Gives the inconsistencies between the weights of small and big sample fish and the sum of the small and big weights in the associated well

Source: R/logbook_distribution_control.R

The purpose of the logbook_distribution_control function is to provide a table of data that contains an inconsistency between the small and large sample weights and the sum of the small and big weights of the associated well

logbook_distribution_control(
  dataframe1,
  dataframe2,
  dataframe3,
  dataframe4,
  output,
  species_category_small_big = c("ALB", "YFT", "BET", "SKJ"),
  species_category_unknown = c("SKJ"),
  weight_category_small = c("W-1"),
  weight_category_big = c("W-2"),
  weight_category_unknown = c("W-9")
)

Arguments

dataframe1

data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_distribution_control () function.

dataframe2

data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_distribution_control () function.

dataframe3

data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_distribution_control () function.

dataframe4

data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_distribution_control () function.

output

character expected. Kind of expected output. You can choose between "message", "report" or "logical".

species_category_small_big

character expected. Default values: c("ALB", "YFT", "BET", "SKJ"). List of the inventory of species (FAO code) used to calculate weight category small and big in well

species_category_unknown

character expected. Default values: c("SKJ"). Vector of species categorized as small if weight category information is missing

weight_category_small

character expected. Default values: c("W-1"). Vector of small weight category codes

weight_category_big

character expected. Default values: c("W-2"). Vector of big weight category codes

weight_category_unknown

character expected. Default values: c("W-9"). Vector of unknown weight category codes

Value

The function returns a character with output is "message", a data.frame with output is "report", a logical with output is "logical"

Details

The input dataframe must contain all these columns for the function to work :

  • sample_id

  • sample_well

  • trip_id

  • sample_smallsweight

  • sample_bigsweight

  • well_id

  • well_label

  • trip_id

  • wellactivity_id

  • well_id

  • wellactivityspecies_id

  • wellactivity_id

  • weightcategory_code

  • species_fao_code

  • wellactivityspecies_weight

Examples

#Sample 1 and 2 are ok,
#Sample 3 has not small weight in well,
#Sample 4 has not bigs weight in sample,
#Sample 5 has different bigs weight,
#Sample 6 and 7 has different small weight
dataframe1 <- data.frame(sample_id = c("1", "2", "3", "4", "5", "6", "7"),
                         sample_well = c("well_1", "well_2", "well_3", "well_4", "well_5",
                                         "well_6","well_7"),
                         trip_id = c("1", "1", "1", "1", "1", "1", "1"),
                         sample_smallsweight = c(6, 25, 14, 0, NA, 10, 8),
                         sample_bigsweight = c(12, 0, 9, NA, 6, 0, 0))
dataframe2 <- data.frame(well_id = c("1", "2", "3", "4", "5", "6", "7"),
                         well_label = c("well_1", "well_2", "well_3", "well_4", "well_5", "well_6",
                                        "well_7"),
                         trip_id = c("1", "1", "1", "1", "1", "1", "1"))
dataframe3 <- data.frame(wellactivity_id = c("1", "2", "3", "4", "5", "6", "7", "8"),
                         well_id = c("1", "1", "2", "3", "4", "5", "6", "7"))
dataframe4 <- data.frame(wellactivityspecies_id = c("1", "2", "3", "4", "5", "6", "7", "8", "9",
                                                    "10", "11", "12", "13", "14"),
                         wellactivity_id = c("1", "1", "1", "2", "3", "4", "4", "5", "6", "7",
                                             "7", "7", "8", "8"),
                         weightcategory_code = c("W-1", "W-9", "W-2", "W-2", "W-1", "W-2", "W-9",
                                                 "W-2", "W-2", "W-1", "W-9", "W-9", "W-1", "W-1"),
                         species_fao_code = c("BET", "SKJ", "SKJ", "ALB", "SKJ", "BET", "BET",
                                              "ALB", "SKJ", "SKJ", "SKJ", "BET", "ALB", "JOS"),
                         wellactivityspecies_weight = c(4, 2, 7, 5, 25, 9, 14, 5, 17, 10, 5, 2, 7,
                                                        1))
logbook_distribution_control(dataframe1, dataframe2, dataframe3, dataframe4, output = "report")
#>   sample_id logical sample_smallsweight sample_bigsweight sample_well
#> 1         1    TRUE                   6                12      well_1
#> 2         2    TRUE                  25                 0      well_2
#> 3         3   FALSE                  14                 9      well_3
#> 4         4   FALSE                   0                NA      well_4
#> 5         5   FALSE                  NA                 6      well_5
#> 6         6   FALSE                  10                 0      well_6
#> 7         7   FALSE                   8                 0      well_7
#>   weight_sum_small_filter weight_sum_big_filter weight_sum_small weight_sum_big
#> 1                       6                    12                6             12
#> 2                      25                   NaN               25            NaN
#> 3                     NaN                     9               14              9
#> 4                     NaN                     5              NaN              5
#> 5                     NaN                    17              NaN             17
#> 6                      15                   NaN               17            NaN
#> 7                       7                   NaN                8            NaN