# Test for Bullish Impulse if (candidate[0] < candidate[1] and candidate[1] > candidate[2] and candidate[2] < candidate[3] and candidate[3] > candidate[4] and candidate[4] < candidate[5]): if is_valid_impulse(candidate): pattern_type = "Bullish Impulse" valid_patterns.append({ "start_date": pivot_dates[i], "end_date": pivot_dates[i+5], "start_price": candidate[0], "end_price": candidate[5], "type": pattern_type, "waves": candidate.tolist() })
# 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 elliott wave python code
A web-based analyzer that projects future price zones using Fibonacci extensions and provides trade setup recommendations. Advanced Analysis and Fibonacci Integration # Test for Bullish Impulse if (candidate[0] <
pip install numpy pandas scipy matplotlib python elliott_wave.py candidate[1] and candidate[1] >
# Mark peaks and troughs in the dataframe pivots.loc[data.index[peak_idx], 'type'] = 'peak' pivots.loc[data.index[trough_idx], 'type'] = 'trough'