Update 20241019-reduce-size-difference-between-capsules-and-mesh-volu…

…me.md

decisions/20241019-reduce-size-difference-between-capsules-and-mesh-volume.md

@@ -19,108 +19,9 @@ The goal is to minimize the size discrepancies between the capsules surrounding
 
 - The objective is to minimize the size differences between the capsules (nodes) and the volume of the skin mesh. This is quantified using a cost function that measures the deviation from ideal capsule sizes.
 
-### Implementation Using GDScript
-
-```gdscript
-# SPDX-FileCopyrightText: 2024 K. S. Ernest "iFire" Lee <[email protected]>
-# SPDX-License-Identifier: MIT
-
-extends Node
-
-class Node:
-    var id: int
-    var position: Vector3
-    var flow: float = 0.0
-    var target_size: float = 0.0  # Ideal size for the capsule around this node
-
-    func _init(id: int, position: Vector3, target_size: float):
-        self.id = id
-        self.position = position
-        self.target_size = target_size
-
-class Edge:
-    var u: Node
-    var v: Node
-    var cost_function: Callable
-
-    func _init(u: Node, v: Node, cost_function: Callable):
-        self.u = u
-        self.v = v
-        self.cost_function = cost_function
-
-class BiMDF:
-    var nodes: Dictionary = {}
-    var edges: Array = []
-
-    func add_node(position: Vector3, target_size: float) -> Node:
-        var new_node = Node(nodes.size(), position, target_size)
-        nodes[new_node.id] = new_node
-        return new_node
-
-    func add_edge(u: Node, v: Node, cost_function: Callable) -> Edge:
-        var new_edge = Edge(u, v, cost_function)
-        edges.append(new_edge)
-        return new_edge
-
-    func solve() -> Dictionary:
-        # Placeholder for Bi-MDF algorithm implementation
-        # Return a sample output structure for demonstration
-        return {"cost": 0, "solution": {}}
-
-# Cost Function Definitions
-func quad_deviation(flow: float, target: float) -> float:
-    return pow(flow - target, 2)  # Quadratic cost based on deviation
-
-# Function to create a cost function with specific parameters
-func create_cost_function(target_size: float, weight: float) -> Callable:
-    return Callable(self, "quad_deviation").bind(target_size * weight)
-
-# Main function to set up and run the Bi-MDF problem
-func _ready():
-    var bimdf = BiMDF.new()
-    var array_mesh: ArrayMesh = preload("res://path_to_your_mesh.mesh")
-    var mesh_data_tool = MeshDataTool.new()
-    mesh_data_tool.create_from_surface(array_mesh, 0)
-
-    # Extract vertices using MeshDataTool
-    var vertex_count = mesh_data_tool.get_vertex_count()
-    for i in range(vertex_count):
-        var vertex_position = mesh_data_tool.get_vertex(i)
-        bimdf.add_node(vertex_position, 1.0)  # Assuming a default target size for simplicity
-
-    # Example setup for bones (if applicable)
-    var bone1 = bimdf.add_node(Vector3(0, 0, 0), 3.0)  # Position and target size for bone1
-    var bone2 = bimdf.add_node(Vector3(1, 0, 0), 2.0)  # Position and target size for bone2
-
-    # Example skin weights (adjust according to your specific setup)
-    var weights = {
-        vertex1: [0.5, 0.5],  # Vertex 1 influenced equally by bone1 and bone2
-        vertex2: [0.7, 0.3],  # More influence from bone1
-        vertex3: [0.9, 0.1],  # Mostly bone1
-        vertex4: [0.6, 0.4],  # Somewhat balanced
-        vertex5: [0.4, 0.6],  # More influence from bone2
-        vertex6: [0.2, 0.8],  # Mostly bone2
-        vertex7: [0.3, 0.7],  # More influence from bone2
-        vertex8: [0.5, 0.5]   # Equally influenced
-    }
-
-    # Connect bones to vertices based on skin weights
-    for vertex_id in weights.keys():
-        var vertex = bimdf.nodes[vertex_id]
-        var weight1 = weights[vertex_id][0]
-        var weight2 = weights[vertex_id][1]
-        var cost_func1 = create_cost_function(vertex.target_size, weight1)
-        var cost_func2 = create_cost_function(vertex.target_size, weight2)
-        bimdf.add_edge(bone1, vertex, cost_func1)
-        bimdf.add_edge(bone2, vertex, cost_func2)
-
-    # Solve the Bi-MDF problem
-    var result = bimdf.solve()
-    print("Total cost: ", result["cost"])
-
-    for edge in bimdf.edges:
-        print("Flow on edge: ", edge.u.flow + edge.v.flow)  # Placeholder for flow values
-```
+### Implementation
+
+I have no idea.
 
 ## The Benefits