Gives the inconsistencies between size class of the samples depending on the species and measurement type and the valid threshold

Source: R/logbook_length_class_control.R

The purpose of the logbook_length_class_control function is to provide a table of data that contains an inconsistency between the size class of the samples depending on the species and measurement type and the valid threshold (Default : 80)

logbook_length_class_control(
  dataframe1,
  output,
  size_measure_type = c("FL", "PD1"),
  threshold = c(10, 80)
)

Arguments

dataframe1

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

output

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

size_measure_type

character expected. Default values: c("FL", "PD1"). Vector of the size measure type controlled.

threshold

numeric expected. Default values: 10 and 80. Vector containing the lower and upper acceptable threshold for the size measured

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 :

  • samplespeciesmeasure_id

  • sizemeasuretype_code

  • samplespeciesmeasure_sizeclass

Examples

#Activity 1 and 2 are ok,
#Activity 3 has size class is less than threshold,
#Activity 4 has size class is greater than threshold,
#Activity 5 has size class is missing
dataframe1 <- data.frame(samplespeciesmeasure_id = c("1", "2", "3", "4", "5"),
                         sizemeasuretype_code = c("FL", "PD1", "PD1", "FL", "FL"),
                         samplespeciesmeasure_sizeclass = c(25, 75, 5, 83, NA))
logbook_length_class_control(dataframe1, output = "report")
#>   samplespeciesmeasure_id logical samplespeciesmeasure_sizeclass
#> 1                       1    TRUE                             25
#> 2                       2    TRUE                             75
#> 3                       3   FALSE                              5
#> 4                       4   FALSE                             83
#> 5                       5   FALSE                             NA