[DM-32470] Dark verification in OCPS calibration script from DM-31897 fails because NOISe is too low with respect nominal readnoise - Jira

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Type: Story
Status: Done
Resolution: Done
Fix Version/s: None
Component/s: None
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Story Points:
2
Epic Link:
f21b-drp-isr
Team:
Data Release Production
Urgent?:
No

Description

When testing DARK verification for the OCPS calibration script in ~~DM-31897~~, the noise level for some amplifiers is below the nominal amp readnoise, but by more than 5%. This violates one of the noise tests from DMTN-101 NOISE that requires the noise scatter to be "within 5% of the nominal readnoise".

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05/Nov/21 1:16 AM

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is child task of

DM-31897 Have OCPS scripts use cp_verify output

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Andrés Alejandro Plazas Malagón added a comment - 05/Nov/21 1:21 AM

When testing the OCPS script from ~~DM-31897~~ using ComCam with 10 biases, 10 darks, and 14 flats, the verification tests pass for the biases (when taking only 2 biases they fail). However, for the 10 darks the NOISE tests fail:

Failures:

{2021110300039: {\'NOISE\': 14}, 2021110300040: {\'NOISE\': 14}, 2021110300041: {\'NOISE\': 14}, 2021110300042: {\'NOISE\': 14}, 2021110300043: {\'NOISE\': 14}, 2021110300044: {\'NOISE\': 14}, 2021110300045: {\'NOISE\': 14}, 2021110300046: {\'NOISE\': 14}, 2021110300047: {\'NOISE\': 14}, 2021110300048: {\'NOISE\': 14}}

Looking at one of the darks with the image viewer, there's nothing obvious (for dark 2021110300039):

In more detail:

cameraName = 'LSSTComCam'

verifyCollection = 'u/ocps/097f84fec1fd4c8d960f4bea48a92ec0'

genCollection = 'u/ocps/15599d65321b4ed195891161c7ded48c'

butler = dB.Butler("/repo/LSSTComCam", collections=[verifyCollection, genCollection])

camera = butler.get('camera', instrument=cameraName, exposure=2021110300079)

detStats = butler.get("verifyDarkStats", instrument=cameraName, detector=0, exposure=2021110300079, visit=2021110300079)

{2021110300079: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 2021110300081: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 2021110300082: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 2021110300083: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 2021110300084: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 2021110300085: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 2021110300086: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 2021110300087: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 2021110300088: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 2021110300089: {'FAILURES': ['R22_S00 C00 NOISE',

   'R22_S00 C01 NOISE',

   'R22_S00 C02 NOISE',

   'R22_S00 C03 NOISE',

   'R22_S00 C04 NOISE',

   'R22_S00 C05 NOISE',

   'R22_S00 C06 NOISE',

   'R22_S00 C10 NOISE',

   'R22_S00 C11 NOISE',

   'R22_S00 C12 NOISE',

   'R22_S00 C13 NOISE',

   'R22_S00 C14 NOISE',

   'R22_S00 C15 NOISE',

   'R22_S00 C16 NOISE']},

 'SUCCESS': False}

Command ran by OCPS:

OUTPUT_COLLECTION=u/ocps/097f84fec1fd4c8d960f4bea48a92ec0

+ pipetask --long-log run -p '${CP_VERIFY_DIR}/pipelines/VerifyDark.yaml' -b /repo/LSSTComCam -o u/ocps/097f84fec1fd4c8d960f4bea48a92ec0 -i LSSTComCam/raw/all -j 8 -i u/ocps/15599d65321b4ed195891161c7ded48c -i LSSTComCam/calib/u/plazas/2021SEP16.1,LSSTComCam/calib --register-dataset-types --output-run u/ocps/097f84fec1fd4c8d960f4bea48a92ec0/run -d 'instrument='\''LSSTComCam'\'' AND detector IN (0) AND exposure IN (2021110300079, 2021110300081, 2021110300082, 2021110300083, 2021110300084, 2021110300085, 2021110300086, 2021110300087, 2021110300088, 2021110300089)'

Chris found that he issue is that the NOISE test is from DMTN-101 requires the scatter has to be "within 5% of the nominal readnoise". We are getting results smaller than the nominal readnoise, but more than 5% different. The CR_NOISE test checks that the CR_NOISE is within 5% of the NOISE, which is true:

detector = camera[0]

for amp in sorted(detector.getAmplifiers(), key=lambda x: x.getName()):

    print(f"{amp.getName()}, {amp.getReadNoise()}")

C00, 8.8

C01, 9.7

C02, 10.5

C03, 10.7

C04, 10.6

C05, 9.1

C06, 8.3

C07, 6.9

C10, 8.7

C11, 10.0

C12, 10.9

C13, 11.2

C14, 11.2

C15, 10.5

C16, 8.7

C17, 7.3

for exp, stats in runStats.items():

    detStats = butler.get("verifyDarkDetStats", instrument=cameraName, detector=0, exposure=exp)

    for amp, ampStats in detStats['AMP'].items():

        print(exp, amp, ampStats['CR_NOISE'], ampStats['NOISE'])

2021110300079 C00 8.102450482599478 8.101896735357455

2021110300079 C01 8.530749119295585 8.529709014883057

2021110300079 C02 9.107895021146737 9.106895382557074

2021110300079 C03 9.435514799586075 9.435156479516717

2021110300079 C04 9.154113623420288 9.153156087056209

2021110300079 C05 8.007940242293927 8.007655546251812

2021110300079 C06 7.276195192649853 7.275816552904176

2021110300079 C07 6.5846439858885555 6.584110780335858

2021110300079 C10 8.029076026299784 7.903138186537734

2021110300079 C11 8.96611085659837 8.965392983660626

2021110300079 C12 9.766453254294458 9.766207659542854

2021110300079 C13 9.94714864613451 9.946623849351258

2021110300079 C14 9.739929831797868 9.73979429066459

2021110300079 C15 8.912106946857465 8.910773140862494

2021110300079 C16 7.828648575549569 7.828099089606608

2021110300079 C17 6.95921262850001 6.958774582534627

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Andrés Alejandro Plazas Malagón added a comment - 05/Nov/21 1:21 AM When testing the OCPS script from DM-31897 using ComCam with 10 biases, 10 darks, and 14 flats, the verification tests pass for the biases (when taking only 2 biases they fail). However, for the 10 darks the NOISE tests fail: Failures: {2021110300039: {\'NOISE\': 14}, 2021110300040: {\'NOISE\': 14}, 2021110300041: {\'NOISE\': 14}, 2021110300042: {\'NOISE\': 14}, 2021110300043: {\'NOISE\': 14}, 2021110300044: {\'NOISE\': 14}, 2021110300045: {\'NOISE\': 14}, 2021110300046: {\'NOISE\': 14}, 2021110300047: {\'NOISE\': 14}, 2021110300048: {\'NOISE\': 14}} Looking at one of the darks with the image viewer, there's nothing obvious (for dark 2021110300039 ): In more detail: cameraName = 'LSSTComCam' verifyCollection = 'u/ocps/097f84fec1fd4c8d960f4bea48a92ec0' genCollection = 'u/ocps/15599d65321b4ed195891161c7ded48c' butler = dB.Butler( "/repo/LSSTComCam" , collections = [verifyCollection, genCollection]) camera = butler.get( 'camera' , instrument = cameraName, exposure = 2021110300079 ) detStats = butler.get( "verifyDarkStats" , instrument = cameraName, detector = 0 , exposure = 2021110300079 , visit = 2021110300079 ) {2021110300079: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 2021110300081: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 2021110300082: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 2021110300083: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 2021110300084: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 2021110300085: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 2021110300086: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 2021110300087: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 2021110300088: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 2021110300089: {'FAILURES': ['R22_S00 C00 NOISE', 'R22_S00 C01 NOISE', 'R22_S00 C02 NOISE', 'R22_S00 C03 NOISE', 'R22_S00 C04 NOISE', 'R22_S00 C05 NOISE', 'R22_S00 C06 NOISE', 'R22_S00 C10 NOISE', 'R22_S00 C11 NOISE', 'R22_S00 C12 NOISE', 'R22_S00 C13 NOISE', 'R22_S00 C14 NOISE', 'R22_S00 C15 NOISE', 'R22_S00 C16 NOISE']}, 'SUCCESS': False} Command ran by OCPS: OUTPUT_COLLECTION=u/ocps/097f84fec1fd4c8d960f4bea48a92ec0 + pipetask --long-log run -p '${CP_VERIFY_DIR}/pipelines/VerifyDark.yaml' -b /repo/LSSTComCam -o u/ocps/097f84fec1fd4c8d960f4bea48a92ec0 -i LSSTComCam/raw/all -j 8 -i u/ocps/15599d65321b4ed195891161c7ded48c -i LSSTComCam/calib/u/plazas/2021SEP16.1,LSSTComCam/calib --register-dataset-types --output-run u/ocps/097f84fec1fd4c8d960f4bea48a92ec0/run -d 'instrument='\''LSSTComCam'\'' AND detector IN (0) AND exposure IN (2021110300079, 2021110300081, 2021110300082, 2021110300083, 2021110300084, 2021110300085, 2021110300086, 2021110300087, 2021110300088, 2021110300089)' Chris found that he issue is that the NOISE test is from DMTN-101 requires the scatter has to be "within 5% of the nominal readnoise". We are getting results smaller than the nominal readnoise, but more than 5% different. The CR_NOISE test checks that the CR_NOISE is within 5% of the NOISE, which is true: detector = camera[ 0 ] for amp in sorted (detector.getAmplifiers(), key = lambda x: x.getName()): print (f "{amp.getName()}, {amp.getReadNoise()}" ) C00, 8.8 C01, 9.7 C02, 10.5 C03, 10.7 C04, 10.6 C05, 9.1 C06, 8.3 C07, 6.9 C10, 8.7 C11, 10.0 C12, 10.9 C13, 11.2 C14, 11.2 C15, 10.5 C16, 8.7 C17, 7.3 for exp, stats in runStats.items(): detStats = butler.get("verifyDarkDetStats", instrument=cameraName, detector=0, exposure=exp) for amp, ampStats in detStats['AMP'].items(): print(exp, amp, ampStats['CR_NOISE'], ampStats['NOISE']) 2021110300079 C00 8.102450482599478 8.101896735357455 2021110300079 C01 8.530749119295585 8.529709014883057 2021110300079 C02 9.107895021146737 9.106895382557074 2021110300079 C03 9.435514799586075 9.435156479516717 2021110300079 C04 9.154113623420288 9.153156087056209 2021110300079 C05 8.007940242293927 8.007655546251812 2021110300079 C06 7.276195192649853 7.275816552904176 2021110300079 C07 6.5846439858885555 6.584110780335858 2021110300079 C10 8.029076026299784 7.903138186537734 2021110300079 C11 8.96611085659837 8.965392983660626 2021110300079 C12 9.766453254294458 9.766207659542854 2021110300079 C13 9.94714864613451 9.946623849351258 2021110300079 C14 9.739929831797868 9.73979429066459 2021110300079 C15 8.912106946857465 8.910773140862494 2021110300079 C16 7.828648575549569 7.828099089606608 2021110300079 C17 6.95921262850001 6.958774582534627

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Christopher Waters added a comment - 09/Nov/21 11:41 PM

I've added a metadataStatistics method to CpVerifyStatsTask that allows the ISR metadata to be read to extract the read noise as measured in the overscan region (a value that we've been measuring and ignoring for a long time). If this is enabled, we use that read noise values from there instead of the quoted camera values. I think this solves two issues: 1) the test is now closer to the text of DMTN-101; 2) we should no longer trigger because the dark tests believe the measured noise to be too low for the read noise.

There is an additional test populated that notes if the measured and quoted read noise values disagree, which we do not currently fail on, but may want to do so in the future.

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Christopher Waters added a comment - 09/Nov/21 11:41 PM I've added a metadataStatistics method to CpVerifyStatsTask that allows the ISR metadata to be read to extract the read noise as measured in the overscan region (a value that we've been measuring and ignoring for a long time). If this is enabled, we use that read noise values from there instead of the quoted camera values. I think this solves two issues: 1) the test is now closer to the text of DMTN-101; 2) we should no longer trigger because the dark tests believe the measured noise to be too low for the read noise. There is an additional test populated that notes if the measured and quoted read noise values disagree, which we do not currently fail on, but may want to do so in the future.

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Andrés Alejandro Plazas Malagón added a comment - 15/Nov/21 10:14 PM

Look good, thank you for working on this fix!. I just requested some clarifications.

In addition, shouldn't the quoted noise values in the amps be updated if they differ considerably from the empirical ones measured in the overscan?

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Andrés Alejandro Plazas Malagón added a comment - 15/Nov/21 10:14 PM Look good, thank you for working on this fix!. I just requested some clarifications. In addition, shouldn't the quoted noise values in the amps be updated if they differ considerably from the empirical ones measured in the overscan?

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Andrés Alejandro Plazas Malagón added a comment - 20/Nov/21 4:18 AM - edited

Re-running the script with the following parameters and the code from this ticket seems to have worked:

configuration = yaml.safe_dump({"n_bias": 10,

                                "n_dark": 10,

                                "exp_times_dark": 5, #, 5, 5, 5, 10, 10, 10, 10, 10],

                                "n_flat": 14,

                                "exp_times_flat": [10, 10, 20, 20, 30, 30, 40, 40, 50, 50, 60, 60, 70, 70],

                                "detectors": "(0)",

                                "calib_collection": "LSSTComCam/calib/u/plazas/daily.2021NOV19.test3",

                                "do_verify": True,

                                "number_verification_tests_threshold_dark": 8,

                                "input_collections_verify_bias": "LSSTComCam/calib/u/plazas/2021SEP16.1,LSSTComCam/calib",

                                "input_collections_verify_dark": "LSSTComCam/calib/u/plazas/2021SEP16.1,LSSTComCam/calib",

                                "input_collections_verify_flat": "LSSTComCam/calib/u/plazas/2021SEP16.1,LSSTComCam/calib",

                                "certify_calib_begin_date": "1980-01-01",

                                "certify_calib_end_date": "2051-12-31",

                                "script_mode": "BIAS_DARK_FLAT",

                                "do_defects": True,

                                "do_ptc": True})

print(configuration)

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Andrés Alejandro Plazas Malagón added a comment - 20/Nov/21 4:18 AM - edited Re-running the script with the following parameters and the code from this ticket seems to have worked: configuration = yaml.safe_dump({ "n_bias" : 10 , "n_dark" : 10 , "exp_times_dark" : 5 , #, 5, 5, 5, 10, 10, 10, 10, 10], "n_flat" : 14 , "exp_times_flat" : [ 10 , 10 , 20 , 20 , 30 , 30 , 40 , 40 , 50 , 50 , 60 , 60 , 70 , 70 ], "detectors" : "(0)" , "calib_collection" : "LSSTComCam/calib/u/plazas/daily.2021NOV19.test3" , "do_verify" : True , "number_verification_tests_threshold_dark" : 8 , "input_collections_verify_bias" : "LSSTComCam/calib/u/plazas/2021SEP16.1,LSSTComCam/calib" , "input_collections_verify_dark" : "LSSTComCam/calib/u/plazas/2021SEP16.1,LSSTComCam/calib" , "input_collections_verify_flat" : "LSSTComCam/calib/u/plazas/2021SEP16.1,LSSTComCam/calib" , "certify_calib_begin_date" : "1980-01-01" , "certify_calib_end_date" : "2051-12-31" , "script_mode" : "BIAS_DARK_FLAT" , "do_defects" : True , "do_ptc" : True }) print (configuration)

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Andrés Alejandro Plazas Malagón added a comment - 20/Nov/21 4:19 AM - edited

Notice

"number_verification_tests_threshold_dark": 8

as opposed to the current default

"number_verification_tests_threshold_dark": 16

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Andrés Alejandro Plazas Malagón added a comment - 20/Nov/21 4:19 AM - edited Notice "number_verification_tests_threshold_dark": 8 as opposed to the current default "number_verification_tests_threshold_dark": 16

Data Management

Dark verification in OCPS calibration script from DM-31897 fails because NOISe is too low with respect nominal readnoise

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