PassiveTreeParser.kt

// parses a v3 PSG file
object PassiveTreeParser {

    fun readData(inputStream: InputStream): SkillTreeGraph {
        val data = DataTypeReader(inputStream, order = ByteOrder.LITTLE_ENDIAN).readPassiveTreeData()
        val remainingBytes = inputStream.readAllBytes()
        require(remainingBytes.isEmpty()) { "$remainingBytes bytes were not processed" }

        return data
    }

    private fun DataTypeReader.readPassiveTreeData(): SkillTreeGraph =
        when (val version = readByte().toInt()) {
            3 -> V3Decoder.decode(this)
            else -> throw UnsupportedOperationException("Missing decoder for version $version")
        }

    private object V3Decoder {
        fun decode(reader: DataTypeReader): SkillTreeGraph = with(reader) {
            val type = readByte()
            val orbitCount = readByte()
            val orbits = (0 until orbitCount).map { readByte().toUByte() }
            val rootNodeCount = readInt()
            val rootNodeIds = (0 until rootNodeCount).map { readInt().also { skip(4) } }
            val nodeGroupCount = readInt()
            val nodeGroups = (0 until nodeGroupCount).map { readNodeGroup() }

            return SkillTreeGraph(
                version = 3,
                type = type.toInt(),
                orbits = orbits.map { it.toInt() },
                rootIds = rootNodeIds,
                groups = nodeGroups,
            )
        }

        private fun DataTypeReader.readNodeGroup(): SkillTreeGraph.Group {
            val x = readFloat()
            val y = readFloat()
            val groupAssociationKey = readInt()
            val groupBackgroundOverride = readInt()
            val isJewelPositionReference = readByte().toInt() != 0
            val nodeCount = readInt()
            val nodes = (0 until nodeCount).map { readNode() }

            return SkillTreeGraph.Group(
                location = x to y,
                groupAssociationKey = groupAssociationKey,
                groupBackgroundOverride = groupBackgroundOverride,
                isJewelPositionReference = isJewelPositionReference,
                nodes = nodes,
            )
        }

        private fun DataTypeReader.readNode(): SkillTreeGraph.NodeRef {
            val id = readInt()
            val radius = readInt()
            val position = readInt()
            val connectionCount = readInt()
            val nodeConnections = (0 until connectionCount).map { readConnection() }

            return SkillTreeGraph.NodeRef(
                id = id,
                orbit = radius,
                orbitIndex = position,
                connectedNodeIds = nodeConnections,
            )
        }

        private fun DataTypeReader.readConnection(): SkillTreeGraph.ConnectionRef {
            val nodeId = readInt()
            val orbit = readInt()

            return SkillTreeGraph.ConnectionRef(
                nodeId = nodeId,
                orbit = orbit,
            )
        }
    }
}

SkillTreeGraph.kt

data class SkillTreeGraph(
    val version: Int,
    val type: Int,
    val orbits: List<Int>,
    val rootIds: List<Int>,
    val groups: List<Group>,
) {
    data class Group(
        val location: Pair<Float, Float>,
        val groupAssociationKey: Int,
        val groupBackgroundOverride: Int,
        val isJewelPositionReference: Boolean,
        val nodes: List<NodeRef>,
    )

    data class NodeRef(
        val id: Int,
        val orbit: Int,
        val orbitIndex: Int,
        val connectedNodeIds: List<ConnectionRef>,
    )

    data class ConnectionRef(
        val nodeId: Int,
        val orbit: Int,
    )
}

@jrobinson3k1 I started digging into these binaries because I wanted to build a dependency graph, for calculation purposes. But I did end up cobbling a quick visualization for the x,y coords, and it does look a bit wonky, but maybe it is just the code that chatgpt wrote that is wrong idk.

Now that I have all the attribute data, names, icons, dependencies/relationships of the skills ... I can see the whole picture of how to make a script that will find "optimal" builds given different constraints. My worry was that hard-coding all the data manually would quickly become out-of-sync with the actual game, which is why I wanted to read it directly from the game files instead.

And I already had the datc64 decoded, there are several places that have the "schema" for each of the files available. Noted the graph_id column in that database, which is why I wanted to read the psg.