tests/testthat/_snaps/flux_fitting.md

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

works for exponential fitting

Code
  distinct(select(flux_fitting(co2_conc, conc, datetime, fit_type = "exp_zhao18"),
  f_fluxid, f_slope))
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 205 points out of 210 seconds
   fluxID 6 : slope was estimated on 206 points out of 210 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          1.56 
  2 2          0.853
  3 3          0.303
  4 4          1.13 
  5 5          1.46 
  6 6          0.426

works for linear fitting

Code
  distinct(select(flux_fitting(co2_conc, conc, datetime, fit_type = "lin"),
  f_fluxid, f_slope))
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 205 points out of 210 seconds
   fluxID 6 : slope was estimated on 206 points out of 210 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1         0.113 
  2 2         0.110 
  3 3         0.115 
  4 4         0.0431
  5 5        -0.105 
  6 6         0.117

works for quadratic fitting

Code
  distinct(select(flux_fitting(co2_conc, conc, datetime, fit_type = "qua"),
  f_fluxid, f_slope))
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 205 points out of 210 seconds
   fluxID 6 : slope was estimated on 206 points out of 210 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          1.60 
  2 2          0.978
  3 3          0.251
  4 4          1.24 
  5 5          0.876
  6 6          0.474

works for exponential fitting with cut

Code
  distinct(select(flux_fitting(co2_conc, conc, datetime, fit_type = "exp_zhao18",
    start_cut = 20), f_fluxid, f_slope))
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 185 points out of 190 seconds
   fluxID 6 : slope was estimated on 186 points out of 190 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          1.46 
  2 2          1.01 
  3 3          0.241
  4 4          1.32 
  5 5          1.08 
  6 6          0.337

works for linear fitting with cut

Code
  distinct(select(flux_fitting(co2_conc, conc, datetime, fit_type = "line",
    start_cut = 20), f_fluxid, f_slope))
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 185 points out of 190 seconds
   fluxID 6 : slope was estimated on 186 points out of 190 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1         0.0214
  2 2         0.0596
  3 3         0.0978
  4 4        -0.0327
  5 5        -0.195 
  6 6         0.0877

removing duplicated datetime

Code
  flux_fitting(rep_data, conc, datetime, fit_type = "exponential")
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 205 points out of 210 seconds
   fluxID 6 : slope was estimated on 206 points out of 210 seconds
Output
  # A tibble: 1,251 x 29
     datetime            temp_air temp_soil  conc   PAR turfID       type 
     <dttm>                 <dbl>     <dbl> <dbl> <dbl> <fct>        <fct>
   1 2022-07-28 23:43:35    NA         NA    447. NA    156 AN2C 156 ER   
   2 2022-07-28 23:43:36     7.22      10.9  447.  1.68 156 AN2C 156 ER   
   3 2022-07-28 23:43:37    NA         NA    448. NA    156 AN2C 156 ER   
   4 2022-07-28 23:43:38    NA         NA    449. NA    156 AN2C 156 ER   
   5 2022-07-28 23:43:39    NA         NA    449. NA    156 AN2C 156 ER   
   6 2022-07-28 23:43:40    NA         NA    450. NA    156 AN2C 156 ER   
   7 2022-07-28 23:43:41    NA         NA    451. NA    156 AN2C 156 ER   
   8 2022-07-28 23:43:42    NA         NA    451. NA    156 AN2C 156 ER   
   9 2022-07-28 23:43:43    NA         NA    453. NA    156 AN2C 156 ER   
  10 2022-07-28 23:43:44    NA         NA    453. NA    156 AN2C 156 ER   
  # i 1,241 more rows
  # i 22 more variables: f_start <dttm>, f_end <dttm>, f_fluxid <fct>,
  #   f_ratio <dbl>, f_flag_match <chr>, f_time <dbl>, f_cut <fct>,
  #   f_rsquared_lm <dbl>, f_adj_rsquared_lm <dbl>, f_slope_lm <dbl>,
  #   f_intercept_lm <dbl>, f_pvalue_lm <dbl>, f_fit_lm <dbl>, f_Cz <dbl>,
  #   f_Cm <dbl>, f_a <dbl>, f_b <dbl>, f_tz <dbl>, f_slope <dbl>, f_fit <dbl>,
  #   f_fit_slope <dbl>, f_start_z <dttm>

works for exp_tz fitting

Code
  distinct(select(flux_fitting(co2_conc, conc, datetime, fit_type = "exp_tz"),
  f_fluxid, f_slope))
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 205 points out of 210 seconds
   fluxID 6 : slope was estimated on 206 points out of 210 seconds
Output
  # A tibble: 6 x 2
    f_fluxid  f_slope
    <fct>       <dbl>
  1 1        2253.   
  2 2         966.   
  3 3           0.376
  4 4        1613.   
  5 5           1.18 
  6 6           0.493

works for exp_zhao18 with missing data

Code
  distinct(select(flux_fitting(co2_conc_missing, conc, datetime, fit_type = "exp_zhao18",
    end_cut = 60, t_zero = 20), f_fluxid, f_slope))
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 1 : slope was estimated on 28 points out of 150 seconds
   fluxID 2 : slope was estimated on 61 points out of 150 seconds
   fluxID 3 : slope was estimated on 42 points out of 150 seconds
   fluxID 6 dropped (no data in the conc column)
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          0.376
  2 2          0.462
  3 3         -6.33 
  4 4          0.686
  5 5          0.751
  6 6         NA

works for exp_zhao18 with mid missing data

Code
  distinct(select(flux_fitting(co2_conc_mid_missing, conc, datetime, fit_type = "exp_zhao18",
    end_cut = 60, t_zero = 20), f_fluxid, f_slope))
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 1 : slope was estimated on 139 points out of 150 seconds
   fluxID 2 : slope was estimated on 114 points out of 150 seconds
   fluxID 4 : slope was estimated on 103 points out of 150 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          0.841
  2 2          0.579
  3 3          0.472
  4 4          0.620
  5 5          0.751
  6 6          0.475

works for exp_tz with mid missing data

Code
  distinct(select(flux_fitting(co2_conc_mid_missing, conc, datetime, fit_type = "exp_tz",
    end_cut = 60, t_zero = 20), f_fluxid, f_slope))
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 1 : slope was estimated on 139 points out of 150 seconds
   fluxID 2 : slope was estimated on 114 points out of 150 seconds
   fluxID 4 : slope was estimated on 103 points out of 150 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          0.555
  2 2          0.387
  3 3          0.280
  4 4          0.498
  5 5          0.579
  6 6          0.198

works for quadratic with mid missing data

Code
  distinct(select(flux_fitting(co2_conc_mid_missing, conc, datetime, fit_type = "quadratic",
    end_cut = 60, t_zero = 20), f_fluxid, f_slope))
Condition
  Warning in `flux_fitting()`:

   fluxID 1 : slope was estimated on 139 points out of 150 seconds
   fluxID 2 : slope was estimated on 114 points out of 150 seconds
   fluxID 4 : slope was estimated on 103 points out of 150 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          0.645
  2 2          0.394
  3 3          0.258
  4 4          0.525
  5 5          0.672
  6 6          0.314

exp_tz: optim produces non-finite values

Code
  distinct(select(flux_fitting(test_data, conc, datetime, fit_type = "exp_tz",
    end_cut = 60, t_zero = 20), f_fluxid, f_slope))
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 1 : slope was estimated on 28 points out of 150 seconds
   fluxID 2 : slope was estimated on 61 points out of 150 seconds
   fluxID 3 : slope was estimated on 42 points out of 150 seconds
   fluxID 4 : slope is NA, most likely an issue with the model optimization.
          Check your data or use a different model.
   fluxID 6 dropped (no data in the conc column)
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1         0.367 
  2 2         0.317 
  3 3         0.0834
  4 4        NA     
  5 5         0.579 
  6 6        NA

exp_zhao18: optim produces non-finite values

Code
  distinct(select(flux_fitting(test_data, conc, datetime, fit_type = "exp_zhao18",
    end_cut = 60, t_zero = 20), f_fluxid, f_slope))
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 1 : slope was estimated on 28 points out of 150 seconds
   fluxID 2 : slope was estimated on 61 points out of 150 seconds
   fluxID 3 : slope was estimated on 42 points out of 150 seconds
   fluxID 4 : slope is NA, most likely an issue with the model optimization.
          Check your data or use a different model.
   fluxID 6 dropped (no data in the conc column)
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          0.376
  2 2          0.462
  3 3         -6.33 
  4 4         NA    
  5 5          0.751
  6 6         NA

works for exp_hm fitting

Code
  distinct(select(flux_fitting(co2_conc, conc, datetime, fit_type = "exp_hm"),
  f_fluxid, f_slope))
Message
  Cutting measurements...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope is NA, most likely an issue with the model optimization.
          Check your data or use a different model.
   fluxID 6 : slope was estimated on 206 points out of 210 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          1.93 
  2 2          1.12 
  3 3          0.356
  4 4          1.57 
  5 5         NA    
  6 6          0.641

fitting works with 0 second end cut

Code
  test_fit
Output
  # A tibble: 1,251 x 20
     datetime            temp_air temp_soil  conc   PAR turfID       type 
     <dttm>                 <dbl>     <dbl> <dbl> <dbl> <fct>        <fct>
   1 2022-07-28 23:43:35    NA         NA    447. NA    156 AN2C 156 ER   
   2 2022-07-28 23:43:36     7.22      10.9  447.  1.68 156 AN2C 156 ER   
   3 2022-07-28 23:43:37    NA         NA    448. NA    156 AN2C 156 ER   
   4 2022-07-28 23:43:38    NA         NA    449. NA    156 AN2C 156 ER   
   5 2022-07-28 23:43:39    NA         NA    449. NA    156 AN2C 156 ER   
   6 2022-07-28 23:43:40    NA         NA    450. NA    156 AN2C 156 ER   
   7 2022-07-28 23:43:41    NA         NA    451. NA    156 AN2C 156 ER   
   8 2022-07-28 23:43:42    NA         NA    451. NA    156 AN2C 156 ER   
   9 2022-07-28 23:43:43    NA         NA    453. NA    156 AN2C 156 ER   
  10 2022-07-28 23:43:44    NA         NA    453. NA    156 AN2C 156 ER   
  # i 1,241 more rows
  # i 13 more variables: f_start <dttm>, f_end <dttm>, f_fluxid <fct>,
  #   f_ratio <dbl>, f_flag_match <chr>, f_time <dbl>, f_cut <fct>,
  #   f_rsquared <dbl>, f_adj_rsquared <dbl>, f_slope <dbl>, f_intercept <dbl>,
  #   f_pvalue <dbl>, f_fit <dbl>

Code
  distinct(select(flux_fitting(co2_conc, conc, datetime, fit_type = "exponential"),
  f_fluxid, f_slope))
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 205 points out of 210 seconds
   fluxID 6 : slope was estimated on 206 points out of 210 seconds
Output
  # A tibble: 6 x 2
    f_fluxid f_slope
    <fct>      <dbl>
  1 1          1.56 
  2 2          0.853
  3 3          0.303
  4 4          1.13 
  5 5          1.46 
  6 6          0.426

fitting works with 30 second end cut

Code
  flux_fitting(co2_conc, conc, datetime, end_cut = 30, fit_type = "lin")
Output
  # A tibble: 1,251 x 20
     datetime            temp_air temp_soil  conc   PAR turfID       type 
     <dttm>                 <dbl>     <dbl> <dbl> <dbl> <fct>        <fct>
   1 2022-07-28 23:43:35    NA         NA    447. NA    156 AN2C 156 ER   
   2 2022-07-28 23:43:36     7.22      10.9  447.  1.68 156 AN2C 156 ER   
   3 2022-07-28 23:43:37    NA         NA    448. NA    156 AN2C 156 ER   
   4 2022-07-28 23:43:38    NA         NA    449. NA    156 AN2C 156 ER   
   5 2022-07-28 23:43:39    NA         NA    449. NA    156 AN2C 156 ER   
   6 2022-07-28 23:43:40    NA         NA    450. NA    156 AN2C 156 ER   
   7 2022-07-28 23:43:41    NA         NA    451. NA    156 AN2C 156 ER   
   8 2022-07-28 23:43:42    NA         NA    451. NA    156 AN2C 156 ER   
   9 2022-07-28 23:43:43    NA         NA    453. NA    156 AN2C 156 ER   
  10 2022-07-28 23:43:44    NA         NA    453. NA    156 AN2C 156 ER   
  # i 1,241 more rows
  # i 13 more variables: f_start <dttm>, f_end <dttm>, f_fluxid <fct>,
  #   f_ratio <dbl>, f_flag_match <chr>, f_time <dbl>, f_cut <fct>,
  #   f_rsquared <dbl>, f_adj_rsquared <dbl>, f_slope <dbl>, f_intercept <dbl>,
  #   f_pvalue <dbl>, f_fit <dbl>

Code
  flux_fitting(co2_conc, conc, datetime, end_cut = 30, fit_type = "exponential")
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Output
  # A tibble: 1,251 x 29
     datetime            temp_air temp_soil  conc   PAR turfID       type 
     <dttm>                 <dbl>     <dbl> <dbl> <dbl> <fct>        <fct>
   1 2022-07-28 23:43:35    NA         NA    447. NA    156 AN2C 156 ER   
   2 2022-07-28 23:43:36     7.22      10.9  447.  1.68 156 AN2C 156 ER   
   3 2022-07-28 23:43:37    NA         NA    448. NA    156 AN2C 156 ER   
   4 2022-07-28 23:43:38    NA         NA    449. NA    156 AN2C 156 ER   
   5 2022-07-28 23:43:39    NA         NA    449. NA    156 AN2C 156 ER   
   6 2022-07-28 23:43:40    NA         NA    450. NA    156 AN2C 156 ER   
   7 2022-07-28 23:43:41    NA         NA    451. NA    156 AN2C 156 ER   
   8 2022-07-28 23:43:42    NA         NA    451. NA    156 AN2C 156 ER   
   9 2022-07-28 23:43:43    NA         NA    453. NA    156 AN2C 156 ER   
  10 2022-07-28 23:43:44    NA         NA    453. NA    156 AN2C 156 ER   
  # i 1,241 more rows
  # i 22 more variables: f_start <dttm>, f_end <dttm>, f_fluxid <fct>,
  #   f_ratio <dbl>, f_flag_match <chr>, f_time <dbl>, f_cut <fct>,
  #   f_rsquared_lm <dbl>, f_adj_rsquared_lm <dbl>, f_slope_lm <dbl>,
  #   f_intercept_lm <dbl>, f_pvalue_lm <dbl>, f_fit_lm <dbl>, f_Cz <dbl>,
  #   f_Cm <dbl>, f_a <dbl>, f_b <dbl>, f_tz <dbl>, f_slope <dbl>, f_fit <dbl>,
  #   f_fit_slope <dbl>, f_start_z <dttm>

fitting works with 60 second end cut

Code
  flux_fitting(co2_conc, end_cut = 60, conc, datetime, fit_type = "lin")
Output
  # A tibble: 1,251 x 20
     datetime            temp_air temp_soil  conc   PAR turfID       type 
     <dttm>                 <dbl>     <dbl> <dbl> <dbl> <fct>        <fct>
   1 2022-07-28 23:43:35    NA         NA    447. NA    156 AN2C 156 ER   
   2 2022-07-28 23:43:36     7.22      10.9  447.  1.68 156 AN2C 156 ER   
   3 2022-07-28 23:43:37    NA         NA    448. NA    156 AN2C 156 ER   
   4 2022-07-28 23:43:38    NA         NA    449. NA    156 AN2C 156 ER   
   5 2022-07-28 23:43:39    NA         NA    449. NA    156 AN2C 156 ER   
   6 2022-07-28 23:43:40    NA         NA    450. NA    156 AN2C 156 ER   
   7 2022-07-28 23:43:41    NA         NA    451. NA    156 AN2C 156 ER   
   8 2022-07-28 23:43:42    NA         NA    451. NA    156 AN2C 156 ER   
   9 2022-07-28 23:43:43    NA         NA    453. NA    156 AN2C 156 ER   
  10 2022-07-28 23:43:44    NA         NA    453. NA    156 AN2C 156 ER   
  # i 1,241 more rows
  # i 13 more variables: f_start <dttm>, f_end <dttm>, f_fluxid <fct>,
  #   f_ratio <dbl>, f_flag_match <chr>, f_time <dbl>, f_cut <fct>,
  #   f_rsquared <dbl>, f_adj_rsquared <dbl>, f_slope <dbl>, f_intercept <dbl>,
  #   f_pvalue <dbl>, f_fit <dbl>

Code
  flux_fitting(co2_conc, conc, datetime, end_cut = 60, fit_type = "exponential")
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Output
  # A tibble: 1,251 x 29
     datetime            temp_air temp_soil  conc   PAR turfID       type 
     <dttm>                 <dbl>     <dbl> <dbl> <dbl> <fct>        <fct>
   1 2022-07-28 23:43:35    NA         NA    447. NA    156 AN2C 156 ER   
   2 2022-07-28 23:43:36     7.22      10.9  447.  1.68 156 AN2C 156 ER   
   3 2022-07-28 23:43:37    NA         NA    448. NA    156 AN2C 156 ER   
   4 2022-07-28 23:43:38    NA         NA    449. NA    156 AN2C 156 ER   
   5 2022-07-28 23:43:39    NA         NA    449. NA    156 AN2C 156 ER   
   6 2022-07-28 23:43:40    NA         NA    450. NA    156 AN2C 156 ER   
   7 2022-07-28 23:43:41    NA         NA    451. NA    156 AN2C 156 ER   
   8 2022-07-28 23:43:42    NA         NA    451. NA    156 AN2C 156 ER   
   9 2022-07-28 23:43:43    NA         NA    453. NA    156 AN2C 156 ER   
  10 2022-07-28 23:43:44    NA         NA    453. NA    156 AN2C 156 ER   
  # i 1,241 more rows
  # i 22 more variables: f_start <dttm>, f_end <dttm>, f_fluxid <fct>,
  #   f_ratio <dbl>, f_flag_match <chr>, f_time <dbl>, f_cut <fct>,
  #   f_rsquared_lm <dbl>, f_adj_rsquared_lm <dbl>, f_slope_lm <dbl>,
  #   f_intercept_lm <dbl>, f_pvalue_lm <dbl>, f_fit_lm <dbl>, f_Cz <dbl>,
  #   f_Cm <dbl>, f_a <dbl>, f_b <dbl>, f_tz <dbl>, f_slope <dbl>, f_fit <dbl>,
  #   f_fit_slope <dbl>, f_start_z <dttm>

renaming works

Code
  flux_fitting(co2_conc_names, co2, date_time, f_start, finish, fit_type = "lin")
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 205 points out of 210 seconds
   fluxID 6 : slope was estimated on 206 points out of 210 seconds
Output
  # A tibble: 1,251 x 20
     date_time           temp_air temp_soil   co2   PAR turfID       type 
     <dttm>                 <dbl>     <dbl> <dbl> <dbl> <fct>        <fct>
   1 2022-07-28 23:43:35    NA         NA    447. NA    156 AN2C 156 ER   
   2 2022-07-28 23:43:36     7.22      10.9  447.  1.68 156 AN2C 156 ER   
   3 2022-07-28 23:43:37    NA         NA    448. NA    156 AN2C 156 ER   
   4 2022-07-28 23:43:38    NA         NA    449. NA    156 AN2C 156 ER   
   5 2022-07-28 23:43:39    NA         NA    449. NA    156 AN2C 156 ER   
   6 2022-07-28 23:43:40    NA         NA    450. NA    156 AN2C 156 ER   
   7 2022-07-28 23:43:41    NA         NA    451. NA    156 AN2C 156 ER   
   8 2022-07-28 23:43:42    NA         NA    451. NA    156 AN2C 156 ER   
   9 2022-07-28 23:43:43    NA         NA    453. NA    156 AN2C 156 ER   
  10 2022-07-28 23:43:44    NA         NA    453. NA    156 AN2C 156 ER   
  # i 1,241 more rows
  # i 13 more variables: f_start <dttm>, finish <dttm>, f_fluxid <fct>,
  #   f_ratio <dbl>, f_flag_match <chr>, f_time <dbl>, f_cut <fct>,
  #   f_rsquared <dbl>, f_adj_rsquared <dbl>, f_slope <dbl>, f_intercept <dbl>,
  #   f_pvalue <dbl>, f_fit <dbl>

Code
  flux_fitting(co2_conc_names, co2, date_time, f_start, finish, fit_type = "exponential")
Message
  Cutting measurements...
  Estimating starting parameters for optimization...
  Optimizing fitting parameters...
  Calculating fits and slopes...
  Done.
Condition
  Warning in `flux_fitting()`:

   fluxID 5 : slope was estimated on 205 points out of 210 seconds
   fluxID 6 : slope was estimated on 206 points out of 210 seconds
Output
  # A tibble: 1,251 x 29
     date_time           temp_air temp_soil   co2   PAR turfID       type 
     <dttm>                 <dbl>     <dbl> <dbl> <dbl> <fct>        <fct>
   1 2022-07-28 23:43:35    NA         NA    447. NA    156 AN2C 156 ER   
   2 2022-07-28 23:43:36     7.22      10.9  447.  1.68 156 AN2C 156 ER   
   3 2022-07-28 23:43:37    NA         NA    448. NA    156 AN2C 156 ER   
   4 2022-07-28 23:43:38    NA         NA    449. NA    156 AN2C 156 ER   
   5 2022-07-28 23:43:39    NA         NA    449. NA    156 AN2C 156 ER   
   6 2022-07-28 23:43:40    NA         NA    450. NA    156 AN2C 156 ER   
   7 2022-07-28 23:43:41    NA         NA    451. NA    156 AN2C 156 ER   
   8 2022-07-28 23:43:42    NA         NA    451. NA    156 AN2C 156 ER   
   9 2022-07-28 23:43:43    NA         NA    453. NA    156 AN2C 156 ER   
  10 2022-07-28 23:43:44    NA         NA    453. NA    156 AN2C 156 ER   
  # i 1,241 more rows
  # i 22 more variables: f_start <dttm>, finish <dttm>, f_fluxid <fct>,
  #   f_ratio <dbl>, f_flag_match <chr>, f_time <dbl>, f_cut <fct>,
  #   f_rsquared_lm <dbl>, f_adj_rsquared_lm <dbl>, f_slope_lm <dbl>,
  #   f_intercept_lm <dbl>, f_pvalue_lm <dbl>, f_fit_lm <dbl>, f_Cz <dbl>,
  #   f_Cm <dbl>, f_a <dbl>, f_b <dbl>, f_tz <dbl>, f_slope <dbl>, f_fit <dbl>,
  #   f_fit_slope <dbl>, f_start_z <dttm>

quadratic fit works

Code
  flux_fitting(co2_conc, conc, datetime, f_start, f_end, f_fluxid, fit_type = "quadratic",
    t_zero = 10, end_cut = 30)
Output
  # A tibble: 1,251 x 30
     datetime            temp_air temp_soil  conc   PAR turfID       type 
     <dttm>                 <dbl>     <dbl> <dbl> <dbl> <fct>        <fct>
   1 2022-07-28 23:43:35    NA         NA    447. NA    156 AN2C 156 ER   
   2 2022-07-28 23:43:36     7.22      10.9  447.  1.68 156 AN2C 156 ER   
   3 2022-07-28 23:43:37    NA         NA    448. NA    156 AN2C 156 ER   
   4 2022-07-28 23:43:38    NA         NA    449. NA    156 AN2C 156 ER   
   5 2022-07-28 23:43:39    NA         NA    449. NA    156 AN2C 156 ER   
   6 2022-07-28 23:43:40    NA         NA    450. NA    156 AN2C 156 ER   
   7 2022-07-28 23:43:41    NA         NA    451. NA    156 AN2C 156 ER   
   8 2022-07-28 23:43:42    NA         NA    451. NA    156 AN2C 156 ER   
   9 2022-07-28 23:43:43    NA         NA    453. NA    156 AN2C 156 ER   
  10 2022-07-28 23:43:44    NA         NA    453. NA    156 AN2C 156 ER   
  # i 1,241 more rows
  # i 23 more variables: f_start <dttm>, f_end <dttm>, f_fluxid <fct>,
  #   f_ratio <dbl>, f_flag_match <chr>, f_time <dbl>, f_cut <fct>,
  #   f_rsquared_lm <dbl>, f_adj_rsquared_lm <dbl>, f_slope_lm <dbl>,
  #   f_intercept_lm <dbl>, f_pvalue_lm <dbl>, f_fit_lm <dbl>, f_param1 <dbl>,
  #   f_param2 <dbl>, f_rsquared <dbl>, f_adj_rsquared <dbl>, f_intercept <dbl>,
  #   f_pvalue <dbl>, f_slope <dbl>, f_fit <dbl>, f_fit_slope <dbl>, ...

fluxible documentation built on June 25, 2025, 1:08 a.m.