add macd view

README.md

@@ -7,7 +7,7 @@ Pypi上已经存在一个名为chan的库，以致于这个库没法上传到Pyp
 
 执行以下代码直接从github安装：
 ```
-pip install git+git://github.com/zengbin93/chan.git
+pip install git+git://github.com/zengbin93/chan.git -U
 ```
 
 ## K线数据样例

chan/utils.py

@@ -15,186 +15,6 @@ def clean_cache():
     os.mkdir(cache_path)
 
 
-def preprocess(kline):
-    """去除包含关系
-
-    :param kline: pd.DataFrame
-        K线，columns = ["symbol", "dt", "open", "close", "high", "low", "vol"]
-    :return: pd.DataFrame
-    """
-    kline['high_m'] = None
-    kline['low_m'] = None
-
-    # 首行处理
-    last_h = kline.loc[0, 'high']
-    last_l = kline.loc[0, 'low']
-
-    if last_h >= kline.loc[1, 'high']:
-        direction = 0  # 下跌
-    else:
-        direction = 1  # 上涨
-
-    for i, row in kline.iterrows():
-        cur_h, cur_l = row['high'], row['low']
-
-        # 左包含 or 右包含
-        if (cur_h <= last_h and cur_l >= last_l) or (cur_h >= last_h and cur_l <= last_l):
-            if direction == 0:
-                last_h = min(last_h, cur_h)
-                last_l = min(last_l, cur_l)
-            elif direction == 1:
-                last_h = max(last_h, cur_h)
-                last_l = max(last_l, cur_l)
-            else:
-                raise ValueError
-
-            # 尾行更新 high low
-            if i == len(kline) - 1:
-                kline.loc[i, 'high_m'] = last_h
-                kline.loc[i, 'low_m'] = last_l
-            continue
-
-        # 当期行与上一行之间无包含关系，更新上一行 high low
-        kline.loc[i - 1, 'high_m'] = last_h
-        kline.loc[i - 1, 'low_m'] = last_l
-
-        # 更新 direction, last_h, last_l
-        if last_h >= cur_h:
-            direction = 0  # 下跌
-        else:
-            direction = 1  # 上涨
-
-        last_h = cur_h
-        last_l = cur_l
-
-    # 根据包含关系的检查结果，生成新的 K 线数据
-    kline_new = kline[['symbol', 'dt', 'open', 'close', 'high_m', 'low_m']]
-    kline_new = kline_new.rename({"high_m": "high", "low_m": "low"}, axis='columns')
-    kline_new = kline_new.dropna(subset=['high', 'low'])
-    kline_new = kline_new.reset_index(drop=True)
-
-    return kline_new
-
-
-def find_bi(kline):
-    """找出全部分型，并验证有效性
-
-    0 - 顶分型
-    1 - 底分型
-    2 - 无效分型
-
-    一个分型能否成为笔的一部分，至少需要看到后面两个分型的情况才能确定。
-
-    :param kline: pd.DataFrame
-        经过预处理，去除了包含关系的 K 线，
-        columns = ["symbol", "dt", "open", "close", "high", "low", "vol"]
-    :return: kline: pd.DataFrame
-    """
-    kline['fx'] = None
-    kline['bi'] = None
-
-    for i in range(1, len(kline) - 1):
-        data = kline.iloc[i - 1: i + 2]
-        row = kline.iloc[i]
-        if max(data['high']) == row['high']:
-            kline.loc[row.name, 'fx'] = 0
-        elif min(data['low']) == row['low']:
-            kline.loc[row.name, 'fx'] = 1
-        else:
-            continue
-
-    # 确定分型的有效性：满足结合律；实现方式：从后往前，不满足结合律就处理成无效分型
-    last_index = None
-
-    # for i in kline.index[::-1]:
-    for i in kline.index:
-        if kline.loc[i, 'fx'] not in [0, 1]:
-            continue
-
-        if kline.loc[i, 'fx'] in [0, 1]:
-            if last_index is None:
-                last_index = i
-            else:
-                curr_index = i
-                if curr_index - last_index < 4:
-                    kline.loc[last_index, 'fx'] = 2
-                    kline.loc[curr_index, 'fx'] = 2
-                    kline_part = kline.iloc[:i]
-                    last_index = kline_part[kline_part['fx'].isin([0, 1])].iloc[-1].name
-                    last_index = int(last_index)
-                else:
-                    last_index = curr_index
-
-    # 添加 笔标记 - 从第一个有效顶分型开始标记
-    kline['bi_mark'] = None
-    mark = 0
-    for i, row in kline.iterrows():
-        if mark == 0 and row['fx'] == 0:
-            kline.loc[i, 'bi_mark'] = mark
-            kline.loc[i, 'bi'] = kline.loc[i, 'high']
-            mark += 1
-            continue
-
-        if mark > 0 and row['fx'] in [0, 1]:
-            kline.loc[i, 'bi_mark'] = mark
-            mark += 1
-            if row['fx'] == 0:
-                kline.loc[i, 'bi'] = kline.loc[i, 'high']
-            elif row['fx'] == 1:
-                kline.loc[i, 'bi'] = kline.loc[i, 'low']
-            else:
-                raise ValueError("fx value error, valid is 0 or 1,"
-                                 " current is %i" % row['fx'])
-
-    return kline
-
-
-def find_xd(kline):
-    """线段查找。输入：确定了分型的 K 线；输出：加入线段查找结果的 K 线
-
-    :param kline: pd.DataFrame
-        K线，columns = ["symbol", "dt", "open", "close", "high", "low", "vol"]
-    :return:
-    """
-    # 找出所有可能的线段终点
-    gd1 = kline[kline['bi_mark'] == 0].iloc[0]
-    gd2 = kline[kline['bi_mark'] == 2].iloc[0]
-
-    if gd1['high'] < gd2['high']:
-        direction = "向上"
-    else:
-        direction = "向下"
-
-    i = 4
-    mark = 0
-    kline['xd_mark'] = None
-
-    while i <= kline['bi_mark'].max():
-        gd1 = kline[kline['bi_mark'] == i - 3].iloc[0]
-        dd1 = kline[kline['bi_mark'] == i - 2].iloc[0]
-        gd2 = kline[kline['bi_mark'] == i - 1].iloc[0]
-        dd2 = kline[kline['bi_mark'] == i].iloc[0]
-
-        # 第二个顶分型的最高价小于或等于第一个顶分型的最高价，向上过程有可能结束
-        if direction == "向上" and gd2['high'] <= gd1['high']:
-            kline.loc[gd1.name, 'xd_mark'] = mark
-            mark += 1
-            direction = "向下"
-
-        # 第二个底分型的最低价大于或等于第一个底分型的最低价，向下过程有可能结束
-        elif direction == "向下" and dd2['low'] >= dd1['low']:
-            kline.loc[dd1.name, 'xd_mark'] = mark
-            mark += 1
-            direction = "向上"
-
-        i += 2
-
-    # 线段有效的基础： 标准特征序列中至少含一笔
-    # 添加 线段标记 - 从第一个有效顶分型开始标记
-
-    return kline
-
-
 def ma(kline, params=(5, 10, 20, 60, 120, 250)):
     """计算指定周期的若干 MA 均线