def test_13A_537__calibration__PPR__regression(): """Run VLA calibration regression with a PPR file. PPR name: PPR_13A-537.xml Dataset: 13A-537/13A-537.sb24066356.eb24324502.56514.05971091435 """ ref_directory = 'pl-regressiontest/13A-537' pt = PipelineTester( visname=['13A-537.sb24066356.eb24324502.56514.05971091435'], ppr=f'{ref_directory}/PPR_13A-537.xml', input_dir=ref_directory, output_dir='13A_537__calibration__PPR__regression', expectedoutput_dir=ref_directory, ) > pt.run(telescope='vla', omp_num_threads=1) tests/regression/fast/vla_fast_test.py:44: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/testing_utils.py:381: in run self.__compare_results(new_file, default_relative_tolerance) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = <tests.testing_utils.PipelineTester object at 0x7f83923eae10> new_file = '13A-537.sb24066356.eb24324502.56514.05971091435.NEW.results.txt' relative_tolerance = 1e-07 def __compare_results(self, new_file: str, relative_tolerance: float) -> None: """ Compare results between new one loaded from file and old one. Args: new_file : file path of new results relative_tolerance : relative tolerance of output value """ with open(self.expectedoutput_file) as expected_fd, open(new_file) as new_fd: expected_results = expected_fd.readlines() new_results = new_fd.readlines() errors = [] worst_diff = (0, 0) worst_percent_diff = (0, 0) for old, new in zip(expected_results, new_results): try: oldkey, oldval, tol = self.__sanitize_results_string(old) newkey, newval, _ = self.__sanitize_results_string(new) except ValueError as e: errorstr = "The results: {0} could not be parsed. Error: {1}".format(new, str(e)) errors.append(errorstr) continue assert oldkey == newkey, f"Expected key {oldkey} does not match new key {newkey}." tolerance = tol if tol else relative_tolerance if newval is not None: LOG.info('Comparing %s to %s with a rel. tolerance of %s', oldval, newval, tolerance) if oldval != pytest.approx(newval, rel=tolerance): diff = oldval-newval percent_diff = (oldval-newval)/oldval * 100 if oldval != 0 else 100 if abs(diff) > abs(worst_diff[0]): worst_diff = diff, oldkey if abs(percent_diff) > abs(worst_percent_diff[0]): worst_percent_diff = percent_diff, oldkey errorstr = f"{oldkey}\n\tvalues differ by > a relative difference of {tolerance}\n\texpected: {oldval}\n\tnew: {newval}\n\tdiff: {diff}\n\tpercent_diff: {percent_diff}%" errors.append(errorstr) elif oldval is not None: # If only the new value is None, fail errorstr = f"{oldkey}\n\tvalue is None\n\texpected: {oldval}\n\tnew: {newval}" errors.append(errorstr) else: # If old and new values are both None, this is expected, so pass LOG.info('Comparing %s and %s... both values are None.', oldval, newval) [LOG.warning(x) for x in errors] n_errors = len(errors) if n_errors > 0: summary_str = f"Worst absolute diff, {worst_diff[1]}: {worst_diff[0]}\nWorst percentage diff, {worst_percent_diff[1]}: {worst_percent_diff[0]}%" errors.append(summary_str) > pytest.fail("Failed to match {0} result value{1} within tolerance{1} :\n{2}".format( n_errors, '' if n_errors == 1 else 's', '\n'.join(errors)), pytrace=True) E Failed: Failed to match 23 result values within tolerances : E s10.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 15177536 E new: 15177530 E diff: 6 E percent_diff: 3.9532108505623046e-05% E s10.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_4.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 11498690 E new: 11498688 E diff: 2 E percent_diff: 1.7393285669932836e-05% E s10.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_8.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 3678846 E new: 3678842 E diff: 4 E percent_diff: 0.00010872974840479869% E s12.hifv_fluxboot.13A-537.sb24066356.eb24324502.56514.05971091435.flux_densities.spw_0 E values differ by > a relative difference of 1e-07 E expected: 0.7150094554333849 E new: 0.7149940856445874 E diff: 1.5369788797459094e-05 E percent_diff: 0.002149592383801846% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 48816984 E new: 48816966 E diff: 18 E percent_diff: 3.687241309295142e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 48585580 E new: 48585562 E diff: 18 E percent_diff: 3.704802947705883e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_2.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 7526954 E new: 7526956 E diff: -2 E percent_diff: -2.6571173412246175e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_2.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 7526954 E new: 7526956 E diff: -2 E percent_diff: -2.6571173412246175e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_3.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 6902474 E new: 6902460 E diff: 14 E percent_diff: 0.00020282582737725634% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_3.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 6902474 E new: 6902460 E diff: 14 E percent_diff: 0.00020282582737725634% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_4.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 11498690 E new: 11498688 E diff: 2 E percent_diff: 1.7393285669932836e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_4.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 11498690 E new: 11498688 E diff: 2 E percent_diff: 1.7393285669932836e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_8.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 3678846 E new: 3678842 E diff: 4 E percent_diff: 0.00010872974840479869% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_8.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 3678846 E new: 3678842 E diff: 4 E percent_diff: 0.00010872974840479869% E s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 29069541 E new: 29068884 E diff: 657 E percent_diff: 0.002260097605256306% E s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_5.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 9127246 E new: 9127166 E diff: 80 E percent_diff: 0.000876496590537825% E s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_6.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 7154924 E new: 7154697 E diff: 227 E percent_diff: 0.0031726402684361145% E s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_7.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 7755435 E new: 7755085 E diff: 350 E percent_diff: 0.004512964134184607% E s16.hifv_statwt.13A-537.sb24066356.eb24324502.56514.05971091435.mean E values differ by > a relative difference of 1e-07 E expected: 0.6294125096532232 E new: 0.6294256901955095 E diff: -1.318054228638399e-05 E percent_diff: -0.0020941023707402723% E s16.hifv_statwt.13A-537.sb24066356.eb24324502.56514.05971091435.variance E values differ by > a relative difference of 1e-07 E expected: 0.06275818592512647 E new: 0.06276085915536926 E diff: -2.6732302427917576e-06 E percent_diff: -0.004259572203028701% E s8.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 14429428 E new: 14429416 E diff: 12 E percent_diff: 8.316337972648673e-05% E s8.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_2.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 7526954 E new: 7526956 E diff: -2 E percent_diff: -2.6571173412246175e-05% E s8.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_3.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 6902474 E new: 6902460 E diff: 14 E percent_diff: 0.00020282582737725634% E Worst absolute diff, s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after: 657 E Worst percentage diff, s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_7.num_rows_flagged.after: 0.004512964134184607% tests/testing_utils.py:440: Failed@pytest.mark.seven @pytest.mark.mpi def test_2023_1_00228_S__uid___A002_X1199f9e_X7c24__procedure_hifa_calimage_diffgain__regression(): """Run ALMA cal+image regression on a 7m B2B dataset with differential gain calibration. Recipe name: procedure_hifa_calimage_diffgain Dataset: 2023.1.00228.S: uid___A002_X1199f9e_X7c24 """ ref_directory = 'pl-regressiontest/2023.1.00228.S' pt = PipelineTester( visname=['uid___A002_X1199f9e_X7c24'], recipe='procedure_hifa_calimage_diffgain.xml', input_dir=ref_directory, expectedoutput_dir=ref_directory, ) > pt.run() tests/regression/fast/alma_if_fast_test.py:142: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/testing_utils.py:381: in run self.__compare_results(new_file, default_relative_tolerance) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = <tests.testing_utils.PipelineTester object at 0x7f4e40640b30> new_file = 'uid___A002_X1199f9e_X7c24.NEW.results.txt' relative_tolerance = 1e-07 def __compare_results(self, new_file: str, relative_tolerance: float) -> None: """ Compare results between new one loaded from file and old one. Args: new_file : file path of new results relative_tolerance : relative tolerance of output value """ with open(self.expectedoutput_file) as expected_fd, open(new_file) as new_fd: expected_results = expected_fd.readlines() new_results = new_fd.readlines() errors = [] worst_diff = (0, 0) worst_percent_diff = (0, 0) for old, new in zip(expected_results, new_results): try: oldkey, oldval, tol = self.__sanitize_results_string(old) newkey, newval, _ = self.__sanitize_results_string(new) except ValueError as e: errorstr = "The results: {0} could not be parsed. Error: {1}".format(new, str(e)) errors.append(errorstr) continue assert oldkey == newkey, f"Expected key {oldkey} does not match new key {newkey}." tolerance = tol if tol else relative_tolerance if newval is not None: LOG.info('Comparing %s to %s with a rel. tolerance of %s', oldval, newval, tolerance) if oldval != pytest.approx(newval, rel=tolerance): diff = oldval-newval percent_diff = (oldval-newval)/oldval * 100 if oldval != 0 else 100 if abs(diff) > abs(worst_diff[0]): worst_diff = diff, oldkey if abs(percent_diff) > abs(worst_percent_diff[0]): worst_percent_diff = percent_diff, oldkey errorstr = f"{oldkey}\n\tvalues differ by > a relative difference of {tolerance}\n\texpected: {oldval}\n\tnew: {newval}\n\tdiff: {diff}\n\tpercent_diff: {percent_diff}%" errors.append(errorstr) elif oldval is not None: # If only the new value is None, fail errorstr = f"{oldkey}\n\tvalue is None\n\texpected: {oldval}\n\tnew: {newval}" errors.append(errorstr) else: # If old and new values are both None, this is expected, so pass LOG.info('Comparing %s and %s... both values are None.', oldval, newval) [LOG.warning(x) for x in errors] n_errors = len(errors) if n_errors > 0: summary_str = f"Worst absolute diff, {worst_diff[1]}: {worst_diff[0]}\nWorst percentage diff, {worst_percent_diff[1]}: {worst_percent_diff[0]}%" errors.append(summary_str) > pytest.fail("Failed to match {0} result value{1} within tolerance{1} :\n{2}".format( n_errors, '' if n_errors == 1 else 's', '\n'.join(errors)), pytrace=True) E Failed: Failed to match 6 result values within tolerances : E s21.hif_applycal.uid___A002_X1199f9e_X7c24.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 249574780 E new: 249563260 E diff: 11520 E percent_diff: 0.004615851008663616% E s21.hif_applycal.uid___A002_X1199f9e_X7c24.scan_11.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 1958304 E new: 1935264 E diff: 23040 E percent_diff: 1.176528261189274% E s21.hif_applycal.uid___A002_X1199f9e_X7c24.scan_13.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 1736584 E new: 1716424 E diff: 20160 E percent_diff: 1.1608997894717445% E s21.hif_applycal.uid___A002_X1199f9e_X7c24.scan_15.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 1755616 E new: 1775776 E diff: -20160 E percent_diff: -1.148314893461896% E s21.hif_applycal.uid___A002_X1199f9e_X7c24.scan_9.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 1861520 E new: 1873040 E diff: -11520 E percent_diff: -0.6188491125531823% E s21.hif_applycal.uid___A002_X1199f9e_X7c24.spw_31.qa.metric.phase_vs_freqslope E values differ by > a relative difference of 1e-07 E expected: 46.569797759406356 E new: 46.56980701614873 E diff: -9.256742373509041e-06 E percent_diff: -1.9877136725678237e-05% E Worst absolute diff, s21.hif_applycal.uid___A002_X1199f9e_X7c24.scan_11.num_rows_flagged.after: 23040 E Worst percentage diff, s21.hif_applycal.uid___A002_X1199f9e_X7c24.scan_11.num_rows_flagged.after: 1.176528261189274% tests/testing_utils.py:440: Faileddef test_13A_537__procedure_hifv__regression(): """Run VLA calibration regression for standard procedure_hifv.xml recipe. Recipe name: procedure_hifv Dataset: 13A-537/13A-537.sb24066356.eb24324502.56514.05971091435 """ ref_directory = 'pl-regressiontest/13A-537' pt = PipelineTester( visname=['13A-537.sb24066356.eb24324502.56514.05971091435'], recipe='procedure_hifv.xml', input_dir=ref_directory, output_dir='13A_537__procedure_hifv__regression', expectedoutput_dir=ref_directory, ) > pt.run(telescope='vla', omp_num_threads=1) tests/regression/fast/vla_fast_test.py:25: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/testing_utils.py:381: in run self.__compare_results(new_file, default_relative_tolerance) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = <tests.testing_utils.PipelineTester object at 0x7f84bc7bd220> new_file = '13A-537.sb24066356.eb24324502.56514.05971091435.NEW.results.txt' relative_tolerance = 1e-07 def __compare_results(self, new_file: str, relative_tolerance: float) -> None: """ Compare results between new one loaded from file and old one. Args: new_file : file path of new results relative_tolerance : relative tolerance of output value """ with open(self.expectedoutput_file) as expected_fd, open(new_file) as new_fd: expected_results = expected_fd.readlines() new_results = new_fd.readlines() errors = [] worst_diff = (0, 0) worst_percent_diff = (0, 0) for old, new in zip(expected_results, new_results): try: oldkey, oldval, tol = self.__sanitize_results_string(old) newkey, newval, _ = self.__sanitize_results_string(new) except ValueError as e: errorstr = "The results: {0} could not be parsed. Error: {1}".format(new, str(e)) errors.append(errorstr) continue assert oldkey == newkey, f"Expected key {oldkey} does not match new key {newkey}." tolerance = tol if tol else relative_tolerance if newval is not None: LOG.info('Comparing %s to %s with a rel. tolerance of %s', oldval, newval, tolerance) if oldval != pytest.approx(newval, rel=tolerance): diff = oldval-newval percent_diff = (oldval-newval)/oldval * 100 if oldval != 0 else 100 if abs(diff) > abs(worst_diff[0]): worst_diff = diff, oldkey if abs(percent_diff) > abs(worst_percent_diff[0]): worst_percent_diff = percent_diff, oldkey errorstr = f"{oldkey}\n\tvalues differ by > a relative difference of {tolerance}\n\texpected: {oldval}\n\tnew: {newval}\n\tdiff: {diff}\n\tpercent_diff: {percent_diff}%" errors.append(errorstr) elif oldval is not None: # If only the new value is None, fail errorstr = f"{oldkey}\n\tvalue is None\n\texpected: {oldval}\n\tnew: {newval}" errors.append(errorstr) else: # If old and new values are both None, this is expected, so pass LOG.info('Comparing %s and %s... both values are None.', oldval, newval) [LOG.warning(x) for x in errors] n_errors = len(errors) if n_errors > 0: summary_str = f"Worst absolute diff, {worst_diff[1]}: {worst_diff[0]}\nWorst percentage diff, {worst_percent_diff[1]}: {worst_percent_diff[0]}%" errors.append(summary_str) > pytest.fail("Failed to match {0} result value{1} within tolerance{1} :\n{2}".format( n_errors, '' if n_errors == 1 else 's', '\n'.join(errors)), pytrace=True) E Failed: Failed to match 23 result values within tolerances : E s10.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 15177536 E new: 15177530 E diff: 6 E percent_diff: 3.9532108505623046e-05% E s10.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_4.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 11498690 E new: 11498688 E diff: 2 E percent_diff: 1.7393285669932836e-05% E s10.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_8.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 3678846 E new: 3678842 E diff: 4 E percent_diff: 0.00010872974840479869% E s12.hifv_fluxboot.13A-537.sb24066356.eb24324502.56514.05971091435.flux_densities.spw_0 E values differ by > a relative difference of 1e-07 E expected: 0.7150094554333849 E new: 0.7149940856445874 E diff: 1.5369788797459094e-05 E percent_diff: 0.002149592383801846% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 48816984 E new: 48816966 E diff: 18 E percent_diff: 3.687241309295142e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 48585580 E new: 48585562 E diff: 18 E percent_diff: 3.704802947705883e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_2.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 7526954 E new: 7526956 E diff: -2 E percent_diff: -2.6571173412246175e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_2.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 7526954 E new: 7526956 E diff: -2 E percent_diff: -2.6571173412246175e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_3.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 6902474 E new: 6902460 E diff: 14 E percent_diff: 0.00020282582737725634% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_3.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 6902474 E new: 6902460 E diff: 14 E percent_diff: 0.00020282582737725634% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_4.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 11498690 E new: 11498688 E diff: 2 E percent_diff: 1.7393285669932836e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_4.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 11498690 E new: 11498688 E diff: 2 E percent_diff: 1.7393285669932836e-05% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_8.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 3678846 E new: 3678842 E diff: 4 E percent_diff: 0.00010872974840479869% E s14.hifv_applycals.13A-537.sb24066356.eb24324502.56514.05971091435.scan_8.num_rows_flagged.before E values differ by > a relative difference of 1e-07 E expected: 3678846 E new: 3678842 E diff: 4 E percent_diff: 0.00010872974840479869% E s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 29069541 E new: 29068884 E diff: 657 E percent_diff: 0.002260097605256306% E s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_5.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 9127246 E new: 9127166 E diff: 80 E percent_diff: 0.000876496590537825% E s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_6.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 7154924 E new: 7154697 E diff: 227 E percent_diff: 0.0031726402684361145% E s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_7.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 7755435 E new: 7755085 E diff: 350 E percent_diff: 0.004512964134184607% E s16.hifv_statwt.13A-537.sb24066356.eb24324502.56514.05971091435.mean E values differ by > a relative difference of 1e-07 E expected: 0.6294125096532232 E new: 0.6294256901955095 E diff: -1.318054228638399e-05 E percent_diff: -0.0020941023707402723% E s16.hifv_statwt.13A-537.sb24066356.eb24324502.56514.05971091435.variance E values differ by > a relative difference of 1e-07 E expected: 0.06275818592512647 E new: 0.06276085915536926 E diff: -2.6732302427917576e-06 E percent_diff: -0.004259572203028701% E s8.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 14429428 E new: 14429416 E diff: 12 E percent_diff: 8.316337972648673e-05% E s8.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_2.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 7526954 E new: 7526956 E diff: -2 E percent_diff: -2.6571173412246175e-05% E s8.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_3.num_rows_flagged.after E values differ by > a relative difference of 1e-07 E expected: 6902474 E new: 6902460 E diff: 14 E percent_diff: 0.00020282582737725634% E Worst absolute diff, s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.num_rows_flagged.after: 657 E Worst percentage diff, s15.hifv_checkflag.13A-537.sb24066356.eb24324502.56514.05971091435.scan_7.num_rows_flagged.after: 0.004512964134184607% tests/testing_utils.py:440: Failed