Loop of calculation of gain and phase in multisim

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  On a similar note to the posts at https://forums.ni.com/t5/High-Speed-Digitizers/How-are-offset-and-gain-in-the-niScope-fetch-function... and http://forums.ni.com/t5/High-Speed-Digitizers/Where-to-find-gain-and-offset-of-USB-5132-running-in-C... , I try to extract the file to output data from the gain and offset of our USB-5132 digitizer.  The file contains the event argument e.Result 'Fetch' and is sent to file in c# as follows:

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• Where is the gain and offset of USB-5132, running in c#?

  Hello

  I just read the post https://forums.ni.com/t5/High-Speed-Digitizers/How-are-offset-and-gain-in-the-niScope-fetch-function... on the gain and offset of the digitizer, to be used to rebuild data.  Like the other poster, I would also like to find the gain and offset of our USB-5132, but spin in c#.  Someone would be able to tell me the location of the gain and offset of our device, in the drivers c#?  (If I try to estimate myself parameters digitizer my reconstruction is OK but not perfect).  Thank you very much.

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  All together.

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  Class name % ofClass average test Score
  1 Niobe 7 8 8.4
  1 alena 4 7 7.5
  1 9 7 8.9 Estia
  1 Lilly 10 8 9.8
  1 Sandra 6 8 8.3
  1 Melanie 8 8 8.1
  Nadia 2 8 3 4.4
  Sayuki 2 9 8 8.4
  Diasy 2 7 8 8.0
  Flower 2 7 8 6.5
  Diana 2 6 8 7.3
  3 Flora 7 8 5.8
  Sukiya 3 4 8 8.4
  Samantha 3 10 8 7.7
  Roxanne 3 7 8 6.9
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  -By class, I need to calculate the % of class score (sum averages / people in the class)
  
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  SQL> ed
  Wrote file afiedt.buf
  
    1  with t as (select 1 as Class, 'Niobe' as Nm, 7 as Score, 8 as Tests, 8.4 as Average from dual union all
    2             select 1, 'Alena', 4, 7, 7.5 from dual union all
    3             select 1, 'Estia', 9, 7, 8.9 from dual union all
    4             select 1, 'Lilly', 10, 8, 9.8 from dual union all
    5             select 1, 'Sandra', 6, 8, 8.3 from dual union all
    6             select 1, 'Melanie', 8, 8, 8.1 from dual union all
    7             select 2, 'Nadia', 3, 8, 4.4 from dual union all
    8             select 2, 'Sayuki', 9, 8, 8.4 from dual union all
    9             select 2, 'Diasy', 7, 8, 8.0 from dual union all
   10             select 2, 'Blossom', 7, 8, 6.5 from dual union all
   11             select 2, 'Diana', 6, 8, 7.3 from dual union all
   12             select 3, 'Flora', 7, 8, 5.8 from dual union all
   13             select 3, 'Sukiya', 4, 8, 8.4 from dual union all
   14             select 3, 'Samantha', 10, 8, 7.7 from dual union all
   15             select 3, 'Roxanne', 7, 8, 6.9 from dual union all
   16             select 3, 'Eline', 8, 8, 7.4 from dual)
   17  --
   18  -- END OF TEST DATA
   19  --
   20  select class, nm as "NAME", score, tests, average
   21        ,round(((average*tests)+score)/(tests+1),1) as avg_person
   22        ,round((average / sum(average) over (partition by class))*100,1) as class_average
   23  from t
   24* order by class, nm
  SQL> /
  
       CLASS NAME          SCORE      TESTS    AVERAGE AVG_PERSON CLASS_AVERAGE
  ---------- -------- ---------- ---------- ---------- ---------- -------------
           1 Alena             4          7        7.5        7.1          14.7
           1 Estia             9          7        8.9        8.9          17.5
           1 Lilly            10          8        9.8        9.8          19.2
           1 Melanie           8          8        8.1        8.1          15.9
           1 Niobe             7          8        8.4        8.2          16.5
           1 Sandra            6          8        8.3          8          16.3
           2 Blossom           7          8        6.5        6.6          18.8
           2 Diana             6          8        7.3        7.2          21.1
           2 Diasy             7          8          8        7.9          23.1
           2 Nadia             3          8        4.4        4.2          12.7
           2 Sayuki            9          8        8.4        8.5          24.3
           3 Eline             8          8        7.4        7.5          20.4
           3 Flora             7          8        5.8        5.9            16
           3 Roxanne           7          8        6.9        6.9          19.1
           3 Samantha         10          8        7.7          8          21.3
           3 Sukiya            4          8        8.4        7.9          23.2
  
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