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Re domain specific module (#62)
* setup domain specific module * . * . * . * fix boolean suite * int array mean and var * update variance to accept different modes * . * DRY a little * scenarios * fmt * . * . * . * . * start reporting * . * fixy * . * . * . * . * . * . * welfords algorithm * . * . * . * . * . * Add BegBin * . * . * pareto plot * . * . * . * [autofix.ci] apply automated fixes * . * . * . * [autofix.ci] apply automated fixes * . * . * scenarr is now a monoid * [autofix.ci] apply automated fixes * oep * . * . * [autofix.ci] apply automated fixes * fix * . * . * . * . * . * . * poisson * . * . * . * . * stats * . * . * [autofix.ci] apply automated fixes * . * . * . * . * [autofix.ci] apply automated fixes * . * . * [autofix.ci] apply automated fixes * . --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
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‎.github/copilot-instructions.md‎

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@@ -45,6 +45,17 @@ vecxt/
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│ ├── src-jvm/ # JVM-specific tests
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│ ├── src-js/ # Js-specific tests
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│ └── src-native/ # Scala Native-specific tests
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├── vecxt_re/ # Domain specific library for reinsurance calculations
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│ ├── src/ # Cross-platform shared source code
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│ ├── src-jvm/ # JVM-specific implementations (SIMD Vector API)
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│ ├── src-js/ # JavaScript-specific implementations
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│ ├── src-js-native/ # JavaScript / native shared (DRY) implementations
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│ ├── src-native/ # Scala Native-specific implementations
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│ └── test/ # Cross-platform test suite (munit)
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│ ├── src/ # Shared test source files
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│ ├── src-jvm/ # JVM-specific tests
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│ ├── src-js/ # Js-specific tests
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│ └── src-native/ # Scala Native-specific tests
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├── vecxt/ # Main source directory and core published module
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│ ├── src/ # Cross-platform shared source code
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│ ├── src-jvm/ # JVM-specific implementations (SIMD Vector API)
@@ -81,4 +92,8 @@ Follow styleguide.md for coding conventions
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Use inline methods where possible to avoid dispatch overhead where possible.
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## GitHub Actions CI
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The project uses GitHub Actions for CI/CD
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The project uses GitHub Actions for CI/CD
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## Vecxt Re
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Contains a bunch of domain specific code for reinsurance calculations, structures, and various reinsurance contract types. It will often rely on Vecxt. You should view the principles as the same - correctness above all else - performance matters. It also aims to eexpose a consistent cross platform API.

‎.github/workflows/autofix.yml‎

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name: 'autofix.ci'
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on:
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pull_request:
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jobs:
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autofix:
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if: github.event.pull_request.draft == false
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-java@v4
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with:
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distribution: 'temurin'
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java-version: 25
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- name: Run autoformat
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run: ./mill mill.scalalib.scalafmt.ScalafmtModule/reformatAll __.sources
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- uses: autofix-ci/action@ff86a557419858bb967097bfc916833f5647fa8c

‎.github/workflows/ci.yml‎

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- name: Test
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run: ./mill vecxtensions.${{ matrix.project }}.test
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- name: Test
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run: ./mill vecxt_re.${{ matrix.project }}.test
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- name: Laws Test
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if: matrix.project == 'jvm'
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run: ./mill laws.${{ matrix.project }}.test

‎.gitignore‎

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biases1.csv
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biases2.csv
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.DS_Store
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.venv/
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experiments/src/bhd.scala

‎.vscode/launch.json‎

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{
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// Use IntelliSense to learn about possible attributes.
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// Hover to view descriptions of existing attributes.
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// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
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"version": "0.2.0",
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"configurations": [
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{
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"type": "scala",
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"request": "launch",
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"name": "test Suite",
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"buildTarget": "vecxt.jvm.test",
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"testClass": "vecxt.LongArraysSuite",
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"jvmOptions": [
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"--add-modules=jdk.incubator.vector"
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],
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"args": [
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"-oD"
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]
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"name": "plotIndex",
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"mainClass": "experiments.plotIndex",
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"buildTarget": "file:///Users/simon/Code/vecxt/experiments",
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"args": [],
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"jvmOptions": [],
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"env": {}
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},
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{
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"type": "scala",
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"request": "launch",
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"name": "debug test",
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"buildTarget": "vecxt.jvm.test",
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"testClass": "vecxt.MatrixAdditionTest",
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"jvmOptions": [
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"--add-modules=jdk.incubator.vector"
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],
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"args": [
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"-oD"
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],
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"env": {},
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"internalConsoleOptions": "openOnSessionStart",
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"preLaunchTask": "",
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"postDebugTask": ""
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"name": "readXl",
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"mainClass": "experiments.readXl",
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"buildTarget": "file:///Users/simon/Code/vecxt/experiments",
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"args": [],
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"jvmOptions": [],
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"env": {}
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},
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{
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"type": "scala",
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"request": "attach",
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"name": "Attach debugger",
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// name of the module that is being debugging
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"buildTarget": "vecxt.jvm.test",
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// Host of the jvm to connect to
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"hostName": "localhost",
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// Port to connect to
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"port": 5005
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"request": "launch",
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"name": "pricingFun",
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"mainClass": "experiments.pricingFun",
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"buildTarget": "file:///Users/simon/Code/vecxt/experiments",
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"args": [],
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"jvmOptions": [],
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"env": {}
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}
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]
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}

‎.vscode/mcp.json‎

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{
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"servers": {
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"vecxt-metals": {
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"url": "http://localhost:51891/sse",
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"type": "sse"
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"url": "http://localhost:51891/mcp",
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"type": "http"
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}
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}
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}

‎.vscode/tasks.json‎

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{
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"label": "compiledClassesAndSemanticDbFiles",
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"type": "shell",
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"command": "./mill __.compiledClassesAndSemanticDbFiles",
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"command": "./mill __.jvm.compiledClassesAndSemanticDbFiles",
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"runOptions": {
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"runOn": "folderOpen"
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},

‎benchmark/package.mill‎

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def scalaVersion = build.vecxt.jvm.scalaVersion
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def jmhCoreVersion = "1.37"
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override def forkArgs: T[Seq[String]] = super.forkArgs() ++ build.vecIncubatorFlag
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override def moduleDeps: Seq[JavaModule] = Seq(build.vecxt.jvm, build.vecxtensions.jvm)
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override def moduleDeps: Seq[JavaModule] = Seq(build.vecxt.jvm, build.vecxtensions.jvm, build.vecxt_re.jvm)
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def enableBsp = false
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// override def generateBenchmarkSources = T{

‎benchmark/src/LossReportBenchmark.scala‎

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package vecxt.benchmark
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import org.openjdk.jmh.annotations.*
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import org.openjdk.jmh.infra.Blackhole
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import scala.compiletime.uninitialized
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import scala.util.Random
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import vecxt_re.*
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import vecxt_re.ReReporting.*
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import vecxt.all.*
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// ./mill benchmark.runJmh "vecxt.benchmark.LossReportBenchmark" -jvmArgs --add-modules=jdk.incubator.vector -rf json -wi 1 -i 3 -f 1
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/** 231] Benchmark (numEventsStr) (numIterationsStr) Mode Cnt Score Error Units 231] LossReportBenchmark.lossReport_fast
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* 10000 100 thrpt 3 177346.981 ± 24137.324 ops/s 231] LossReportBenchmark.lossReport_fast 10000 1000 thrpt 3
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* 180400.504 ± 8719.687 ops/s 231] LossReportBenchmark.lossReport_fast 100000 100 thrpt 3 11731.510 ± 1945.957 ops/s
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* 231] LossReportBenchmark.lossReport_fast 100000 1000 thrpt 3 17443.246 ± 425.030 ops/s 231]
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* LossReportBenchmark.lossReport_separate 10000 100 thrpt 3 46850.187 ± 7232.734 ops/s 231]
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* LossReportBenchmark.lossReport_separate 10000 1000 thrpt 3 49876.719 ± 5238.487 ops/s 231]
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* LossReportBenchmark.lossReport_separate 100000 100 thrpt 3 3360.234 ± 326.993 ops/s 231]
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* LossReportBenchmark.lossReport_separate 100000 1000 thrpt 3 4706.819 ± 615.832 ops/s
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*/
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@State(Scope.Thread)
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class LossReportBenchmark extends BLASBenchmark:
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@Param(Array("10000", "100000"))
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var numEventsStr: String = uninitialized
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@Param(Array("100", "1000"))
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var numIterationsStr: String = uninitialized
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var years: Array[Int] = uninitialized
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var ceded: Array[Double] = uninitialized
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var layerObj: Layer = uninitialized
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@Setup(Level.Trial)
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def setup: Unit =
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val rng = new Random(0)
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val numEvents = numEventsStr.toInt
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val numIterations = numIterationsStr.toInt
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val yrs = Array.ofDim[Int](numEvents)
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var i = 0
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while i < numEvents do
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yrs(i) = rng.nextInt(numIterations) + 1 // 1-based group indices
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i += 1
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end while
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java.util.Arrays.sort(yrs)
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years = yrs
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ceded = Array.ofDim[Double](numEvents)
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i = 0
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while i < numEvents do
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// random loss values between 0 and 100
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ceded(i) = rng.nextDouble() * 100.0
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i += 1
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end while
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// Choose a layer with a moderate aggLimit to cause some exhaustion hits
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layerObj = Layer(occLimit = Some(100.0), aggLimit = Some(50.0))
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()
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end setup
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@Benchmark
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def lossReport_fast(bh: Blackhole) =
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val calcd = (layerObj, ceded)
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val r = calcd.lossReport(numIterationsStr.toInt, years, ReportDenominator.FirstLimit)
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// consume fields so JMH doesn't optimize away
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bh.consume(r.el)
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bh.consume(r.stdDev)
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bh.consume(r.attachProb)
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bh.consume(r.exhaustProb)
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end lossReport_fast
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@Benchmark
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def lossReport_separate(bh: Blackhole) =
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val calcd = (layerObj, ceded)
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val n = numIterationsStr.toInt
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val reportLimit = ReportDenominator.FirstLimit.fromlayer(layerObj)
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val el = calcd.expectedLoss(n) / reportLimit
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val std = calcd.std(n, years) / reportLimit
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val attach = calcd.attachmentProbability(n, years)
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val exhaust = calcd.exhaustionProbability(n, years)
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bh.consume(el)
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bh.consume(std)
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bh.consume(attach)
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bh.consume(exhaust)
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end lossReport_separate
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end LossReportBenchmark

‎benchmark/src/groupOpsBenchmark.scala‎

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import org.openjdk.jmh.infra.Blackhole
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import scala.compiletime.uninitialized
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import vecxtensions.*
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import vecxt_re.*
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import java.util.Random
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import java.util.concurrent.TimeUnit
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// ./mill benchmark.runJmh "vecxt.benchmark.LossReportBenchmark" -jvmArgs --add-modules=jdk.incubator.vector -rf json -wi 1 -i 3 -f 1
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@State(Scope.Thread)
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@BenchmarkMode(Array(Mode.AverageTime))
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@OutputTimeUnit(TimeUnit.NANOSECONDS)
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bh.consume(valuesCopy2)
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end benchGroupDiffInPlace
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@Benchmark
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def benchGroupSum(bh: Blackhole): Unit =
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val (uniqueGroups, sums) = groupSum(groups, values)
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bh.consume(uniqueGroups)
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bh.consume(sums)
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end benchGroupSum
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// @Benchmark
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// def benchGroupSum(bh: Blackhole): Unit =
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// // groupSum in vecxt_re takes nitr; compute number of groups then call it
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// var maxGroup = 0
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// var i = 0
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// while i < groups.length do
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// if groups(i) > maxGroup then maxGroup = groups(i)
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// end if
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// i += 1
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// end while
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// val numGroups = maxGroup + 1
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// val sums = groupSum(groups, values, numGroups)
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// val uniqueGroups = Array.tabulate(numGroups)(identity)
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// bh.consume(uniqueGroups)
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// bh.consume(sums)
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// end benchGroupSum
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end GroupOpsBenchmark

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