read_noise_data = data['READ_NOISE'] system_noise_data = data['SYSTEM_NOISE'] total_noise_data = data['TOTAL_NOISE'] for amp, read_noise, system_noise, total_noise in zip(amps, read_noise_data, system_noise_data, total_noise_data): results.append(lcatr.schema.valid(lcatr.schema.get('read_noise'), amp=amp, read_noise=read_noise, system_noise=system_noise, total_noise=total_noise)) results.extend(siteUtils.jobInfo()) results.append(eotestUtils.eotestCalibrations()) fe55_acq_job_id = siteUtils.get_prerequisite_job_id('*_fe55_fe55_*.fits', jobname=siteUtils.getProcessName('fe55_acq')) md = dict(system_noise_file=dict(JOB_ID=fe55_acq_job_id)) results.extend(eotestUtils.eotestCalibsPersist('system_noise_file', metadata=md)) files = glob.glob('*read_noise?*.fits') for fitsfile in files: eotestUtils.addHeaderData(fitsfile, LSST_NUM=sensor_id, TESTTYPE='FE55', DATE=eotestUtils.utc_now_isoformat(), CCD_MANU=siteUtils.getCcdVendor().upper()) data_products = [lcatr.schema.fileref.make(item) for item in files] results.extend(data_products) lcatr.schema.write_file(results) lcatr.schema.validate_file()
results = siteUtils.jobInfo() results.append(eotestUtils.eotestCalibrations()) sensor_id = siteUtils.getUnitId() qe_data = pyfits.open('%s_QE.fits' % sensor_id)['QE_BANDS'].data QE = OrderedDict((band, []) for band in qe_data.field('BAND')) for amp in range(1, 17): values = qe_data.field('AMP%02i' % amp) for band, value in zip(QE, values): QE[band].append(value) for band in QE: results.append(lcatr.schema.valid(lcatr.schema.get('qe_analysis'), band=band, QE=np.mean(QE[band]))) qe_acq_job_id = siteUtils.get_prerequisite_job_id('*_lambda_flat_*.fits', jobname=siteUtils.getProcessName('qe_acq')) md = dict(photodiode_ratio_file=dict(JOB_ID=qe_acq_job_id), illumination_non_uniformity_file=dict(JOB_ID=qe_acq_job_id)) results.extend(eotestUtils.eotestCalibsPersist('photodiode_ratio_file', 'illumination_non_uniformity_file', metadata=md)) qe_files = glob.glob('*QE*.*') for item in qe_files: if item.endswith('.fits'): eotestUtils.addHeaderData(item, LSST_NUM=sensor_id, TESTTYPE='LAMBDA', DATE=eotestUtils.utc_now_isoformat(), CCD_MANU=siteUtils.getCcdVendor().upper()) results.extend([lcatr.schema.fileref.make(item) for item in qe_files]) lcatr.schema.write_file(results) lcatr.schema.validate_file()
TESTTYPE='LAMBDA', DATE=eotestUtils.utc_now_isoformat(), CCD_MANU=ccd_vendor) results.extend( [siteUtils.make_fileref(item, folder=slot) for item in qe_files]) # Persist the png files. metadata = dict(CCD_MANU=ccd_vendor, LSST_NUM=sensor_id, TESTTYPE='LAMBDA', TEST_CATEGORY='EO') results.extend( siteUtils.persist_png_files('%s*.png' % sensor_id, sensor_id, folder=slot, metadata=metadata)) sensor_id = raft.sensor_names[0] qe_acq_job_id = siteUtils.get_prerequisite_job_id( ('S*/%s_lambda_flat_*.fits' % sensor_id), jobname=siteUtils.getProcessName('qe_raft_acq')) md = dict(photodiode_ratio_file=dict(JOB_ID=qe_acq_job_id), illumination_non_uniformity_file=dict(JOB_ID=qe_acq_job_id)) results.extend( eotestUtils.eotestCalibsPersist('photodiode_ratio_file', 'illumination_non_uniformity_file', metadata=md)) results.extend(siteUtils.jobInfo()) lcatr.schema.write_file(results) lcatr.schema.validate_file()
total_noise_data = data['TOTAL_NOISE'] for amp, read_noise, system_noise, total_noise in zip(amps, read_noise_data, system_noise_data, total_noise_data): results.append( lcatr.schema.valid(lcatr.schema.get('read_noise'), amp=amp, read_noise=read_noise, system_noise=system_noise, total_noise=total_noise)) results.extend(siteUtils.jobInfo()) results.append(eotestUtils.eotestCalibrations()) fe55_acq_job_id = siteUtils.get_prerequisite_job_id( '*_fe55_fe55_*.fits', jobname=siteUtils.getProcessName('fe55_acq')) md = dict(system_noise_file=dict(JOB_ID=fe55_acq_job_id)) results.extend( eotestUtils.eotestCalibsPersist('system_noise_file', metadata=md)) files = glob.glob('*read_noise?*.fits') for fitsfile in files: eotestUtils.addHeaderData(fitsfile, LSST_NUM=sensor_id, TESTTYPE='FE55', DATE=eotestUtils.utc_now_isoformat(), CCD_MANU=siteUtils.getCcdVendor().upper()) data_products = [lcatr.schema.fileref.make(item) for item in files] results.extend(data_products)
total_noise_data = data['TOTAL_NOISE'] for amp, read_noise, system_noise, total_noise in zip( amps, read_noise_data, system_noise_data, total_noise_data): print "sensor = %s amp = %d read_noise = %f" % (sensor_id, amp, read_noise) # results.append(lcatr.schema.valid(lcatr.schema.get('read_noise'), # amp=amp, read_noise=read_noise, # system_noise=system_noise, # total_noise=total_noise)) results.extend(siteUtils.jobInfo()) results.append(eotestUtils.eotestCalibrations()) fe55_acq_job_id = siteUtils.get_prerequisite_job_id( '*/%s_fe55_fe55_*.fits' % sensor_id, jobname=siteUtils.getProcessName('fe55_acq')) md = dict(system_noise_file=dict(JOB_ID=fe55_acq_job_id)) results.extend( eotestUtils.eotestCalibsPersist('system_noise_file', metadata=md)) files = glob.glob('*read_noise?*.fits') for fitsfile in files: eotestUtils.addHeaderData(fitsfile, LSST_NUM=sensor_id, TESTTYPE='FE55', DATE=eotestUtils.utc_now_isoformat(), CCD_MANU=siteUtils.getCcdVendor().upper()) data_products = [lcatr.schema.fileref.make(item) for item in files] results.extend(data_products)
sensor_id = siteUtils.getUnitId() qe_data = pyfits.open('%s_QE.fits' % sensor_id)['QE_BANDS'].data QE = OrderedDict((band, []) for band in qe_data.field('BAND')) for amp in range(1, 17): values = qe_data.field('AMP%02i' % amp) for band, value in zip(QE, values): QE[band].append(value) for band in QE: results.append( lcatr.schema.valid(lcatr.schema.get('qe_analysis'), band=band, QE=np.mean(QE[band]))) qe_acq_job_id = siteUtils.get_prerequisite_job_id( '*_lambda_flat_*.fits', jobname=siteUtils.getProcessName('qe_acq')) md = dict(photodiode_ratio_file=dict(JOB_ID=qe_acq_job_id), illumination_non_uniformity_file=dict(JOB_ID=qe_acq_job_id)) results.extend( eotestUtils.eotestCalibsPersist('photodiode_ratio_file', 'illumination_non_uniformity_file', metadata=md)) qe_files = glob.glob('*QE*.*') for item in qe_files: if item.endswith('.fits'): eotestUtils.addHeaderData(item, LSST_NUM=sensor_id, TESTTYPE='LAMBDA', DATE=eotestUtils.utc_now_isoformat(), CCD_MANU=siteUtils.getCcdVendor().upper()) results.extend([lcatr.schema.fileref.make(item) for item in qe_files])
read_noise_data = data['READ_NOISE'] system_noise_data = data['SYSTEM_NOISE'] total_noise_data = data['TOTAL_NOISE'] for amp, read_noise, system_noise, total_noise in zip(amps, read_noise_data, system_noise_data, total_noise_data): results.append(lcatr.schema.valid(lcatr.schema.get('read_noise_raft'), amp=amp, read_noise=read_noise, system_noise=system_noise, total_noise=total_noise, slot=slot, sensor_id=wgSlotName)) # sensor_id=sensor_id)) # fe55_acq_job_id = siteUtils.get_prerequisite_job_id('S*/%s_fe55_fe55_*.fits' % sensor_id, fe55_acq_job_id = siteUtils.get_prerequisite_job_id('S*/%s_fe55_fe55_*.fits' % wgSlotName, jobname=siteUtils.getProcessName('fe55_raft_acq')) # files = glob.glob('%s_read_noise?*.fits' % sensor_id) files = glob.glob('%s_read_noise?*.fits' % wgSlotName) for fitsfile in files: eotestUtils.addHeaderData(fitsfile, LSST_NUM=sensor_id, TESTTYPE='FE55', DATE=eotestUtils.utc_now_isoformat(), CCD_MANU=ccd_vendor) data_products = [siteUtils.make_fileref(item, folder=slot) for item in files] results.extend(data_products) # Persist the png files. metadata = dict(CCD_MANU=ccd_vendor, LSST_NUM=sensor_id, TESTTYPE='FE55', TEST_CATEGORY='EO')