.\pandas-ta\pandas_ta\candles\cdl_inside.py
# -*- coding: utf-8 -*- # 从 pandas_ta.utils 中导入 candle_color 和 get_offset 函数 from pandas_ta.utils import candle_color, get_offset # 从 pandas_ta.utils 中导入 verify_series 函数 from pandas_ta.utils import verify_series # 定义函数 cdl_inside，用于识别 Inside Bar 蜡烛形态 def cdl_inside(open_, high, low, close, asbool=False, offset=None, **kwargs): """Candle Type: Inside Bar""" # 验证参数是否为 Series 类型 open_ = verify_series(open_) high = verify_series(high) low = verify_series(low) close = verify_series(close) # 获取偏移量 offset = get_offset(offset) # 计算结果 inside = (high.diff() < 0) & (low.diff() > 0) # 如果 asbool 为 False，则将结果乘以蜡烛颜色 if not asbool: inside *= candle_color(open_, close) # 偏移结果 if offset != 0: inside = inside.shift(offset) # 处理填充 if "fillna" in kwargs: inside.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: inside.fillna(method=kwargs["fill_method"], inplace=True) # 设置结果的名称和类别 inside.name = f"CDL_INSIDE" inside.category = "candles" return inside # 设置 cdl_inside 函数的文档字符串 cdl_inside.__doc__ = \ """Candle Type: Inside Bar An Inside Bar is a bar that is engulfed by the prior highs and lows of it's previous bar. In other words, the current bar is smaller than it's previous bar. Set asbool=True if you want to know if it is an Inside Bar. Note by default asbool=False so this returns a 0 if it is not an Inside Bar, 1 if it is an Inside Bar and close > open, and -1 if it is an Inside Bar but close < open. Sources: https://www.tradingview.com/script/IyIGN1WO-Inside-Bar/ Calculation: Default Inputs: asbool=False inside = (high.diff() < 0) & (low.diff() > 0) if not asbool: inside *= candle_color(open_, close) Args: open_ (pd.Series): Series of 'open's high (pd.Series): Series of 'high's low (pd.Series): Series of 'low's close (pd.Series): Series of 'close's asbool (bool): Returns the boolean result. Default: False offset (int): How many periods to offset the result. Default: 0 Kwargs: fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method Returns: pd.Series: New feature """
.\pandas-ta\pandas_ta\candles\cdl_pattern.py
# -*- coding: utf-8 -*- # 导入必要的类型和模块 from typing import Sequence, Union from pandas import Series, DataFrame # 从当前目录下的文件中导入指定函数 from . import cdl_doji, cdl_inside # 从 pandas_ta.utils 模块中导入 get_offset 和 verify_series 函数 from pandas_ta.utils import get_offset, verify_series # 从 pandas_ta 模块中导入 Imports 对象 from pandas_ta import Imports # 定义所有的蜡烛图形式样 ALL_PATTERNS = [ "2crows", "3blackcrows", "3inside", "3linestrike", "3outside", "3starsinsouth", "3whitesoldiers", "abandonedbaby", "advanceblock", "belthold", "breakaway", "closingmarubozu", "concealbabyswall", "counterattack", "darkcloudcover", "doji", "dojistar", "dragonflydoji", "engulfing", "eveningdojistar", "eveningstar", "gapsidesidewhite", "gravestonedoji", "hammer", "hangingman", "harami", "haramicross", "highwave", "hikkake", "hikkakemod", "homingpigeon", "identical3crows", "inneck", "inside", "invertedhammer", "kicking", "kickingbylength", "ladderbottom", "longleggeddoji", "longline", "marubozu", "matchinglow", "mathold", "morningdojistar", "morningstar", "onneck", "piercing", "rickshawman", "risefall3methods", "separatinglines", "shootingstar", "shortline", "spinningtop", "stalledpattern", "sticksandwich", "takuri", "tasukigap", "thrusting", "tristar", "unique3river", "upsidegap2crows", "xsidegap3methods" ] # 定义函数 cdl_pattern，接收开盘价、最高价、最低价、收盘价等参数，返回 DataFrame 类型 def cdl_pattern(open_, high, low, close, name: Union[str, Sequence[str]]="all", scalar=None, offset=None, **kwargs) -> DataFrame: """Candle Pattern""" # 验证参数 open_ = verify_series(open_) high = verify_series(high) low = verify_series(low) close = verify_series(close) offset = get_offset(offset) scalar = float(scalar) if scalar else 100 # pandas-ta 中已实现的蜡烛图形式样 pta_patterns = { "doji": cdl_doji, "inside": cdl_inside, } # 如果 name 参数为 "all"，则将其替换为所有蜡烛图形式样 if name == "all": name = ALL_PATTERNS # 如果 name 参数为字符串类型，则转换为列表 if type(name) is str: name = [name] # 如果导入了 talib 模块 if Imports["talib"]: import talib.abstract as tala # 初始化结果字典 result = {} # 对于给定的每个图案名称进行迭代 for n in name: # 检查图案名称是否在 ALL_PATTERNS 列表中 if n not in ALL_PATTERNS: # 如果不在，打印错误消息，并跳过当前迭代 print(f"[X] There is no candle pattern named {n} available!") continue # 检查图案是否已在 pta_patterns 字典中定义 if n in pta_patterns: # 如果已定义，调用对应的函数计算图案结果 pattern_result = pta_patterns[n](open_, high, low, close, offset=offset, scalar=scalar, **kwargs) # 将图案结果添加到结果字典中 result[pattern_result.name] = pattern_result else: # 如果图案未在 pta_patterns 中定义 # 检查是否已导入 TA-Lib 模块 if not Imports["talib"]: # 如果未导入，打印错误消息，并跳过当前迭代 print(f"[X] Please install TA-Lib to use {n}. (pip install TA-Lib)") continue # 根据图案名称创建对应的 TA-Lib 函数对象 pattern_func = tala.Function(f"CDL{n.upper()}") # 调用 TA-Lib 函数计算图案结果 pattern_result = Series(pattern_func(open_, high, low, close, **kwargs) / 100 * scalar) # 设置图案结果的索引与 close 的索引一致 pattern_result.index = close.index # 处理偏移 if offset != 0: # 将图案结果进行偏移 pattern_result = pattern_result.shift(offset) # 处理填充 if "fillna" in kwargs: # 如果指定了填充值，使用指定值填充缺失值 pattern_result.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: # 如果指定了填充方法，使用指定方法填充缺失值 pattern_result.fillna(method=kwargs["fill_method"], inplace=True) # 将图案结果添加到结果字典中，以"CDL_"加大写的图案名称作为键 result[f"CDL_{n.upper()}"] = pattern_result # 如果结果字典为空，则返回 if len(result) == 0: return # 准备要返回的 DataFrame df = DataFrame(result) # 设置 DataFrame 的名称属性 df.name = "CDL_PATTERN" # 设置 DataFrame 的 category 属性 df.category = "candles" # 返回 DataFrame return df # 设置 cdl_pattern 的文档字符串，描述蜡烛图模式的使用方法和参数说明 cdl_pattern.__doc__ = \ """Candle Pattern A wrapper around all candle patterns. Examples: Get all candle patterns (This is the default behaviour) >>> df = df.ta.cdl_pattern(name="all") Or >>> df.ta.cdl("all", append=True) # = df.ta.cdl_pattern("all", append=True) Get only one pattern >>> df = df.ta.cdl_pattern(name="doji") Or >>> df.ta.cdl("doji", append=True) Get some patterns >>> df = df.ta.cdl_pattern(name=["doji", "inside"]) Or >>> df.ta.cdl(["doji", "inside"], append=True) Args: open_ (pd.Series): Series of 'open's high (pd.Series): Series of 'high's low (pd.Series): Series of 'low's close (pd.Series): Series of 'close's name: (Union[str, Sequence[str]]): name of the patterns scalar (float): How much to magnify. Default: 100 offset (int): How many periods to offset the result. Default: 0 Kwargs: fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method Returns: pd.DataFrame: one column for each pattern. """ # 将 cdl_pattern 函数的引用赋值给 cdl 变量，用于简化调用 cdl = cdl_pattern
PandasTA 源码解析（二）（2）https://developer.aliyun.com/article/1506017
