def find_swing_points(self, prices: np.ndarray) -> pd.DataFrame: """Identify swing highs and lows.""" highs = argrelextrema(prices, np.greater, order=self.swing_window)[0] lows = argrelextrema(prices, np.less, order=self.swing_window)[0]
return { 'pattern': pattern_type, 'waves': waves, 'valid': impulse_ok or corrective_ok, 'fibonacci_levels': fibs, 'swing_points': swings_df } Example usage & visualization ------------------------------- if name == " main ": import matplotlib.pyplot as plt elliott wave python code
# Rule 1: Wave 2 retrace < 100% of Wave 1 if w2['magnitude'] >= w1['magnitude']: return False def find_swing_points(self, prices: np
def detect_elliott_waves(self, prices: np.ndarray) -> Dict: """ Main function: returns detected wave structure and validation. """ swings_df = self.find_swing_points(prices) waves = self.label_swing_waves(swings_df) prices: np.ndarray) ->
# Plotting plt.figure(figsize=(14, 6)) plt.plot(price_series, label='Price', color='black', alpha=0.6)
impulse_ok = self.check_impulse_rules(waves) corrective_ok = self.check_corrective_rules(waves)