flux_gpp.md
In fluxible: Ecosystem Gas Fluxes Calculations for Closed Loop Chamber Setup

GPP calculation

Code
  flux_gpp(co2_fluxes, type, f_start, f_flux, id_cols = "turfID", cols_keep = c(
    "temp_soil"))
Condition
  Warning in `flux_gpp()`:

   NEE missing for measurement turfID: 156 AN2C 156
Output
  # A tibble: 9 x 5
    f_start             type  f_flux temp_soil turfID      
    <dttm>              <chr>  <dbl>     <dbl> <fct>       
  1 2022-07-28 23:43:35 ER      95.6      10.8 156 AN2C 156
  2 2022-07-28 23:47:22 GPP     33.8      10.7 74 WN2C 155 
  3 2022-07-28 23:47:22 NEE     52.4      10.7 74 WN2C 155 
  4 2022-07-28 23:52:10 ER      18.6      10.7 74 WN2C 155 
  5 2022-07-28 23:59:32 GPP    -20.5      10.8 109 AN3C 109
  6 2022-07-28 23:59:32 NEE     69.4      10.8 109 AN3C 109
  7 2022-07-29 00:03:10 ER      89.9      10.6 109 AN3C 109
  8 2022-07-29 00:06:35 GPP     NA        12.2 29 WN3C 106 
  9 2022-07-29 00:06:35 NEE     26.2      12.2 29 WN3C 106

keeping more than one columns

Code
  flux_gpp(co2_fluxes, type, f_start, f_flux, id_cols = "turfID", cols_keep = c(
    "temp_soil", "temp_fahr"))
Condition
  Warning in `flux_gpp()`:

   NEE missing for measurement turfID: 156 AN2C 156
Output
  # A tibble: 9 x 6
    f_start             type  f_flux temp_soil temp_fahr turfID      
    <dttm>              <chr>  <dbl>     <dbl>     <dbl> <fct>       
  1 2022-07-28 23:43:35 ER      95.6      10.8      45.2 156 AN2C 156
  2 2022-07-28 23:47:22 GPP     33.8      10.7      45.3 74 WN2C 155 
  3 2022-07-28 23:47:22 NEE     52.4      10.7      45.3 74 WN2C 155 
  4 2022-07-28 23:52:10 ER      18.6      10.7      45.4 74 WN2C 155 
  5 2022-07-28 23:59:32 GPP    -20.5      10.8      46.0 109 AN3C 109
  6 2022-07-28 23:59:32 NEE     69.4      10.8      46.0 109 AN3C 109
  7 2022-07-29 00:03:10 ER      89.9      10.6      45.9 109 AN3C 109
  8 2022-07-29 00:06:35 GPP     NA        12.2      45.9 29 WN3C 106 
  9 2022-07-29 00:06:35 NEE     26.2      12.2      45.9 29 WN3C 106

GPP calculation works with several id cols

Code
  flux_gpp(fluxes, type, datetime, flux, id_cols = c("turfid", "campaign"))
Output
  # A tibble: 9 x 5
    datetime            type   flux turfid campaign
    <chr>               <chr> <dbl> <chr>     <dbl>
  1 2024-02-11 10:00:00 GPP      -2 A             1
  2 2024-02-11 10:00:00 NEE       3 A             1
  3 2024-02-11 10:00:10 ER        5 A             1
  4 2024-02-11 10:00:20 GPP      -5 A             2
  5 2024-02-11 10:00:20 NEE       2 A             2
  6 2024-02-11 10:00:30 ER        7 A             2
  7 2024-02-11 10:00:40 GPP      -2 B             3
  8 2024-02-11 10:00:40 NEE       9 B             3
  9 2024-02-11 10:00:50 ER       11 B             3

missing NEE and several id cols

Code
  flux_gpp(fluxes, type, datetime, flux, id_cols = c("turfid", "campaign"))
Condition
  Warning in `flux_gpp()`:

   NEE missing for measurement turfid: C, campaign: 3
   NEE missing for measurement turfid: D, campaign: 4
   NEE missing for measurement turfid: A, campaign: 4
Output
  # A tibble: 12 x 5
     datetime            type   flux turfid campaign
     <chr>               <chr> <dbl> <chr>     <dbl>
   1 2024-02-11 10:00:00 GPP      -2 A             1
   2 2024-02-11 10:00:00 NEE       3 A             1
   3 2024-02-11 10:00:10 ER        5 A             1
   4 2024-02-11 10:00:20 GPP      -5 A             2
   5 2024-02-11 10:00:20 NEE       2 A             2
   6 2024-02-11 10:00:30 ER        7 A             2
   7 2024-02-11 10:00:40 GPP      -2 B             3
   8 2024-02-11 10:00:40 NEE       9 B             3
   9 2024-02-11 10:00:50 ER       11 B             3
  10 2024-02-11 10:01:00 ER       10 C             3
  11 2024-02-11 10:01:10 ER       13 D             4
  12 2024-02-11 10:01:20 ER        8 A             4

option to keep all the cols

Code
  select(flux_gpp(test_df, type, f_start, id_cols = "turfID", cols_keep = "all"),
  !c(f_start, PAR, type, f_flux))
Condition
  Warning in `flux_gpp()`:

   NEE missing for measurement turfID: 156 AN2C 156
Output
  # A tibble: 9 x 8
    f_fluxid f_slope_tz f_temp_air_ave temp_soil temp_fahr temp_kelvin treatment
    <fct>         <dbl>          <dbl>     <dbl>     <dbl>       <dbl> <chr>    
  1 1             1.56            7.31      10.8      45.2        280. A        
  2 2             0.853           7.38      10.7      45.3        281. A        
  3 2             0.853           7.38      10.7      45.3        281. A        
  4 3             0.303           7.46      10.7      45.4        281. A        
  5 4             1.13            7.77      10.8      46.0        281. B        
  6 4             1.13            7.77      10.8      46.0        281. B        
  7 5             1.46            7.71      10.6      45.9        281. C        
  8 6             0.426           7.75      12.2      45.9        281. C        
  9 6             0.426           7.75      12.2      45.9        281. C        
  # i 1 more variable: turfID <fct>

cols keep takes values from NEE

Code
  select(flux_gpp(test_df, type, f_start, id_cols = "turfID", cols_keep = "all"),
  turfID, type, test_keep)
Condition
  Warning in `flux_gpp()`:

   NEE missing for measurement turfID: 156 AN2C 156
Output
  # A tibble: 9 x 3
    turfID       type  test_keep
    <fct>        <chr> <chr>    
  1 156 AN2C 156 ER    ER_val   
  2 74 WN2C 155  GPP   <NA>     
  3 74 WN2C 155  NEE   <NA>     
  4 74 WN2C 155  ER    ER_val   
  5 109 AN3C 109 GPP   NEE_val  
  6 109 AN3C 109 NEE   NEE_val  
  7 109 AN3C 109 ER    ER_val   
  8 29 WN3C 106  GPP   NEE_val  
  9 29 WN3C 106  NEE   NEE_val

GPP calculation works with several id cols, and extra fluxes

Code
  flux_gpp(fluxes, type, datetime, flux, id_cols = c("turfid", "campaign"))
Output
  # A tibble: 8 x 5
    datetime            type   flux turfid campaign
    <chr>               <chr> <dbl> <chr>     <dbl>
  1 2024-02-11 10:00:00 GPP      -2 A             1
  2 2024-02-11 10:00:00 NEE       3 A             1
  3 2024-02-11 10:00:10 ER        5 A             1
  4 2024-02-11 10:00:20 GPP      -5 A             2
  5 2024-02-11 10:00:20 NEE       2 A             2
  6 2024-02-11 10:00:30 ER        7 A             2
  7 2024-02-12 08:00:10 soilR     3 B             3
  8 2024-02-12 09:00:15 soilR     6 A             4