0.5.3 删除pyecharts绘制K线

czsc/analyze.py

@@ -11,7 +11,7 @@ except ImportError:
 import pandas as pd
 import numpy as np
 from datetime import datetime
-from czsc.utils import plot_ka, plot_kline
+from czsc.utils import plot_ka
 
 
 def find_zs(points):
@@ -287,7 +287,8 @@ class KlineAnalyze:
                     "fx_mark": "g",
                     "fx": k2['high'],
                     "fx_high": k2['high'],
-                    "fx_low": max(k1['low'], k3['low']),
+                    # "fx_low": min(k1['low'], k3['low']),
+                    "fx_low": k2['low'],
                 }
                 self.fx_list.append(fx)
 
@@ -298,7 +299,8 @@ class KlineAnalyze:
                     "dt": k2['dt'],
                     "fx_mark": "d",
                     "fx": k2['low'],
-                    "fx_high": min(k1['high'], k2['high']),
+                    # "fx_high": max(k1['high'], k2['high']),
+                    "fx_high": k2['high'],
                     "fx_low": k2['low'],
                 }
                 self.fx_list.append(fx)
@@ -366,8 +368,8 @@ class KlineAnalyze:
                 kn_inside = [x for x in right_kn if last_bi['dt'] <= x['dt'] <= bi['dt']]
                 if len(kn_inside) >= self.min_bi_k:
                     # 确保相邻两个顶底之间不存在包含关系
-                    if (last_bi['fx_mark'] == 'g' and bi['fx_high'] < last_bi['fx_low']) or \
-                            (last_bi['fx_mark'] == 'd' and bi['fx_low'] > last_bi['fx_high']):
+                    if (last_bi['fx_mark'] == 'g' and bi['fx_low'] < last_bi['fx_low']) or \
+                            (last_bi['fx_mark'] == 'd' and bi['fx_high'] > last_bi['fx_high']):
                         if self.verbose:
                             print("新增笔标记：{}".format(bi))
                         self.bi_list.append(bi)
@@ -544,16 +546,24 @@ class KlineAnalyze:
         if self.verbose:
             print("更新结束\n\n")
 
-    def to_df(self, ma_params=(5, 20), use_macd=False, max_count=1000):
+    def to_df(self, ma_params=(5, 20), use_macd=False, max_count=1000, mode="raw"):
         """整理成 df 输出
 
         :param ma_params: tuple of int
             均线系统参数
         :param use_macd: bool
         :param max_count: int
+        :param mode: str
+            使用K线类型， raw = 原始K线，new = 去除包含关系的K线
         :return: pd.DataFrame
         """
-        bars = self.kline_raw[-max_count:]
+        if mode == "raw":
+            bars = self.kline_raw[-max_count:]
+        elif mode == "new":
+            bars = self.kline_raw[-max_count:]
+        else:
+            raise ValueError
+
         fx_list = {x["dt"]: {"fx_mark": x["fx_mark"], "fx": x['fx']} for x in self.fx_list[-(max_count // 2):]}
         bi_list = {x["dt"]: {"fx_mark": x["fx_mark"], "bi": x['bi']} for x in self.bi_list[-(max_count // 4):]}
         xd_list = {x["dt"]: {"fx_mark": x["fx_mark"], "xd": x['xd']} for x in self.xd_list[-(max_count // 8):]}
@@ -584,19 +594,6 @@ class KlineAnalyze:
             df.loc[:, "macd"] = diff
         return df
 
-    def to_html(self, file_html="kline.html", width="1400px", height="680px"):
-        """保存成 html
-
-        :param file_html: str
-            html文件名
-        :param width: str
-            页面宽度
-        :param height: str
-            页面高度
-        :return:
-        """
-        plot_kline(self, file_html=file_html, width=width, height=height)
-
     def to_image(self, file_image, mav=(5, 20, 120, 250), max_k_count=1000, dpi=50):
         """保存成图片
 

czsc/utils.py

 # coding: utf-8
 
 import pandas as pd
-from pyecharts import options as opts
-from pyecharts.commons.utils import JsCode
-from pyecharts.charts import Kline, Line, Bar, Grid, Scatter
 import mplfinance as mpf
 import matplotlib as mpl
 import matplotlib.pyplot as plt
 
 
-def plot_kline(ka, bs=None, file_html="kline.html", width="1400px", height="680px"):
-    """
-
-    :param ka: KlineAnalyze
-    :param bs: pd.DataFrame
-        买卖点，包含三个字段 ["操作提示", "交易时间", "交易价格"]
-    :param file_html: str
-    :param width: str
-    :param height: str
-    :return: None
-    """
-    df = ka.to_df(use_macd=True, ma_params=(5, 20,))
-    x = df.dt.to_list()
-    title = "%s | %s 至 %s" % (ka.symbol, ka.start_dt, ka.end_dt)
-    kline = (
-        Kline()
-            .add_xaxis(xaxis_data=x)
-            .add_yaxis(
-            series_name="",
-            y_axis=df[['open', 'close', 'low', 'high']].values.tolist(),
-            itemstyle_opts=opts.ItemStyleOpts(
-                color="#ef232a",
-                color0="#14b143",
-                border_color="#ef232a",
-                border_color0="#14b143",
-            ),
-        )
-            .set_series_opts(
-            markarea_opts=opts.MarkAreaOpts(is_silent=True)
-        )
-            .set_global_opts(
-            title_opts=opts.TitleOpts(title=title, pos_left="0"),
-            xaxis_opts=opts.AxisOpts(
-                type_="category",
-                is_scale=True,
-                boundary_gap=False,
-                axisline_opts=opts.AxisLineOpts(is_on_zero=False),
-                splitline_opts=opts.SplitLineOpts(is_show=False),
-                split_number=20,
-                min_="dataMin",
-                max_="dataMax",
-            ),
-            yaxis_opts=opts.AxisOpts(
-                is_scale=True, splitline_opts=opts.SplitLineOpts(is_show=True),
-                axislabel_opts=opts.LabelOpts(is_show=True, position="inside")
-            ),
-            tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="line"),
-            datazoom_opts=[
-                opts.DataZoomOpts(
-                    is_show=False, type_="inside", xaxis_index=[0, 0], range_end=100
-                ),
-                opts.DataZoomOpts(
-                    is_show=True, xaxis_index=[0, 1], pos_top="96%", range_end=100
-                ),
-                opts.DataZoomOpts(is_show=False, xaxis_index=[0, 2], range_end=100),
-            ],
-            # 三个图的 axis 连在一块
-            axispointer_opts=opts.AxisPointerOpts(
-                is_show=True,
-                link=[{"xAxisIndex": "all"}],
-                label=opts.LabelOpts(background_color="#777"),
-            ),
-        )
-    )
-
-    kline_line = (
-        Line()
-            .add_xaxis(xaxis_data=x)
-            .add_yaxis(
-            series_name="笔",
-            y_axis=df.bi.tolist(),
-            is_smooth=False,
-            is_connect_nones=True,
-            symbol='diamond',
-            symbol_size=8,
-            linestyle_opts=opts.LineStyleOpts(opacity=1, type_='dotted', width=2),
-            label_opts=opts.LabelOpts(is_show=False),
-        )
-            .add_yaxis(
-            series_name="线段",
-            y_axis=df.xd.tolist(),
-            is_smooth=False,
-            is_connect_nones=True,
-            symbol='triangle',
-            symbol_size=12,
-            linestyle_opts=opts.LineStyleOpts(opacity=1, type_='solid', width=2),
-            label_opts=opts.LabelOpts(is_show=True, position='right'),
-        )
-            .set_global_opts(
-            xaxis_opts=opts.AxisOpts(
-                type_="category",
-                grid_index=1,
-                axislabel_opts=opts.LabelOpts(is_show=False),
-            ),
-            yaxis_opts=opts.AxisOpts(
-                grid_index=1,
-                split_number=3,
-                axisline_opts=opts.AxisLineOpts(is_on_zero=False),
-                axistick_opts=opts.AxisTickOpts(is_show=False),
-                splitline_opts=opts.SplitLineOpts(is_show=False),
-                axislabel_opts=opts.LabelOpts(is_show=True, position="inside"),
-            ),
-        )
-    )
-    # Overlap Kline + Line
-    overlap_kline_line = kline.overlap(kline_line)
-
-    if isinstance(bs, pd.DataFrame) and len(bs) > 0:
-        c = (
-            Scatter()
-                .add_xaxis(bs['交易时间'].to_list())
-                .add_yaxis(
-                "买卖点",
-                bs['交易价格'].to_list(),
-                label_opts=opts.LabelOpts(
-                    is_show=True,
-                    position="left",
-                    formatter=JsCode(
-                        "function(params){return bsName[params.dataIndex][0];}"
-                    )
-                ),
-            ))
-        overlap_kline_line = overlap_kline_line.overlap(c)
-
-    # draw volume
-    bar_1 = (
-        Bar()
-            .add_xaxis(xaxis_data=x)
-            .add_yaxis(
-            series_name="Volumn",
-            yaxis_data=df.vol.tolist(),
-            xaxis_index=1,
-            yaxis_index=1,
-            label_opts=opts.LabelOpts(is_show=False),
-            itemstyle_opts=opts.ItemStyleOpts(
-                color=JsCode(
-                    """
-                function(params) {
-                    var colorList;
-                    if (barData[params.dataIndex][1] > barData[params.dataIndex][0]) {
-                        colorList = '#ef232a';
-                    } else {
-                        colorList = '#14b143';
-                    }
-                    return colorList;
-                }
-                """
-                )
-            ),
-        )
-            .set_global_opts(
-            xaxis_opts=opts.AxisOpts(
-                type_="category",
-                grid_index=1,
-                axislabel_opts=opts.LabelOpts(is_show=False),
-            ),
-            yaxis_opts=opts.AxisOpts(
-                axislabel_opts=opts.LabelOpts(is_show=True, position='inside')
-            ),
-            legend_opts=opts.LegendOpts(is_show=False),
-        )
-    )
-
-    # Bar-2 (Overlap Bar + Line)
-    bar_2 = (
-        Bar()
-            .add_xaxis(xaxis_data=x)
-            .add_yaxis(
-            series_name="MACD",
-            yaxis_data=df.macd.tolist(),
-            xaxis_index=2,
-            yaxis_index=2,
-            label_opts=opts.LabelOpts(is_show=False),
-            itemstyle_opts=opts.ItemStyleOpts(
-                color=JsCode(
-                    """
-                        function(params) {
-                            var colorList;
-                            if (params.data >= 0) {
-                              colorList = '#ef232a';
-                            } else {
-                              colorList = '#14b143';
-                            }
-                            return colorList;
-                        }
-                        """
-                )
-            ),
-        )
-            .set_global_opts(
-            xaxis_opts=opts.AxisOpts(
-                type_="category",
-                grid_index=2,
-                axislabel_opts=opts.LabelOpts(is_show=False),
-            ),
-            yaxis_opts=opts.AxisOpts(
-                grid_index=2,
-                split_number=4,
-                axisline_opts=opts.AxisLineOpts(is_on_zero=False),
-                axistick_opts=opts.AxisTickOpts(is_show=False),
-                splitline_opts=opts.SplitLineOpts(is_show=False),
-                axislabel_opts=opts.LabelOpts(is_show=True, position="inside"),
-            ),
-            legend_opts=opts.LegendOpts(is_show=False),
-        )
-    )
-
-    line_2 = (
-        Line()
-            .add_xaxis(xaxis_data=x)
-            .add_yaxis(
-            series_name="DIF",
-            y_axis=df['diff'].tolist(),
-            xaxis_index=2,
-            yaxis_index=2,
-            label_opts=opts.LabelOpts(is_show=False),
-        )
-            .add_yaxis(
-            series_name="DEA",
-            y_axis=df['dea'].tolist(),
-            xaxis_index=2,
-            yaxis_index=2,
-            label_opts=opts.LabelOpts(is_show=False),
-        )
-            .set_global_opts(legend_opts=opts.LegendOpts(is_show=False))
-    )
-
-    # draw MACD
-    overlap_bar_line = bar_2.overlap(line_2)
-
-    # 最后的 Grid
-    grid_chart = Grid(init_opts=opts.InitOpts(width=width, height=height, page_title=title))
-    grid_chart.add_js_funcs("var barData = {}".format(df[['open', 'close', 'low', 'high']].values.tolist()))
-    if isinstance(bs, pd.DataFrame) and len(bs) > 0:
-        grid_chart.add_js_funcs("var bsName = {}".format(bs[["操作提示", "交易价格"]].values.tolist()))
-
-    grid_chart.add(
-        overlap_kline_line,
-        grid_opts=opts.GridOpts(pos_left="3%", pos_right="1%", height="60%"),
-    )
-    grid_chart.add(
-        bar_1,
-        grid_opts=opts.GridOpts(pos_left="3%", pos_right="1%", pos_top="71%", height="10%"),
-    )
-    grid_chart.add(
-        overlap_bar_line,
-        grid_opts=opts.GridOpts(pos_left="3%", pos_right="1%", pos_top="82%", height="14%"),
-    )
-    grid_chart.render(path=file_html)
-
-
 def plot_ka(ka, file_image, mav=(5, 20, 120, 250), max_k_count=1000, dpi=50):
     """绘制 ka，保存到 file_image"""
     df = ka.to_df(use_macd=True, ma_params=(5, 20,))