添加了次次周期的显示
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jackyu66git
+112
-1
@@ -1180,6 +1180,16 @@ def index():
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else:
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default_element = default_main
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# 次次周期默认比次周期小一档
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if timeframe_keys:
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try:
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idx_el = timeframe_keys.index(default_element)
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default_sub_sub = timeframe_keys[idx_el - 1] if idx_el > 0 else timeframe_keys[0]
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except ValueError:
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default_sub_sub = timeframe_keys[0]
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else:
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default_sub_sub = default_element
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default_symbol = 'BTC/USDT:USDT' if 'BTC/USDT:USDT' in symbols else (symbols[0] if symbols else '')
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return render_template(
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@@ -1189,6 +1199,7 @@ def index():
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a_stock_symbols=A_STOCK_SYMBOLS,
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default_main_timeframe=default_main,
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default_element_timeframe=default_element,
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default_sub_sub_timeframe=default_sub_sub,
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default_symbol=default_symbol,
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timeframe_keys_json=json.dumps(timeframe_keys),
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data_service_available=DATA_SERVICE_AVAILABLE,
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@@ -1211,8 +1222,9 @@ def analyze():
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# 获取客户端请求的时区
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client_timezone = request.args.get('timezone', 'Asia/Shanghai')
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# 获取分形元素时间周期
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# 获取分形元素时间周期与次次周期
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element_timeframe = request.args.get('element_timeframe')
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sub_sub_timeframe = request.args.get('sub_sub_timeframe')
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# 获取是否只需要分形元素数据的参数
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elements_only_param = request.args.get('elements_only')
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@@ -1221,6 +1233,9 @@ def analyze():
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# 验证小周期是否小于主周期
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if element_timeframe and not is_smaller_or_equal_timeframe(element_timeframe, timeframe):
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return jsonify({'error': '分形元素时间周期必须小于或等于主图表时间周期'})
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# 验证次次周期是否小于等于次周期
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if sub_sub_timeframe and element_timeframe and not is_smaller_or_equal_timeframe(sub_sub_timeframe, element_timeframe):
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return jsonify({'error': '次次周期必须小于或等于次周期'})
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# 获取数据
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df = get_kl_data(symbol, timeframe, start_time=start_time, end_time=end_time)
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@@ -1597,6 +1612,102 @@ def analyze():
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'zs_count': int(bsp.zs_count) if hasattr(bsp, 'zs_count') else 0
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} for bsp in element_analysis.get('bsp_list', [])]
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# 次次周期：仅当已指定次周期且次次周期有效时获取
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if sub_sub_timeframe and is_smaller_or_equal_timeframe(sub_sub_timeframe, element_timeframe):
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sub_sub_df = get_kl_data(symbol, sub_sub_timeframe, start_time=start_time, end_time=end_time)
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if sub_sub_df is not None and len(sub_sub_df) > 0:
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sub_sub_df = add_indicators(sub_sub_df)
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sub_sub_analysis = analyze_chan(sub_sub_df, symbol, sub_sub_timeframe)
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result['sub_sub_timeframe'] = sub_sub_timeframe
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result['sub_sub_bi_list'] = [{
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'start_time': bi.start_klc.end_time if isinstance(bi.start_klc.end_time, str) else bi.start_klc.end_time.astimezone(client_tz).isoformat(),
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'end_time': (bi.end_klc.end_time if isinstance(bi.end_klc.end_time, str) else bi.end_klc.end_time.astimezone(client_tz).isoformat()) if bi.end_klc else None,
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'sure_time': format_time_safely(bi.sure_time, client_tz) if bi.sure_time else None,
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'start_price': bi.start_klc.low if convert_direction(bi.dir) == 1 else bi.start_klc.high,
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'end_price': bi.end_klc.high if convert_direction(bi.dir) == 1 else bi.end_klc.low if bi.end_klc else None,
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'direction': convert_direction(bi.dir),
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'macd_div': float(bi.macd_div) if hasattr(bi, 'macd_div') else 0
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} for bi in sub_sub_analysis['bi_list'] if bi.end_klc]
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result['sub_sub_uncompleted_bi_list'] = [{
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'start_time': bi.start_klc.end_time if isinstance(bi.start_klc.end_time, str) else bi.start_klc.end_time.astimezone(client_tz).isoformat(),
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'end_time': None,
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'sure_time': format_time_safely(bi.sure_time, client_tz) if bi.sure_time else None,
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'start_price': bi.start_klc.low if convert_direction(bi.dir) == 1 else bi.start_klc.high,
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'end_price': None,
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'direction': convert_direction(bi.dir),
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'macd_div': float(bi.macd_div) if hasattr(bi, 'macd_div') else 0
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} for bi in sub_sub_analysis['bi_list'] if not bi.end_klc]
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result['sub_sub_seg_list'] = [{
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'start_time': seg.start_bi.start_klc.end_time if isinstance(seg.start_bi.start_klc.end_time, str) else seg.start_bi.start_klc.end_time.astimezone(client_tz).isoformat(),
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'end_time': (seg.end_bi.end_klc.end_time if isinstance(seg.end_bi.end_klc.end_time, str) else seg.end_bi.end_klc.end_time.astimezone(client_tz).isoformat()) if seg.end_bi else None,
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'sure_time': format_time_safely(seg.sure_time, client_tz) if seg.sure_time else None,
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'start_price': seg.start_bi.start_klc.low if convert_direction(seg.dir) == 1 else seg.start_bi.start_klc.high,
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'end_price': seg.end_bi.end_klc.high if convert_direction(seg.dir) == 1 else seg.end_bi.end_klc.low if seg.end_bi else None,
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'direction': convert_direction(seg.dir)
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} for seg in sub_sub_analysis['seg_list'] if seg.is_sure]
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result['sub_sub_uncompleted_seg_list'] = get_uncompleted_seg_list(sub_sub_analysis['seg_list'], client_tz)
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result['sub_sub_zs_list'] = [{
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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(),
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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, 'is_sure': zs.is_sure
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} for zs in sub_sub_analysis['zs_list'] if zs.end_klc]
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result['sub_sub_uncompleted_zs_list'] = [{
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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(),
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'end_time': None, 'zg': zs.zg, 'zd': zs.zd, 'gg': zs.gg, 'dd': zs.dd, 'is_sure': zs.is_sure
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} for zs in sub_sub_analysis['zs_list'] if not zs.is_sure]
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result['sub_sub_bi_zs_list'] = [{
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'start_time': (
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(zs.start_klc.end_time if isinstance(zs.start_klc.end_time, str) else zs.start_klc.end_time.astimezone(client_tz).isoformat())
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if getattr(zs.start_klc, 'end_time', None) else
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(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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),
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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, 'is_sure': bool(getattr(zs, 'is_sure', False))
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} for zs in sub_sub_analysis.get('bi_zs_list', []) if getattr(zs, 'is_sure', False)]
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result['sub_sub_uncompleted_bi_zs_list'] = [{
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'start_time': (
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(zs.start_klc.end_time if isinstance(zs.start_klc.end_time, str) else zs.start_klc.end_time.astimezone(client_tz).isoformat())
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if getattr(zs.start_klc, 'end_time', None) else
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(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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),
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'end_time': None, 'zg': zs.zg, 'zd': zs.zd, 'gg': zs.gg, 'dd': zs.dd, 'is_sure': bool(getattr(zs, 'is_sure', False))
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} for zs in sub_sub_analysis.get('bi_zs_list', []) if not getattr(zs, 'is_sure', False)]
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result['sub_sub_klc_fx_info'] = [{
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'time': format_time_safely(point['time'], client_tz),
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'price': float(point['price']),
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'fx_type': point['fx_type'],
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'is_bottom': bool(point['is_bottom']),
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'fx_strength': float(point['fx_strength']),
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'fx_strength_level': str(point['fx_strength_level']),
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'is_strong_fx': bool(point['is_strong_fx'])
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} for point in sub_sub_analysis['klc_fx_info']]
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result['sub_sub_bsp_list'] = [{
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'time': format_time_safely(bsp.end_time, client_tz),
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'price': float(bsp.klc.low if str(bsp.dir) == 'Chan_BSP_DIR.BUY' else bsp.klc.high),
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'type': str(bsp.type).replace('Chan_BSP_TYPE.', ''),
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'dir': str(bsp.dir).replace('Chan_BSP_DIR.', ''),
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'is_sure': bool(bsp.is_sure),
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'sure_time': format_time_safely(bsp.sure_time, client_tz) if bsp.sure_time else None,
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'zs_count': int(bsp.zs_count) if hasattr(bsp, 'zs_count') else 0
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} for bsp in sub_sub_analysis.get('bsp_list', [])]
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result['sub_sub_chan_macd'] = serialize_chan_macd_data(sub_sub_analysis.get('chan_macd', {}), client_tz)
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try:
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sub_sub_klc_trend = []
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for klc in sub_sub_analysis.get('klc_list', []):
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trend_val = getattr(klc, 'trend', None)
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t_obj = getattr(klc, 'end_time', None) or getattr(klc, 'start_time', None)
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if trend_val is None or t_obj is None:
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continue
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trend_name = str(trend_val)
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if '.' in trend_name:
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trend_name = trend_name.split('.')[-1]
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time_str = format_time_safely(t_obj, client_tz)
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if time_str:
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sub_sub_klc_trend.append({'time': time_str, 'trend': trend_name})
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result['sub_sub_klc_trend'] = sub_sub_klc_trend
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except Exception:
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result['sub_sub_klc_trend'] = []
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pass
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return jsonify(result)
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