probula: Sanitize where the rng state is created

It should only be created in top-level executable files (which in this
project means Spec files)

src/main/scala/symsim/concrete/BdlConcreteExpectedSarsa.scala

@@ -13,7 +13,8 @@ case class BdlConcreteExpectedSarsa [
   val gamma: Double,
   val epsilon0: Probability,
   val episodes: Int,
-) extends BdlLearn[State, ObservableState, Action, Double, Randomized2],
+) (using val rng: probula.RNG)
+  extends BdlLearn[State, ObservableState, Action, Double, Randomized2],
   ConcreteExactRL[State, ObservableState, Action],
   NoDecay:
 

src/main/scala/symsim/concrete/BdlConcreteSarsa.scala

@@ -13,7 +13,8 @@ case class BdlConcreteSarsa [
   val gamma: Double,
   val epsilon0: Probability,
   val episodes: Int,
-) extends BdlLearn[State, ObservableState, Action, Double, Randomized2],
+) (using val rng: probula.RNG)
+  extends BdlLearn[State, ObservableState, Action, Double, Randomized2],
   ConcreteExactRL[State, ObservableState, Action],
   NoDecay:
 

src/main/scala/symsim/concrete/ConcreteExactRL.scala

@@ -3,9 +3,6 @@ package concrete
 
 import cats.kernel.BoundedEnumerable
 
-given spire.random.rng.SecureJava = 
-  spire.random.rng.SecureJava.apply
-
 trait ConcreteExactRL[State, ObservableState, Action]
   extends ExactRL[State, ObservableState, Action, Double, Randomized2]:
 
@@ -24,10 +21,12 @@ trait ConcreteExactRL[State, ObservableState, Action]
 
   // TODO: unclear if this is general (if it turns out to be the same im
   // symbolic or approximate algos we should promote this to the trait
+
+  given rng: probula.RNG
 
   def runQ: (Q, List[Q]) =
-    val initials = agent.initialize.sample(episodes)
-    val outcome = learn (vf.initialize, List[VF](), initials).sample()
+    val initials = agent.initialize.sample (episodes)
+    val outcome = learn (vf.initialize, List[VF] (), initials).sample ()
     (outcome._1, outcome._2)
 
   override def run: Policy =

src/main/scala/symsim/concrete/ConcreteExpectedSarsa.scala

@@ -7,7 +7,8 @@ case class ConcreteExpectedSarsa[State, ObservableState, Action] (
  val gamma: Double,
  val epsilon0: Probability,
  val episodes: Int,
-) extends ExpectedSarsa[State, ObservableState, Action, Double, Randomized2],
+) (using val rng: probula.RNG) 
+  extends ExpectedSarsa[State, ObservableState, Action, Double, Randomized2],
   ConcreteExactRL[State, ObservableState, Action],
   NoDecay:
 

src/main/scala/symsim/concrete/ConcreteQLearning.scala

@@ -13,7 +13,8 @@ case class ConcreteQLearning [
   val gamma: Double,
   val epsilon0: Probability,
   val episodes: Int,
-) extends QLearning[State, ObservableState, Action, Double, Randomized2],
+) (using val rng: probula.RNG) 
+  extends QLearning[State, ObservableState, Action, Double, Randomized2],
   ConcreteExactRL[State, ObservableState, Action],
   NoDecay:
 

src/main/scala/symsim/concrete/ConcreteQLearningWithDecay.scala

@@ -15,7 +15,8 @@ case class ConcreteQLearningWithDecay [
   val epsilon0: Probability,
   val episodes: Int,
 
-) extends QLearning[State, ObservableState, Action, Double, Randomized2],
+) (using val rng: probula.RNG) 
+  extends QLearning[State, ObservableState, Action, Double, Randomized2],
   ConcreteExactRL[State, ObservableState, Action],
   BoundedEpsilonDecay:
 

src/main/scala/symsim/concrete/ConcreteSarsa.scala

@@ -13,7 +13,8 @@ case class ConcreteSarsa [
   val gamma: Double,
   val epsilon0: Probability,
   val episodes: Int,
-) extends Sarsa[State, ObservableState, Action, Double, Randomized2],
+) (using val rng: probula.RNG) 
+  extends Sarsa[State, ObservableState, Action, Double, Randomized2],
   ConcreteExactRL[State, ObservableState, Action],
   NoDecay:
 

src/main/scala/symsim/concrete/Randomized2.scala

@@ -95,7 +95,7 @@ object Randomized2:
     /** Perform an imperative operation that depends on one sample from this
      *  Randomized.  This is mostly meant for IO at this point.
      */
-    def run (f: A => Unit): Unit = f(self.sample ())
+    def run (f: A => Unit) (using RNG): Unit = f(self.sample ())
 
     def filter (p: A => Boolean): Randomized2[A] = 
       self.filter (p)

src/main/scala/symsim/examples/concrete/simplebandit/Bandit.scala

@@ -59,7 +59,7 @@ class BanditInstances (banditReward: List [Randomized2[BanditReward]]) (using pr
   extends AgentConstraints[BanditState, BanditState, BanditAction, BanditReward, Randomized2]:
 
     given enumAction: BoundedEnumerable[BanditAction] = 
-      BoundedEnumerableFromList (List.range(0, banditReward.size)*)
+      BoundedEnumerableFromList (List.range (0, banditReward.size)*)
 
     given enumState: BoundedEnumerable[BanditState] =
       BoundedEnumerableFromList (false, true)

src/test/scala/symsim/ExperimentSpec.scala

@@ -10,8 +10,6 @@ import symsim.concrete.Randomized2
 import cats.syntax.all.*
 import symsim.concrete.Randomized2.*
 
-given spire.random.rng.SecureJava = 
-  spire.random.rng.SecureJava.apply
 
 trait ExperimentSpec[State, ObservableState, Action]
   extends org.scalatest.freespec.AnyFreeSpec,
@@ -70,12 +68,13 @@ trait ExperimentSpec[State, ObservableState, Action]
     policies: List[setup.Policy], 
     initials: Option[Randomized2[State]] = None,
     noOfEpisodes: Int = 5
-  ):  EvaluationResults = 
+  ) (using probula.RNG):  EvaluationResults = 
     val ss: Randomized2[State] = initials.getOrElse (setup.agent.initialize)
     for p <- policies
         episodeRewards: Randomized2[Randomized2[Double]] = 
           setup.evaluate (p, ss)
-        rewards: Randomized2[Double] = episodeRewards.map { e => e.sample () }
+        rewards: Randomized2[Double] = 
+          episodeRewards.map { e => e.sample () }
     yield rewards.sample (noOfEpisodes).toList  
 
 

src/test/scala/symsim/concrete/BdlConcreteExpectedSarsaIsExpectedSarsa.scala

@@ -5,6 +5,8 @@ import symsim.examples.concrete.mountaincar.MountainCar
 
 private val mountainCar = 
   new MountainCar (using spire.random.rng.SecureJava.apply)
+private given spire.random.rng.SecureJava = 
+  spire.random.rng.SecureJava.apply
 
 import mountainCar.instances.given
 

src/test/scala/symsim/examples/concrete/braking/CarIsAgentSpec.scala

@@ -4,8 +4,12 @@ package examples.concrete.braking
 import laws.AgentLaws
 import laws.EpisodicLaws
 
+private given spire.random.rng.SecureJava = 
+  spire.random.rng.SecureJava.apply
+private val car = new Car 
+
 class CarIsAgentSpec
   extends SymSimSpec:
 
-  checkAll ("concrete.braking.Car is an Agent", AgentLaws (new Car).laws)
-  checkAll ("concrete.braking.Car is Episodic", EpisodicLaws (new Car).laws)
+  checkAll ("concrete.braking.Car is an Agent", AgentLaws (car).laws)
+  checkAll ("concrete.braking.Car is Episodic", EpisodicLaws (car).laws)

src/test/scala/symsim/examples/concrete/cartpole/Experiments.scala

@@ -1,9 +1,9 @@
 package symsim
 package examples.concrete.cartpole
 
-// Import evidence that states and actions can be enumerated
-private val cartPole = 
-  new CartPole (using spire.random.rng.SecureJava.apply)
+private given spire.random.rng.SecureJava = 
+  spire.random.rng.SecureJava.apply
+private val cartPole: CartPole = new CartPole 
 import cartPole.instances.{enumAction, enumState}
 
 class Experiments extends 

src/test/scala/symsim/examples/concrete/cliffwalking/Experiments.scala

@@ -1,8 +1,10 @@
 package symsim
 package examples.concrete.cliffWalking
 
-private val cliffWalking = 
-  new CliffWalking (using spire.random.rng.SecureJava.apply)
+
+private given spire.random.rng.SecureJava = 
+  spire.random.rng.SecureJava.apply
+private val cliffWalking: CliffWalking = new CliffWalking 
 import cliffWalking.instances.{enumAction, enumState}
 
 class Experiments

src/test/scala/symsim/examples/concrete/mountaincar/Experiments.scala

@@ -1,8 +1,10 @@
 package symsim
 package examples.concrete.mountaincar
 
-private val mountainCar = 
-  new MountainCar (using spire.random.rng.SecureJava.apply)
+
+private given spire.random.rng.SecureJava = 
+  spire.random.rng.SecureJava.apply
+private val mountainCar: MountainCar = new MountainCar 
 import mountainCar.instances.{enumAction, enumState}
 
 class Experiments

src/test/scala/symsim/examples/concrete/pumping/Experiments.scala

@@ -1,7 +1,10 @@
 package symsim
 package examples.concrete.pumping
 
-private val pump = new Pump (using spire.random.rng.SecureJava.apply)
+
+private given spire.random.rng.SecureJava = 
+  spire.random.rng.SecureJava.apply
+private val pump: Pump = new Pump
 
 class Experiments
   extends ExperimentSpec[PumpState, ObservablePumpState, PumpAction]:

src/test/scala/symsim/examples/concrete/simplebandit/Experiments.scala

@@ -1,6 +1,9 @@
 package symsim
 package examples.concrete.simplebandit
 
+private given spire.random.rng.SecureJava = 
+  spire.random.rng.SecureJava.apply
+
 class Experiments
   extends ExperimentSpec[BanditState,BanditState,BanditAction]:
 

src/test/scala/symsim/examples/concrete/simplemaze/SarsaExperiments.scala

@@ -1,7 +1,7 @@
 package symsim
 package examples.concrete.simplemaze
 
-given spire.random.rng.SecureJava = 
+private given spire.random.rng.SecureJava = 
   spire.random.rng.SecureJava.apply
 
 private val maze = new Maze

src/test/scala/symsim/examples/concrete/windygrid/WindyGridSpec.scala

@@ -10,7 +10,8 @@ import symsim.concrete.ConcreteSarsa
 import symsim.concrete.Randomized2
 import symsim.concrete.Randomized2.given
 
-given spire.random.rng.SecureJava = spire.random.rng.SecureJava.apply
+private given spire.random.rng.SecureJava = 
+  spire.random.rng.SecureJava.apply
 
 private val windyGrid = new WindyGrid