Elliott Wave Python Code • Must Try

price_series = np.concatenate([wave1[:100], wave2[100:200], wave3[200:300], wave4[300:400], wave5[400:500]])

swings = sorted(swings, key=lambda x: x['index']) return pd.DataFrame(swings) elliott wave python code

# Annotate wave numbers (first 5 waves if exist) waves = result['waves'] for i, wave in enumerate(waves[:5]): mid_idx = (wave['start_idx'] + wave['end_idx']) // 2 mid_price = (wave['start_price'] + wave['end_price']) / 2 plt.text(mid_idx, mid_price, str(i+1), fontsize=12, fontweight='bold', bbox=dict(facecolor='yellow', alpha=0.7)) price_series = np

def fibonacci_ratios(self, wave: Dict) -> Dict: """Calculate Fibonacci retracements/extensions for a wave.""" mag = wave['magnitude'] return { '0.382': mag * 0.382, '0.5': mag * 0.5, '0.618': mag * 0.618, '1.0': mag, '1.272': mag * 1.272, '1.618': mag * 1.618, } price_series = np.concatenate([wave1[:100]

# Generate synthetic price data (uptrend with pullbacks) np.random.seed(42) t = np.linspace(0, 100, 500) # Simulated Elliott wave: 5 waves up wave1 = 100 + 10 * np.sin(t * 0.05) + 0.1 * t wave2 = wave1 - 4 * np.sin(t * 0.1) wave3 = wave2 + 15 * np.sin(t * 0.03) wave4 = wave3 - 6 * np.sin(t * 0.08) wave5 = wave4 + 8 * np.sin(t * 0.02)

def check_corrective_rules(self, waves: List[Dict]) -> bool: """Check 3-wave corrective pattern (A,B,C).""" if len(waves) < 3: return False

# Rule 3: Wave 4 price overlap with Wave 1? # For uptrend impulse: w1 up, w2 down, w3 up, w4 down, w5 up # Overlap means low of w4 < high of w1 if w1['direction'] == 'up': wave1_high = max(w1['start_price'], w1['end_price']) wave4_low = min(w4['start_price'], w4['end_price']) if wave4_low <= wave1_high: return False else: # downtrend impulse wave1_low = min(w1['start_price'], w1['end_price']) wave4_high = max(w4['start_price'], w4['end_price']) if wave4_high >= wave1_low: return False