Hi,
Last week I have tried to define a simple exploration task I want to send vectors of parameters. Something like :
val exploration =
DirectSampling(
evaluation = Replication(task hook csvHook, seed, 10),
sampling = density in (100, 506, 992, 4970)
)
Where density parameters are defined directly. I can’t find the “good” way to do that without this error :
org.openmole.core.console.ScalaREPL$CompilationError: (line 92) type mismatch;
found : org.openmole.core.workflow.sampling.Factor[(Int, Int),Int]
required: org.openmole.core.workflow.sampling.Sampling
sampling = density in (100, 506)
^
Error in imports header:
(line -25) type mismatch;
found : org.openmole.core.workflow.sampling.Factor[(Int, Int),Int]
required: org.openmole.core.workflow.sampling.Sampling
sampling = density in (100, 506)
^
Compiling code:
class _92ed33474adfd177f7b9c58e15b52d79747f0dd4Class {
lazy val _imports = new {
}
Someone can give me a hand ?
E.
Note the entire code is here.
//Input variable for
val seed = Val[Int]
val regularOrganisation = Val[Boolean]
val density = Val[Int]
val grid = Val[Boolean]
val grpercCrit = Val[Double]
val MeanPnetw = Val[Double]
val SDPnetw = Val[Double]
val Cooperation = Val[Boolean]
val Recruitment = Val[Boolean]
val rSpatialDistribution = Val[String]
val competition = Val[Boolean]
val networking = Val[Boolean]
val MortNoCompet = Val[Double]
val benefit = Val[Double]
val rVariation = Val[String]
val benefitSurv = Val[Boolean]
// outpput variables
val nbTurtles = Val[Int]
val minimumGrowth = Val[Double]
val maximumGrowth = Val[Double]
val nbIndWithLinks = Val[Double]
val pctIndWithLinks = Val[Double]
val meanNbOfNeighbors = Val[Double]
val minIndividualBiomassAlive = Val[Int]
val maxIndividualBiomassAlive = Val[Int]
val meanPtnew = Val[Double]
val sdB = Val[Double]
val meanB = Val[Double]
val meanGrperc = Val[Double]
val launch = List("setup","random-seed ${seed}","go-300")
val task = NetLogo6Task(workDirectory / "AZOI.nlogo", launch, embedWorkspace = false) set(
inputs += (seed),
// Defined and map inptut send by openMole to Netlogo
netLogoInputs += (regularOrganisation, "regular-organisation"),
netLogoInputs += (density, "density"),
netLogoInputs += (grid, "grid"),
netLogoInputs += (grpercCrit, "grperc-crit"),
netLogoInputs += (MeanPnetw, "Mean-Pnetw"),
netLogoInputs += (SDPnetw, "SD-Pnetw"),
netLogoInputs += (Cooperation, "Cooperation"),
netLogoInputs += (Recruitment, "Recruitment"),
netLogoInputs += (rSpatialDistribution, "r-spatial-distribution"),
netLogoInputs += (competition, "competition"),
netLogoInputs += (networking, "networking"),
netLogoInputs += (MortNoCompet, "Mort-noCompet"),
netLogoInputs += (benefit, "benefit"),
netLogoInputs += (rVariation, "r-variation"),
netLogoInputs += (benefitSurv, "benefit-surv"),
// Defined and map output from Netlogo to openMole
netLogoOutputs += ("nbTurtles", nbTurtles),
netLogoOutputs += ("minimumGrowth", minimumGrowth),
netLogoOutputs += ("maximumGrowth", maximumGrowth),
netLogoOutputs += ("nbIndWithLinks", nbIndWithLinks),
netLogoOutputs += ("pctIndWithLinks", pctIndWithLinks),
netLogoOutputs += ("meanNbOfNeighbors", meanNbOfNeighbors),
netLogoOutputs += ("minIndividualBiomassAlive", minIndividualBiomassAlive),
netLogoOutputs += ("maxIndividualBiomassAlive", maxIndividualBiomassAlive),
netLogoOutputs += ("meanPtnew", meanPtnew),
netLogoOutputs += ("sdB", sdB),
netLogoOutputs += ("meanB", meanB),
netLogoOutputs += ("meanGrperc", meanGrperc),
//Default values. Can be removed if OpenMOLE Vals are set by values coming from the workflow
regularOrganisation := true,
grid := true,
grpercCrit := 0.01,
MeanPnetw := 0.01,
SDPnetw := 0.002,
Cooperation := true,
Recruitment := false,
rSpatialDistribution := "random-high",
competition := false,
networking := false,
MortNoCompet := 0.001,
benefit := 0.25,
rVariation := "no-temporal",
benefitSurv := true
)
val csvHook = CSVHook(workDirectory / "result.csv", seed, nbTurtles, minimumGrowth,
maximumGrowth, nbIndWithLinks, pctIndWithLinks,
meanNbOfNeighbors, minIndividualBiomassAlive,
maxIndividualBiomassAlive, meanPtnew, sdB, meanB,meanGrperc)
val exploration =
DirectSampling(
evaluation = Replication(task hook csvHook, seed, 10),
sampling = density in (100, 506)
)
exploration
//// end
