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compare_bool_resultDate

Attendees

Yong Wook Kim

Bethany Blakely  

Katie Bowman 

Rob Kooper 

Minu Mathew 

Agenda

  1. Automation of GHG file from the server
    • reading multiple datalogger files from the server and unifying them into one raw met file that includes the entire timeline of interest
  2. PyFluxPro demo
  3. PyFluxPro data formatting - should the timestamps start with yyyy-mm-dd 00:00 and end with yyyy-mm-dd 23:00? It depends on the time period selected for eddypro run.
  4. PyFluxPro installation queries.

  5. Differences in 2010 raw met data:

    1. Field name : CPU:EBI_Maize_EC.CR3 -- is there a pattern?
    2. Units : W/meter≤  -- can we make a list of provided units? Or {column name:unit} mapping?
    3. NAN and INF in file
    4. Column names : SoilTempCA50_Avg -- is this in soil key?
  6. Findings in comparing the outputs of EddyPro :
    1. Exactly the same
  7. Finding in comparing the inputs to EddyPro:
    1. Automated has 83 columns and manual has 38 columns.
    2. There are 37 common columns. SHF_1_1_2 is not present in the automated one,  but present in manual.
      1. Common cols : 
        ['SWC_2_2_1', 'Ts_1_5_1', 'Ts_1_3_1', 'Ts_2_1_1','SWC_1_2_1','PPFDr','RH','Ts_2_2_1','SWC_1_5_1','SWC_1_4_1','SWC_1_3_1','SWC_1_1_1',
        'Ts_1_4_1','Ta_1_1_2','Ts_1_1_1','SWC_2_1_1','LWout','Rr','SWC_2_5_1','Tc','Ts_1_2_1','WD','TIMESTAMP','SWin','SWC_2_3_1','SWC_2_4_1',
        'LWin','PPFD','SWout','Ts_2_5_1','Ta_1_1_1','Ts_2_3_1','SHF_1_1_1','Ts_2_4_1','P_rain','Rn','MWS']
      2. Required cols are present (SWin, RH, LWin, PPFD). Locators (_1_1) are present.
      3. SHF_1_1_2 is the only col that is not present in automated. Need to figure out why.
    3. TIMESTAMP format in automated is with hyphen. TIMESTAMP format in manual is with /
    4. Columns that are not-common to both dataframes :
      1. {'Ah_fromRH','CDMBattV_Min','CDMPTempC_Avg(1)','CDMPTempC_Avg(2)','CDMPTempC_Avg(3)','CDMPTempC_Avg(4)','LWDn_Avg','LWUp_Avg',
 'MoistureA_Avg','MoistureC_Avg','PTemp_Avg','RECORD','Rl_net_Avg','Rs_net_Avg','SBTempC_Avg','SBTempK_Avg','SHF_1_1_2','SHF_2_1_1',
 'SW_out_Avg','SoilT_C_Avg','SoilTempA_Avg','SoilTempC_Avg','TC_100cm_Avg','TC_10cm_Avg','TC_20cm_Avg','TC_30cm_Avg','TC_40cm_Avg','TC_50cm_Avg','TC_5cm_Avg',
 'TC_60cm_Avg','TC_75cm_Avg','TargTempC_Avg','TargmV_Avg','U_Avg','VWC_100cm_Avg','VWC_10cm_Avg','VWC_20cm_Avg','VWC_30cm_Avg','VWC_40cm_Avg','VWC_50cm_Avg',
 'VWC_5cm_Avg','VWC_60cm_Avg','VWC_75cm_Avg','V_Avg','batt_volt_Min','cnr4_T_C_Avg','cnr4_T_K_Avg'}


        e. Comparing values of both inputs (common cols only) cell by cell.
        i. False indicates difference in values. True indicates same value. The attached file (compare_bool_result) gives the count of False and True for each cell.
        iii. P_rain has False for 1467 times and True for 22 times
        iv. Rr does not have any False values.
        v. All SWC has 1488 False values and only 1 True value.
        vi. Same for Ts, False values are in 1480s and Trues are under 10.
        vii. Need to investigate more ?

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