swings = sorted(swings, key=lambda x: x['index']) return pd.DataFrame(swings)
# Rule 1: Wave 2 retrace < 100% of Wave 1 if w2['magnitude'] >= w1['magnitude']: return False elliott wave python code
# 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 swings = sorted(swings, key=lambda x: x['index']) return pd
# Mark swing points swings = result['swing_points'] plt.scatter(swings['index'], swings['price'], c='red' if swings['type'].iloc[0]=='high' else 'green', label='Swing points') """ if len(swings_df) < 2: return [] def
# Plotting plt.figure(figsize=(14, 6)) plt.plot(price_series, label='Price', color='black', alpha=0.6)
def label_swing_waves(self, swings_df: pd.DataFrame) -> List[Dict]: """ Convert alternating swing points into wave segments. Returns list of waves with direction, length, and ratio info. """ if len(swings_df) < 2: return []
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, }