添加 StructureZone 结构价值区系统，支持多周期支撑/阻力分析
- 新增 ChanZone.py: 从笔中枢/线段中枢/EMA52 提取价格区，聚类评分 - ChanLun.py 新增 get_structure_zones() 方法 - web/app.py: 独立拉取多周期数据 + 缓存 + limit 传参避免全量传输 - web/index.html: 结构区勾选框 + K线数量输入 + 半透明填充区绘制 - tests/test_chan_zone.py: 24 个单元测试 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
jackyu66git
co-authored by
Claude Opus 4.6
Claude Opus 4.6
parent
d8069e977f
commit
ebcb3dce73
+129
-3
@@ -12,6 +12,7 @@ import io
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import base64
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import time
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import traceback
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from pytz import timezone
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import talib.abstract as ta
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import numpy as np
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@@ -22,6 +23,7 @@ from ChanLun import ChanLun, TF_DF
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from ChanEnum import Chan_BI_DIR, Chan_SEG_DIR, Chan_KLC_FX, Chan_FX_TYPE, Chan_MACDSEG_DIR, Chan_MACDHISTSET_DIR
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from cn_stock_data import ChinaStockData
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from ChanMACD import ChanMACD
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from ChanZone import StructureZoneConfig, analyze_structure_zones_from_serialized
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# 添加买卖点枚举类型
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class TRADE_POINT_TYPE:
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@@ -48,9 +50,22 @@ china_stock = ChinaStockData()
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logger = logging.getLogger(__name__)
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DATA_SERVICE_URL = os.environ.get("DATA_SERVICE_URL", os.environ.get("DATASVC_URL", "http://127.0.0.1:9009"))
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#DATA_SERVICE_URL = os.environ.get("DATA_SERVICE_URL", os.environ.get("DATASVC_URL", "http://192.168.1.9:9009"))
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#DATA_SERVICE_URL = os.environ.get("DATA_SERVICE_URL", os.environ.get("DATASVC_URL", "http://103.179.242.166"))
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# 结构价值区缓存: {tf_name: {'data': ..., 'expires': timestamp}}
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_zone_cache = {}
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def _zone_cache_ttl(tf_name: str) -> int:
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"""根据时间周期返回缓存过期时间（秒）"""
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minutes = timeframe_to_minutes(tf_name) or 5
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if minutes <= 5:
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return 120 # 5m及以下: 2分钟
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elif minutes <= 15:
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return 300 # 15m: 5分钟
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elif minutes <= 60:
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return 600 # 1h: 10分钟
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else:
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return 1800 # 4h+: 30分钟
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DATA_SERVICE_URL = os.environ.get("DATA_SERVICE_URL", os.environ.get("DATASVC_URL", "http://103.179.242.166"))
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DEFAULT_TIMEFRAME_LABELS = OrderedDict([
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("1m", "1分钟"),
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@@ -185,6 +200,8 @@ def _fetch_kl_from_datasvc(symbol, timeframe, start_ms=None, end_ms=None, limit=
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params["start"] = int(start_ms)
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if end_ms is not None:
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params["end"] = int(end_ms)
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if limit is not None:
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params["limit"] = limit
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resp = requests.get(f"{DATA_SERVICE_URL}/api/candles", params=params, timeout=10)
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resp.raise_for_status()
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data = resp.json()
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@@ -1778,6 +1795,115 @@ def analyze():
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pass
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# 结构价值区分析（Structure Zone）—— 独立拉取多周期数据，缓存避免重复请求
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zone_timeframes_str = request.args.get('zone_timeframes', '')
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zone_kl_lines = int(request.args.get('zone_kl_lines', 1000))
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try:
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zone_config = StructureZoneConfig(kl_lines_per_tf=zone_kl_lines)
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if zone_timeframes_str:
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zone_config.zone_timeframes = [t.strip() for t in zone_timeframes_str.split(',') if t.strip()]
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analyses = {}
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ema52_dict = {}
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latest_close = 0.0
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now = time.time()
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def _fetch_single_tf_zone(tf_name):
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"""单个时间周期的结构区数据拉取（线程安全）"""
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cache_key = f"{symbol}:{tf_name}:{zone_kl_lines}"
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cached = _zone_cache.get(cache_key)
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if cached and cached['expires'] > now:
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print(f" 结构区缓存命中: {tf_name}")
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return {
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'tf_name': tf_name,
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'analyses': cached['analyses'],
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'ema52': cached['ema52'],
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'close': cached.get('close', 0.0),
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'cached': True,
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}
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try:
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tf_df = get_kl_data(symbol, tf_name, limit=zone_kl_lines)
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if tf_df is None or len(tf_df) == 0:
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return None
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tf_df = add_indicators(tf_df)
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tf_analysis = analyze_chan(tf_df, symbol, tf_name)
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zs_serialized = [{
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'start_time': (zs.start_klc.end_time if isinstance(zs.start_klc.end_time, str) else zs.start_klc.end_time.astimezone(client_tz).isoformat()) if zs.start_klc else None,
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'end_time': (zs.end_klc.end_time if isinstance(zs.end_klc.end_time, str) else zs.end_klc.end_time.astimezone(client_tz).isoformat()) if zs.end_klc else None,
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'zg': zs.zg, 'zd': zs.zd, 'gg': zs.gg, 'dd': zs.dd,
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'is_sure': zs.is_sure
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} for zs in tf_analysis.get('zs_list', []) if zs.is_sure]
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bi_zs_serialized = [{
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'start_time': ((zs.start_klc.end_time if isinstance(zs.start_klc.end_time, str) else zs.start_klc.end_time.astimezone(client_tz).isoformat()) if getattr(zs.start_klc, 'end_time', None) else (zs.start_klc.start_time if isinstance(zs.start_klc.start_time, str) else zs.start_klc.start_time.astimezone(client_tz).isoformat())),
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'end_time': (zs.end_time if isinstance(zs.end_time, str) else zs.end_time.astimezone(client_tz).isoformat()) if getattr(zs, 'end_time', None) else None,
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'zg': zs.zg, 'zd': zs.zd, 'gg': zs.gg, 'dd': zs.dd,
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'is_sure': bool(getattr(zs, 'is_sure', False))
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} for zs in tf_analysis.get('bi_zs_list', []) if getattr(zs, 'is_sure', False)]
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last_ema = tf_df['ema52'].iloc[-1] if 'ema52' in tf_df.columns else 0
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ema_val = float(last_ema) if last_ema and last_ema > 0 else None
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last_close = float(tf_df['close'].iloc[-1])
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tf_result = {
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'tf_name': tf_name,
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'analyses': {'zs_list': zs_serialized, 'bi_zs_list': bi_zs_serialized},
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'ema52': ema_val,
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'close': last_close,
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'cached': False,
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}
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# 写入缓存
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_zone_cache[cache_key] = {
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'analyses': tf_result['analyses'],
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'ema52': ema_val,
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'close': last_close,
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'expires': now + _zone_cache_ttl(tf_name),
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}
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print(f" 结构区数据: {tf_name} -> zs={len(zs_serialized)}, bi_zs={len(bi_zs_serialized)}, ema52={ema_val}")
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return tf_result
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except Exception as e:
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print(f" 结构区 {tf_name} 拉取失败: {e}")
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return None
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with ThreadPoolExecutor(max_workers=len(zone_config.zone_timeframes)) as executor:
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futures = {executor.submit(_fetch_single_tf_zone, tf): tf for tf in zone_config.zone_timeframes}
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for future in as_completed(futures):
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tf_result = future.result()
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if tf_result is None:
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continue
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tf_name = tf_result['tf_name']
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analyses[tf_name] = tf_result['analyses']
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ema52_dict[tf_name] = tf_result['ema52']
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if tf_result['close'] and (not latest_close or latest_close == 0.0):
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latest_close = tf_result['close']
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structure_zones = analyze_structure_zones_from_serialized(
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analyses, ema52_dict, latest_close, config=zone_config
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)
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result['structure_zones'] = [{
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'id': z.id,
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'lower': z.lower,
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'upper': z.upper,
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'center': z.center,
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'width_pct': z.width_pct,
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'zone_type': z.zone_type,
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'timeframes': z.timeframes,
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'structure_types': z.structure_types,
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'boundary_types': z.boundary_types,
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'overlap_count': z.overlap_count,
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'touch_count': z.touch_count,
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'recency_score': z.recency_score,
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'ema52_distance_pct': z.ema52_distance_pct,
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'ema52_aligned': z.ema52_aligned,
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'strength_score': z.strength_score,
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'confidence': z.confidence,
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'first_seen': z.first_seen,
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'last_seen': z.last_seen,
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'metadata': z.metadata,
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} for z in structure_zones]
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except Exception as e:
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print(f"StructureZone 分析出错: {e}")
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import traceback
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traceback.print_exc()
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result['structure_zones'] = []
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return jsonify(result)
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@app.route('/api/symbols')
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