Gives the inconsistencies between the sample weighting and catch weight

Source: R/logbook_weighting_sample_control.R

The purpose of the logbook_weighting_sample_control function is to provide a table of data that contains an inconsistency between the sample weighting and catch weight for activity

logbook_weighting_sample_control(
  dataframe1,
  dataframe2,
  dataframe3,
  output,
  species = c("YFT", "SKJ", "BET", "ALB", "LTA", "FRI", "TUN", "KAW", "LOT"),
  species_fate = "6",
  epsilon = 0.01
)

Arguments

dataframe1

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

dataframe2

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

dataframe3

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

output

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

species

character expected. Default values: c("YFT", "SKJ", "BET", "ALB", "LTA", "FRI", "TUN", "KAW", "LOT"). list of the inventory of species (FAO code) used to compare to sample weighting.

species_fate

character expected. Default values: "6". Vector of inventory of fate used to compare to sample weighting.

epsilon

numeric expected, default : 0.01. Gives the threshold at which the difference is considered too large.

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 :

  • activity_id

  • catch_id

  • catch_weight

  • speciesfate_code

  • species_fao_code

  • activity_id

  • sampleactivity_id

  • sampleactivity_weightedweight

  • activity_id

Examples

#Activity 1, 3 and 5 are ok,
#Activity 2 has different weight,
#Activity 4 has weighted weight
dataframe1 <- data.frame(activity_id = c("1", "2", "3", "4", "5"))
dataframe2 <- data.frame(catch_id = c("1", "2", "3", "4", "5", "6"),
                         catch_weight = c(4, 2, 5, 10, 3, 8),
                         speciesfate_code = c("6", "6", "6", "6", "6", "6"),
                         species_fao_code = c("YFT", "JOS", "ALB", "YFT", "YFT", "FRI"),
                         activity_id = c("1", "1", "1", "2", "2", "5"))
dataframe3 <- data.frame(sampleactivity_id = c("1", "2", "3", "4", "5"),
                         sampleactivity_weightedweight = c(3, 6, 12.5, NA, 26),
                         activity_id = c("1", "1", "2", "3", "4"))
logbook_weighting_sample_control(dataframe1, dataframe2, dataframe3, output = "report")
#>   activity_id logical weight weightedweight
#> 1           1    TRUE      9            9.0
#> 2           2   FALSE     13           12.5
#> 3           3    TRUE     NA            0.0
#> 4           4   FALSE     NA           26.0
#> 5           5    TRUE      8             NA