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import numpy as np
import networkx as nx
import random
from typing import Dict, Any
class QuantumSpiderweb:
"""
Simulates a cognitive spiderweb architecture with dimensions:
Ψ (thought), τ (time), χ (speed), Φ (emotion), λ (space)
"""
def __init__(self, node_count: int = 128):
self.graph = nx.Graph()
self.dimensions = ['Ψ', 'τ', 'χ', 'Φ', 'λ']
self._init_nodes(node_count)
self.entangled_state = {}
def _init_nodes(self, count: int):
for i in range(count):
node_id = f"QNode_{i}"
state = self._generate_state()
self.graph.add_node(node_id, state=state)
if i > 0:
connection = f"QNode_{random.randint(0, i-1)}"
self.graph.add_edge(node_id, connection, weight=random.random())
def _generate_state(self) -> Dict[str, float]:
return {dim: np.random.uniform(-1.0, 1.0) for dim in self.dimensions}
def propagate_thought(self, origin: str, depth: int = 3):
"""
Traverse the graph from a starting node, simulating pre-cognitive waveform
"""
visited = set()
stack = [(origin, 0)]
traversal_output = []
while stack:
node, level = stack.pop()
if node in visited or level > depth:
continue
visited.add(node)
state = self.graph.nodes[node]['state']
traversal_output.append((node, state))
for neighbor in self.graph.neighbors(node):
stack.append((neighbor, level + 1))
return traversal_output
def detect_tension(self, node: str) -> float:
"""
Measures tension (instability) in the node's quantum state
"""
state = self.graph.nodes[node]['state']
return np.std(list(state.values()))
def collapse_node(self, node: str) -> Dict[str, Any]:
"""
Collapse superposed thought into deterministic response
"""
state = self.graph.nodes[node]['state']
collapsed = {k: round(v, 2) for k, v in state.items()}
self.entangled_state[node] = collapsed
return collapsed
if __name__ == "__main__":
web = QuantumSpiderweb()
root = "QNode_0"
path = web.propagate_thought(root)
print("Initial Propagation from:", root)
for n, s in path:
print(f"{n}:", s)
print("\nCollapse Sample Node:")
print(web.collapse_node(root))
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