Closed bdorney closed 5 years ago
Address Issue #229 using the method provided by @lpetre-ulb.
See #229.
I've tested this in the discussion on issue #229. And also again for one detector on the QC8 stand:
% getCalInfoFromDB.py 1 4 4 ... ... <class 'pandas.core.frame.DataFrame'> Int64Index: 24 entries, 0 to 23 Data columns (total 10 columns): vfatN 24 non-null int64 vfat3_ser_num 24 non-null object vfat3_barcode 24 non-null object iref 24 non-null int64 adc0m 24 non-null float64 adc1m 24 non-null float64 adc0b 24 non-null float64 adc1b 24 non-null float64 cal_dacm 24 non-null float64 cal_dacb 24 non-null float64 dtypes: float64(6), int64(2), object(2) memory usage: 2.1+ KB vfatN vfat3_ser_num vfat3_barcode iref adc0m adc1m adc0b \ 0 0 0x191b 6427 31 1.92493 2.23859 -329.140 1 1 0x1939 6457 31 1.98065 2.24550 -342.038 2 2 0x1943 6467 28 1.92460 2.25281 -319.088 3 3 0x1956 6486 30 1.86553 2.25038 -308.145 4 4 0x1957 6487 29 1.84510 2.24744 -308.706 5 5 0x195a 6490 28 1.93590 2.23457 -322.136 6 6 0x1955 6485 38 1.86152 2.23339 -306.951 7 7 0x18b8 6328 33 1.90315 2.24688 -315.650 8 8 0x190e 6414 31 1.89792 2.26111 -317.626 9 9 0x1978 6520 34 1.88107 2.25189 -315.447 10 10 0x1940 6464 31 1.89072 2.28090 -317.349 11 11 0x194f 6479 36 1.87751 2.27679 -318.173 12 12 0x1958 6488 35 1.92573 2.25850 -318.912 13 13 0x193e 6462 35 1.85784 2.26923 -313.567 14 14 0x192f 6447 34 1.90715 2.25418 -310.419 15 15 0x190a 6410 33 1.92279 2.25316 -333.126 16 16 0x1927 6439 31 1.93912 2.23881 -327.836 17 17 0x1917 6423 35 1.92429 2.27084 -310.123 18 18 0x193f 6463 36 1.90557 2.28043 -306.193 19 19 0x194e 6478 33 1.90205 2.23640 -309.560 20 20 0x1974 6516 30 1.98247 2.25069 -331.131 21 21 0x1944 6468 34 1.89388 2.23282 -315.519 22 22 0x1938 6456 33 1.88957 2.27799 -306.611 23 23 0x1920 6432 35 1.92471 2.26636 -318.315 adc1b cal_dacm cal_dacb 0 -487.162 -0.228743 56.4847 1 -472.364 -0.266546 66.2623 2 -489.879 -0.225235 55.7650 3 -489.510 -0.248689 61.2316 4 -513.931 -0.267046 66.4012 5 -484.000 -0.295372 72.9856 6 -500.378 -0.239769 58.9339 7 -503.828 -0.267739 66.1570 8 -507.285 -0.261367 64.4386 9 -498.244 -0.275515 67.9316 10 -504.804 -0.226073 55.7716 11 -517.217 -0.266157 65.7316 12 -482.786 -0.263122 64.7191 13 -525.109 -0.212659 52.1564 14 -487.167 -0.292268 72.6354 15 -491.969 -0.238228 59.1312 16 -488.974 -0.249747 61.2809 17 -494.646 -0.251427 62.2525 18 -499.209 -0.272566 67.6210 19 -485.884 -0.259950 64.0654 20 -474.131 -0.259606 64.3899 21 -497.568 -0.235806 57.7776 22 -512.526 -0.246898 60.7521 23 -493.704 -0.250019 61.6655 goodbye
Description
Address Issue #229 using the method provided by @lpetre-ulb.
Types of changes
Motivation and Context
See #229.
How Has This Been Tested?
I've tested this in the discussion on issue #229. And also again for one detector on the QC8 stand:
Screenshots (if appropriate):
Checklist: