- Reduced all instances of "seed" to one set.seed() call at app start

- Used unicode encoding instead of the actual symbol for plots' y labels
- Removed crashing species by modifying random number scale factor in modifyFishingMatrix()

tests/testthat/test-constants.R

@@ -5,8 +5,7 @@ CREATE_BASELINE_FILES <- FALSE
 
 NUMBER_OF_STEPS <- 5 # should be an odd multiple of nrows=600 (i.e., 5,15,30)
 FACTOR_VALUE <- 5
-SEED_VALUE   <- 1 
-SEED_OFFSET <- 2000
+SEED_VALUE   <- 7 
 TOLERANCE_VALUE <- 1e-5
 RUN_QUIET <- TRUE
 YLIMIT_DIFFERENCE_PLOTS <- 0.05

tests/testthat/test-rpath.R

@@ -20,6 +20,9 @@ print(paste0("OUTPUT_DATA_DIR: ",         OUTPUT_DATA_DIR)) #RSK
 print(paste0("INPUT_DATA_DIR_BASELINE: ", INPUT_DATA_DIR_BASELINE)) #RSK
 print(paste0("INPUT_DATA_DIR_CURRENT: ",  INPUT_DATA_DIR_CURRENT)) #RSK
 
+# Set the seed here so that all runs will be deterministic.
+set.seed(SEED_VALUE)
+
 # Create the current and output directories if they don't already exist.
 if (! dir.exists(INPUT_DATA_DIR_CURRENT)) {
   dir.create(INPUT_DATA_DIR_CURRENT,recursive=TRUE)
@@ -612,7 +615,6 @@ testthat::test_that("Rpath Unit Tests", {
       # in the tests.yml file but don't fail when run via R-CMD-Check.yml.
       #
       # This line doesn't fail in git actions (it's just not the exact logic I need)
-      # set.seed(modNum*typeNum*SEED_OFFSET)
       # REcosystem_scenario_jitter$forcing$ForcedBio <- jitter(REcosystem_scenario_jitter$forcing$ForcedBio,factor=FACTOR_VALUE)
       #
       # Another way to jitter
@@ -626,7 +628,7 @@ testthat::test_that("Rpath Unit Tests", {
       #  speciesBiomass <- REcosystem_scenario_jitter$start_state$Biomass[aSpecies]
       #  totSpeciesBiomass <- totSpeciesBiomass + speciesBiomass
       #  for (month in 1:numMonths) {
-      #    randVal <- randomNumber(modNum*typeNum*SEED_OFFSET+speciesNum*numMonths+month)
+      #    randVal <- ...
       #    jitteredValue <- speciesBiomass * (1.0 + randVal)
       #    totRandVal <- totRandVal + randVal
       #    jitterVector <- append(jitterVector,jitteredValue)
@@ -742,7 +744,7 @@ testthat::test_that("Rpath Unit Tests", {
   numMonths <- nrow(REcosystem_scenario$fishing$ForcedEffort)
   REcosystem_scenario_jitter <- REcosystem_scenario
   fishingOriginalData  <- list(REcosystem_scenario$fishing$ForcedEffort, REcosystem_scenario$fishing$ForcedFRate, REcosystem_scenario$fishing$ForcedCatch)
-  typeData             <- list(FORCED_EFFORT,FORCED_FRATE,FORCED_CATCH)
+  typeData             <- list(FORCED_EFFORT, FORCED_FRATE, FORCED_CATCH)
   for (i in 1:length(fishingOriginalData)) {
     theTypeData  <- typeData[[i]]
     modNum <- modNum + 1

tests/testthat/test-utils-jitter.R

@@ -6,15 +6,13 @@ source("test-constants.R")
 #'
 #' @param matrix : data matrix to be jittered
 #' @param factor : the R jitter factor (the larger the number the greater the jitter amount)
-#' @param seedOffset : offset to the seed value, useful for getting "groups" of seed values
 #' @param xlabel : x axis label for plot
 #' @param ylabel : y axis label for plot 
 #' @param title : main title for plot
 #'
 #' @return Returns the jittered matrix
 #' 
-addJitter <- function(matrix,seedOffset,xlabel,ylabel,title) {
-  set.seed(seedOffset) # *SEED_VALUE)
+addJitter <- function(matrix,xlabel,ylabel,title) {
   # From jitter() doc: If amount == 0, jitter returns factor * z/50, where
   # z = max(x0) - min(x), aka the range. So if factor=5 and amount=0, jitter()
   # returns a random value within a tenth of the range.
@@ -28,26 +26,26 @@ addJitter <- function(matrix,seedOffset,xlabel,ylabel,title) {
 
 #' Create a jittered vector
 #' 
-#' Used for jittering a matrix column. Can't use replicate because need to pass a different seed for every value for reproducibility.
+#' Used for jittering a matrix column.
 #'
+#' @param typeData : the type of data to be jittered
 #' @param value : value to add jitter to
 #' @param numElements : number of elements in vector
-#' @param seedOffset : offset to the main seed value
 #' @param xlabel : x axis label for plot
 #' @param ylabel : y axis label for plot
 #' @param title : main title for plot
+#' @param title : the type of random number (positive only or any)
 #'
 #' @return Returns the column-jittered matrix
 #' 
-createJitterVectorFromValue <- function(typeData,value,numElements,seedOffset,xlabel,ylabel,title,randomNumberType) {
+createJitterVectorFromValue <- function(typeData,value,numElements,xlabel,ylabel,title,randomNumberType) {
   jitterVector <- c()
   migrationScaleFactor <- 1
   if (typeData == FORCED_MIGRATION) {
       migrationScaleFactor = FORCED_MIGRATION_SCALE_FACTOR_JITTER # = 1000
   }
   for (i in 1:numElements) {
-    #   jitteredValue <- addJitter(value,seedOffset+i,'','','')
-    randVal <- randomNumber(seedOffset+i,migrationScaleFactor*JITTER_AMOUNT_PCT,randomNumberType) # JITTER_AMOUNT_PCT = 0.01
+    randVal <- randomNumber(migrationScaleFactor*JITTER_AMOUNT_PCT,randomNumberType)
     jitteredValue <- value * (1.0 + randVal)
     jitterVector <- append(jitterVector,jitteredValue)
   }

tests/testthat/test-utils-plot.R

@@ -19,7 +19,7 @@ source("test-constants.R")
 plotResultsSuperimposed <- function(BaseData,CurrData,baseAlg,currAlg,tableName,forcedData,forcedType,species) {
   plots  <- list()
   group  <- species
-  yLabel <- "Biomass (mt/km²)"
+  yLabel <- "Biomass (mt/km\U00B2)"
   currDf <- data.frame()
   baseDf <- data.frame()
 
@@ -80,7 +80,7 @@ plotResultsSuperimposed <- function(BaseData,CurrData,baseAlg,currAlg,tableName,
 plotResultsDifference <- function(BaseData,CurrData,baseAlg,currAlg,tableName,forcedData,forcedType,species) {
   plots  <- list()
   group  <- species
-  yLabel <- "Biomass (mt/km²)"
+  yLabel <- "Biomass (mt/km\U00B2)"
   diffDf <- data.frame()
 
   for (member in group) {

tests/testthat/test-utils.R

@@ -2,15 +2,15 @@ source("test-constants.R")
 
 #' Random number generator
 #' 
-#' This function returns a seeded random number from a uniform distribution between
+#' This function returns a random number from a uniform distribution between
 #' a min and max value.
 #'
-#' @param seed : the random "seed" value to make the function deterministic
+#' @param pctToJitter : the percent to jitter (value=0.5 means 50%)
+#' @param positiveOnly : boolean that signifies random number returned is limited to non-negative numbers
 #'
 #' @return Returns the random value
 #' 
-randomNumber <- function(seed,pctToJitter,positiveOnly) {
-  set.seed(seed)
+randomNumber <- function(pctToJitter,positiveOnly) {
   minJitter <- -pctToJitter
   maxJitter <- pctToJitter
   if (positiveOnly) {
@@ -112,7 +112,7 @@ modifyFishingMatrix <- function(modNum,species,fleets,typeData,forcingData,model
   const2 <- 1
   upperLimit <- 0.5
   usePBValue <- FALSE
-  scaleFactorPB <- 0.01 # Needed this to add enough randomness to the plots, else they'd be fairly smooth
+  scaleFactorPB <- 0.0001 # Needed this to add enough randomness to the plots, else they'd be fairly smooth
   if (typeData == "Forced Effort") {
     speciesOrFleets <- fleets
   } else if (typeData == "Forced FRate" || typeData == "Forced Catch") {
@@ -132,14 +132,11 @@ modifyFishingMatrix <- function(modNum,species,fleets,typeData,forcingData,model
   for (i in 1:length(speciesOrFleets)) {
     item <- speciesOrFleets[i]
     vectorData           <- ForcedMatrix[,item]
-    # matrixDataWithJitter <- addJitter(matrixData,modNum*SEED_OFFSET*SEED_VALUE+i,"Months","Effort",paste0(typeData," with Random Noise - ",item))
     newVectorWithJitter <- c()
     for (value in vectorData) {
       j <- j + 1
       # Not sure why I need the [1] index here, this should always be just a single value but sometimes it's a list
-      # Forced Effort: jitteredValue <- (randomNumber(i+j,0.5))[1]
-      # Forced FRate:  pb[species index]*randomNumber(i+j,0.5))[1]
-      jitteredValue <- (const1+const2*randomNumber(i+j,upperLimit,randomNumberType))[1]
+      jitteredValue <- (const1+const2*randomNumber(upperLimit,randomNumberType))[1]
       newVectorWithJitter = append(newVectorWithJitter,jitteredValue)
     }
     ForcedMatrix[,item]  <- newVectorWithJitter
@@ -170,21 +167,20 @@ modifyForcingMatrix <- function (modNum,species,modifyType,typeData,forcingData,
       speciesBiomass <- scenario$start_state$Biomass[aSpecies]
       startValue <- speciesBiomass
       if (typeData == FORCED_MIGRATION) {
-        # rval <- (randomNumber(i,FORCED_MIGRATION_BIOMASS_PCT)+FORCED_MIGRATION_BIOMASS_PCT)/2.0
-        rval <- randomNumber(i,FORCED_MIGRATION_BIOMASS_PCT,randomNumberType)
+        # rval <- (randomNumber(FORCED_MIGRATION_BIOMASS_PCT)+FORCED_MIGRATION_BIOMASS_PCT)/2.0
+        rval <- randomNumber(FORCED_MIGRATION_BIOMASS_PCT,randomNumberType)
         startValue <- rval
         # print(paste0("species: ",aSpecies,", biomass: ",speciesBiomass,", randomNum: ",rval,", startValue: ",startValue))
       }
-      # print(paste0(modNum," ",i," ",SEED_OFFSET," ",aSpecies))
       if (modifyType == JITTERED) {
         # print(paste0("start value: ",i,", ",startValue))
-        ForcedMatrix[,aSpecies] <- createJitterVectorFromValue(typeData, startValue, numMonths, modNum*i*SEED_OFFSET, 
-                                                               "Months","Biomass (mt/km²)",
+        ForcedMatrix[,aSpecies] <- createJitterVectorFromValue(typeData, startValue, numMonths, 
+                                                               "Months","Biomass (mt/km\U00B2)",
                                                                paste0(typeData,' with ',modifyType,' Noise - ',aSpecies),
                                                                POSITIVE_AND_NEGATIVE)
       } else {
         stepType <- ((i-1)%%3)+1 # Only current step types are 1, 2, or 3
-        ForcedMatrix[,aSpecies] <- stepifyBiomass(typeData, startValue, numMonths, stepType, "Months","Biomass (mt/km²)",
+        ForcedMatrix[,aSpecies] <- stepifyBiomass(typeData, startValue, numMonths, stepType, "Months","Biomass (mt/km\U00B2)",
                                                   paste0(typeData,' with ',modifyType,' Noise - ',aSpecies), scaleFactors[i])
       }
     }