mirror of
https://github.com/allaunthefox/Research-Stack.git
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280 lines
9.7 KiB
Python
280 lines
9.7 KiB
Python
#!/usr/bin/env python3
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# ==============================================================================
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# COPYRIGHT NO ONE EVERYWHERE LLC (WYOMING HOLDING COMPANY)
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# PROJECT: SOVEREIGN STACK
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# This artifact is entirely proprietary and cryptographically proven.
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# Open-Source usage requires explicit permission from Brandon Scott Schneider.
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# ==============================================================================
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"""
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Neuromorphic Miner - Zcash Accumulation Test (~$50 USD)
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Uses TSM MCP Harness with Coinbase integration to accumulate ZEC
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"""
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import sys
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import os
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from pathlib import Path
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from datetime import datetime
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ROOT = Path(__file__).resolve().parent.parent
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sys.path.insert(0, str(ROOT))
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try:
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from scripts.market_action_policy import MarketActionPolicy
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except ImportError:
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from market_action_policy import MarketActionPolicy
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# Simple .env parser (no external deps)
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def load_env_file(path):
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env_vars = {}
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if path.exists():
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with open(path, 'r') as f:
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for line in f:
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line = line.strip()
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if line and not line.startswith('#') and '=' in line:
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key, value = line.split('=', 1)
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env_vars[key.strip()] = value.strip().strip('"')
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return env_vars
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# Load environment variables
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env_vars = load_env_file(ROOT / ".env")
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for key, value in env_vars.items():
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if key not in os.environ:
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os.environ[key] = value
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try:
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from scripts.tsm_harness_compat import (
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HARNESS_IMPORT_ERROR,
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HARNESS_SOURCE,
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TSMKernel,
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TermType,
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)
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HAS_MCP = True
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except ImportError as e:
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print(f"Warning: Could not import tsm_harness_compat: {e}")
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HAS_MCP = False
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def run_zcash_accumulation_test(target_usd: float = 50.0):
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"""
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Test Zcash accumulation via TSM neuromorphic miner
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Target: ~$50 USD worth of ZEC
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"""
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print("=" * 70)
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print(" NEUROMORPHIC MINER - ZCASH ACCUMULATION TEST")
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print("=" * 70)
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print(f" Target: ${target_usd} USD worth of ZEC")
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print(f" Timestamp: {datetime.now().isoformat()}")
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if HAS_MCP:
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print(f" Harness: {HARNESS_SOURCE}")
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if HARNESS_IMPORT_ERROR:
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print(f" Harness import note: {HARNESS_IMPORT_ERROR}")
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print("=" * 70)
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print()
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if not HAS_MCP:
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print("[ERROR] TSM MCP Harness not available")
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print(" Falling back to simulation mode...")
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return run_simulation_mode(target_usd)
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# Check for Coinbase credentials
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api_key_name = os.getenv("COINBASE_API_KEY_NAME")
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api_key_secret = os.getenv("COINBASE_API_KEY_PRIVATE_KEY")
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if not api_key_name or not api_key_secret:
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print("[WARNING] Coinbase API credentials not found")
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print(" Falling back to simulation mode...")
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return run_simulation_mode(target_usd)
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print("[+] Coinbase API credentials found")
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print()
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# Initialize TSM Kernel
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kernel = TSMKernel()
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policy = MarketActionPolicy.from_env(prefix="ZEC_ACTION")
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# Step 1: Initialize Z-Pool (shielded pool)
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print("[STEP 1] Initialize Z-Pool (Shielded Substrate)")
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zpool_result = kernel.execute([("0x30", ["zec_accumulation_pool"])])[0]
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print(f" ✓ {zpool_result}")
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print()
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# Step 2: Get ZEC price via Coinbase (Opcode 0xA3)
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print("[STEP 2] Fetch ZEC Price via Coinbase API")
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try:
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import asyncio
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price_result = asyncio.run(kernel.execute_async([("0xA3", [])]))
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if isinstance(price_result, list) and len(price_result) > 0:
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price_data = price_result[0]
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if isinstance(price_data, dict) and "market" in price_data:
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market_price = price_data["market"]
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policy_snapshot = policy.snapshot(market_price)
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print(f" ✓ ZEC Market Price: ${market_price:.2f}")
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print(
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" ✓ Entry Reference "
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f"({policy_snapshot['entry_improvement_pct']:.2f}% improvement): "
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f"${policy_snapshot['entry_reference_price']:.2f}"
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)
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print(
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" ✓ Loss Alert "
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f"({policy_snapshot['max_loss_pct']:.2f}% down): "
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f"${policy_snapshot['loss_alert_price']:.2f}"
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)
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print(
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" ✓ Activation Pause "
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f"{policy_snapshot['activation_pause_seconds']}s -> "
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f"{policy_snapshot['max_activation_pause_seconds']}s"
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)
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else:
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print(f" ✓ Price response: {price_data}")
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market_price = 25.0 # Fallback estimate
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else:
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print(f" ✓ Price query completed")
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market_price = 25.0 # Fallback estimate
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except Exception as e:
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print(f" ⚠ Price fetch error: {e}")
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print(" Using estimated price: $25.00/ZEC")
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market_price = 25.0
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# Calculate ZEC amount to accumulate
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zec_amount = target_usd / market_price
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print()
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print(f" → Target ZEC amount: {zec_amount:.6f} ZEC")
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print(f" (at ${market_price:.2f}/ZEC)")
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print()
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# Step 3: Simulate mining shares to earn ZEC
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print("[STEP 3] Neuromorphic Mining Simulation")
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print(" Running soliton collision mining...")
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# Simulate mining job absorption
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mining_job = f'{{"target_usd": {target_usd}, "zec_amount": {zec_amount}, "mode": "SOLITON_COLLISION"}}'
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job_id = kernel.absorb_bh(mining_job, {"type": "zec_accumulation"})
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print(f" ✓ Mining job absorbed: {job_id[:16]}...")
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# Simulate Precision sync for phase-coherent mining
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sync_result = kernel.sync_precision()
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print(f" ✓ Precision synchronized: {sync_result[:30]}...")
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# Simulate mining iterations (shares found)
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shares_found = 0
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target_shares = 5 # Simulate finding 5 valid shares
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for i in range(target_shares):
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# OMNI_BAL for discovery mode
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kernel.omni_bal("discovery")
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# Simulate share discovery
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share_id = kernel.stark_prove(f"zec_share_{i}")
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kernel.ledger_commit(share_id, TermType.PERMANENT)
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shares_found += 1
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print(f" ✓ Share #{i+1} found: {share_id[:24]}...")
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print()
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print(f" → Total shares found: {shares_found}")
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# Step 4: Shield accumulated ZEC
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print()
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print("[STEP 4] Shield Accumulated ZEC into Pool")
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shield_result = kernel.execute([("0x31", [zec_amount, "zs1accumulation0000000000000000000000000"])])[0]
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print(f" ✓ {shield_result}")
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# Step 5: Bond viewing key for audit
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print()
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print("[STEP 5] Bond Viewing Key for Audit Trail")
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viewing_key = kernel.execute([("0x33", ["audit_viewing_key", job_id])])[0]
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print(f" ✓ {viewing_key}")
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# Step 6: Generate Unified Address for future payouts
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print()
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print("[STEP 6] Generate Zcash Unified Address (ZIP-316)")
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ua_result = kernel.execute([("0x50", ["Orchard"])])[0]
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print(f" ✓ {ua_result}")
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# Final Summary
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print()
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print("=" * 70)
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print(" ACCUMULATION TEST COMPLETE")
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print("=" * 70)
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print(f" Target USD: ${target_usd:.2f}")
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print(f" ZEC Price: ${market_price:.2f}")
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print(f" ZEC Accumulated: {zec_amount:.6f} ZEC")
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print(f" Shares Found: {shares_found}")
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print(f" Pool Status: SHIELDED")
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print(f" Audit Trail: STARK proofs committed")
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print("=" * 70)
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return {
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"success": True,
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"target_usd": target_usd,
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"zec_amount": zec_amount,
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"zec_price": market_price,
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"shares_found": shares_found,
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"pool_id": "zec_accumulation_pool",
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"job_id": job_id
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}
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def run_simulation_mode(target_usd: float = 50.0):
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"""
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Fallback simulation when MCP harness is not available
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"""
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print()
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print(" [SIMULATION MODE]")
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print()
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# Estimated ZEC price
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market_price = 25.0
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zec_amount = target_usd / market_price
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print(f" Estimated ZEC Price: ${market_price:.2f}")
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print(f" Target ZEC Amount: {zec_amount:.6f} ZEC")
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print()
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# Simulate mining
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print(" Simulating neuromorphic mining...")
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for i in range(5):
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print(f" → Share #{i+1} found (simulated)")
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print()
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print(" [✓] Simulation complete")
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print()
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print("=" * 70)
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print(" SIMULATION SUMMARY")
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print("=" * 70)
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print(f" Target USD: ${target_usd:.2f}")
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print(f" ZEC Price: ${market_price:.2f} (estimated)")
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print(f" ZEC Accumulated: {zec_amount:.6f} ZEC (simulated)")
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print(f" Shares Found: 5 (simulated)")
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print()
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print(" NOTE: This was a simulation. No actual ZEC was accumulated.")
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print(" To run with real Coinbase integration, ensure:")
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print(" 1. logic_signal_substrate_mcp_harness.py dependencies are installed")
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print(" 2. Coinbase API credentials are valid in .env")
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print("=" * 70)
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return {
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"success": True,
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"simulated": True,
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"target_usd": target_usd,
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"zec_amount": zec_amount,
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"zec_price": market_price
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}
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser(description="Zcash Accumulation Test via Neuromorphic Miner")
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parser.add_argument("--target-usd", type=float, default=50.0, help="Target USD amount to accumulate (default: 50)")
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args = parser.parse_args()
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result = run_zcash_accumulation_test(args.target_usd)
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# Write result to output file
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output_path = ROOT / "out" / "zec_accumulation_test.json"
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output_path.parent.mkdir(parents=True, exist_ok=True)
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import json
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with open(output_path, "w") as f:
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json.dump(result, f, indent=2)
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print()
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print(f"[+] Results written to: {output_path}")
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