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Visualization.scala
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package porcEpic
import scala.reflect.ClassTag
import io.circe._
import io.circe.syntax._
import io.circe.generic.semiauto._
import java.nio.file._
import java.io.File
object HistoryElement {
implicit val clientIdEncoder: Encoder[ClientId] = Encoder.encodeInt.contramap(ClientId.toInt)
implicit val timeEncoder: Encoder[Time] = Encoder.encodeLong.contramap(Time.toLong)
implicit val historyElementEncoder: Encoder[HistoryElement] = deriveEncoder
def apply[I, O](
operation: Operation[I, O],
describe: Operation[I, O] => String,
): HistoryElement =
new HistoryElement(
ClientId = operation.clientId,
Start = operation.invocation,
End = operation.response,
Description = describe(operation)
)
}
case class HistoryElement(
ClientId: ClientId,
Start: Time,
End: Time,
Description: String
)
object LinearizationStep {
implicit val operationIdEncoder: Encoder[OperationId] = Encoder.encodeInt.contramap(OperationId.toInt)
implicit val linearizationStepEncoder: Encoder[LinearizationStep] = deriveEncoder
}
case class LinearizationStep(
Index: OperationId,
StateDescription: String
)
object PartitionVisualizationData {
implicit val partitionVisualizationDataEncoder: Encoder[PartitionVisualizationData] = deriveEncoder
}
case class PartitionVisualizationData(
History: List[HistoryElement],
PartialLinearizations: List[List[LinearizationStep]],
LargestIndex: Map[Int, Int]
)
type VisualizationData = List[PartitionVisualizationData]
extension (data: List[PartitionVisualizationData]) {
def save(): File = {
val dir = Files.createTempDirectory("porc-epic").toAbsolutePath
val json = data.asJson.spaces2
Files.writeString(dir.resolve("data.js"), s"const data = $json")
def copyResource(filename: String): Unit = {
val input = getClass.getResourceAsStream(s"/visualization/$filename")
try Files.copy(input, dir.resolve(filename))
finally input.close()
}
List(
"app.js",
"style.css",
"visualization.html"
).foreach(copyResource)
dir.toFile
}
}
given timeOrdering: Ordering[Time] = Ordering.by(Time.toLong)
extension [S, I, O](specification: Specification[S, I, O])(using ci: ClassTag[I], co: ClassTag[O]) {
def visualize(
info: LinearizationInfo[I, O],
path: String
): Unit = {}
def visualize(
info: LinearizationInfo[I, O],
describeOperation: Operation[I, O] => String,
describeState: S => String,
): VisualizationData = {
info.history.zipWithIndex.map { (partition, i) =>
val n = partition.length / 2
val callValue = Array.ofDim[I](n)
val returnValue = Array.ofDim[O](n)
val operations = Entry.toOperations(partition)
val history =
operations
.map(operation => HistoryElement(operation, describeOperation))
.sortBy(element => (element.Start, element.End))
operations.foreach { operation =>
callValue(OperationId.toInt(operation.id)) = operation.input
returnValue(OperationId.toInt(operation.id)) = operation.output
}
val largestIndex = scala.collection.mutable.Map.empty[Int, Int]
val largestSize = Array.ofDim[Int](n)
val partialLinearizations =
info.partialLinearizations(i).sortBy(_.length).zipWithIndex.map{ (partial, i) =>
val linearization = Array.ofDim[LinearizationStep](partial.length)
var state = specification.initialState
partial.zipWithIndex.foreach { (histId, j) =>
val (isLinearizable, nextState) =
specification.apply(
state = state,
input = callValue(OperationId.toInt(histId)),
output = returnValue(OperationId.toInt(histId))
)
state = nextState
if (!isLinearizable) {
throw new Exception("valid partial linearization returned non-ok result from model step")
}
linearization(j) = LinearizationStep(
Index = histId,
StateDescription = describeState(state)
)
if (largestSize(OperationId.toInt(histId)) < partial.length) {
largestSize(OperationId.toInt(histId)) = partial.length
largestIndex(OperationId.toInt(histId)) = i
}
}
linearization.toList
}
PartitionVisualizationData(
History = history,
PartialLinearizations = partialLinearizations,
LargestIndex = largestIndex.toMap
)
}
}
}