V0.9.26 更新一批代码 (#161)

* 0.9.26 update * 0.9.26 新增两个信号函数 * 0.9.26 update * 0.9.26 新增按持仓权重进行回测的模块 * 0.9.26 update * 0.9.26 update * 0.9.26 update * 0.9.26 update * 0.9.26 更新一批信号函数 * 0.9.26 更新信号函数 * 0.9.26 update * 0.9.26 新增信号函数 * 0.9.26 update
waditu · Aug 11, 2023 · ffc7240 · ffc7240
1 parent c431de6
commit ffc7240
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diff --git a/.github/workflows/pythonpackage.yml b/.github/workflows/pythonpackage.yml
@@ -5,7 +5,7 @@ name: Python package
 
 on:
   push:
-    branches: [ master, V0.9.25 ]
+    branches: [ master, V0.9.26 ]
   pull_request:
     branches: [ master ]
 

diff --git a/czsc/__init__.py b/czsc/__init__.py
@@ -12,24 +12,27 @@
 from czsc import aphorism
 from czsc.analyze import CZSC
 from czsc.objects import Freq, Operate, Direction, Signal, Factor, Event, RawBar, NewBar, Position
-from czsc.utils.cache import home_path, get_dir_size, empty_cache_path
+
 from czsc.traders import CzscTrader, CzscSignals, generate_czsc_signals, check_signals_acc, get_unique_signals
 from czsc.traders import PairsPerformance, combine_holds_and_pairs, combine_dates_and_pairs, stock_holds_performance
 from czsc.traders import DummyBacktest, SignalsParser, get_signals_by_conf, get_signals_config, get_signals_freqs
+from czsc.traders import WeightBacktest, get_ensemble_weight
+from czsc.sensors import holds_concepts_effect, CTAResearch, EventMatchSensor
 from czsc.strategies import CzscStrategyBase, CzscJsonStrategy
+
 from czsc.utils import KlineChart, BarGenerator, resample_bars, dill_dump, dill_load, read_json, save_json
 from czsc.utils import get_sub_elements, get_py_namespace, freqs_sorted, x_round, import_by_name, create_grid_params
 from czsc.utils import cal_trade_price, cross_sectional_ic, update_bbars, update_tbars, update_nbars
 from czsc.utils import CrossSectionalPerformance
-from czsc.sensors import holds_concepts_effect, CTAResearch, EventMatchSensor
 from czsc.utils.signal_analyzer import SignalAnalyzer, SignalPerformance
 from czsc.utils.stats import daily_performance, net_value_stats, subtract_fee
+from czsc.utils.cache import home_path, get_dir_size, empty_cache_path
 
 
-__version__ = "0.9.25"
+__version__ = "0.9.26"
 __author__ = "zengbin93"
 __email__ = "[email protected]"
-__date__ = "20230716"
+__date__ = "20230726"
 
 
 def welcome():

diff --git a/czsc/objects.py b/czsc/objects.py
@@ -12,11 +12,13 @@
 from dataclasses import dataclass, field
 from datetime import datetime
 from loguru import logger
-from typing import List, Callable, AnyStr, Dict, Optional
+from deprecated import deprecated
+from typing import List, Callable, Dict
 from czsc.enum import Mark, Direction, Freq, Operate
 from czsc.utils.corr import single_linear
 
 
+@deprecated(version="1.0.0", reason="请使用 RawBar")
 @dataclass
 class Tick:
     symbol: str
@@ -911,6 +913,7 @@ def pairs(self):
 
         return pairs
 
+    @deprecated(version="1.0.0", reason="请使用 czsc.utils.stats.evaluate_pairs")
     def evaluate_pairs(self, trade_dir: str = "多空") -> dict:
         """评估交易表现
 
@@ -1037,7 +1040,9 @@ def evaluate(self, trade_dir: str = "多空") -> dict:
         :param trade_dir: 交易方向，可选值 ['多头', '空头', '多空']
         :return: 交易表现
         """
-        p = self.evaluate_pairs(trade_dir)
+        from czsc.utils.stats import evaluate_pairs
+
+        p = evaluate_pairs(pd.DataFrame(self.pairs), trade_dir)
         p.update(self.evaluate_holds(trade_dir))
         return p
 

diff --git a/czsc/sensors/feature.py b/czsc/sensors/feature.py
@@ -138,8 +138,13 @@ def report(self):
 
 
 class FixedNumberSelector:
-    """选择固定数量（等权）的交易品种"""
-
+    """选择固定数量（等权）的交易品种
+    
+    可优化项：
+    1. 传入 res_path, 将分析过程和分析结果保存下来
+    2. 支持传入大盘择时信号，例如：大盘择时信号为空头时，多头只平不开
+    """
+
     def __init__(self, dfs, k, d, **kwargs):
         """
         

diff --git a/czsc/signals/__init__.py b/czsc/signals/__init__.py
@@ -65,6 +65,8 @@
     vol_double_ma_V230214,
     vol_ti_suo_V221216,
     vol_gao_di_V221218,
+    vol_window_V230731,
+    vol_window_V230801,
 )
 
 from czsc.signals.bar import (
@@ -98,6 +100,9 @@
     bar_shuang_fei_V230507,
     bar_limit_down_V230525,
     bar_eight_V230702,
+    bar_window_std_V230731,
+    bar_window_ps_V230731,
+    bar_window_ps_V230801,
 )
 
 from czsc.signals.jcc import (
@@ -184,13 +189,15 @@
     tas_low_trend_V230627,
     tas_atr_V230630,
     tas_accelerate_V230531,
+    tas_angle_V230802,
 
     tas_rumi_V230704,
     tas_macd_dist_V230408,
     tas_macd_dist_V230409,
     tas_macd_dist_V230410,
     cat_macd_V230518,
     cat_macd_V230520,
+    tas_macd_bc_V230803,
 )
 
 from czsc.signals.pos import (
@@ -200,6 +207,8 @@
     pos_bar_stop_V230524,
     pos_fix_exit_V230624,
     pos_profit_loss_V230624,
+    pos_status_V230808,
+    pos_holds_V230807,
 )
 
 

diff --git a/czsc/signals/bar.py b/czsc/signals/bar.py
@@ -1468,3 +1468,167 @@ def bar_eight_V230702(c: CZSC, **kwargs) -> OrderedDict:
         v1 = "转折平衡市"
 
     return create_single_signal(k1=k1, k2=k2, k3=k3, v1=v1)
+
+
+def bar_window_std_V230731(c: CZSC, **kwargs) -> OrderedDict:
+    """指定窗口内波动率的特征
+
+    参数模板："{freq}_D{di}W{window}M{m}N{n}_窗口波动V230731"
+
+    **信号逻辑：**
+
+    滚动计算最近m根K线的波动率，分成n层，最大值为n，最小值为1；
+    最近window根K线的最大值为max_layer，最小值为min_layer。
+    以这两个值作为窗口内的波动率特征。
+
+    **信号列表：**
+
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N7_低波N6_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N6_低波N6_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N8_低波N6_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N9_低波N6_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N9_低波N9_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N9_低波N8_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N8_低波N8_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N8_低波N7_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N7_低波N7_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N7_低波N5_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N6_低波N5_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N5_低波N4_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N5_低波N3_任意_0')
+    - Signal('60分钟_D2W3M100N10_窗口波动V230731_高波N4_低波N3_任意_0')
+
+    :param c: CZSC对象
+    :param kwargs: 参数字典
+    
+        - :param di: 信号计算截止倒数第i根K线
+        - :param w: 观察的窗口大小。
+        - :param m: 计算分位数所需取K线的数量。
+        - :param n: 分层的数量。
+
+    :return: 信号识别结果
+    """
+    di = int(kwargs.get("di", 1))
+    w = int(kwargs.get("w", 5))
+    m = int(kwargs.get("m", 100))
+    n = int(kwargs.get("n", 10))
+
+    # 更新STD20波动率缓存
+    cache_key = "STD20"
+    for i, bar in enumerate(c.bars_raw):
+        if cache_key in bar.cache:
+            continue
+        bar.cache[cache_key] = 0 if i < 5 else np.std([x.close for x in c.bars_raw[max(i-20, 0):i]])
+
+    freq = c.freq.value
+    k1, k2, k3 = f"{freq}_D{di}W{w}M{m}N{n}_窗口波动V230731".split('_')
+    v1 = "其他"
+
+    if len(c.bars_raw) < di + m + w:
+        return create_single_signal(k1=k1, k2=k2, k3=k3, v1=v1)
+
+    stds = [x.cache[cache_key] for x in get_sub_elements(c.bars_raw, di=di, n=m)]
+    layer = pd.qcut(stds, n, labels=False, duplicates='drop')
+    max_layer = max(layer[-w:]) + 1
+    min_layer = min(layer[-w:]) + 1
+
+    v1, v2 = f"高波N{max_layer}", f"低波N{min_layer}"
+    return create_single_signal(k1=k1, k2=k2, k3=k3, v1=v1, v2=v2)
+
+
+
+def bar_window_ps_V230731(c: CZSC, **kwargs) -> OrderedDict:
+    """指定窗口内支撑压力位分位数计算，贡献者：chenlei
+
+    参数模板："{freq}_W{w}M{m}N{n}L{l}_支撑压力位V230731"
+
+    **信号逻辑：**
+
+    1. 计算最近 N 笔的最高价 NH 和最低价 NL，这个可以近似理解成价格的支撑和压力位
+    2. 计算并缓存最新K线的收盘价格 C 处于 NH、NL 之间的位置，计算方法为 P = （C - NL）/ (NH - NL)
+    3. 取最近 M 个 P 值序列，按分位数分层，分层数量为 L，分层的最大值为最近的压力，最小值为最近的支撑，当前值为最近的价格位置
+
+    **信号列表：**
+
+    - Signal('15分钟_W5M40N8L5_支撑压力位V230731_压力N5_支撑N5_当前N5_0')
+    - Signal('15分钟_W5M40N8L5_支撑压力位V230731_压力N5_支撑N4_当前N5_0')
+    - Signal('15分钟_W5M40N8L5_支撑压力位V230731_压力N5_支撑N4_当前N4_0')
+    - Signal('15分钟_W5M40N8L5_支撑压力位V230731_压力N5_支撑N3_当前N5_0')
+    - Signal('15分钟_W5M40N8L5_支撑压力位V230731_压力N5_支撑N2_当前N2_0')
+    - Signal('15分钟_W5M40N8L5_支撑压力位V230731_压力N5_支撑N1_当前N2_0')
+
+    :param c: CZSC对象
+    :param kwargs: 参数字典
+
+        - :param w: 评价分位数分布用的窗口大小
+        - :param m: 计算分位数所需取K线的数量。
+        - :param n: 最近N笔
+        - :param l: 分层的数量。
+
+    :return: 信号识别结果
+    """
+    w = int(kwargs.get("w", 5))
+    m = int(kwargs.get("m", 40))
+    n = int(kwargs.get("n", 8))
+    l = int(kwargs.get("l", 5))
+
+    assert m > l * 2 > 2, "参数 m 必须大于 l * 2，且 l 必须大于 2"
+    assert w < m, "参数 w 必须小于 m"
+
+    freq = c.freq.value
+    k1, k2, k3 = f"{freq}_W{w}M{m}N{n}L{l}_支撑压力位V230731".split('_')
+    if len(c.bi_list) <  n+2:
+        return create_single_signal(k1=k1, k2=k2, k3=k3, v1="其他")
+
+    # 更新支撑压力位位置
+    cache_key_pct = "pct"
+    H_line, L_line = max([x.high for x in c.bi_list[-n:]]), min([x.low for x in c.bi_list[-n:]])
+    for i, bar in enumerate(c.bars_raw):
+        if cache_key_pct in bar.cache:
+            continue  
+        bar.cache[cache_key_pct] = (bar.close - L_line) / (H_line - L_line)
+
+    fenweis = [x.cache[cache_key_pct] for x in get_sub_elements(c.bars_raw, n=m)]
+    layer = pd.qcut(fenweis, l, labels=False, duplicates='drop')
+    max_layer = max(layer[-w:]) + 1
+    min_layer = min(layer[-w:]) + 1
+
+    v1, v2, v3 = f"压力N{max_layer}", f"支撑N{min_layer}", f"当前N{layer[-1]+1}"
+    return create_single_signal(k1=k1, k2=k2, k3=k3, v1=v1, v2=v2, v3=v3)
+
+
+def bar_window_ps_V230801(c: CZSC, **kwargs) -> OrderedDict:
+    """指定窗口内支撑压力位分位数计算
+
+    参数模板："{freq}_N{n}W{w}_支撑压力位V230801"
+
+    **信号逻辑：**
+
+    1. 计算最近 N 笔的最高价 NH 和最低价 NL，这个可以近似理解成价格的支撑和压力位
+    2. 计算并缓存最新K线的收盘价格 C 处于 NH、NL 之间的位置，计算方法为 P = （C - NL）/ (NH - NL)
+    3. 取最近 M 个 P 值序列，四舍五入精确到小数点后1位，作为当前K线的分位数
+
+    **信号列表：**
+
+    :param c: CZSC对象
+    :param kwargs: 参数字典
+
+        - :param w: 评价分位数分布用的窗口大小
+        - :param n: 最近N笔
+
+    :return: 信号识别结果
+    """
+    w = int(kwargs.get("w", 5))
+    n = int(kwargs.get("n", 8))
+
+    freq = c.freq.value
+    k1, k2, k3 = f"{freq}_N{n}W{w}_支撑压力位V230801".split('_')
+    if len(c.bi_list) < n+2:
+        return create_single_signal(k1=k1, k2=k2, k3=k3, v1="其他")
+
+    ubi = c.ubi
+    H_line, L_line = max([x.high for x in c.bi_list[-n:]] + [ubi['high']]), min([x.low for x in c.bi_list[-n:]] + [ubi['low']])
+
+    pcts = [int(max((x.close - L_line) / (H_line - L_line), 0) * 10) for x in c.bars_raw[-w:]]
+    v1, v2, v3 = f"最大N{max(pcts)}", f"最小N{min(pcts)}", f"当前N{pcts[-1]}"
+    return create_single_signal(k1=k1, k2=k2, k3=k3, v1=v1, v2=v2, v3=v3)