298 lines
12 KiB
Python
298 lines
12 KiB
Python
import asyncio
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import logging
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import time
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from collections import deque
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from datetime import datetime, timedelta
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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from matplotlib.colors import LogNorm
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from core.data_provider import DataProvider, MarketTick
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from core.config import get_config
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# Configure logging
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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class COBStabilityTester:
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def __init__(self, symbol='ETHUSDT', duration_seconds=15):
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self.symbol = symbol
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self.duration = timedelta(seconds=duration_seconds)
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self.ticks = deque()
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# Set granularity (buckets) based on symbol
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if 'ETH' in symbol.upper():
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self.price_granularity = 1.0 # 1 USD for ETH
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elif 'BTC' in symbol.upper():
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self.price_granularity = 10.0 # 10 USD for BTC
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else:
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self.price_granularity = 1.0 # Default 1 USD
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logger.info(f"Using price granularity: ${self.price_granularity} for {symbol}")
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# Initialize DataProvider the same way as clean_dashboard
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logger.info("Initializing DataProvider like in clean_dashboard...")
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self.data_provider = DataProvider() # Use default constructor like clean_dashboard
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# Initialize COB data collection like clean_dashboard does
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self.cob_data_received = 0
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self.latest_cob_data = {}
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# Store all COB snapshots for heatmap generation
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self.cob_snapshots = deque()
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self.price_data = [] # For price line chart
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self.start_time = None
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self.subscriber_id = None
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def _tick_callback(self, tick: MarketTick):
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"""Callback function to receive ticks from the DataProvider."""
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if self.start_time is None:
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self.start_time = datetime.now()
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logger.info(f"Started collecting ticks at {self.start_time}")
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# Store all ticks
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self.ticks.append(tick)
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def _cob_data_callback(self, symbol: str, cob_data: dict):
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"""Callback function to receive COB data from the DataProvider."""
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# Debug: Log first few callbacks to see what symbols we're getting
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if self.cob_data_received < 5:
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logger.info(f"DEBUG: Received COB data for symbol '{symbol}' (target: '{self.symbol}')")
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# Filter to only our requested symbol - handle both formats (ETH/USDT and ETHUSDT)
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normalized_symbol = symbol.replace('/', '')
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normalized_target = self.symbol.replace('/', '')
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if normalized_symbol != normalized_target:
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if self.cob_data_received < 5:
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logger.info(f"DEBUG: Skipping symbol '{symbol}' (normalized: '{normalized_symbol}' vs target: '{normalized_target}')")
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return
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self.cob_data_received += 1
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self.latest_cob_data[symbol] = cob_data
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# Store the complete COB snapshot for heatmap generation
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if 'bids' in cob_data and 'asks' in cob_data:
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snapshot = {
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'timestamp': cob_data.get('timestamp', datetime.now()),
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'bids': cob_data['bids'],
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'asks': cob_data['asks'],
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'stats': cob_data.get('stats', {})
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}
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self.cob_snapshots.append(snapshot)
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# Convert COB data to tick-like format for analysis
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if 'stats' in cob_data and 'mid_price' in cob_data['stats']:
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mid_price = cob_data['stats']['mid_price']
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if mid_price > 0:
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# Store price data for line chart
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self.price_data.append({
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'timestamp': cob_data.get('timestamp', datetime.now()),
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'price': mid_price
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})
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# Create a synthetic tick from COB data
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synthetic_tick = MarketTick(
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symbol=symbol,
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timestamp=cob_data.get('timestamp', datetime.now()),
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price=mid_price,
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volume=cob_data.get('stats', {}).get('total_volume', 0),
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quantity=0, # Not available in COB data
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side='unknown', # COB data doesn't have side info
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trade_id=f"cob_{self.cob_data_received}",
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is_buyer_maker=False,
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raw_data=cob_data
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)
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self.ticks.append(synthetic_tick)
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if self.cob_data_received % 10 == 0: # Log every 10th update
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logger.info(f"COB update #{self.cob_data_received}: {symbol} @ ${mid_price:.2f}")
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async def run_test(self):
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"""Run the data collection and plotting test."""
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logger.info(f"Starting COB stability test for {self.symbol} for {self.duration.total_seconds()} seconds...")
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# Initialize COB collection like clean_dashboard does
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try:
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logger.info("Starting COB collection in data provider...")
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self.data_provider.start_cob_collection()
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logger.info("Started COB collection in data provider")
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# Subscribe to COB updates
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logger.info("Subscribing to COB data updates...")
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self.data_provider.subscribe_to_cob(self._cob_data_callback)
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logger.info("Subscribed to COB data updates from data provider")
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except Exception as e:
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logger.error(f"Failed to start COB collection or subscribe: {e}")
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# Subscribe to ticks as fallback
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try:
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self.subscriber_id = self.data_provider.subscribe_to_ticks(self._tick_callback, symbols=[self.symbol])
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logger.info("Subscribed to tick data as fallback")
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except Exception as e:
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logger.warning(f"Failed to subscribe to ticks: {e}")
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# Start the data provider's real-time streaming
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try:
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await self.data_provider.start_real_time_streaming()
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logger.info("Started real-time streaming")
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except Exception as e:
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logger.error(f"Failed to start real-time streaming: {e}")
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# Collect data for the specified duration
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self.start_time = datetime.now()
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while datetime.now() - self.start_time < self.duration:
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await asyncio.sleep(1)
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logger.info(f"Collected {len(self.ticks)} ticks so far...")
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# Stop streaming and unsubscribe
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await self.data_provider.stop_real_time_streaming()
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self.data_provider.unsubscribe_from_ticks(self.subscriber_id)
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logger.info(f"Finished collecting data. Total ticks: {len(self.ticks)}")
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# Plot the results
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if self.price_data and self.cob_snapshots:
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self.create_price_heatmap_chart()
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elif self.ticks:
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self._create_simple_price_chart()
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else:
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logger.warning("No data was collected. Cannot generate plot.")
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def create_price_heatmap_chart(self):
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"""Create a visualization with price chart and order book heatmap."""
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if not self.price_data or not self.cob_snapshots:
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logger.warning("Insufficient data to plot.")
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return
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logger.info(f"Creating price and order book heatmap chart...")
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# Prepare data
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price_df = pd.DataFrame(self.price_data)
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price_df['timestamp'] = pd.to_datetime(price_df['timestamp'])
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# Extract order book data for heatmap
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heatmap_data = []
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for snapshot in self.cob_snapshots:
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timestamp = snapshot['timestamp']
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for side in ['bids', 'asks']:
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for order in snapshot[side]:
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# Handle both dict and list formats
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if isinstance(order, dict):
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price = order['price']
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size = order['size']
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elif isinstance(order, (list, tuple)) and len(order) >= 2:
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price = float(order[0])
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size = float(order[1])
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else:
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logger.warning(f"Unknown order format: {order}")
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continue
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bucketed_price = round(price / self.price_granularity) * self.price_granularity
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heatmap_data.append({
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'time': timestamp,
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'price': bucketed_price,
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'size': size,
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'side': side
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})
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heatmap_df = pd.DataFrame(heatmap_data)
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# Create plot
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fig, ax1 = plt.subplots(figsize=(16, 8))
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# Plot price line
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ax1.plot(price_df['timestamp'], price_df['price'], 'cyan', linewidth=1, label='Price')
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# Prepare heatmap
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for side, cmap in zip(['bids', 'asks'], ['Greens', 'Reds']):
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side_df = heatmap_df[heatmap_df['side'] == side]
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if not side_df.empty:
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hist, xedges, yedges = np.histogram2d(
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side_df['time'].astype(np.int64) // 10**9,
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side_df['price'],
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bins=[np.unique(side_df['time'].astype(np.int64) // 10**9), np.arange(price_df['price'].min(), price_df['price'].max(), self.price_granularity)],
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weights=side_df['size']
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)
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ax1.pcolormesh(pd.to_datetime(xedges, unit='s'), yedges, hist.T, cmap=cmap, alpha=0.5)
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# Enhance plot
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ax1.set_title(f'Price Chart with Order Book Heatmap - {self.symbol}')
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ax1.set_xlabel('Time')
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ax1.set_ylabel('Price (USDT)')
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ax1.legend(loc='upper left')
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ax1.grid(True, alpha=0.3)
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plt.tight_layout()
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plot_filename = f"price_heatmap_chart_{self.symbol.replace('/', '_')}_{datetime.now():%Y%m%d_%H%M%S}.png"
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plt.savefig(plot_filename, dpi=150)
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logger.info(f"Price and heatmap chart saved to {plot_filename}")
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plt.show()
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def _create_simple_price_chart(self):
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"""Create a simple price chart as fallback"""
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logger.info("Creating simple price chart as fallback...")
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prices = []
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times = []
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for tick in self.ticks:
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if tick.price > 0:
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prices.append(tick.price)
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times.append(tick.timestamp)
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if not prices:
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logger.warning("No price data to plot")
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return
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fig, ax = plt.subplots(figsize=(15, 8))
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ax.plot(pd.to_datetime(times), prices, 'cyan', linewidth=1)
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ax.set_title(f'Price Chart - {self.symbol}')
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ax.set_xlabel('Time')
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ax.set_ylabel('Price (USDT)')
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fig.autofmt_xdate()
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plot_filename = f"cob_price_chart_{self.symbol.replace('/', '_')}_{datetime.now():%Y%m%d_%H%M%S}.png"
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plt.savefig(plot_filename)
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logger.info(f"Price chart saved to {plot_filename}")
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plt.show()
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async def main(symbol='ETHUSDT', duration_seconds=15):
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"""Main function to run the COB test with configurable parameters.
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Args:
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symbol: Trading symbol (default: ETHUSDT)
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duration_seconds: Test duration in seconds (default: 15)
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"""
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logger.info(f"Starting COB test with symbol={symbol}, duration={duration_seconds}s")
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tester = COBStabilityTester(symbol=symbol, duration_seconds=duration_seconds)
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await tester.run_test()
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if __name__ == "__main__":
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import sys
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# Parse command line arguments
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symbol = 'ETHUSDT' # Default
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duration = 15 # Default
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if len(sys.argv) > 1:
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symbol = sys.argv[1]
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if len(sys.argv) > 2:
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try:
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duration = int(sys.argv[2])
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except ValueError:
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logger.warning(f"Invalid duration '{sys.argv[2]}', using default 15 seconds")
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logger.info(f"Configuration: Symbol={symbol}, Duration={duration}s")
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logger.info(f"Granularity: {'1 USD for ETH' if 'ETH' in symbol.upper() else '10 USD for BTC' if 'BTC' in symbol.upper() else '1 USD default'}")
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try:
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asyncio.run(main(symbol, duration))
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except KeyboardInterrupt:
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logger.info("Test interrupted by user.")
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