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

GPP calculation

Code
  flux_diff(co2_fluxes, type, f_flux, id_cols = "turfID", cols_keep = c(
    "temp_soil", "f_start"), type_a = "NEE", type_b = "ER", diff_name = "GPP")
Condition
  Warning in `flux_diff()`:

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

without f_datetime

Code
  flux_diff(co2_fluxes, type, f_flux, id_cols = "turfID", cols_keep = c(
    "temp_soil"), type_a = "NEE", type_b = "ER", diff_name = "GPP")
Condition
  Warning in `flux_diff()`:

   type_a or type_b missing for measurement turfID: 156 AN2C 156
   type_a or type_b missing for measurement turfID: 29 WN3C 106
Output
  # A tibble: 8 x 4
    type  f_flux temp_soil turfID      
    <chr>  <dbl>     <dbl> <fct>       
  1 ER      95.6      10.8 156 AN2C 156
  2 ER      18.6      10.7 74 WN2C 155 
  3 GPP     33.8      10.7 74 WN2C 155 
  4 NEE     52.4      10.7 74 WN2C 155 
  5 ER      89.9      10.6 109 AN3C 109
  6 GPP    -20.5      10.8 109 AN3C 109
  7 NEE     69.4      10.8 109 AN3C 109
  8 NEE     26.2      12.2 29 WN3C 106

keeping more than one columns

Code
  flux_diff(co2_fluxes, type, f_flux, id_cols = "turfID", cols_keep = c(
    "temp_soil", "temp_fahr", "f_start"), type_a = "NEE", type_b = "ER",
  diff_name = "GPP")
Condition
  Warning in `flux_diff()`:

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

GPP calculation works with several id cols

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

missing NEE and several id cols

Code
  flux_diff(fluxes, type, flux, id_cols = c("turfid", "campaign"), type_a = "NEE",
  type_b = "ER", diff_name = "GPP", cols_keep = c("datetime"))
Condition
  Warning in `flux_diff()`:

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

option to keep all the cols

Code
  select(flux_diff(test_df, type, id_cols = "turfID", cols_keep = "all", type_a = "NEE",
    type_b = "ER", diff_name = "GPP"), !c(f_start, PAR, type, f_flux))
Condition
  Warning in `flux_diff()`:

   type_a or type_b missing for measurement turfID: 156 AN2C 156
   type_a or type_b missing for measurement turfID: 29 WN3C 106
Output
  # A tibble: 8 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 3             0.303           7.46      10.7      45.4        281. A        
  3 2             0.853           7.38      10.7      45.3        281. A        
  4 2             0.853           7.38      10.7      45.3        281. A        
  5 5             1.46            7.71      10.6      45.9        281. C        
  6 4             1.13            7.77      10.8      46.0        281. B        
  7 4             1.13            7.77      10.8      46.0        281. B        
  8 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_diff(test_df, type, id_cols = "turfID", cols_keep = "all", type_a = "NEE",
    type_b = "ER", diff_name = "GPP"), turfID, type, test_keep)
Condition
  Warning in `flux_diff()`:

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

GPP calculation works with several id cols, and extra fluxes

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

type named differently

Code
  suppressWarnings(flux_diff(test, flux_type, f_flux, id_cols = "turfID",
    cols_keep = c("temp_soil", "f_start"), type_a = "NEE", type_b = "ER",
    diff_name = "GPP"))
Output
  # A tibble: 8 x 5
    flux_type f_flux temp_soil f_start             turfID      
    <chr>      <dbl>     <dbl> <dttm>              <fct>       
  1 ER          95.6      10.8 2022-07-28 23:43:35 156 AN2C 156
  2 ER          18.6      10.7 2022-07-28 23:52:10 74 WN2C 155 
  3 GPP         33.8      10.7 2022-07-28 23:47:22 74 WN2C 155 
  4 NEE         52.4      10.7 2022-07-28 23:47:22 74 WN2C 155 
  5 ER          89.9      10.6 2022-07-29 00:03:10 109 AN3C 109
  6 GPP        -20.5      10.8 2022-07-28 23:59:32 109 AN3C 109
  7 NEE         69.4      10.8 2022-07-28 23:59:32 109 AN3C 109
  8 NEE         26.2      12.2 2022-07-29 00:06:35 29 WN3C 106