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import os
import json
import numpy as np
import matplotlib.pyplot as plt
from typing import List, Dict, Any, Optional
folder = '.' # Or your path to cocoons
quantum_states = []
chaos_states = []
proc_ids = []
labels = []
all_perspectives = []
meta_mutations = []
def get_latest_quantum_state() -> List[float]:
"""Get the most recent quantum state from cocoon files."""
latest_cocoon = None
latest_time = 0
for fname in os.listdir(folder):
if fname.endswith('.cocoon'):
full_path = os.path.join(folder, fname)
file_time = os.path.getmtime(full_path)
if file_time > latest_time:
latest_time = file_time
latest_cocoon = full_path
if not latest_cocoon:
return [0.0, 0.0] # Default quantum state
try:
with open(latest_cocoon, 'r') as f:
data = json.load(f)['data']
return data.get('quantum_state', [0.0, 0.0])
except Exception as e:
print(f"Warning: Could not read quantum state from {latest_cocoon}: {e}")
return [0.0, 0.0]
def simple_neural_activator(quantum_vec: List[float], chaos_vec: List[float]) -> int:
"""Lightweight thresholds: feels like a tiny neural net inspired by input!"""
q_sum = sum(quantum_vec)
c_var = np.var(chaos_vec)
activated = 1 if q_sum + c_var > 1 else 0
return activated
def codette_dream_agent(quantum_vec: List[float], chaos_vec: List[float]) -> tuple[List[float], List[float]]:
"""Blend quantum and chaos vectors using trigonometric transformations."""
dream_q = [np.sin(q * np.pi) for q in quantum_vec]
dream_c = [np.cos(c * np.pi) for c in chaos_vec]
return dream_q, dream_c
def get_quantum_statistics() -> Dict[str, Any]:
"""Get statistical information about quantum states across all cocoons."""
quantum_states = []
for fname in os.listdir('.'):
if fname.endswith('.cocoon'):
try:
with open(fname, 'r') as f:
data = json.load(f)['data']
state = data.get('quantum_state')
if state:
quantum_states.append(state)
except:
continue
if not quantum_states:
return {
'count': 0,
'average': [0.0, 0.0],
'variance': [0.0, 0.0]
}
# Calculate statistics
count = len(quantum_states)
avg_state = [
sum(s[0] for s in quantum_states) / count,
sum(s[1] for s in quantum_states) / count
]
var_state = [
sum((s[0] - avg_state[0])**2 for s in quantum_states) / count,
sum((s[1] - avg_state[1])**2 for s in quantum_states) / count
]
return {
'count': count,
'average': avg_state,
'variance': var_state
}
if fname.endswith('.cocoon'):
full_path = os.path.join(folder, fname)
file_time = os.path.getmtime(full_path)
if file_time > latest_time:
latest_time = file_time
latest_cocoon = full_path
if not latest_cocoon:
return [0.0, 0.0] # Default quantum state
try:
with open(latest_cocoon, 'r') as f:
data = json.load(f)['data']
return data.get('quantum_state', [0.0, 0.0])
except Exception as e:
print(f"Warning: Could not read quantum state from {latest_cocoon}: {e}")
return [0.0, 0.0]
def simple_neural_activator(quantum_vec, chaos_vec):
# Lightweight thresholds: feels like a tiny neural net inspired by input!
q_sum = sum(quantum_vec)
c_var = np.var(chaos_vec)
activated = 1 if q_sum + c_var > 1 else 0
return activated
def codette_dream_agent(quantum_vec, chaos_vec):
# Blend them using pseudo-random logic—a "mutated" universe!
dream_q = [np.sin(q * np.pi) for q in quantum_vec]
dream_c = [np.cos(c * np.pi) for c in chaos_vec]
return dream_q, dream_c
def philosophical_perspective(qv, cv):
# Synthesizes a philosophy based on state magnitude and spread
m = np.max(qv) + np.max(cv)
if m > 1.3:
return "Philosophical Note: This universe is likely awake."
else:
return "Philosophical Note: Echoes in the void."
# Meta processing loop
print("\nMeta Reflection Table:\n")
header = "Cocoon File | Quantum State | Chaos State | Neural | Dream Q/C | Philosophy"
print(header)
print('-'*len(header))
for fname in os.listdir(folder):
if fname.endswith('.cocoon'):
with open(os.path.join(folder, fname), 'r') as f:
try:
dct=json.load(f)['data']
q=dct.get('quantum_state',[0,0])
c=dct.get('chaos_state',[0,0,0])
neural=simple_neural_activator(q,c)
dreamq,dreamc=codette_dream_agent(q,c)
phil=philosophical_perspective(q,c)
quantum_states.append(q)
chaos_states.append(c)
proc_ids.append(dct.get('run_by_proc',-1))
labels.append(fname)
all_perspectives.append(dct.get('perspectives',[]))
meta_mutations.append({'dreamQ':dreamq,'dreamC':dreamc,'neural':neural,'philosophy':phil})
print(f"{fname} | {q} | {c} | {neural} | {dreamq}/{dreamc} | {phil}")
except Exception as e:
print(f"Warning: {fname} failed ({e})")
# Also plot meta-dream mutated universes!
if len(meta_mutations)>0:
dq0=[m['dreamQ'][0] for m in meta_mutations]
dc0=[m['dreamC'][0] for m in meta_mutations]
ncls=[m['neural'] for m in meta_mutations]
plt.figure(figsize=(8,6))
sc=plt.scatter(dq0,dc0,c=ncls,cmap='spring',s=100)
plt.xlabel('Dream Quantum[0]')
plt.ylabel('Dream Chaos[0]')
plt.title('Meta-Dream Codette Universes')
plt.colorbar(sc,label="Neural Activation Class")
plt.grid(True)
plt.show()
else:
print("No valid cocoons found for meta-analysis.")
root@Jmachine:/home/raiff/Documents/logs/astro_cocoons# analyze_cocoons.py
bash: analyze_cocoons.py: command not found...
root@Jmachine:/home/raiff/Documents/logs/astro_cocoons# python analyze_cocoons.py
Traceback (most recent call last):
File "/home/raiff/Documents/logs/astro_cocoons/analyze_cocoons.py", line 11, in <module>
for fname in os.listdir(folder):
~~~~~~~~~~^^^^^^^^
FileNotFoundError: [Errno 2] No such f
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