Version for StoX 4.2.1.

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: RstoxBase
 Version: 2.2.1
-Date: 2026-06-25
+Date: 2026-07-06
 Title: Base StoX Functions
 Authors@R: c(
   person(given = "Arne Johannes", 
@@ -47,7 +47,7 @@ Imports:
     jsonlite (>= 1.6),
     lwgeom (>= 0.2-0),
     maps (>= 0.2-0),
-    RstoxData (>= 2.2.0),
+    RstoxData (>= 2.2.1),
     sf (>= 0.9.0),
     stringi (>= 1.4.0),
     units (>= 0.7),

NEWS.md

@@ -1,3 +1,7 @@
+# RstoxBase v2.2.1  (2026-07-04)
+* Fixed bug in SuperIndividuals() due to SampleWeight or SampleNumber = 0. This is now OK if there are no individuals with length in the sample.
+
+
 # RstoxBase v2.2.1-9006  (2026-06-22)
 * Reduced processing time for the functions MeanNASC, AcousticDensity, MeanDensity and Abundance to approximately 30% for a StoX project with large acoustic data (regular survey with 10 m channels and 0.1 nautical mile log distance). This can lead to approximately 50 % reduction in Bootstrap time.
 

R/Abundance.R

@@ -372,6 +372,7 @@ SuperIndividuals <- function(
     SuperIndividualsData[, Abundance := Abundance * individualWeightFactor]
 
     # Test whether the sum of the Abundance is equal to that of the QuantityData. Note that if all SuperIndividualsData$Abundance and all QuantityData$Data$Abundance are NA, the totalAbundanceInSuperIndividualsData and totalAbundanceInQuantityData will be 0 due to the na.rm = TRUE. Before, testEqualTo1() was used here, but this returned NA for 0 / 0 = NaN, and the condition in the test failed. Thus the testEqual() is used instead:
+
     totalAbundanceInSuperIndividualsData <- sum(SuperIndividualsData$Abundance, na.rm = TRUE)
     totalAbundanceInQuantityData <- sum(QuantityData$Data$Abundance, na.rm = TRUE)
     if(!testEqual(totalAbundanceInSuperIndividualsData, totalAbundanceInQuantityData)) {

R/LengthDistribution.R

@@ -152,14 +152,13 @@ LengthDistribution <- function(
     #LengthDistributionData <- addLayerProcessData(LengthDistributionData, dataType = "LengthDistributionData", layerProcessData = if(IncludeLayer) BioticLayer)
     ######################################################
 
-
     #######################################################
     ##### 5. Aggregate multiple samples to each haul: #####
     #######################################################
     # Create a data table of different raising factors in the columns:
     raisingFactorTable <- data.frame(
-        Weight = LengthDistributionData$CatchFractionWeight / LengthDistributionData$SampleWeight, 
-        Number = LengthDistributionData$CatchFractionNumber / LengthDistributionData$SampleNumber#, 
+        Weight = ifelse(LengthDistributionData$SampleWeight == 0, NA, LengthDistributionData$CatchFractionWeight / LengthDistributionData$SampleWeight), 
+        Number = ifelse(LengthDistributionData$SampleNumber == 0, NA, LengthDistributionData$CatchFractionNumber / LengthDistributionData$SampleNumber)#, 
         #Percent = 1
     )
 
@@ -177,6 +176,8 @@ LengthDistribution <- function(
     raisingFactorIndex <- apply(raisingFactorTable, 1, getIndexOfFirstNonNA, LengthDistributionType = LengthDistributionType)
     LengthDistributionData$raisingFactor <- raisingFactorTable[cbind(seq_along(raisingFactorIndex), raisingFactorIndex)]
 
+
+
     # Set raisingFactor to 1 if LengthDistributionType == "Percent" and only one sample:
     if(LengthDistributionType == "Percent") {
         LengthDistributionData[numberOfSubSamples == 1 & is.na(raisingFactor), raisingFactor := 1]