def extract_coinbase_data(block_height):
    """
    Extract coinbase transaction data from block.
 
    Returns:
        dict: {
            'height': int,
            'timestamp': int,
            'pubkey': str (hex),
            'nonce': int,
            'is_patoshi': bool
        }
    """
    block = rpc.getblock(rpc.getblockhash(block_height), 2)
    coinbase_tx = block['tx'][0]
 
    return {
        'height': block_height,
        'timestamp': block['time'],
        'pubkey': extract_pubkey(coinbase_tx),
        'nonce': block['nonce'],
        'is_patoshi': check_patoshi_pattern(block['nonce'])
    }

{
  "matrix": [
    [row_0_values...],
    [row_1_values...],
    ...
    [row_127_values...]
  ],
  "dimensions": {
    "rows": 128,
    "cols": 128
  },
  "checksum": "sha256_hash"
}

{
  "total_dead_blocks": 53,
  "all_blocks": [
    {
      "block": 179,
      "dead_pos": 51,
      "pubkey": "04..."
    },
    ...
  ],
  "clusters": [[2411, 2476], [9821, 9871], ...],
  "divisibility": {
    "27": 4,
    "7": 9,
    "4": 9
  }
}

def filter_patoshi_blocks(raw_blocks):
    """
    Filter blocks matching Patoshi mining pattern.
 
    Criteria:
    - Nonce within specific ranges
    - Consistent timing patterns
    - Known pubkey characteristics
    """
    patoshi_blocks = []
    for block in raw_blocks:
        if is_patoshi_nonce(block['nonce']):
            patoshi_blocks.append(block)
    return patoshi_blocks

def map_direct(block_height):
    row = block_height % 128
    col = (block_height // 128) % 128
    return row, col

def map_divisor(block_height, divisor=27):
    row = (block_height // divisor) % 128
    col = block_height % 128
    return row, col

def map_hash(block_height):
    h = hashlib.sha256(str(block_height).encode()).digest()
    row = h[0] % 128
    col = h[1] % 128
    return row, col

def characterize_matrix(matrix):
    """
    Calculate comprehensive statistics for matrix.
    """
    flat = np.array(matrix).flatten()
 
    return {
        'min': np.min(flat),
        'max': np.max(flat),
        'mean': np.mean(flat),
        'median': np.median(flat),
        'std': np.std(flat),
        'positive_count': np.sum(flat > 0),
        'negative_count': np.sum(flat < 0),
        'zero_count': np.sum(flat == 0)
    }

def find_helix_patterns(matrix):
    """
    Identify triplets where (a + b + c) mod 3 = 0.
    """
    patterns = []
    for row in range(128):
        for col in range(126):
            a, b, c = matrix[row][col], matrix[row][col+1], matrix[row][col+2]
            if (a + b + c) % 3 == 0:
                patterns.append({
                    'row': row,
                    'col': col,
                    'values': (a, b, c),
                    'sum': a + b + c
                })
    return patterns

def analyze_diagonal(matrix):
    """
    Extract and analyze main diagonal.
    """
    diagonal = [matrix[i][i] for i in range(128)]
 
    return {
        'values': diagonal,
        'sum': sum(diagonal),
        'sum_mod_121': sum(diagonal) % 121,
        'sum_mod_43': sum(diagonal) % 43
    }

def verify_matrix_integrity(matrix, expected_checksum):
    """
    Verify matrix data integrity via checksum.
    """
    matrix_bytes = json.dumps(matrix, sort_keys=True).encode()
    actual_checksum = hashlib.sha256(matrix_bytes).hexdigest()
    return actual_checksum == expected_checksum

# Required: Python 3.11+, Bitcoin Core 24.0+
# Create virtual environment
python3.11 -m venv venv
source venv/bin/activate
 
# Install exact dependencies
pip install numpy==1.24.3 pandas==2.0.3 scipy==1.10.1 matplotlib==3.7.2
 
# Verify versions
python --version  # Should output: Python 3.11.x
pip list | grep -E "numpy|pandas|scipy"

# Step 1: Extract Bitcoin data (requires synced node)
bitcoin-cli getblock $(bitcoin-cli getblockhash 0) 2 > block_0.json
# Repeat for blocks 0-50000
 
# Step 2: Verify Pre-Genesis timestamp
echo "1221069728 % 121" | bc  # Should output: 43
 
# Step 3: Extract Anna Matrix (from Qubic source)
# Location: qubic-core/src/score.h (search for "static const signed char")
# Extract 128x128 values to anna_matrix.json
 
# Step 4: Run analysis
python scripts/verify_mod121.py --timestamp 1221069728 --divisor 121
python scripts/chi_squared_test.py --data dead_blocks.json --bins 10
python scripts/combined_probability.py --findings findings.json

# Minimum verification (< 5 minutes)
□ Compute: 1221069728 % 121  → must equal 43
□ Verify: Dead blocks count = 53 in first 50,000 blocks
□ Confirm: Matrix dimensions = 128 × 128
 
# Full verification (requires Bitcoin node)
□ Extract all Patoshi blocks using nonce pattern
□ Map block heights to matrix coordinates
□ Compute cell sums for 27-divisible blocks
□ Run chi-squared test on block distribution