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visual: redesign bottom panel, price axis cleanup and bid/ask indicator

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- Bottom panel: dual bid/ask bars per cluster (red=sell, blue=buy) with white volume label inside and delta block below
- Price axis: labels every 10 rows (~7.5pts) instead of every row — cleaner, closer to original
- Price axis: bid/ask spread boxes with arrow indicator (shows on live market open)
- Price axis zoom: inverted so drag-up = zoom in, matching original behavior
- Current price line rendered last (always on top of all bars)
- Bar colors: corrected — ask (buy) = blue, bid (sell) = pink
- Backend: close_time field added to cluster JSON; bar_volume M1 annotation (triggers after replay)
- Backend: last_bid/ask tracked and injected into active cluster WS message

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
rufinomec-afk
2026-06-06 15:53:05 -03:00
co-authored by Claude Sonnet 4.6
parent 11a0921e20
commit 54f269b0ce
4 changed files with 224 additions and 90 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend/aggregator.py
+4
View File
@@ -18,6 +18,7 @@ class FootprintCluster:
self.total_delta: float = 0.0
self.total_volume: float = 0.0
self.total_ticks: int = 0
self.close_time: Optional[int] = None
# levels: price_float -> { 'ask': float, 'bid': float }
# internally we keep float keys to make sorting and arithmetic easy
@@ -40,6 +41,7 @@ class FootprintCluster:
self.open_price = price
self.close_price = price
self.close_time = timestamp_msc
self.total_ticks += 1
# Round price to the nearest tick_size to avoid float precision issues
@@ -316,9 +318,11 @@ class FootprintCluster:
"high": float(self.high) if self.high is not None else None,
"low": float(self.low) if self.low is not None else None,
"poc": float(self.poc) if self.poc is not None else None,
"close_time": int(self.close_time) if self.close_time is not None else None,
"total_delta": float(self.total_delta),
"total_volume": float(self.total_volume),
"total_ticks": int(self.total_ticks),
"bar_volume": None,
"levels": levels_str,
"stacked": {
"buy": bool(self.stacked.get("buy", False)),
backend/mt5_collector.py
+74
View File
@@ -25,6 +25,9 @@ class MT5Collector:
self.seen_ticks_buffer = set()
self.last_mid_price = 0.0
self.last_is_buy = True
self.last_bid = 0.0
self.last_ask = 0.0
self._history_annotated = False
async def connect_mt5(self) -> bool:
"""
@@ -130,6 +133,11 @@ class MT5Collector:
await self.disconnect_mt5()
continue
# Annotate history once replay is complete (first under-full batch = caught up)
if not self._history_annotated and len(ticks) < 1000:
self._history_annotated = True
await self.annotate_history_bar_volume()
if len(ticks) > 0:
logger.info(f"Fetched {len(ticks)} ticks starting at {ticks[0]['time_msc']}")
for tick in ticks:
@@ -153,6 +161,8 @@ class MT5Collector:
ask_price = float(tick['ask'])
last_price = float(tick['last'])
if bid_price > 0: self.last_bid = bid_price
if ask_price > 0: self.last_ask = ask_price
mid_price = (bid_price + ask_price) / 2.0 if (bid_price > 0 and ask_price > 0) else 0.0
prev_mid = self.last_mid_price
@@ -189,7 +199,22 @@ class MT5Collector:
# flooding the WebSocket during historical replay
import time as _time
is_live = ((_time.time() * 1000) - msc) < 10_000
# Annotate live closed clusters with M1 bar volume
if is_live and closed_json and closed_json.get('open_time') and closed_json.get('close_time'):
bar_vol = await self.fetch_bar_volume(
closed_json['open_time'], closed_json['close_time']
)
closed_json['bar_volume'] = bar_vol
# Sync back to history buffer
for h in self.aggregator.history:
if h['cluster_id'] == closed_json['cluster_id']:
h['bar_volume'] = bar_vol
break
if is_live:
active_json['bid'] = self.last_bid
active_json['ask'] = self.last_ask
self.on_update_callback(active_json, closed_json)
await asyncio.sleep(0.1)
@@ -200,6 +225,55 @@ class MT5Collector:
await self.disconnect_mt5()
await asyncio.sleep(2.0)
async def fetch_bar_volume(self, open_time_msc: int, close_time_msc: int) -> int:
"""Sum tick_volume of M1 bars that overlap with the cluster's time range."""
from datetime import datetime
# Expand range by 1 minute on each side to capture partial bars
open_dt = datetime.fromtimestamp((open_time_msc - 60_000) / 1000.0)
close_dt = datetime.fromtimestamp((close_time_msc + 60_000) / 1000.0)
rates = await asyncio.to_thread(
mt5.copy_rates_range, self.symbol, mt5.TIMEFRAME_M1, open_dt, close_dt
)
if rates is None or len(rates) == 0:
return 0
total = 0
for r in rates:
bar_start_msc = int(r['time']) * 1000
bar_end_msc = bar_start_msc + 60_000
# Count bar if it overlaps with cluster period
if bar_start_msc < close_time_msc and bar_end_msc > open_time_msc:
total += int(r['tick_volume'])
return total
async def annotate_history_bar_volume(self):
"""Batch-fetch M1 bars and annotate all history clusters with bar_volume."""
if not self.aggregator.history:
return
first_open = self.aggregator.history[0].get('open_time') or 0
last_close = self.aggregator.history[-1].get('close_time') or self.aggregator.history[-1].get('open_time') or 0
if not first_open or not last_close:
return
from datetime import datetime
open_dt = datetime.fromtimestamp((first_open - 60_000) / 1000.0)
close_dt = datetime.fromtimestamp((last_close + 60_000) / 1000.0)
all_rates = await asyncio.to_thread(
mt5.copy_rates_range, self.symbol, mt5.TIMEFRAME_M1, open_dt, close_dt
)
if all_rates is None or len(all_rates) == 0:
logger.warning("annotate_history_bar_volume: no M1 bars returned")
return
for cluster in self.aggregator.history:
c_open = cluster.get('open_time') or 0
c_close = cluster.get('close_time') or c_open
total = 0
for r in all_rates:
bar_start_msc = int(r['time']) * 1000
bar_end_msc = bar_start_msc + 60_000
if bar_start_msc < c_close and bar_end_msc > c_open:
total += int(r['tick_volume'])
cluster['bar_volume'] = total
logger.info(f"annotate_history_bar_volume: annotated {len(self.aggregator.history)} clusters")
async def stop(self):
self.running = False
await self.disconnect_mt5()