Applying the Law of Attraction to a Network
We'll use the math from your double pendulum simulation as inspiration for our network. We'll create nodes with attributes (e.g., personality traits, interests) and connect them based on their similarity.



python



import numpy as np

class Node:
    def __init__(self, name):
        self.name = name
        self.attributes = {}
        self.connections = []

class AttractionNetwork:
    def __init__(self):
        self.nodes = {}

    def add_node(self, node):
        """Add a new node to the network"""
        if node.name not in self.nodes:
            self.nodes[node.name] = Node(node)

    def connect_nodes(self, node1_name, node2_name, attraction_type):
        """
        Connect two nodes with an attracting quality.

        :param node1_name: Name of the first node
        :type node1_name: str
        :param node2_name: Name of the second node
        :type node2_name: str
        :param attraction_type: Attracting quality (e.g., "outdoors", "art")
        """
        if node1_name in self.nodes and node2_name in self.nodes:
            self.nodes[node1_name].connections.append((node2_name, attraction_type))
            self.nodes[node2_name]. connections.append((node1_name, attraction_type))

    def attract(self):
        """Find nodes with similar attributes"""
        attracted = []
        for node1 in self.nodes.values():
            for node2 in self.nodes.values():
                if node1 != node2:
                    similarity = len(set(node1.attributes) & set(node2.attributes))
                    distance = 0
                    for key, value in node1.attributes.items():
                        if key not in node2 attributes or abs(value - node2[key]) > 5:
                            distance += 1
                    attractivity = np.exp(-distance / (similarity + 10))  # simple attraction function
                    if attractivity > 0.7:  # threshold for connection
                        self.connect_nodes(node1_name, node2_name, "similar")
        return attracted

# Create nodes with similar attributes
network = AttractionNetwork()
network.add_node(Node("outdoors", {"hiking": True, "camping": False}))
network.add_node(Node("art", {"music": True, "dancing": False}))

network.connect_nodes("outdoors", "art", "similar")

# Simulate the attraction between nodes
attracted = network.attract()

for node in attracted:
    print(f"Node {node} is attracting")



In this code:
We have two Node classes, each with a name and attributes.
The AttractionNetwork class has methods to add new nodes, connect them based on their similarity, and attract other nodes.
We use the law of attraction as an inspiration for our connection function. This is