Provides a table of how many fluxes were attributed which quality flag. This function is incorporated in flux_quality as a message, but can be used alone to extract a dataframe with the flag count.
Usage
flux_flag_count(
flags_df,
f_fluxid = f_fluxid,
f_quality_flag = f_quality_flag,
f_flags = c("ok", "discard", "zero", "force_discard", "start_error", "no_data",
"force_ok", "force_zero", "force_lm", "no_slope")
)Arguments
- flags_df
dataframe of flux slopes
- f_fluxid
column containing fluxes unique ID
- f_quality_flag
column containing the quality flags
- f_flags
list of flags used in the dataset (if different from default from flux_quality). If not provided, it will list only the flags that are present in the dataset (no showing 0).
Value
a dataframe with the number of fluxes for each quality flags and their proportion to the total
Examples
data(co2_conc)
slopes <- flux_fitting(co2_conc, conc, datetime, fit_type = "exp_zhao18")
#> Cutting measurements...
#> Estimating starting parameters for optimization...
#> Optimizing fitting parameters...
#> Calculating fits and slopes...
#> Done.
#> Warning:
#> fluxID 5 : slope was estimated on 205 points out of 210 seconds
#> fluxID 6 : slope was estimated on 206 points out of 210 seconds
slopes_flag <- flux_quality(slopes, conc)
#>
#> 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 %
flux_flag_count(slopes_flag)
#> # A tibble: 10 × 3
#> f_quality_flag n ratio
#> <fct> <int> <dbl>
#> 1 ok 3 0.5
#> 2 discard 2 0.333
#> 3 zero 1 0.167
#> 4 force_discard 0 0
#> 5 start_error 0 0
#> 6 no_data 0 0
#> 7 force_ok 0 0
#> 8 force_zero 0 0
#> 9 force_lm 0 0
#> 10 no_slope 0 0