R/logbook_weighting_sample_control.R
logbook_weighting_sample_control.RdThe purpose of the logbook_weighting_sample_control function is to provide a table of data that contains an inconsistency between the sample weighting and weight in well
logbook_weighting_sample_control(
dataframe1,
dataframe2,
output,
species = c("YFT", "SKJ", "BET", "ALB", "LTA", "FRI", "TUN", "KAW", "LOT"),
epsilon = 0.01
)data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_weighting_sample_control () function.
data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_weighting_sample_control () function.
character expected. Kind of expected output. You can choose between "message", "report" or "logical".
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.
numeric expected, default : 0.01. Gives the threshold at which the difference is considered too large.
The function returns a character with output is "message", a data.frame with output is "report", a logical with output is "logical"
The input dataframe must contain all these columns for the function to work :
sampleactivity_id
sampleactivity_weightedweight
sample_well
activity_id
trip_id
wellactivityspecies_id
wellactivityspecies_weight
species_fao_code
well_label
activity_id
trip_id
#Sample activity 1, 2, 3, 4, 5, 6 and 7 are ok,
#Sample Activity 8 has weights missing from the well,
#Sample Activity 9 does not take into account all species
#Sample Activity 10 does not take into account all well
#Sample Activity 11 has weighted weight missing
dataframe1 <- data.frame(sampleactivity_id = c("1", "2", "3", "4", "5", "6", "7", "8", "9",
"10", "11"),
sampleactivity_weightedweight = c(3, 6, 20, 6.25, 13.75, 7.6, 2, 2,
26, 13, NA),
sample_well = c("well_1", "well_2", "well_1", "well_1", "well_2",
"well_1", "well_2", "well_1", "well_1", "well_1",
"well_1"),
activity_id = c("1", "1", "2", "3", "3", "4", "5", "6", "7", "8", "9"),
trip_id = c("1", "1", "2", "3", "3", "4", "4", "5", "6", "7", "8"))
dataframe2 <- data.frame(wellactivityspecies_id = c("1", "2", "3", "4", "5", "6", "7", "8", "9",
"10", "11", "12", "13", "14", "15", "16", "17"),
wellactivityspecies_weight = c(3, 2, 4, 1, 15, 5, 5, 11, 4, 4, 6, 9,
2, 26, 2, 13, 6),
species_fao_code = c("YFT", "SKJ", "ALB", "JOS", "YFT", "FRI", "YFT",
"SKJ", "BET", "YFT", "YFT", "ALB", "YFT", "ALB",
"YFT", "BET", "ALB"),
well_label = c("well_1", "well_2", "well_2", "well_2", "well_1", "well_2",
"well_1", "well_2", "well_3", "well_1", "well_2", "well_3",
"well_2", "well_1", "well_1", "well_1", "well_2"),
activity_id = c("1", "1", "1", "1", "2", "2", "3", "3", "3", "4", "4", "4",
"5", "7", "7", "8", "8"),
trip_id = c("1", "1", "1", "1", "2", "2", "3", "3", "3", "4", "4", "4",
"4", "6", "6", "7", "7"))
logbook_weighting_sample_control(dataframe1, dataframe2, output = "report")
#> sampleactivity_id sampleactivity_weightedweight logical weightedweight_well
#> 1 1 3.00 TRUE 3.00
#> 2 2 6.00 TRUE 6.00
#> 3 3 20.00 TRUE 20.00
#> 4 4 6.25 TRUE 6.25
#> 5 5 13.75 TRUE 13.75
#> 6 6 7.60 TRUE 7.60
#> 7 7 2.00 TRUE 2.00
#> 8 8 2.00 FALSE NA
#> 9 9 26.00 FALSE 28.00
#> 10 10 13.00 FALSE 19.00
#> 11 11 NA FALSE NA