Entropy monitor

.jvmopts

@@ -1,4 +1,5 @@
 -XX:+UseG1GC
 -XX:+UseStringDeduplication
--Xmx8G
+-Xms8g
+-Xmx28g
 -Xss4M

.scalafmt.conf

@@ -1,18 +1,20 @@
-version = 2.7.5
-
+version = 3.5.9
 maxColumn = 120
 
-align.arrowEnumeratorGenerator = true
-align.openParenCallSite = true
-align.preset=more
-continuationIndent.defnSite = 4
+style = defaultWithAlign
 danglingParentheses.preset = true
-includeCurlyBraceInSelectChains = false
-newlines.alwaysBeforeTopLevelStatements = true
-newlines.penalizeSingleSelectMultiArgList = false
+indentOperator.preset = "spray"
+align.arrowEnumeratorGenerator = true
+align.openParenCallSite = false
+align.openParenDefnSite = false
+align.tokens = [{code = "="}, {code = "<-"}, {code = ":="}, {code = "->"}, {code = "%"}, {code = "%%"}]
+continuationIndent.callSite = 2
+continuationIndent.defnSite = 2
 optIn.breakChainOnFirstMethodDot = true
-optIn.configStyleArguments = true
+
+spaces {
+  inImportCurlyBraces = true
+}
+
 project.git = true
-rewrite.rules = [ RedundantBraces, RedundantParens, PreferCurlyFors]
-runner.optimizer.forceConfigStyleOnOffset = 120
-runner.optimizer.forceConfigStyleMinArgCount = 3
+runner.dialect = scala213

README.md

@@ -12,7 +12,7 @@ A few aspects differentiate Thylacine from other Bayesian inference frameworks:
 * Framework and design largely de-coupled from Bayesian graphical representations of the problem (more details in the FAQ below)
 * Designed to be multi-threaded from the ground up using a high-performance Software Transactional Memory (STM) implementation to facilitate efficient concurrency across the differing computational profiles for sampling, integration, visualisation, etc.
 * Analytic gradient calculations can be specified on a component level that enables automatic differentiation to be used in gradient calculations. This is essential if aiming to perform high-dimension inference using gradient information.
-* A growing list of advanced algorithms/concepts have already been implementated:
+* A growing list of advanced algorithms/concepts have already been implemented:
   * Gaussian analytic posteriors
   * Optimisation
     * Hooke & Jeeves

build.sbt

@@ -1,25 +1,25 @@
-ThisBuild / baseVersion := "0.5.0"
+ThisBuild / baseVersion := "0.6.0"
 
-ThisBuild / organization := "ai.entrolution"
-ThisBuild / organizationName := "Greg von Nessi"
+ThisBuild / organization      := "ai.entrolution"
+ThisBuild / organizationName  := "Greg von Nessi"
 ThisBuild / publishGithubUser := "gvonness"
-ThisBuild / publishFullName := "Greg von Nessi"
+ThisBuild / publishFullName   := "Greg von Nessi"
 
 ThisBuild / homepage := Some(url("https://github.com/gvonness/thylacine"))
 ThisBuild / scmInfo := Some(
   ScmInfo(url("https://github.com/gvonness/thylacine"), "git@github.com:gvonness/thylacine.git")
 )
 
 ThisBuild / startYear := Some(2020)
-ThisBuild / endYear := Some(2022)
+ThisBuild / endYear   := Some(2022)
 
 ThisBuild / spiewakCiReleaseSnapshots := false
-ThisBuild / spiewakMainBranches := Seq("main")
+ThisBuild / spiewakMainBranches       := Seq("main")
 
 ThisBuild / sonatypeCredentialHost := "s01.oss.sonatype.org"
-ThisBuild / sonatypeRepository := "https://s01.oss.sonatype.org/service/local"
+ThisBuild / sonatypeRepository     := "https://s01.oss.sonatype.org/service/local"
 
-scalaVersion := DependencyVersions.scala2p13Version
+scalaVersion                   := DependencyVersions.scala2p13Version
 ThisBuild / crossScalaVersions := Seq(DependencyVersions.scala2p13Version)
 
 Global / idePackagePrefix := Some("ai.entrolution")

project/Dependencies.scala

@@ -1,9 +1,9 @@
-import sbt._
+import sbt.*
 
 object DependencyVersions {
   val scala2p13Version = "2.13.11"
 
-  val bengalStmVersion           = "0.9.2"
+  val bengalStmVersion           = "0.9.3"
   val bigMathVersion             = "2.3.0"
   val breezeVersion              = "2.1.0"
   val catsEffectVersion          = "3.4.8"
@@ -13,7 +13,7 @@ object DependencyVersions {
 }
 
 object Dependencies {
-  import DependencyVersions._
+  import DependencyVersions.*
 
   private val bengalStm: ModuleID =
     "ai.entrolution" %% "bengal-stm" % bengalStmVersion

project/build.properties

@@ -1 +1 @@
-sbt.version=1.7.1
+sbt.version=1.9.2

src/main/scala/thylacine/config/ConjugateGradientConfig.scala

@@ -18,8 +18,8 @@ package ai.entrolution
 package thylacine.config
 
 case class ConjugateGradientConfig(
-    convergenceThreshold: Double,
-    goldenSectionTolerance: Double,
-    lineProbeExpansionFactor: Double,
-    numberOfResultsToRetain: Int
+  convergenceThreshold: Double,
+  goldenSectionTolerance: Double,
+  lineProbeExpansionFactor: Double,
+  numberOfResultsToRetain: Int
 )

src/main/scala/thylacine/config/CoordinateSlideConfig.scala

@@ -18,8 +18,8 @@ package ai.entrolution
 package thylacine.config
 
 case class CoordinateSlideConfig(
-    convergenceThreshold: Double,
-    goldenSectionTolerance: Double,
-    lineProbeExpansionFactor: Double,
-    numberOfPriorSamplesToSetScale: Option[Int]
+  convergenceThreshold: Double,
+  goldenSectionTolerance: Double,
+  lineProbeExpansionFactor: Double,
+  numberOfPriorSamplesToSetScale: Option[Int]
 )

src/main/scala/thylacine/config/HmcmcConfig.scala

@@ -18,9 +18,9 @@ package ai.entrolution
 package thylacine.config
 
 case class HmcmcConfig(
-    stepsBetweenSamples: Int,
-    stepsInDynamicsSimulation: Int,
-    warmupStepCount: Int,
-    dynamicsSimulationStepSize: Double,
-    sampleParallelism: Option[Int]
+  stepsBetweenSamples: Int,
+  stepsInDynamicsSimulation: Int,
+  warmupStepCount: Int,
+  dynamicsSimulationStepSize: Double,
+  sampleParallelism: Option[Int]
 )

src/main/scala/thylacine/config/HookeAndJeevesConfig.scala

@@ -18,6 +18,6 @@ package ai.entrolution
 package thylacine.config
 
 case class HookeAndJeevesConfig(
-    convergenceThreshold: Double,
-    numberOfPriorSamplesToSetScale: Option[Int]
+  convergenceThreshold: Double,
+  numberOfPriorSamplesToSetScale: Option[Int]
 )

src/main/scala/thylacine/config/LeapfrogMcmcConfig.scala

@@ -18,7 +18,7 @@ package ai.entrolution
 package thylacine.config
 
 case class LeapfrogMcmcConfig(
-    stepsBetweenSamples: Int,
-    warmupStepCount: Int,
-    samplePoolSize: Int
+  stepsBetweenSamples: Int,
+  warmupStepCount: Int,
+  samplePoolSize: Int
 )

src/main/scala/thylacine/config/MdsConfig.scala

@@ -18,8 +18,8 @@ package ai.entrolution
 package thylacine.config
 
 case class MdsConfig(
-    convergenceThreshold: Double,
-    expansionMultiplier: Double,
-    contractionMultiplier: Double,
-    numberOfPriorSamplesToSetStartingPoint: Option[Int]
+  convergenceThreshold: Double,
+  expansionMultiplier: Double,
+  contractionMultiplier: Double,
+  numberOfPriorSamplesToSetStartingPoint: Option[Int]
 )

src/main/scala/thylacine/config/SlqConfig.scala

@@ -18,11 +18,11 @@ package ai.entrolution
 package thylacine.config
 
 case class SlqConfig(
-    poolSize: Int,
-    abscissaNumber: Int,
-    domainScalingIncrement: Double,
-    targetAcceptanceProbability: Double,
-    sampleParallelism: Int,
-    maxIterationCount: Int,
-    minIterationCount: Int
+  poolSize: Int,
+  abscissaNumber: Int,
+  domainScalingIncrement: Double,
+  targetAcceptanceProbability: Double,
+  sampleParallelism: Int,
+  maxIterationCount: Int,
+  minIterationCount: Int
 )

src/main/scala/thylacine/model/components/forwardmodel/ForwardModel.scala

@@ -28,7 +28,7 @@ private[thylacine] trait ForwardModel[F[_]] extends GenericMapping with CanValid
   // Note that input validation should be done within
   // the surrounding likelihood
   private[thylacine] def evalAt(
-      input: IndexedVectorCollection
+    input: IndexedVectorCollection
   ): F[VectorContainer]
 
   private[thylacine] final def evalAt(input: Map[String, Vector[Double]]): F[Vector[Double]] =
@@ -37,7 +37,7 @@ private[thylacine] trait ForwardModel[F[_]] extends GenericMapping with CanValid
   // Note that input validation should be done within
   // the surrounding likelihood
   private[thylacine] def jacobianAt(
-      input: IndexedVectorCollection
+    input: IndexedVectorCollection
   ): F[IndexedMatrixCollection]
 
   private[thylacine] final def jacobianAt(input: Map[String, Vector[Double]]): F[Map[String, Vector[Vector[Double]]]] =

src/main/scala/thylacine/model/components/forwardmodel/InMemoryMemoizedForwardModel.scala

@@ -20,7 +20,7 @@ package thylacine.model.components.forwardmodel
 import thylacine.model.core.StmImplicits
 import thylacine.model.core.computation.CachedComputation
 import thylacine.model.core.values.IndexedVectorCollection.ModelParameterCollection
-import thylacine.model.core.values.{IndexedMatrixCollection, VectorContainer}
+import thylacine.model.core.values.{ IndexedMatrixCollection, VectorContainer }
 
 private[thylacine] trait InMemoryMemoizedForwardModel[F[_]] extends ForwardModel[F] {
   this: StmImplicits[F] =>
@@ -29,12 +29,12 @@ private[thylacine] trait InMemoryMemoizedForwardModel[F[_]] extends ForwardModel
   protected val jacobianCache: CachedComputation[F, IndexedMatrixCollection]
 
   private[thylacine] override final def evalAt(
-      input: ModelParameterCollection
+    input: ModelParameterCollection
   ): F[VectorContainer] =
     evalCache.performComputation(input)
 
   private[thylacine] override def jacobianAt(
-      input: ModelParameterCollection
+    input: ModelParameterCollection
   ): F[IndexedMatrixCollection] =
     jacobianCache.performComputation(input)
 }

src/main/scala/thylacine/model/components/forwardmodel/LinearForwardModel.scala

@@ -24,7 +24,7 @@ import thylacine.model.core.computation.CachedComputation
 import thylacine.model.core.values._
 import thylacine.model.core.values.modelparameters.ModelParameterContext
 
-import breeze.linalg.{DenseMatrix, DenseVector}
+import breeze.linalg.{ DenseMatrix, DenseVector }
 import cats.effect.kernel.Async
 import cats.syntax.all._
 
@@ -33,13 +33,13 @@ import scala.annotation.unused
 // A linear forward model may work across more than
 // one model parameter generator
 case class LinearForwardModel[F[_]: STM: Async](
-    protected override val evalCache: CachedComputation[F, VectorContainer],
-    protected override val jacobianCache: CachedComputation[F, IndexedMatrixCollection],
-    private[thylacine] val transform: IndexedMatrixCollection,
-    private[thylacine] val vectorOffset: Option[VectorContainer],
-    override val domainDimension: Int,
-    override val rangeDimension: Int,
-    private[thylacine] override val validated: Boolean = false
+  protected override val evalCache: CachedComputation[F, VectorContainer],
+  protected override val jacobianCache: CachedComputation[F, IndexedMatrixCollection],
+  private[thylacine] val transform: IndexedMatrixCollection,
+  private[thylacine] val vectorOffset: Option[VectorContainer],
+  override val domainDimension: Int,
+  override val rangeDimension: Int,
+  private[thylacine] override val validated: Boolean = false
 ) extends StmImplicits[F]
     with InMemoryMemoizedForwardModel[F] {
   if (!validated) {
@@ -54,9 +54,9 @@ case class LinearForwardModel[F[_]: STM: Async](
       this
     } else {
       this.copy(
-        transform = transform.getValidated,
+        transform    = transform.getValidated,
         vectorOffset = vectorOffset.map(_.getValidated),
-        validated = true
+        validated    = true
       )
     }
 
@@ -66,17 +66,17 @@ case class LinearForwardModel[F[_]: STM: Async](
     transform
 
   private[thylacine] override def jacobianAt(
-      input: IndexedVectorCollection
+    input: IndexedVectorCollection
   ): F[IndexedMatrixCollection] =
     Async[F].pure(getJacobian)
 }
 
 object LinearForwardModel {
 
   def of[F[_]: STM: Async](
-      transform: IndexedMatrixCollection,
-      vectorOffset: Option[VectorContainer],
-      evalCacheDepth: Option[Int]
+    transform: IndexedMatrixCollection,
+    vectorOffset: Option[VectorContainer],
+    evalCacheDepth: Option[Int]
   ): F[LinearForwardModel[F]] = {
     val rangeDimension: Int =
       transform.index.head._2.rowTotalNumber
@@ -109,7 +109,7 @@ object LinearForwardModel {
     }
 
     def transformedEval(
-        input: IndexedVectorCollection
+      input: IndexedVectorCollection
     ): VectorContainer =
       VectorContainer(applyOffset(rawMatrixTransform * rawMappings.modelParameterCollectionToRawVector(input)))
 
@@ -125,37 +125,37 @@ object LinearForwardModel {
 
   @unused
   private[thylacine] def of[F[_]: STM: Async](
-      identifier: ModelParameterIdentifier,
-      values: Vector[Vector[Double]],
-      evalCacheDepth: Option[Int]
+    identifier: ModelParameterIdentifier,
+    values: Vector[Vector[Double]],
+    evalCacheDepth: Option[Int]
   ): F[LinearForwardModel[F]] =
     of[F](
-      transform = IndexedMatrixCollection(identifier, values),
-      vectorOffset = None,
+      transform      = IndexedMatrixCollection(identifier, values),
+      vectorOffset   = None,
       evalCacheDepth = evalCacheDepth
     )
 
   def of[F[_]: STM: Async](
-      label: String,
-      values: Vector[Vector[Double]],
-      evalCacheDepth: Option[Int]
+    label: String,
+    values: Vector[Vector[Double]],
+    evalCacheDepth: Option[Int]
   ): F[LinearForwardModel[F]] =
     of[F](
-      transform = IndexedMatrixCollection(ModelParameterIdentifier(label), values),
-      vectorOffset = None,
+      transform      = IndexedMatrixCollection(ModelParameterIdentifier(label), values),
+      vectorOffset   = None,
       evalCacheDepth = evalCacheDepth
     )
 
   @unused
   def identityOf[F[_]: STM: Async](
-      label: String,
-      dimension: Int,
-      evalCacheDepth: Option[Int]
+    label: String,
+    dimension: Int,
+    evalCacheDepth: Option[Int]
   ): F[LinearForwardModel[F]] =
     of[F](
       transform = IndexedMatrixCollection
         .squareIdentity(ModelParameterIdentifier(label), dimension),
-      vectorOffset = None,
+      vectorOffset   = None,
       evalCacheDepth = evalCacheDepth
     )
 }