use common williams market structure calcs
This commit is contained in:
Dobromir Popov
@@ -19,16 +19,19 @@ import logging
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from datetime import datetime
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import json
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import pandas as pd
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import numpy as np
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# Import core components from main system
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try:
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from core.data_provider import DataProvider
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from core.orchestrator import TradingOrchestrator
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from core.config import get_config
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from core.williams_market_structure import WilliamsMarketStructure
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except ImportError as e:
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print(f"Warning: Could not import main system components: {e}")
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print("Running in standalone mode with limited functionality")
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DataProvider = None
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WilliamsMarketStructure = None
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TradingOrchestrator = None
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get_config = lambda: {}
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@@ -200,66 +203,90 @@ class AnnotationDashboard:
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def _get_pivot_markers_for_timeframe(self, symbol: str, timeframe: str, df: pd.DataFrame) -> dict:
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"""
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Get pivot markers for a specific timeframe
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Returns dict with indices mapping to pivot info for that candle
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Get pivot markers for a specific timeframe using WilliamsMarketStructure directly
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Returns dict with all pivot points and identifies which are the last high/low per level
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"""
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try:
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if not self.data_provider:
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if WilliamsMarketStructure is None:
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logger.warning("WilliamsMarketStructure not available")
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return {}
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# Get Williams pivot levels for this timeframe
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pivot_levels = self.data_provider.get_williams_pivot_levels(
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symbol=symbol,
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base_timeframe=timeframe,
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limit=len(df)
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if df is None or len(df) < 10:
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logger.warning(f"Insufficient data for pivot calculation: {len(df) if df is not None else 0} bars")
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return {}
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# Convert DataFrame to numpy array format expected by Williams Market Structure
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ohlcv_array = df[['open', 'high', 'low', 'close', 'volume']].copy()
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# Add timestamp as first column (convert to milliseconds)
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timestamps = df.index.astype(np.int64) // 10**6 # pandas index is ns -> convert to ms
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ohlcv_array.insert(0, 'timestamp', timestamps)
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ohlcv_array = ohlcv_array.to_numpy()
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# Initialize Williams Market Structure with default distance
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# We'll override it in the calculation call
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williams = WilliamsMarketStructure(min_pivot_distance=1)
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# Calculate recursive pivot points with min_pivot_distance=2
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# This ensures 5 candles per pivot (tip + 2 prev + 2 next)
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pivot_levels = williams.calculate_recursive_pivot_points(
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ohlcv_array,
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min_pivot_distance=2
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)
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if not pivot_levels:
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logger.debug(f"No pivot levels found for {symbol} {timeframe}")
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return {}
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# Build a map of timestamp -> pivot info
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# Also track last high/low per level for drawing horizontal lines
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pivot_map = {}
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last_pivots = {} # {level: {'high': (ts_str, idx), 'low': (ts_str, idx)}}
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# For each level (1-5), find the last high and last low pivot
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# For each level (1-5), collect ALL pivot points
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for level_num, trend_level in pivot_levels.items():
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if not hasattr(trend_level, 'pivot_points') or not trend_level.pivot_points:
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continue
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# Find last high and last low for this level
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last_high = None
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last_low = None
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last_pivots[level_num] = {'high': None, 'low': None}
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# Add ALL pivot points to the map
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for pivot in trend_level.pivot_points:
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ts_str = pivot.timestamp.strftime('%Y-%m-%d %H:%M:%S')
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if ts_str not in pivot_map:
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pivot_map[ts_str] = {'highs': [], 'lows': []}
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pivot_info = {
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'level': level_num,
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'price': pivot.price,
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'strength': pivot.strength,
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'is_last': False # Will be updated below
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}
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if pivot.pivot_type == 'high':
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last_high = pivot
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pivot_map[ts_str]['highs'].append(pivot_info)
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last_pivots[level_num]['high'] = (ts_str, len(pivot_map[ts_str]['highs']) - 1)
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elif pivot.pivot_type == 'low':
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last_low = pivot
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# Add to pivot map
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if last_high:
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ts_str = last_high.timestamp.strftime('%Y-%m-%d %H:%M:%S')
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if ts_str not in pivot_map:
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pivot_map[ts_str] = {'highs': [], 'lows': []}
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pivot_map[ts_str]['highs'].append({
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'level': level_num,
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'price': last_high.price,
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'strength': last_high.strength
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})
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if last_low:
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ts_str = last_low.timestamp.strftime('%Y-%m-%d %H:%M:%S')
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if ts_str not in pivot_map:
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pivot_map[ts_str] = {'highs': [], 'lows': []}
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pivot_map[ts_str]['lows'].append({
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'level': level_num,
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'price': last_low.price,
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'strength': last_low.strength
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})
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pivot_map[ts_str]['lows'].append(pivot_info)
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last_pivots[level_num]['low'] = (ts_str, len(pivot_map[ts_str]['lows']) - 1)
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# Mark the last high and last low for each level
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for level_num, last_info in last_pivots.items():
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if last_info['high']:
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ts_str, idx = last_info['high']
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pivot_map[ts_str]['highs'][idx]['is_last'] = True
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if last_info['low']:
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ts_str, idx = last_info['low']
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pivot_map[ts_str]['lows'][idx]['is_last'] = True
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logger.info(f"Found {len(pivot_map)} pivot candles for {symbol} {timeframe} (from {len(df)} candles)")
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return pivot_map
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except Exception as e:
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logger.error(f"Error getting pivot markers for {timeframe}: {e}")
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import traceback
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logger.error(traceback.format_exc())
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return {}
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def _setup_routes(self):
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