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

works for exponential fitting

Code
  dplyr::distinct(dplyr::select(flux_quality(slopes0, conc), f_fluxid,
  f_quality_flag, f_RMSE, f_cor_coef, f_ratio, f_gfactor))
Message

   Total number of measurements: 6

   ok    3   50 %
   discard   2   33 %
   zero      1   17 %
   force_discard     0   0 %
   start_error   0   0 %
   no_data   0   0 %
   force_ok      0   0 %
   force_zero    0   0 %
   force_lm      0   0 %
   no_slope      0   0 %
Output
  # A tibble: 6 x 6
    f_fluxid f_quality_flag f_RMSE f_cor_coef f_ratio f_gfactor
    <fct>    <chr>           <dbl>      <dbl>   <dbl>     <dbl>
  1 1        discard         23.5       0.211   1         13.8 
  2 2        ok              14.0       0.336   1          7.74
  3 3        ok               2.51      0.949   1          2.63
  4 4        zero            15.0       0.112   1         26.2 
  5 5        discard         12.0      -0.315   0.976    -14.0 
  6 6        ok               6.19      0.640   0.981      3.65

works for linear fitting

Code
  dplyr::distinct(dplyr::select(flux_quality(slopes30lin, conc), f_fluxid,
  f_quality_flag, f_pvalue, f_rsquared))
Message

   Total number of measurements: 6

   ok    5   83 %
   zero      1   17 %
   discard   0   0 %
   force_discard     0   0 %
   start_error   0   0 %
   no_data   0   0 %
   force_ok      0   0 %
   force_zero    0   0 %
   force_lm      0   0 %
   no_slope      0   0 %
Output
  # A tibble: 12 x 4
     f_fluxid f_quality_flag  f_pvalue f_rsquared
     <fct>    <chr>              <dbl>      <dbl>
   1 1        ok             1.23e-166    0.986  
   2 1        <NA>           1.23e-166    0.986  
   3 2        ok             1.43e-207    0.995  
   4 2        <NA>           1.43e-207    0.995  
   5 3        ok             3.06e- 96    0.913  
   6 3        <NA>           3.06e- 96    0.913  
   7 4        ok             1.04e-108    0.937  
   8 4        <NA>           1.04e-108    0.937  
   9 5        zero           2.84e-  1    0.00646
  10 5        <NA>           2.84e-  1    0.00646
  11 6        ok             1.39e-114    0.946  
  12 6        <NA>           1.39e-114    0.946

works for quadratic fitting

Code
  dplyr::distinct(dplyr::select(flux_quality(slopes30qua, conc), f_fluxid,
  f_quality_flag, f_pvalue, f_rsquared, f_gfactor))
Message

   Total number of measurements: 6

   ok    5   83 %
   zero      1   17 %
   discard   0   0 %
   force_discard     0   0 %
   start_error   0   0 %
   no_data   0   0 %
   force_ok      0   0 %
   force_zero    0   0 %
   force_lm      0   0 %
   no_slope      0   0 %
Output
  # A tibble: 12 x 5
     f_fluxid f_quality_flag  f_pvalue f_rsquared f_gfactor
     <fct>    <chr>              <dbl>      <dbl>     <dbl>
   1 1        ok             9.51e-297      1.00       1.45
   2 1        <NA>           9.51e-297      1.00      NA   
   3 2        ok             1.08e-292      0.999      1.26
   4 2        <NA>           1.08e-292      0.999     NA   
   5 3        ok             2.44e-173      0.989      2.11
   6 3        <NA>           2.44e-173      0.989     NA   
   7 4        ok             8.52e-217      0.996      1.97
   8 4        <NA>           8.52e-217      0.996     NA   
   9 5        zero           9.68e- 55      0.755    -40.5 
  10 5        <NA>           9.68e- 55      0.755     NA   
  11 6        ok             5.13e-191      0.993      1.86
  12 6        <NA>           5.13e-191      0.993     NA

kappamax with HM model

Code
  dplyr::distinct(dplyr::select(dplyr::filter(flux_quality(slopeshm, conc,
    f_pvalue = f_pvalue_lm, f_rsquared = f_rsquared_lm, kappamax = TRUE), f_cut ==
    "keep"), f_fluxid, f_quality_flag, f_slope_corr, f_model))
Message

   Number of measurements with linear fit: 1

   Total number of measurements: 6

   ok    5   83 %
   zero      1   17 %
   discard   0   0 %
   force_discard     0   0 %
   start_error   0   0 %
   no_data   0   0 %
   force_ok      0   0 %
   force_zero    0   0 %
   force_lm      0   0 %
   no_slope      0   0 %
Output
  # A tibble: 6 x 4
    f_fluxid f_quality_flag f_slope_corr f_model
    <fct>    <chr>                 <dbl> <chr>  
  1 1        ok                    0.727 exp_hm 
  2 2        ok                    0.418 exp_hm 
  3 3        ok                    0.374 exp_hm 
  4 4        ok                    0.725 exp_hm 
  5 5        zero                  0     linear 
  6 6        ok                    0.404 exp_hm

kappamax with zhao18 model

Code
  dplyr::distinct(dplyr::select(dplyr::filter(flux_quality(slopesexp, conc,
    f_pvalue = f_pvalue_lm, f_rsquared = f_rsquared_lm, kappamax = TRUE), f_cut ==
    "keep"), f_fluxid, f_quality_flag, f_slope_corr, f_model))
Message

   Number of measurements with linear fit: 1

   Total number of measurements: 6

   ok    5   83 %
   zero      1   17 %
   discard   0   0 %
   force_discard     0   0 %
   start_error   0   0 %
   no_data   0   0 %
   force_ok      0   0 %
   force_zero    0   0 %
   force_lm      0   0 %
   no_slope      0   0 %
Output
  # A tibble: 6 x 4
    f_fluxid f_quality_flag f_slope_corr f_model   
    <fct>    <chr>                 <dbl> <chr>     
  1 1        ok                    0.775 exp_zhao18
  2 2        ok                    0.504 exp_zhao18
  3 3        ok                    0.337 exp_zhao18
  4 4        ok                    0.676 exp_zhao18
  5 5        zero                  0     linear    
  6 6        ok                    0.425 exp_zhao18

works in a pipeline

Code
  dplyr::distinct(dplyr::select(flux_quality(flux_fitting(co2_conc, conc,
    datetime, fit_type = "exp_hm"), f_conc = conc, f_pvalue = f_pvalue_lm,
  f_rsquared = f_rsquared_lm, kappamax = TRUE), f_fluxid, f_quality_flag, f_RMSE,
  f_cor_coef, f_ratio, f_gfactor))
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
Message

   Number of measurements with linear fit: 4

   Total number of measurements: 6

   discard   3   50 %
   ok    2   33 %
   zero      1   17 %
   force_discard     0   0 %
   start_error   0   0 %
   no_data   0   0 %
   force_ok      0   0 %
   force_zero    0   0 %
   force_lm      0   0 %
   no_slope      0   0 %
Output
  # A tibble: 6 x 6
    f_fluxid f_quality_flag f_RMSE f_cor_coef f_ratio f_gfactor
    <fct>    <chr>           <dbl>      <dbl>   <dbl>     <dbl>
  1 1        discard        NA         NA       1         NA   
  2 2        discard        NA         NA       1         NA   
  3 3        ok              0.550      0.949   1          3.10
  4 4        zero           NA         NA       1         NA   
  5 5        discard        NA         NA       0.976     NA   
  6 6        ok              7.02       0.640   0.981      5.50