pse.oms

// seed for the random number generator
val seed = Val[Long]

// Model parameters for static landscape optimization
val ecoLandscapeRadius = Val[Double]
val ecoConnectivityArea = Val[Double]
val ecoServicesScalingExp = Val[Double]
val ecoServicesMaxArea = Val[Double]
val yEcoService = Val[Double]
val planningArea = Val[Double]
val managementArea = Val[Double]
val nHouseholdsSupportedPerHiIntUnit = Val[Double]
val fractionOfMngUnitsSparing = Val[Double]
val initFractionAgricultural = Val[Double]
val initFractionDegraded = Val[Double]

// Number of replicas to estimate ES robustness
val n = Val[Int]

// Outputs
val average = Val[Double]
val robustness = Val[Double]
val pop = Val[Int]

val model = ScalaTask(
    """
    import MultiScaleAgrarianSES._

    //val n = 1
    //val ecoLandscapeRadius = 4.0
    
    val n = 10
    val ecoLandscapeRadius = 30.0
    
    val ecoServicesScalingExp = 0.25
    val yEcoService = 0.5 
    val nHouseholdsSupportedPerHiIntUnit = 20.0
    val initFractionDegraded = 0.0
    val ecoConnectivityArea = 0.007 // this is an area of 19, thus a connectivity range of 2 cells
    
    val (average,robustness,pop): (Double, Double, Int)  = Simulation(
                                                                ecoLandscapeRadius.toInt,
                                                                ecoConnectivityArea,
                                                                ecoServicesScalingExp,
                                                                ecoServicesMaxArea,
                                                                yEcoService,
                                                                planningArea,
                                                                managementArea,
                                                                nHouseholdsSupportedPerHiIntUnit,
                                                                fractionOfMngUnitsSparing,
                                                                initFractionAgricultural,
                                                                initFractionDegraded,
                                                                seed
                                                            )
                                                            .runInitialization
                                                            .outputStaticLandscapeOptimization(n)
    
    """
    ) set (
        
        inputs += ( 
                    ecoServicesMaxArea,
                    planningArea,
                    managementArea,
                    fractionOfMngUnitsSparing,
                    initFractionAgricultural,
                    seed),

        outputs += (average,
                    robustness,
                    pop,
                    ecoConnectivityArea),

        plugins += (pluginsOf[MultiScaleAgrarianSES.Simulation],
                    pluginsOf[MultiScaleAgrarianSES.Matrix])
        
)

val env = SLURMEnvironment(
    "bengochead",
    "muse-login.meso.umontpellier.fr",
    // optional parameters
    partition = "defq",
    time = 1 hour,
    sharedDirectory = "/scratch/bengochead/openmole/AgrarianMultiScale"
  )

PSEEvolution(
   evaluation = model,
   parallelism = 1,
   termination = 1,
   genome = Seq(
     //ecoConnectivityArea in (0.003,0.04),  // these are radiuses between from 1 to 6
     ecoServicesMaxArea in (0.1,1.0),
     planningArea in (0.005,0.2),
     managementArea in (0.005,0.2),
     fractionOfMngUnitsSparing in (0.0,1.0),
     initFractionAgricultural in (0.0,0.95)
   ),
   objective = Seq(
     average in (0.0 to 1.0 by 0.1),  
     robustness in (0.0 to 1.0 by 0.1),
     pop in (0.0 to 25000 by 2500)
   ),
   reject = "managementArea < planningArea",
   stochastic = Stochastic(seed = seed, reevaluate = 0.2, sample = 100)
 ) hook (workDirectory / "pse_static", frequency = 1) on env