0.9.26 更新信号函数

waditu · Aug 11, 2023 · 8901373 · 8901373
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diff --git a/czsc/signals/__init__.py b/czsc/signals/__init__.py
@@ -101,6 +101,8 @@
     bar_limit_down_V230525,
     bar_eight_V230702,
     bar_window_std_V230731,
+    bar_window_ps_V230731,
+    bar_window_ps_V230801,
 )
 
 from czsc.signals.jcc import (

diff --git a/czsc/signals/bar.py b/czsc/signals/bar.py
@@ -1534,3 +1534,101 @@ def bar_window_std_V230731(c: CZSC, **kwargs) -> OrderedDict:
 
     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"
+
+    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)
+
+    freq = c.freq.value
+    k1, k2, k3 = f"{freq}_W{w}M{m}N{n}L{l}_支撑压力位V230731".split('_')
+    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))
+
+    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']])
+    freq = c.freq.value
+    k1, k2, k3 = f"{freq}_N{n}W{w}_支撑压力位V230801".split('_')
+
+    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)
diff --git a/examples/signals_dev/bar_window_ps_V230731.py b/examples/signals_dev/bar_window_ps_V230731.py
@@ -0,0 +1,83 @@
+import sys
+sys.path.insert(0, '.')
+sys.path.insert(0, '..')
+
+from collections import OrderedDict
+import pandas as pd
+import numpy as np
+from czsc.connectors import research
+from czsc import CZSC, check_signals_acc, get_sub_elements
+from czsc.utils import create_single_signal
+
+
+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"
+
+    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)
+
+    freq = c.freq.value
+    k1, k2, k3 = f"{freq}_W{w}M{m}N{n}L{l}_支撑压力位V230731".split('_')
+    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 main():
+    symbols = research.get_symbols('A股主要指数')
+    bars = research.get_raw_bars(symbols[0], '15分钟', '20191101', '20210101', fq='前复权')
+
+    signals_config = [
+        {'name': bar_window_ps_V230731, 'freq': '15分钟'},
+    ]
+    check_signals_acc(bars, signals_config=signals_config) # type: ignore
+
+if __name__ == '__main__':
+    main()
diff --git a/examples/signals_dev/bar_window_ps_V230801.py b/examples/signals_dev/bar_window_ps_V230801.py
@@ -0,0 +1,60 @@
+import sys
+sys.path.insert(0, '.')
+sys.path.insert(0, '..')
+
+from collections import OrderedDict
+import pandas as pd
+import numpy as np
+from czsc.connectors import research
+from czsc import CZSC, check_signals_acc, get_sub_elements
+from czsc.utils import create_single_signal
+
+
+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))
+
+    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']])
+    freq = c.freq.value
+    k1, k2, k3 = f"{freq}_N{n}W{w}_支撑压力位V230801".split('_')
+    bars = c.bars_raw[-w:]
+    pcts = [int(max((x.close - L_line) / (H_line - L_line), 0) * 10) for x in bars]
+    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)
+
+
+def main():
+    symbols = research.get_symbols('A股主要指数')
+    bars = research.get_raw_bars(symbols[0], '15分钟', '20191101', '20210101', fq='前复权')
+
+    signals_config = [
+        {'name': bar_window_ps_V230801, 'freq': '15分钟'},
+    ]
+    check_signals_acc(bars, signals_config=signals_config) # type: ignore
+
+if __name__ == '__main__':
+    main()