NanoBrain-unitypackage/Editor/Dag.cs

using System.Collections.Generic;
using System.Linq;
using UnityEngine;
using UnityEditor;

namespace NanoBrain.Unity {
    public class Dag {

        public class Node {
            public int id;
            public Vector2 position;
            public float radius = 20f; // circle radius
            public Nucleus nucleus;
        }

        public class Edge {
            public int fromId;
            public int toId;
        }

        public List<Node> nodes = new();
        public List<Edge> edges = new();

        public Node FindNode(string name, bool justBaseName = true) {
            if (justBaseName) {
                int colonPos = name.IndexOf(":");
                if (colonPos > 0)
                    name = name[..colonPos];
            }
            foreach (Node node in this.nodes) {
                string nodeName = node.nucleus.name;
                if (justBaseName) {
                    int colonPos = nodeName.IndexOf(":");
                    if (colonPos > 0)
                        nodeName = nodeName[..colonPos];
                }
                if (nodeName == name)
                    return node;
            }
            return null;
        }

        public static Node GetNodeById(Dag dag, int id) => dag.nodes.FirstOrDefault(x => x.id == id);

        public static void ComputeLayout(Dag dag) {
            Dictionary<int, List<int>> adjacency = dag.nodes.ToDictionary(n => n.id, n => new List<int>());
            Dictionary<int, int> outdegree = dag.nodes.ToDictionary(node => node.id, n => 0);
            foreach (Edge edge in dag.edges) {
                if (!adjacency.ContainsKey(edge.fromId) || !adjacency.ContainsKey(edge.toId))
                    continue;
                adjacency[edge.fromId].Add(edge.toId);
                outdegree[edge.fromId]++;
            }

            // Kahn's algorithm to compute topological layers (horizontal layers)
            // build parent list (reverse adjacency) and parentIndegree = number of children each parent has
            Dictionary<int, List<int>> parents = dag.nodes.ToDictionary(n => n.id, _ => new List<int>());
            Dictionary<int, int> childCount = dag.nodes.ToDictionary(n => n.id, _ => 0);

            foreach (Edge edge in dag.edges) {
                if (!adjacency.ContainsKey(edge.fromId) || !adjacency.ContainsKey(edge.toId)) continue;
                adjacency[edge.fromId].Add(edge.toId);
                parents[edge.toId].Add(edge.fromId);   // parent of 'to' is 'from'
                childCount[edge.fromId]++;              // outdegree
            }

            Dictionary<int, int> column = new();
            Queue<int> queue = new(outdegree.Where(keyValue => keyValue.Value == 0).Select(keyValue => keyValue.Key));
            foreach (int id in queue)
                column[id] = 0;

            // process parents (reverse traversal)
            while (queue.Count > 0) {
                int nodeId = queue.Dequeue();
                int col = column[nodeId];
                foreach (int parentIx in parents[nodeId]) {
                    if (!column.ContainsKey(parentIx) || column[parentIx] < col + 1)
                        column[parentIx] = col + 1;
                    childCount[parentIx]--;               // decrement remaining unprocessed children
                    if (childCount[parentIx] == 0)
                        queue.Enqueue(parentIx);
                }
            }

            // Any unreachable nodes -> assign next layers
            int maxColumn = column.Count > 0 ? column.Values.Max() : 0;
            foreach (Node node in dag.nodes) {
                if (!column.ContainsKey(node.id)) {
                    maxColumn++;
                    column[node.id] = maxColumn;
                }
            }

            // Group nodes by column (left to right)
            List<List<int>> columns =
                column.
                GroupBy(kv => kv.Value).
                OrderBy(g => g.Key).
                Select(g => g.Select(x => x.Key).ToList()).
                ToList();

            // Same code without using Linq
            // Build layers dictionary: layerIndex -> List<int> nodeIds
            // Dictionary<int, List<int>> layersDict = new();
            // foreach (KeyValuePair<int, int> kv in layer) {
            //     int nodeId = kv.Key;
            //     int layerIndex = kv.Value;
            //     if (!layersDict.TryGetValue(layerIndex, out List<int> list)) {
            //         list = new List<int>();
            //         layersDict[layerIndex] = list;
            //     }
            //     list.Add(nodeId);
            // }

            // // Determine sorted layer indices
            // List<int> layerIndices = new(layersDict.Keys);
            // layerIndices.Sort(); // ascending order

            // // Build final List<List<int>> in sorted order
            // List<List<int>> layers = new();
            // foreach (int idx in layerIndices) {
            //     layers.Add(layersDict[idx]);
            // }

            float hSpacing = 100f;
            float totalHeight = 400f;

            // Place nodes: x increases with column index, y spaced within column
            for (int columnIx = 0; columnIx < columns.Count; columnIx++) {
                List<int> nodeList = columns[columnIx];
                float spacing = totalHeight / nodeList.Count;
                float margin = 10 + spacing / 2;
                for (int i = 0; i < nodeList.Count; i++) {
                    int index = nodeList[i];
                    Node node = GetNodeById(dag, index);
                    if (node == null)
                        continue;
                    float x = (hSpacing * 1.5f) + columnIx * hSpacing;
                    //float y = 400 - totalHeight / 2f + i * vSpacing;
                    float y = margin + i * spacing;
                    // Debug.Log($"({li}, {i}) -> {x}, {y}");
                    node.position = new Vector2(x, y);
                }
            }

            //Repaint();
        }
    }
}