def test_wfs_image2(self): """ Regression test of the WFS&C `calwebb_wfs-image2.cfg` pipeline """ data_base = 'jw82600026001_02101_00001_nrca1_rate' ext = '.fits' input_name = '{}{}'.format(data_base, ext) input_file = self.get_data(self.test_dir, 'sdp_jw82600_wfs', 'level2a', input_name) collect_pipeline_cfgs('cfgs') Step.from_cmdline([os.path.join('cfgs', 'calwebb_wfs-image2.cfg'), input_file]) cal_name = input_name.replace('rate', 'cal') output_name = input_name.replace('rate','cal_ref') outputs = [(cal_name, output_name)] self.compare_outputs(outputs) output_files = glob.glob('*') output_files.remove('cfgs') # these would happen when docopy=True if input_name in output_files: output_files.remove(input_name) if output_name in output_files: output_files.remove(output_name) assert cal_name in output_files output_files.remove(cal_name) assert not output_files, 'Unexpected output files {}'.format(output_files)
def test_image3_pipeline2(self): """Regression test definitions for CALIMAGE3 pipeline. Regression test of calwebb_image3 pipeline on NIRCam simulated long-wave data with a 6-point dither. """ asn_file = self.get_data(self.test_dir, "jw10002-o001_20171116t191235_image3_002_asn.json") for file in raw_from_asn(asn_file): self.get_data(self.test_dir, file) collect_pipeline_cfgs('config') args = [ 'config/calwebb_image3.cfg', asn_file, '--steps.tweakreg.kernel_fwhm=2', '--steps.tweakreg.snr_threshold=5', '--steps.tweakreg.enforce_user_order=True', '--steps.tweakreg.searchrad=10', '--steps.tweakreg.fitgeometry=rscale' ] Step.from_cmdline(args) outputs = [('jw10002001001_01101_00004_nrcblong_o001_crf.fits', 'jw10002001001_01101_00004_nrcblong_o001_crf_ref.fits'), {'files':('jw10002-o001_t002_nircam_f444w_i2d.fits', 'jw10002-o001_t002_nircam_f444w_i2d_ref.fits'), 'pars':{'ignore_keywords':self.ignore_keywords+['NAXIS1','TFORM*'], 'ignore_fields':self.ignore_keywords, 'rtol':0.0001} } ] self.compare_outputs(outputs)
def test_nrs_fs_spec3(self): """ Regression test of calwebb_spec3 pipeline performed on NIRSpec fixed-slit data. """ cfg_dir = './cfgs' collect_pipeline_cfgs(cfg_dir) datapath = ['test_datasets', 'fss', '93045', 'level2b'] asn_file = self.get_data(*datapath, 'jw93045-o010_20180725t035735_spec3_001_asn.json') for file in raw_from_asn(asn_file): self.get_data(*datapath, file) args = [ path.join(cfg_dir, 'calwebb_spec3.cfg'), asn_file ] Step.from_cmdline(args) # Compare results outputs = [('jw00023001001_01101_00001_NRS1_cal.fits', 'jw00023001001_01101_00001_NRS1_cal_ref.fits'), ('jw00023001001_01101_00001_NRS1_s2d.fits', 'jw00023001001_01101_00001_NRS1_s2d_ref.fits'), ('jw00023001001_01101_00001_NRS1_x1d.fits', 'jw00023001001_01101_00001_NRS1_x1d_ref.fits') ] self.compare_outputs(outputs)
def test_image3_pipeline1(self): asn_name = "mosaic_long_asn.json" asn_file = self.get_data('test_calimage3', asn_name) for file in raw_from_asn(asn_file): self.get_data('test_calimage3', file) collect_pipeline_cfgs('config') args = [ 'config/calwebb_image3.cfg', asn_file, '--steps.tweakreg.skip=True', ] Step.from_cmdline(args) outputs = [(# Compare level-2c crf product 'nrca5_47Tuc_subpix_dither1_newpos_a3001_crf.fits', 'nrca5_47Tuc_subpix_dither1_newpos_cal-a3001_ref.fits'), {'files':(# Compare i2d product 'mosaic_long_i2d.fits', 'mosaic_long_i2d_ref.fits'), 'pars': {'ignore_keywords': self.ignore_keywords+['NAXIS1', 'TFORM*'], 'ignore_fields':self.ignore_keywords, 'rtol': 0.0001} }, ('mosaic_long_cat.ecsv', 'mosaic_long_cat_ref.ecsv'), ] self.compare_outputs(outputs)
def run_pipeline(rtdata_module): """Run the calwebb_spec2 pipeline on a NIRSpec lamp exposure.""" rtdata = rtdata_module # Get the input exposure rtdata.get_data('nirspec/lamp/jw00626030001_02103_00005_nrs1_rate.fits') # Run the calwebb_spec2 pipeline; save results from intermediate steps args = [ "jwst.pipeline.Spec2Pipeline", rtdata.input, "--steps.assign_wcs.save_results=true", "--steps.msa_flagging.save_results=true", "--steps.flat_field.save_results=true", # Hardwire extract1d ref file selection until CRDS-525 is implemented "--steps.extract_1d.override_extract1d=/grp/crds/jwst/references/jwst/jwst_nirspec_extract1d_0001.asdf" ] Step.from_cmdline(args) return rtdata
def run_pipeline(jail, rtdata_module): """Run the calwebb_spec2 pipeline on an ASN of nodded MIRI LRS fixedslit exposures.""" rtdata = rtdata_module # Get the spec2 ASN and its members rtdata.get_data("miri/lrs/MIRI_FM_MIRIMAGE_P750L_PATHLOSS_8C.00.00.fits") rtdata.get_asn("miri/lrs/jw00623-o032_20191210t195246_spec2_001_asn.json") # Run the calwebb_spec2 pipeline; save results from intermediate steps args = ["calwebb_spec2", rtdata.input, "--save_bsub=true", "--steps.assign_wcs.save_results=true", "--steps.flat_field.save_results=true", "--steps.srctype.save_results=true", "--steps.pathloss.save_results=true", "--steps.pathloss.override_pathloss=MIRI_FM_MIRIMAGE_P750L_PATHLOSS_8C.00.00.fits", "--steps.bkg_subtract.save_combined_background=true" ] Step.from_cmdline(args)
def test_set_input_dir(mk_tmp_dirs): """Simply set the path""" input_file = t_path('data/flat.fits') step = Step.from_cmdline([ 'jwst.stpipe.tests.steps.StepWithModel', input_file, '--input_dir', 'junkdir' ]) # Check that `input_dir` is set. assert step.input_dir == 'junkdir'
def test_cube_build_miri_internal_cal(rtdata, fitsdiff_default_kwargs): """Run cube_build on single file using coord system = internal_cal""" input_file = 'det_image_seq2_MIRIFUSHORT_12SHORTexp1_cal.fits' rtdata.get_data(f"miri/mrs/{input_file}") args = [ 'jwst.cube_build.CubeBuildStep', input_file, '--save_results=true', '--coord_system=internal_cal' ] Step.from_cmdline(args) output = input_file.replace('cal', 'ch1-short_internal_s3d') rtdata.output = output rtdata.get_truth(f"truth/test_miri_cubebuild/{output}") diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs) assert diff.identical, diff.report()
def run_detector1(rtdata_module): """Run detector1 pipeline on MIRI imaging data.""" rtdata = rtdata_module rtdata.get_data("miri/image/det_image_1_MIRIMAGE_F770Wexp1_5stars_uncal.fits") # Run detector1 pipeline only on one of the _uncal files args = ["jwst.pipeline.Detector1Pipeline", rtdata.input, "--save_calibrated_ramp=True", "--steps.dq_init.save_results=True", "--steps.saturation.save_results=True", "--steps.refpix.save_results=True", "--steps.rscd.save_results=True", "--steps.lastframe.save_results=True", "--steps.firstframe.save_results=True", "--steps.reset.save_results=True", "--steps.linearity.save_results=True", "--steps.dark_current.save_results=True", "--steps.jump.rejection_threshold=200", ] Step.from_cmdline(args)
def test_residual_fringe_cal(rtdata, fitsdiff_default_kwargs): """Run residual fringe correction on MIRI IFUShort """ input_file = 'MIRM108-SHORT-6021192005_1_495_MIRIFUSHORT_cal.fits' rtdata.get_data(f"miri/mrs/{input_file}") args = [ 'jwst.residual_fringe.ResidualFringeStep', input_file, '--save_results=true', ] Step.from_cmdline(args) output = input_file.replace('cal', 'residual_fringe') rtdata.output = output rtdata.get_truth(f"truth/test_miri_residual_fringe/{output}") diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs) assert diff.identical, diff.report()
def test_pipeline_commandline_invalid_args(): from io import StringIO args = [ 'jwst.stpipe.tests.test_pipeline.MyPipeline', # The file_name parameters are *required*, and one of them # is missing, so we should get a message to that effect # followed by the commandline usage message. '--flat_filename={0}'.format( abspath(join(dirname(__file__), 'data', 'flat.fits'))), '--steps.flat_field.threshold=47' ] sys.stdout = buffer = StringIO() with pytest.raises(ValueError): Step.from_cmdline(args) help = buffer.getvalue() assert "Multiply by this number" in help
def test_nrs_fs_brightobj_spec2(self): """ Regression test of calwebb_spec2 pipeline performed on NIRSpec fixed-slit data that uses the NRS_BRIGHTOBJ mode (S1600A1 slit). """ input_file = self.get_data(self.test_dir, 'jw84600042001_02101_00001_nrs2_rateints.fits') collect_pipeline_cfgs() args = [ 'calwebb_tso-spec2.cfg', input_file ] Step.from_cmdline(args) outputs = [('jw84600042001_02101_00001_nrs2_calints.fits', 'jw84600042001_02101_00001_nrs2_calints_ref.fits'), ('jw84600042001_02101_00001_nrs2_x1dints.fits', 'jw84600042001_02101_00001_nrs2_x1dints_ref.fits') ] self.compare_outputs(outputs)
def test_nirspec_assignwcs_skip(_jail, rtdata, fitsdiff_default_kwargs, caplog): """ Test of calwebb_spec2 pipeline performed on NIRSpec MSA exposure with the AssignWcs step skipped. The pipeline should abort. """ # Get the input file rtdata.get_data( 'nirspec/mos/f170lp-g235m_mos_observation-6-c0e0_001_dn_nrs1_mod.fits') # Run the calwebb_spec2 pipeline collect_pipeline_cfgs("config") args = [ "config/calwebb_spec2.cfg", rtdata.input, '--steps.assign_wcs.skip=True' ] Step.from_cmdline(args) assert 'Aborting remaining processing for this exposure.' in caplog.text
def test_default_input_dir(mk_tmp_dirs): """Test defaults""" input_file = t_path('data/flat.fits') step = Step.from_cmdline([ 'jwst.stpipe.tests.steps.StepWithModel', input_file ]) # Check that `input_dir` is set. input_path = path.split(input_file)[0] assert step.input_dir == input_path
def run_pipeline(jail, rtdata_module): """Run calwebb_detector1 pipeline on MIRI imaging data.""" rtdata = rtdata_module rtdata.get_data("miri/image/jw00001001001_01101_00001_MIRIMAGE_uncal.fits") collect_pipeline_cfgs("config") args = [ "config/calwebb_detector1.cfg", rtdata.input, "--steps.dq_init.save_results=True", "--steps.lastframe.save_results=True", "--steps.firstframe.save_results=True", "--steps.saturation.save_results=True", "--steps.rscd.save_results=True", "--steps.linearity.save_results=True", "--steps.dark_current.save_results=True", "--steps.refpix.save_results=True", "--steps.jump.rejection_threshold=25", "--steps.jump.save_results=True" ] Step.from_cmdline(args) return rtdata
def test_use_input_dir(mk_tmp_dirs): """Test with a specified path""" input_dir = t_path('data') input_file = 'flat.fits' step = Step.from_cmdline([ 'jwst.stpipe.tests.steps.StepWithModel', input_file, '--input_dir', input_dir ]) # Check that `input_dir` is set. assert step.input_dir == input_dir
def test_step_from_commandline_class_alias(mock_stpipe_entry_points): args = ['stpipe_dummy', '--par1=58', '--par2=hij klm'] step = Step.from_cmdline(args) assert isinstance(step, AnotherDummyStep) assert step.par1 == 58. assert step.par2 == 'hij klm' assert step.par3 is False step.run(1, 2)
def test_miri_mrs_extract1d_center(rtdata, fitsdiff_default_kwargs): """Test running extract_1d on an s3d cube containing a point source with user-supplied center""" rtdata.get_data( "miri/mrs/miri_003_det_image_seq1_MIRIFUSHORT_12SHORTexp1_s3d.fits") args = [ 'jwst.extract_1d.Extract1dStep', rtdata.input, '--output_file=miri_003_det_image_seq1_MIRIFUSHORT_12SHORTexp1_center', '--center_xy=28,28' ] Step.from_cmdline(args) rtdata.output = "miri_003_det_image_seq1_MIRIFUSHORT_12SHORTexp1_center_extract1dstep.fits" # Get the truth file rtdata.get_truth( 'truth/test_miri_mrs_extract1d/miri_003_det_image_seq1_MIRIFUSHORT_12SHORTexp1_center_extract1dstep.fits' ) # Compare the results diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs) assert diff.identical, diff.report()
def test_pipeline_commandline(_jail): args = [ abspath(join(dirname(__file__), 'steps', 'python_pipeline.cfg')), '--steps.flat_field.threshold=47' ] pipe = Step.from_cmdline(args) assert pipe.flat_field.threshold == 47.0 assert pipe.flat_field.multiplier == 2.0 pipe.run()
def run_detector1pipeline(rtdata_module, jail): """Run calwebb_detector1 pipeline on NIRSpec data with IRS2 readout mode.""" rtdata = rtdata_module rtdata.get_data("nirspec/irs2/jw0010010_11010_nrs1_chimera_uncal.fits") collect_pipeline_cfgs("config") Step.from_cmdline([ "config/calwebb_detector1.cfg", rtdata.input, "--steps.dq_init.save_results=True", "--steps.saturation.save_results=True", "--steps.superbias.save_results=True", "--steps.refpix.save_results=True", "--steps.rscd.save_results=True", "--steps.linearity.save_results=True", "--steps.dark_current.save_results=True", "--steps.jump.save_results=True", "--steps.ramp_fit.save_results=True", "--steps.gain_scale.save_results=True", "--steps.jump.rejection_threshold=200", ])
def run_tso_spec2(jail, rtdata_module): """Run stage 2 pipeline on NIRISS SOSS data.""" rtdata = rtdata_module # Run tso-spec2 pipeline on the first _rateints file, saving intermediate products rtdata.get_data( "niriss/soss/jw00625023001_03101_00001-seg001_nis_rateints.fits") args = [ "calwebb_spec2", rtdata.input, "--steps.flat_field.save_results=True", "--steps.srctype.save_results=True", ] Step.from_cmdline(args) # Run tso-spec2 pipeline on the second _rateints file, without saving or # checking any results (simply create a fresh input for level-3 test) rtdata.get_data( "niriss/soss/jw00625023001_03101_00001-seg002_nis_rateints.fits") args = ["calwebb_spec2", rtdata.input] Step.from_cmdline(args)
def run_detector1pipeline(jail, rtdata_module): """Run calwebb_detector1 on NIRCam imaging long data""" rtdata = rtdata_module rtdata.get_data("nircam/image/jw42424001001_01101_00001_nrca5_uncal.fits") collect_pipeline_cfgs("config") # Run detector1 pipeline only on one of the _uncal files args = [ "config/calwebb_detector1.cfg", rtdata.input, "--steps.dq_init.save_results=True", "--steps.saturation.save_results=True", "--steps.superbias.save_results=True", "--steps.refpix.save_results=True", "--steps.linearity.save_results=True", "--steps.dark_current.save_results=True", "--steps.jump.save_results=True", "--steps.jump.rejection_threshold=50.0", ] Step.from_cmdline(args)
def run_tso_spec2_pipeline(jail, rtdata_module, request): """Run the calwebb_spec2 pipeline performed on NIRSpec fixed-slit data that uses the NRS_BRIGHTOBJ mode (S1600A1 slit) """ rtdata = rtdata_module # Get the input exposure rtdata.get_data('nirspec/tso/jw84600042001_02101_00001_nrs2_rateints.fits') # Run the calwebb_spec2 pipeline; collect_pipeline_cfgs("config") args = ["config/calwebb_tso-spec2.cfg", rtdata.input, "--steps.assign_wcs.save_results=True", "--steps.extract_2d.save_results=True", "--steps.wavecorr.save_results=True", "--steps.flat_field.save_results=True", "--steps.photom.save_results=True"] Step.from_cmdline(args) return rtdata
def run_pipeline(jail, rtdata_module): """ Run the calwebb_spec3 pipeline on NIRSpec Fixed-Slit exposures. """ rtdata = rtdata_module # Get the cfg files collect_pipeline_cfgs("config") # Get the ASN file and input exposures rtdata.get_asn('nirspec/fs/jw93045-o010_20180725t035735_spec3_001_asn.json') # Run the calwebb_spec3 pipeline; save results from intermediate steps args = ["config/calwebb_spec3.cfg", rtdata.input, "--steps.outlier_detection.save_results=true", "--steps.resample_spec.save_results=true", "--steps.extract_1d.save_results=true"] Step.from_cmdline(args) return rtdata
def run_spec2(jail, rtdata_module): """Run the Spec2Pipeline on a single exposure""" rtdata = rtdata_module collect_pipeline_cfgs("config") # Setup the inputs file_name = 'jw80600018001_02101_00003_mirifushort_rateints.fits' rtdata.get_data(INPUT_PATH + '/' + file_name) # Run the pipeline args = [ "config/calwebb_tso-spec2.cfg", rtdata.input, '--steps.assign_wcs.save_results=true', '--steps.flat_field.save_results=true', '--steps.srctype.save_results=true', '--steps.fringe.save_results=true', '--steps.photom.save_results=true', ] Step.from_cmdline(args)
def test_saving_pars(tmpdir): """Save the step parameters from the commandline""" cfg_path = t_path(join('steps', 'jwst_generic_pars-makeliststep_0002.asdf')) saved_path = tmpdir.join('savepars.asdf') step = Step.from_cmdline([cfg_path, '--save-parameters', str(saved_path)]) assert saved_path.check() with datamodels.StepParsModel(str(saved_path)) as saved: assert saved.parameters == ParsModelWithPar3.parameters step.closeout()
def run_pipelines(jail, rtdata_module): """Run stage 2-3 pipelines on NIRISS SOSS data.""" rtdata = rtdata_module collect_pipeline_cfgs("config") # Run tso-spec2 pipeline on the first _rateints file, saving intermediate products rtdata.get_data( "niriss/soss/jw00625023001_03101_00001-seg001_nis_rateints.fits") args = [ "config/calwebb_tso-spec2.cfg", rtdata.input, "--steps.flat_field.save_results=True", "--steps.srctype.save_results=True", ] Step.from_cmdline(args) # Run tso-spec2 pipeline on the second _rateints file, without saving or # checking any results (simply create a fresh input for level-3 test) rtdata.get_data( "niriss/soss/jw00625023001_03101_00001-seg002_nis_rateints.fits") args = ["config/calwebb_tso-spec2.cfg", rtdata.input] Step.from_cmdline(args) # Get the level3 assocation json file (though not its members) and run # the tso3 pipeline on all _calints files listed in association rtdata.get_data( "niriss/soss/jw00625-o023_20191210t204036_tso3_001_asn.json") args = ["config/calwebb_tso3.cfg", rtdata.input] Step.from_cmdline(args) return rtdata
def test_nirisssoss2pipeline1(_bigdata): """ Regression test of calwebb_tso_spec2 pipeline performed on NIRISS SOSS data. """ collect_pipeline_cfgs() args = [ 'calwebb_tso_spec2.cfg', op.join( _bigdata, 'pipelines/jw10003001002_03101_00001-seg003_nis_rateints.fits') ] Step.from_cmdline(args) # Compare the _calints products n_cr = 'jw10003001002_03101_00001-seg003_nis_calints.fits' n_ref = _bigdata + '/pipelines/jw10003001002_03101_00001-seg003_nis_calints_ref.fits' h = pf.open(n_cr) href = pf.open(n_ref) result = pf.diff.FITSDiff( h, href, ignore_hdus=['INT_TIMES', 'VAR_POISSON', 'VAR_RNOISE', 'ASDF'], ignore_keywords=['DATE', 'CAL_VER', 'CAL_VCS', 'CRDS_VER', 'CRDS_CTX'], rtol=0.00001) assert result.identical, result.report() # Compare the _x1dints products n_cr = 'jw10003001002_03101_00001-seg003_nis_x1dints.fits' n_ref = _bigdata + '/pipelines/jw10003001002_03101_00001-seg003_nis_x1dints_ref.fits' h = pf.open(n_cr) href = pf.open(n_ref) result = pf.diff.FITSDiff( h, href, ignore_hdus=['INT_TIMES', 'ASDF'], ignore_keywords=['DATE', 'CAL_VER', 'CAL_VCS', 'CRDS_VER', 'CRDS_CTX'], rtol=0.00001) assert result.identical, result.report()
def test_step_from_commandline_par_precedence(command_line_pars, command_line_config_pars, reference_pars, expected_pars, tmp_path, monkeypatch): args = [] class_name = "jwst.stpipe.tests.steps.WithDefaultsStep" config_name = "WithDefaultsStep" reference_type = f"pars-{config_name.lower()}" input_path = join(dirname(__file__), "data", "science.fits") if command_line_config_pars: command_line_config_path = tmp_path/"with_defaults_step.cfg" config = ConfigObj(str(command_line_config_path)) config["class"] = class_name config["name"] = config_name for key, value in command_line_config_pars.items(): config[key] = value config.write() args.append(str(command_line_config_path.absolute())) else: args.append(class_name) args.append(input_path) if command_line_pars: for key, value in command_line_pars.items(): args.append(f"--{key}={value}") reference_file_map = {} if reference_pars: reference_path = tmp_path/f"{reference_type}.asdf" parameters = { "class": class_name, "name": config_name, } parameters.update(reference_pars) model = datamodels.StepParsModel({"parameters": parameters}) model.save(reference_path) reference_file_map[reference_type] = str(reference_path) def mock_get_reference_file(dataset, reference_file_type, observatory=None, asn_exptypes=None): if reference_file_type in reference_file_map: return reference_file_map[reference_file_type] else: raise CrdsLookupError(f"Error determining best reference for '{reference_file_type}' = \ Unknown reference type '{reference_file_type}'") monkeypatch.setattr(crds_client, "get_reference_file", mock_get_reference_file) step = Step.from_cmdline(args) for key, value in expected_pars.items(): assert getattr(step, key) == value
def test_nirisssoss2pipeline1(self): """ Regression test of calwebb_tso_spec2 pipeline performed on NIRISS SOSS data. """ input_file = self.get_data(self.test_dir, 'jw10003001002_03101_00001-seg003_nis_rateints.fits') collect_pipeline_cfgs() args = [ 'calwebb_tso-spec2.cfg', input_file ] Step.from_cmdline(args) outputs = [{'files':('jw10003001002_03101_00001-seg003_nis_calints.fits', 'jw10003001002_03101_00001-seg003_nis_calints_ref.fits'), 'pars':dict(ignore_hdus=['INT_TIMES', 'VAR_POISSON', 'VAR_RNOISE', 'ASDF'])}, {'files':('jw10003001002_03101_00001-seg003_nis_x1dints.fits', 'jw10003001002_03101_00001-seg003_nis_x1dints_ref.fits'), 'pars':dict(ignore_hdus=['INT_TIMES', 'ASDF'])} ] self.compare_outputs(outputs)
def test_step_from_commandline(): args = [ abspath(join(dirname(__file__), 'steps', 'some_other_step.cfg')), '--par1=58', '--par2=hij klm' ] step = Step.from_cmdline(args) assert step.par1 == 58. assert step.par2 == 'hij klm' assert step.par3 is True step.run(1, 2)
def test_step_from_commandline_class(): args = [ 'jwst.stpipe.tests.steps.AnotherDummyStep', '--par1=58', '--par2=hij klm' ] step = Step.from_cmdline(args) assert step.par1 == 58. assert step.par2 == 'hij klm' assert step.par3 is False step.run(1, 2)
def test_image3_pipeline2(self): """Regression test definitions for CALIMAGE3 pipeline. Regression test of calwebb_image3 pipeline on NIRCam simulated long-wave data with a 6-point dither. """ asn_file = self.get_data( self.test_dir, "jw10002-o001_20171116t191235_image3_002_asn.json") for file in raw_from_asn(asn_file): self.get_data(self.test_dir, file) collect_pipeline_cfgs('config') args = [ 'config/calwebb_image3.cfg', asn_file, '--steps.tweakreg.kernel_fwhm=2', '--steps.tweakreg.snr_threshold=5', '--steps.tweakreg.enforce_user_order=True', '--steps.tweakreg.searchrad=10', '--steps.tweakreg.fitgeometry=rscale' ] Step.from_cmdline(args) outputs = [('jw10002001001_01101_00004_nrcblong_o001_crf.fits', 'jw10002001001_01101_00004_nrcblong_o001_crf_ref.fits'), { 'files': ('jw10002-o001_t002_nircam_f444w_i2d.fits', 'jw10002-o001_t002_nircam_f444w_i2d_ref.fits'), 'pars': { 'ignore_keywords': self.ignore_keywords + ['NAXIS1', 'TFORM*'], 'ignore_fields': self.ignore_keywords, 'rtol': 0.0001 } }] self.compare_outputs(outputs)
def test_save_proper_pipeline_container_substeps_withdir(mk_tmp_dirs): """Test how pipeline saving should work""" tmp_current_path, tmp_data_path, tmp_config_path = mk_tmp_dirs args = [ 'jwst.stpipe.tests.steps.ProperPipeline', data_fn_path, '--output_dir=' + tmp_data_path, '--steps.stepwithmodel.save_results=true', '--steps.another_stepwithmodel.save_results=true', '--steps.another_stepwithmodel.output_dir=' + tmp_config_path, '--steps.stepwithcontainer.save_results=true', ] Step.from_cmdline(args) assert path.isfile(path.join(tmp_data_path, 'flat_0_pp.fits')) assert path.isfile(path.join(tmp_data_path, 'flat_1_pp.fits')) assert path.isfile(path.join(tmp_data_path, 'flat_swm.fits')) assert path.isfile(path.join(tmp_config_path, 'flat_aswm.fits')) assert path.isfile(path.join(tmp_data_path, 'flat_0_swc.fits')) assert path.isfile(path.join(tmp_data_path, 'flat_1_swc.fits'))
def run_pipelines(jail, rtdata_module): """Run stage 2 and 3 pipelines on NIRCam TSO image data.""" rtdata = rtdata_module # Run the calwebb_tso-image2 pipeline on each of the 2 inputs rate_files = [ "nircam/tsimg/jw00312006001_02102_00001-seg001_nrcb1_rateints.fits", "nircam/tsimg/jw00312006001_02102_00001-seg002_nrcb1_rateints.fits" ] for rate_file in rate_files: rtdata.get_data(rate_file) args = ["calwebb_image2", rtdata.input] Step.from_cmdline(args) # Get the level3 association json file (though not its members) and run # the tso3 pipeline on all _calints files listed in association rtdata.get_data("nircam/tsimg/jw00312-o006_20191225t115310_tso3_001_asn.json") args = ["calwebb_tso3", rtdata.input] Step.from_cmdline(args) return rtdata
def test_nirisssoss2pipeline1(self): """ Regression test of calwebb_tso_spec2 pipeline performed on NIRISS SOSS data. """ input_file = self.get_data(self.test_dir, 'jw10003001002_03101_00001-seg003_nis_rateints.fits') collect_pipeline_cfgs() args = [ 'calwebb_tso-spec2.cfg', input_file ] Step.from_cmdline(args) outputs = [{'files':('jw10003001002_03101_00001-seg003_nis_calints.fits', 'jw10003001002_03101_00001-seg003_nis_calints_ref.fits'), 'pars':dict(ignore_hdus=['INT_TIMES', 'VAR_POISSON', 'VAR_RNOISE', 'ASDF'])}, {'files':('jw10003001002_03101_00001-seg003_nis_x1dints.fits', 'jw10003001002_03101_00001-seg003_nis_x1dints_ref.fits'), 'pars':dict(ignore_hdus=['INT_TIMES', 'ASDF'])} ] self.compare_outputs(outputs)