Jan-2024 11:45:48 rms 3.8027938560962418
04-Jan-2024 11:45:48 max 6.305795192718506
04-Jan-2024 11:45:48 min 0.28544679284095764
04-Jan-2024 11:45:48 sum 31103.86206844449
04-Jan-2024 11:45:48 median 3.79739773273468
04-Jan-2024 11:45:48 stddev 0.2124022406509363
04-Jan-2024 11:45:48 mean 3.796858162651916
04-Jan-2024 11:45:48 rms 5.3273187281254115
04-Jan-2024 11:45:48 max 134.43093872070312
04-Jan-2024 11:45:48 min -221.74778747558594
04-Jan-2024 11:45:48 sum 32937.74573640153
04-Jan-2024 11:45:48 median 3.9856526851654053
04-Jan-2024 11:45:48 stddev 3.495085023068309
04-Jan-2024 11:45:48 mean 4.020720915088071
04-Jan-2024 11:45:48 rms 4.008290669779586
04-Jan-2024 11:45:48 max 5.441513538360596
04-Jan-2024 11:45:48 min 1.3497779369354248
04-Jan-2024 11:45:48 sum 32807.04150438309
04-Jan-2024 11:45:48 median 4.002278804779053
04-Jan-2024 11:45:48 stddev 0.16807248338680333
04-Jan-2024 11:45:48 mean 4.004765808640521
04-Jan-2024 11:45:48 PASSED
04-Jan-2024 11:45:48
04-Jan-2024 11:45:57 test_task_visstat.py::visstat_test::test_reportingaxes
04-Jan-2024 11:45:57 test_reportingaxes
04-Jan-2024 11:45:57 -----------------------------
04-Jan-2024 11:45:57
04-Jan-2024 11:45:57 Test the reportingaxes parameter.
04-Jan-2024 11:45:57 The output should be a dict and contain all the expected keys.
04-Jan-2024 11:45:57
04-Jan-2024 11:45:57 Iterate over all the possible values.
04-Jan-2024 11:45:57 PASSED
04-Jan-2024 11:45:57
04-Jan-2024 11:45:57 test_task_visstat.py::visstat_test::test_scan
04-Jan-2024 11:45:57 test_scan
04-Jan-2024 11:45:57 ------------
04-Jan-2024 11:45:57
04-Jan-2024 11:45:57 Test the scan selection parameter
04-Jan-2024 11:45:57
04-Jan-2024 11:45:57 Assert that the selction with this parameter will return a different result than no selection.
04-Jan-2024 11:45:57 PASSED
04-Jan-2024 11:45:57
04-Jan-2024 11:45:58 test_task_visstat.py::visstat_test::test_selectdata
04-Jan-2024 11:45:58 test_selectdata
04-Jan-2024 11:45:58 -----------------------
04-Jan-2024 11:45:58
04-Jan-2024 11:45:58 Test the selectdata parameter
04-Jan-2024 11:45:58
04-Jan-2024 11:45:58 Assert that the select data parameter prevents other selection fields from having an affect
04-Jan-2024 11:45:58
04-Jan-2024 11:45:58 Assert that with selectdata=False and an active selection produces the same results as the task with no selection
04-Jan-2024 11:45:58 PASSED
04-Jan-2024 11:45:58
04-Jan-2024 11:45:59 test_task_visstat.py::visstat_test::test_special_cases
04-Jan-2024 11:45:59 Visstat 04: Test of special cases
04-Jan-2024 11:45:59
04-Jan-2024 11:45:59 antenna = 1 ; mean =  0.0
04-Jan-2024 11:45:59
04-Jan-2024 11:45:59 antenna = 2 ; mean =  1.0
04-Jan-2024 11:45:59
04-Jan-2024 11:45:59 antenna = 3 ; mean =  2.0
04-Jan-2024 11:45:59
04-Jan-2024 11:45:59 antenna = 4 ; mean =  3.0
04-Jan-2024 11:45:59 PASSED
04-Jan-2024 11:45:59
04-Jan-2024 11:45:59 test_task_visstat.py::visstat_test::test_spw
04-Jan-2024 11:45:59 test_spw
04-Jan-2024 11:45:59 ---------------
04-Jan-2024 11:45:59
04-Jan-2024 11:45:59 Test the spectral window selection parameter.
04-Jan-2024 11:45:59
04-Jan-2024 11:45:59 Assert that a selection using the spw parameter returns a different result than no selection.
04-Jan-2024 11:45:59 PASSED
04-Jan-2024 11:45:59
04-Jan-2024 11:46:01 test_task_visstat.py::visstat_test::test_timeAvgAcrossScans
04-Jan-2024 11:46:01 Visstat 12: Test of time averaging across scans
04-Jan-2024 11:46:01 PASSED
04-Jan-2024 11:46:01
04-Jan-2024 11:46:02 test_task_visstat.py::visstat_test::test_timeAvgWithinScans
04-Jan-2024 11:46:02 Visstat 11: Test of time averaging within scans
04-Jan-2024 11:46:02 PASSED
04-Jan-2024 11:46:02
04-Jan-2024 11:46:05 test_task_visstat.py::visstat_test::test_timeavg
04-Jan-2024 11:46:05 test_timeaverage
04-Jan-2024 11:46:05 ---------------------
04-Jan-2024 11:46:05
04-Jan-2024 11:46:05 Test the timeaverage parameter
04-Jan-2024 11:46:05
04-Jan-2024 11:46:05 Assert that the dict produced when timeaverage = True is different from the one produced when timeaverage=False
04-Jan-2024 11:46:05 PASSED
04-Jan-2024 11:46:05
04-Jan-2024 11:46:06 test_task_visstat.py::visstat_test::test_timebin
04-Jan-2024 11:46:06 test_timebin
04-Jan-2024 11:46:06 -------------------
04-Jan-2024 11:46:06
04-Jan-2024 11:46:06 Test the timebin parameter
04-Jan-2024 11:46:06
04-Jan-2024 11:46:06 Assert that the result when given a bin width for averaging is different than when none is given.
04-Jan-2024 11:46:06 PASSED
04-Jan-2024 11:46:06
04-Jan-2024 11:46:07 test_task_visstat.py::visstat_test::test_timerange
04-Jan-2024 11:46:07 test_timerange
04-Jan-2024 11:46:07 ------------------
04-Jan-2024 11:46:07
04-Jan-2024 11:46:07 Test the timerange selection parameter
04-Jan-2024 11:46:07
04-Jan-2024 11:46:07 Assert that the selection with this parameter will return a different value than no selection.
04-Jan-2024 11:46:07 PASSED
04-Jan-2024 11:46:07
04-Jan-2024 11:46:07 Failing task since return code of [/Users/casaci/bamboohome/temp/CASA-CPR107-TTO1P-1-ScriptBuildTask-12977486445941704374.sh] was 143 while expected 0
04-Jan-2024 11:46:07 test_task_visstat.py::visstat_test::test_timespan
04-Jan-2024 11:46:07 Finished task 'Test wheel' with result: Failed
04-Jan-2024 11:46:07 Running post build plugin 'Docker Container Cleanup'
04-Jan-2024 11:46:07 Running post build plugin 'NCover Results Collector'
04-Jan-2024 11:46:07 Running post build plugin 'Build Results Label Collector'
04-Jan-2024 11:46:07 Running post build plugin 'Clover Results Collector'
04-Jan-2024 11:46:07 Running post build plugin 'npm Cache Cleanup'
04-Jan-2024 11:46:07 Running post build plugin 'Artifact Copier'
04-Jan-2024 11:46:08 Publishing an artifact: OSX10.14 casatasks wheel
04-Jan-2024 11:46:08 Force Stop build feature is enabled for current plan. Either Bamboo has detected the build has hung or it has been manually stopped.
04-Jan-2024 11:46:08 Attempting to generate stack trace and terminate spawned sub-processes of process id: 90446
04-Jan-2024 11:46:08 Finished publishing of artifact Required job artifact Http Compression On : [OSX10.14 casatasks wheel], patterns: [casatasks*.whl] anchored at: [wheeldirectory/] in 128.4 ms
04-Jan-2024 11:46:08 Finalising the build...
04-Jan-2024 11:46:08 Stopping timer.
04-Jan-2024 11:46:08 Build CASA-CPR107-TTO1P-1 completed.
04-Jan-2024 11:46:08 Found related process: pid: 67187 ppid: 1 pgid: 90443 %cpu: 0.0 %mem: 0.1 cmd: /opt/casa/03/Library/Frameworks/Python.framework/Versions/3.8/Resources/Python.app/Contents/MacOS/Python
04-Jan-2024 11:46:08 getStackTraceAndKillRelatedProcesses for 1 processes
04-Jan-2024 11:46:08 Executing kill -3 67187
04-Jan-2024 11:46:08 Running on server: post build plugin 'Build Hanging Detection Configuration'
04-Jan-2024 11:46:08 Running on server: post build plugin 'NCover Results Collector'
04-Jan-2024 11:46:08 Running on server: post build plugin 'Build Labeller'
04-Jan-2024 11:46:08 Running on server: post build plugin 'Clover Delta Calculator'
04-Jan-2024 11:46:08 Running on server: post build plugin 'Maven Dependencies Postprocessor'
04-Jan-2024 11:46:08 All post build plugins have finished
04-Jan-2024 11:46:08 Generating build results summary...
04-Jan-2024 11:46:08 Saving build results to disk...
04-Jan-2024 11:46:08 Store variable context...
04-Jan-2024 11:46:08 Finished building CASA-CPR107-TTO1P-1.
04-Jan-2024 11:46:13 Killing: 67187
04-Jan-2024 11:46:13 Executing kill 67187
04-Jan-2024 11:46:18 Force Stop build feature is enabled for current plan. Either Bamboo has detected the build has hung or it has been manually stopped.
04-Jan-2024 11:46:18 Has finished generating stack trace and terminating spawned sub-processes of process id: 90446