R/logbook_weighting_control.R
logbook_weighting_control.RdThe purpose of the logbook_weighting_control function is to provide a table of data that contains an inconsistency between the sample weighting
data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_weighting_control () function.
data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_weighting_control () function.
data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_weighting_control () function.
data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_weighting_control () function.
character expected. Kind of expected output. You can choose between "message", "report" or "logical".
character expected. Default values: c("6", "2"). List of two elements, the first is the seine vessel type code, and the second is the baitboat type code.
numeric expected. Default values: 100. Seiner threshold weight
numeric expected. Default values: 0.95. Percentage threshold between weight and weighted weight for seiners
character expected. Default values: c("11"). List of sample type codes for baitboat fresh landings
character expected. Default values: c("L-YFT-10", "L-BET-10", "L-TUN-10"). List of codes for fresh baitboat landings
numeric expected. Default values: 1. Threshold for baitboats with respect to the difference between the weighted weight and the landed fresh weight and the difference between the weight and the weighted weight
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 :
sample_id
sample_smallsweight
sample_bigsweight
sample_totalweight
trip_id
sampletype_code
sampleactivity_id
sampleactivity_weightedweight
sample_id
trip_id
vesseltype_code
vesseltype_label1
landing_id
landing_weight
weightcategory_code
trip_id
#Sample 1, 3, 4, 7, 9, 12, 17 and 18 are ok,
#Sample 2 has a weighted weight ratio over the sum of the weights of small and big individuals below
# the threshold (threshold_ratio),
#Sample 5 has a difference between fresh landing and weighted weight above the
# threshold (threshold_baitboat),
#Sample 6 has no vessel type,
#Sample 8 has no sample type,
#Sample 10 has no sample activity,
#Sample 11 has a difference between total weight and weighted weight above the
# threshold (threshold_baitboat),
#Sample 13 has no sample activity,
#Sample 14 has a difference between sum of the weights of small and big individuals and weighted
# weight above the threshold (threshold_baitboat),
#Sample 15 has the sum of the weights of small and big individuals above the
# threshold (threshold_weight),
#Sample 16 has the sum of the total weight above the threshold (threshold_weight),
#Sample 19 has a weighted weight ratio over the total weight below the threshold (threshold_ratio)
dataframe1 <- data.frame(sample_id = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11",
"12", "13", "14", "15", "16", "17", "18", "19"),
sample_smallsweight = c(10, 32, 2.5, 30, 12, 7, NA, 6, NA, 4, 8, 3, 7, 13,
54, 3, 8, 2, 16),
sample_bigsweight = c(50, 2, 9, 3, 6, 13, 0, 3, 7, 2, 0, 2, 8, 3, 62, 8,
15, 6, 1),
sample_totalweight = c(NA, NA, NA, 33, 8, 9, 142, 2, 14, 10, 3, 0, NA, 0,
0, 104, 24, 36, 12),
trip_id = c("1", "1", "2", "3", "4", "5", "6", "7", "8", "8", "8", "8",
"8", "8", "1", "1", "1", "1", "1"),
sampletype_code = c("1", "1", "1", "11", "11", "1", "1", NA, "1", "1", "1",
"1", "1", "1", "1", NA, NA, NA, NA))
dataframe2 <- data.frame(sampleactivity_id = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10",
"11", "12", "13", "14", "15", "16", "17"),
sampleactivity_weightedweight = c(70, 5, 18, 12, 33, 5, 9, 4, 13, 7, 4, 15,
116, 104, 24, 35, 11),
sample_id = c("1", "1", "2", "3", "4", "5", "6", "8", "9", "11", "12",
"14", "15", "16", "17", "18", "19"))
dataframe3 <- data.frame(trip_id = c("1", "2", "3", "4", "6", "7", "8"),
vesseltype_code = c("6", "6", "2", "2", "3", "2", "2"),
vesseltype_label = c("vessel_type_1", "vessel_type_1", "vessel_type_2",
"vessel_type_2", "vessel_type_3", "vessel_type_2",
"vessel_type_2"))
dataframe4 <- data.frame(landing_id = c("1", "2", "3", "4", "5", "6"),
landing_weight = c(85, 26, 30, 2.6, 20, 3),
weightcategory_code = c("W-1", "W-1", "L-YFT-10", "L-YFT-10", "L-YFT-10",
"L-BET-10"),
trip_id = c("1", "2", "3", "3", "4", "7"))
logbook_weighting_control(dataframe1, dataframe2, dataframe3, dataframe4, output = "report")
#> sample_id logical sample_smallsweight sample_bigsweight sample_totalweight
#> 1 1 TRUE 10.0 50 NA
#> 2 2 FALSE 32.0 2 NA
#> 3 3 TRUE 2.5 9 NA
#> 4 4 TRUE 30.0 3 33
#> 5 5 FALSE 12.0 6 8
#> 6 6 FALSE 7.0 13 9
#> 7 7 TRUE NA 0 142
#> 8 8 FALSE 6.0 3 2
#> 9 9 TRUE NA 7 14
#> 10 10 FALSE 4.0 2 10
#> 11 11 FALSE 8.0 0 3
#> 12 12 TRUE 3.0 2 0
#> 13 13 FALSE 7.0 8 NA
#> 14 14 TRUE 13.0 3 0
#> 15 15 FALSE 54.0 62 0
#> 16 16 FALSE 3.0 8 104
#> 17 17 TRUE 8.0 15 24
#> 18 18 TRUE 2.0 6 36
#> 19 19 FALSE 16.0 1 12
#> sampletype_code weightedweight vesseltype_label sum_landing_weight_baitboat
#> 1 1 75 vessel_type_1 NA
#> 2 1 18 vessel_type_1 NA
#> 3 1 12 vessel_type_1 NA
#> 4 11 33 vessel_type_2 32.6
#> 5 11 5 vessel_type_2 20.0
#> 6 1 9 <NA> NA
#> 7 1 NA vessel_type_3 NA
#> 8 <NA> 4 vessel_type_2 3.0
#> 9 1 13 vessel_type_2 NA
#> 10 1 NA vessel_type_2 NA
#> 11 1 7 vessel_type_2 NA
#> 12 1 4 vessel_type_2 NA
#> 13 1 NA vessel_type_2 NA
#> 14 1 15 vessel_type_2 NA
#> 15 1 116 vessel_type_1 NA
#> 16 <NA> 104 vessel_type_1 NA
#> 17 <NA> 24 vessel_type_1 NA
#> 18 <NA> 35 vessel_type_1 NA
#> 19 <NA> 11 vessel_type_1 NA