def scatter_render_air(self):
c = Scatter()
c.add_xaxis(self.x_value)
c.add_yaxis(
series_name=self.y_name,
y_axis=self.inner_data_pair,
label_opts=opts.LabelOpts(
is_show=self.is_show,
formatter=JsCode(
"function(params){return params.value[2] +' : '+ params.value[1];}"
)))
c.set_global_opts(
title_opts=opts.TitleOpts(title=self.title,
subtitle=self.subtitle),
# tooltip_opts=opts.TooltipOpts(
# formatter=JsCode(
# "function (params) {return params.name + ' : ' + params.value[2];}"
# )
# ),
visualmap_opts=opts.VisualMapOpts(type_="color",
max_=150,
min_=20,
dimension=1),
legend_opts=opts.LegendOpts(pos_left=self.pos_left,
legend_icon=self.legend_icon))
return c
def gen_poit_three(df2):
df = df2[df2.offset=='平']
if len(df) > 0:
dt_list = list(df['datetime'])
price_list = df.apply(lambda record: float(record['price']), axis=1).tolist()
price_list = np.array(price_list)
else:
dt_list = []
price_list = []
c = Scatter()
c.add_xaxis(dt_list)
c.add_yaxis('', price_list)
return c
def gen_poit_close(df2):
df = df2[df2.offset=='平']
if len(df) > 0:
dt_list = list(df['datetime'])
price_list = df.apply(lambda record: float(record['price']), axis=1).tolist()
price_list = np.array(price_list)
else:
dt_list = []
price_list = []
c = Scatter()
c.add_xaxis(dt_list)
c.add_yaxis('', price_list, label_opts=opts.LabelOpts(position='bottom'))
return c
def echarts_scatter(df):
# x = df.iloc[:, 0]
# y = df.iloc[:, 1]
# n = 100 / np.log(df.shape[0]) # 动态散点大小
n = 10 # 静态散点大小
if df.empty is False:
scatter = Scatter(init_opts=opts.InitOpts())
for index, row in df.iterrows():
x = int(row[0])
y = int(row[1])
scatter.add_xaxis(xaxis_data=[x])
scatter.add_yaxis(
series_name=index,
y_axis=[y],
symbol_size=n,
label_opts=opts.LabelOpts(is_show=False),
)
scatter.set_series_opts()
scatter.set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="value",
name="销售",
splitline_opts=opts.SplitLineOpts(is_show=True),
),
yaxis_opts=opts.AxisOpts(
name="同比净增长",
type_="value",
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
tooltip_opts=opts.TooltipOpts(
is_show=True, trigger="item", formatter="{a} <br/>{b}: {c}"
),
# toolbox_opts=opts.ToolboxOpts(is_show=True),
legend_opts=opts.LegendOpts(is_show=False),
)
else:
scatter = Scatter()
return scatter
def scatter_base() -> Scatter:
if len(names) == 0:
pass
elif len(names) >= 1:
c = Scatter()
c.add_xaxis(X)
c.set_global_opts(
toolbox_opts=opts.ToolboxOpts(),
title_opts=opts.TitleOpts(title="ScatterChart"),
yaxis_opts=opts.AxisOpts(name="Data"),
xaxis_opts=opts.AxisOpts(name="Date"),
datazoom_opts=[
opts.DataZoomOpts(),
opts.DataZoomOpts(type_="inside")
],
)
for i in range(0, len(names)):
c.add_yaxis(names[i], Y[i])
return c
# 繪製每年與每月作品數量柱狀圖
# show every year and every month counts of anime bar chart
x, y = transfer_form(group_year), transfer_form(group_year_count)
bar = bar(x, y, '數量(單位:部)', '年份(單位:年)')
bar.render()
x, y = transfer_form(group_month), transfer_form(group_month_count)
bar = bar(x, y, '數量(單位:部)', '月份(單位:月)')
bar.render()
# 觀察評分與觀看數的關係
# show points-views relation in scatter
print(max(df['views']), min(df['views']))
fig = opts.InitOpts(width='1200px', height='600px')
scatter = Scatter(init_opts=fig)
scatter.add_xaxis(xaxis_data=df['views'])
scatter.add_yaxis(
series_name='',
y_axis=df['score'],
# 設計數據值是否展示
label_opts=opts.LabelOpts(is_show=False))
scatter.set_global_opts(title_opts=opts.TitleOpts(title='觀看量-評分關係圖',
pos_left='center',
pos_top='20'),
xaxis_opts=opts.AxisOpts(split_number=25,
name='觀看量(單位:萬)'),
yaxis_opts=opts.AxisOpts(split_number=20, name='分'))
scatter.render()
# 動漫每天平均觀看量
# show avg views per day bar char
def kline_pro(kline: List[dict],
ma: List[dict],
macd: List[dict],
fx: List[dict] = None,
bi: List[dict] = None,
xd: List[dict] = None,
bs: List[dict] = None,
title: str = "缠中说禅K线分析",
width: str = "1200px",
height: str = '680px') -> Grid:
"""绘制缠中说禅K线分析结果
:param kline: K线
:param ma: 均线
:param macd: MACD
:param fx: 分型识别结果
:param bi: 笔识别结果
:param xd: 线段识别结果
:param bs: 买卖点
:param title: 图表标题
:param width: 图表宽度
:param height: 图表高度
:return: 用Grid组合好的图表
"""
# 配置项设置
# ------------------------------------------------------------------------------------------------------------------
bg_color = "#1f212d" # 背景
up_color = "#F9293E"
down_color = "#00aa3b"
init_opts = opts.InitOpts(bg_color=bg_color,
width=width,
height=height,
animation_opts=opts.AnimationOpts(False))
title_opts = opts.TitleOpts(
title=title,
pos_top="1%",
title_textstyle_opts=opts.TextStyleOpts(color=up_color, font_size=20),
subtitle_textstyle_opts=opts.TextStyleOpts(color=down_color,
font_size=12))
label_not_show_opts = opts.LabelOpts(is_show=False)
legend_not_show_opts = opts.LegendOpts(is_show=False)
red_item_style = opts.ItemStyleOpts(color=up_color)
green_item_style = opts.ItemStyleOpts(color=down_color)
k_style_opts = opts.ItemStyleOpts(color=up_color,
color0=down_color,
border_color=up_color,
border_color0=down_color,
opacity=0.8)
legend_opts = opts.LegendOpts(is_show=True,
pos_top="1%",
pos_left="30%",
item_width=14,
item_height=8,
textstyle_opts=opts.TextStyleOpts(
font_size=12, color="#0e99e2"))
brush_opts = opts.BrushOpts(tool_box=["rect", "polygon", "keep", "clear"],
x_axis_index="all",
brush_link="all",
out_of_brush={"colorAlpha": 0.1},
brush_type="lineX")
axis_pointer_opts = opts.AxisPointerOpts(is_show=True,
link=[{
"xAxisIndex": "all"
}])
dz_inside = opts.DataZoomOpts(False, "inside", xaxis_index=[0, 1, 2])
dz_slider = opts.DataZoomOpts(True,
"slider",
xaxis_index=[0, 1, 2],
pos_top="96%",
pos_bottom="0%")
yaxis_opts = opts.AxisOpts(is_scale=True,
axislabel_opts=opts.LabelOpts(
color="#c7c7c7",
font_size=8,
position="inside"))
grid0_xaxis_opts = opts.AxisOpts(
type_="category",
grid_index=0,
axislabel_opts=label_not_show_opts,
split_number=20,
min_="dataMin",
max_="dataMax",
is_scale=True,
boundary_gap=False,
axisline_opts=opts.AxisLineOpts(is_on_zero=False))
tool_tip_opts = opts.TooltipOpts(
trigger="axis",
axis_pointer_type="cross",
background_color="rgba(245, 245, 245, 0.8)",
border_width=1,
border_color="#ccc",
position=JsCode("""
function (pos, params, el, elRect, size) {
var obj = {top: 10};
obj[['left', 'right'][+(pos[0] < size.viewSize[0] / 2)]] = 30;
return obj;
}
"""),
textstyle_opts=opts.TextStyleOpts(color="#000"),
)
# 数据预处理
# ------------------------------------------------------------------------------------------------------------------
dts = [x['dt'] for x in kline]
k_data = [[x['open'], x['close'], x['low'], x['high']] for x in kline]
vol = []
for row in kline:
item_style = red_item_style if row['close'] > row[
'open'] else green_item_style
bar = opts.BarItem(value=row['vol'],
itemstyle_opts=item_style,
label_opts=label_not_show_opts)
vol.append(bar)
macd_bar = []
for row in macd:
item_style = red_item_style if row['macd'] > 0 else green_item_style
bar = opts.BarItem(value=round(row['macd'], 4),
itemstyle_opts=item_style,
label_opts=label_not_show_opts)
macd_bar.append(bar)
diff = [round(x['diff'], 4) for x in macd]
dea = [round(x['dea'], 4) for x in macd]
# K 线主图
# ------------------------------------------------------------------------------------------------------------------
chart_k = Kline()
chart_k.add_xaxis(xaxis_data=dts)
chart_k.add_yaxis(series_name="Kline",
y_axis=k_data,
itemstyle_opts=k_style_opts)
chart_k.set_global_opts(legend_opts=legend_opts,
datazoom_opts=[dz_inside, dz_slider],
yaxis_opts=yaxis_opts,
tooltip_opts=tool_tip_opts,
axispointer_opts=axis_pointer_opts,
brush_opts=brush_opts,
title_opts=title_opts,
xaxis_opts=grid0_xaxis_opts)
# 均线图
# ------------------------------------------------------------------------------------------------------------------
chart_ma = Line()
chart_ma.add_xaxis(xaxis_data=dts)
ma_keys = [x for x in ma[0].keys() if "ma" in x][:3]
ma_colors = ["#39afe6", "#da6ee8", "#00940b"]
for i, k in enumerate(ma_keys):
y_data = [x[k] for x in ma]
chart_ma.add_yaxis(series_name=k.upper(),
y_axis=y_data,
is_smooth=True,
is_selected=False,
symbol_size=0,
label_opts=label_not_show_opts,
linestyle_opts=opts.LineStyleOpts(
opacity=0.8, width=1.0, color=ma_colors[i]))
chart_ma.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_ma)
# 缠论结果
# ------------------------------------------------------------------------------------------------------------------
if fx:
fx_dts = [x['dt'] for x in fx]
fx_val = [x['fx'] for x in fx]
chart_fx = Scatter()
chart_fx.add_xaxis(fx_dts)
chart_fx.add_yaxis(series_name="FX",
y_axis=fx_val,
is_selected=False,
symbol="circle",
symbol_size=6,
label_opts=label_not_show_opts,
itemstyle_opts=opts.ItemStyleOpts(
color="rgba(152, 147, 193, 1.0)", ))
chart_fx.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_fx)
if bi:
bi_dts = [x['dt'] for x in bi]
bi_val = [x['bi'] for x in bi]
chart_bi = Scatter()
chart_bi.add_xaxis(bi_dts)
chart_bi.add_yaxis(series_name="BI",
y_axis=bi_val,
is_selected=True,
symbol="diamond",
symbol_size=10,
label_opts=label_not_show_opts,
itemstyle_opts=opts.ItemStyleOpts(
color="rgba(184, 117, 225, 1.0)", ))
chart_bi.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_bi)
if xd:
xd_dts = [x['dt'] for x in xd]
xd_val = [x['xd'] for x in xd]
chart_xd = Scatter()
chart_xd.add_xaxis(xd_dts)
chart_xd.add_yaxis(series_name="XD",
y_axis=xd_val,
is_selected=True,
symbol="triangle",
symbol_size=10,
itemstyle_opts=opts.ItemStyleOpts(
color="rgba(37, 141, 54, 1.0)", ))
chart_xd.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_xd)
if bs:
b_dts = [x['dt'] for x in bs if x['mark'] == 'buy']
if len(b_dts) > 0:
b_val = [x['buy'] for x in bs if x['mark'] == 'buy']
chart_b = Scatter()
chart_b.add_xaxis(b_dts)
chart_b.add_yaxis(series_name="BUY",
y_axis=b_val,
is_selected=False,
symbol="arrow",
symbol_size=8,
itemstyle_opts=opts.ItemStyleOpts(
color="#f31e1e", ))
chart_b.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_b)
s_dts = [x['dt'] for x in bs if x['mark'] == 'sell']
if len(s_dts) > 0:
s_val = [x['sell'] for x in bs if x['mark'] == 'sell']
chart_s = Scatter()
chart_s.add_xaxis(s_dts)
chart_s.add_yaxis(series_name="SELL",
y_axis=s_val,
is_selected=False,
symbol="pin",
symbol_size=12,
itemstyle_opts=opts.ItemStyleOpts(
color="#45b97d", ))
chart_s.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_s)
# 成交量图
# ------------------------------------------------------------------------------------------------------------------
chart_vol = Bar()
chart_vol.add_xaxis(dts)
chart_vol.add_yaxis(series_name="Volume", y_axis=vol, bar_width='60%')
chart_vol.set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=1,
axislabel_opts=opts.LabelOpts(is_show=True,
font_size=8,
color="#9b9da9"),
),
yaxis_opts=yaxis_opts,
legend_opts=legend_not_show_opts,
)
# MACD图
# ------------------------------------------------------------------------------------------------------------------
chart_macd = Bar()
chart_macd.add_xaxis(dts)
chart_macd.add_yaxis(series_name="MACD", y_axis=macd_bar, bar_width='60%')
chart_macd.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, color="#c7c7c7"),
),
legend_opts=opts.LegendOpts(is_show=False),
)
line = Line()
line.add_xaxis(dts)
line.add_yaxis(series_name="DIFF",
y_axis=diff,
label_opts=label_not_show_opts,
is_symbol_show=False,
linestyle_opts=opts.LineStyleOpts(opacity=0.8,
width=1.0,
color="#da6ee8"))
line.add_yaxis(series_name="DEA",
y_axis=dea,
label_opts=label_not_show_opts,
is_symbol_show=False,
linestyle_opts=opts.LineStyleOpts(opacity=0.8,
width=1.0,
color="#39afe6"))
chart_macd = chart_macd.overlap(line)
grid0_opts = opts.GridOpts(pos_left="0%",
pos_right="1%",
pos_top="12%",
height="58%")
grid1_opts = opts.GridOpts(pos_left="0%",
pos_right="1%",
pos_top="74%",
height="8%")
grid2_opts = opts.GridOpts(pos_left="0%",
pos_right="1%",
pos_top="86%",
height="10%")
grid_chart = Grid(init_opts)
grid_chart.add(chart_k, grid_opts=grid0_opts)
grid_chart.add(chart_vol, grid_opts=grid1_opts)
grid_chart.add(chart_macd, grid_opts=grid2_opts)
return grid_chart
def ka_to_echarts(ka: KlineAnalyze, width="1500px", height='800px'):
# 配置项设置
# ------------------------------------------------------------------------------------------------------------------
bg_color = "#1f212d" # 背景
up_color = "#F9293E"
down_color = "#00aa3b"
init_opts = opts.InitOpts(bg_color=bg_color, width=width, height=height, animation_opts=opts.AnimationOpts(False))
title_opts = opts.TitleOpts(title="{} - {}".format(ka.symbol, ka.name),
subtitle="from {} to {}".format(ka.start_dt, ka.end_dt),
pos_top="1%",
title_textstyle_opts=opts.TextStyleOpts(color=up_color, font_size=20),
subtitle_textstyle_opts=opts.TextStyleOpts(color=down_color, font_size=12))
label_not_show_opts = opts.LabelOpts(is_show=False)
legend_not_show_opts = opts.LegendOpts(is_show=False)
red_item_style = opts.ItemStyleOpts(color=up_color)
green_item_style = opts.ItemStyleOpts(color=down_color)
k_style_opts = opts.ItemStyleOpts(color=up_color, color0=down_color, border_color=up_color,
border_color0=down_color, opacity=0.8)
legend_opts = opts.LegendOpts(is_show=True, pos_top="1%", pos_left="30%", item_width=14, item_height=8,
textstyle_opts=opts.TextStyleOpts(font_size=12, color="#0e99e2"))
brush_opts = opts.BrushOpts(tool_box=["rect", "polygon", "keep", "clear"],
x_axis_index="all", brush_link="all",
out_of_brush={"colorAlpha": 0.1}, brush_type="lineX")
axis_pointer_opts = opts.AxisPointerOpts(is_show=True, link=[{"xAxisIndex": "all"}])
dz_inside = opts.DataZoomOpts(False, "inside", xaxis_index=[0, 1, 2])
dz_slider = opts.DataZoomOpts(True, "slider", xaxis_index=[0, 1, 2], pos_top="96%", pos_bottom="0%")
yaxis_opts = opts.AxisOpts(is_scale=True, axislabel_opts=opts.LabelOpts(color="#c7c7c7", font_size=8, position="inside"))
grid0_xaxis_opts = opts.AxisOpts(type_="category", grid_index=0, axislabel_opts=label_not_show_opts,
split_number=20, min_="dataMin", max_="dataMax",
is_scale=True, boundary_gap=False, axisline_opts=opts.AxisLineOpts(is_on_zero=False))
tool_tip_opts = opts.TooltipOpts(
trigger="axis",
axis_pointer_type="cross",
background_color="rgba(245, 245, 245, 0.8)",
border_width=1,
border_color="#ccc",
position=JsCode("""
function (pos, params, el, elRect, size) {
var obj = {top: 10};
obj[['left', 'right'][+(pos[0] < size.viewSize[0] / 2)]] = 30;
return obj;
}
"""),
textstyle_opts=opts.TextStyleOpts(color="#000"),
)
# 数据预处理
# ------------------------------------------------------------------------------------------------------------------
dts = [x['dt'] for x in ka.kline_raw]
k_data = [[x['open'], x['close'], x['low'], x['high']] for x in ka.kline_raw]
ma = ka.ma
vol = []
for row in ka.kline_raw:
item_style = red_item_style if row['close'] > row['open'] else green_item_style
bar = opts.BarItem(value=row['vol'], itemstyle_opts=item_style, label_opts=label_not_show_opts)
vol.append(bar)
macd = []
for row in ka.macd:
item_style = red_item_style if row['macd'] > 0 else green_item_style
bar = opts.BarItem(value=round(row['macd'], 4), itemstyle_opts=item_style, label_opts=label_not_show_opts)
macd.append(bar)
diff = [round(x['diff'], 4) for x in ka.macd]
dea = [round(x['dea'], 4) for x in ka.macd]
# K 线主图
# ------------------------------------------------------------------------------------------------------------------
chart_k = Kline()
chart_k.add_xaxis(xaxis_data=dts)
chart_k.add_yaxis(series_name="Kline", y_axis=k_data, itemstyle_opts=k_style_opts)
chart_k.set_global_opts(
legend_opts=legend_opts,
datazoom_opts=[dz_inside, dz_slider],
yaxis_opts=yaxis_opts,
tooltip_opts=tool_tip_opts,
axispointer_opts=axis_pointer_opts,
brush_opts=brush_opts,
title_opts=title_opts,
xaxis_opts=grid0_xaxis_opts
)
# 均线图
# ------------------------------------------------------------------------------------------------------------------
chart_ma = Line()
chart_ma.add_xaxis(xaxis_data=dts)
ma_keys = [x for x in ma[0].keys() if "ma" in x][:3]
ma_colors = ["#39afe6", "#da6ee8", "#00940b"]
for i, k in enumerate(ma_keys):
y_data = [x[k] for x in ma]
chart_ma.add_yaxis(series_name=k.upper(), y_axis=y_data, is_smooth=True,
is_selected=False, symbol_size=0, label_opts=label_not_show_opts,
linestyle_opts=opts.LineStyleOpts(opacity=0.8, width=1.0, color=ma_colors[i]))
chart_ma.set_global_opts(xaxis_opts=grid0_xaxis_opts, legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_ma)
# 缠论结果
# ------------------------------------------------------------------------------------------------------------------
fx_dts = [x['dt'] for x in ka.fx_list]
fx_val = [x['fx'] for x in ka.fx_list]
chart_fx = Scatter()
chart_fx.add_xaxis(fx_dts)
chart_fx.add_yaxis(series_name="FX", y_axis=fx_val, is_selected=False,
symbol="circle", symbol_size=6, label_opts=label_not_show_opts,
itemstyle_opts=opts.ItemStyleOpts(color="rgba(152, 147, 193, 1.0)",))
chart_fx.set_global_opts(xaxis_opts=grid0_xaxis_opts, legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_fx)
bi_dts = [x['dt'] for x in ka.bi_list]
bi_val = [x['bi'] for x in ka.bi_list]
chart_bi = Scatter()
chart_bi.add_xaxis(bi_dts)
chart_bi.add_yaxis(series_name="BI", y_axis=bi_val, is_selected=True,
symbol="diamond", symbol_size=10, label_opts=label_not_show_opts,
itemstyle_opts=opts.ItemStyleOpts(color="rgba(184, 117, 225, 1.0)",))
chart_bi.set_global_opts(xaxis_opts=grid0_xaxis_opts, legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_bi)
xd_dts = [x['dt'] for x in ka.xd_list]
xd_val = [x['xd'] for x in ka.xd_list]
chart_xd = Scatter()
chart_xd.add_xaxis(xd_dts)
chart_xd.add_yaxis(series_name="XD", y_axis=xd_val, is_selected=True, symbol="triangle", symbol_size=10,
itemstyle_opts=opts.ItemStyleOpts(color="rgba(37, 141, 54, 1.0)",))
chart_xd.set_global_opts(xaxis_opts=grid0_xaxis_opts, legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_xd)
# 成交量图
# ------------------------------------------------------------------------------------------------------------------
chart_vol = Bar()
chart_vol.add_xaxis(dts)
chart_vol.add_yaxis(series_name="Volume", y_axis=vol, bar_width='60%')
chart_vol.set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=1,
axislabel_opts=opts.LabelOpts(is_show=True, font_size=8, color="#9b9da9"),
),
yaxis_opts=yaxis_opts, legend_opts=legend_not_show_opts,
)
# MACD图
# ------------------------------------------------------------------------------------------------------------------
chart_macd = Bar()
chart_macd.add_xaxis(dts)
chart_macd.add_yaxis(series_name="MACD", y_axis=macd, bar_width='60%')
chart_macd.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, color="#c7c7c7"),
),
legend_opts=opts.LegendOpts(is_show=False),
)
line = Line()
line.add_xaxis(dts)
line.add_yaxis(series_name="DIFF", y_axis=diff, label_opts=label_not_show_opts, is_symbol_show=False,
linestyle_opts=opts.LineStyleOpts(opacity=0.8, width=1.0, color="#da6ee8"))
line.add_yaxis(series_name="DEA", y_axis=dea, label_opts=label_not_show_opts, is_symbol_show=False,
linestyle_opts=opts.LineStyleOpts(opacity=0.8, width=1.0, color="#39afe6"))
chart_macd = chart_macd.overlap(line)
grid0_opts = opts.GridOpts(pos_left="0%", pos_right="1%", pos_top="12%", height="58%")
grid1_opts = opts.GridOpts(pos_left="0%", pos_right="1%", pos_top="74%", height="8%")
grid2_opts = opts.GridOpts(pos_left="0%", pos_right="1%", pos_top="86%", height="10%")
grid_chart = Grid(init_opts)
grid_chart.add(chart_k, grid_opts=grid0_opts)
grid_chart.add(chart_vol, grid_opts=grid1_opts)
grid_chart.add(chart_macd, grid_opts=grid2_opts)
return grid_chart
from pyecharts import options as opts
from pyecharts.charts import Scatter
import pandas as pd
scatter1=Scatter()
# 价格均线
scatter1.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(is_scale=True),
datazoom_opts=[opts.DataZoomOpts()],
title_opts=opts.TitleOpts(title="test"))
df2 = pd.read_csv("F:\\Stock\\html_png_Total_day\\2019-10-10\\2019-10-10_Total_Day.csv")
print(df2['Final portfolio value'].shape[0])
x=range(df2['Final portfolio value'].shape[0])
y=df2['Final portfolio value']/10000
scatter1.add_xaxis(x)
scatter1.add_yaxis("sma",y)
scatter1.render(path='F:\\Stock/html_png_Total_day/aaa.html')
bar = Bar()
bar.add_xaxis(vanguard_club)
bar.add_yaxis('', vanguard_shot, gap="0%")
bar.add_yaxis('', vanguard_speed, gap="0%")
bar.add_yaxis('', vanguard_power, gap="0%")
bar.set_global_opts(
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-30)),
title_opts=opts.TitleOpts(title="各球队前锋数据", subtitle="射术、速度和力量"),
datazoom_opts=opts.DataZoomOpts(),
)
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.render_notebook()
# 锋线散点图
scatter = Scatter()
scatter.add_xaxis(vanguard_club)
scatter.add_yaxis("shot", vanguard_shot, symbol='pin')
scatter.add_yaxis("speed", vanguard_speed, symbol='triangle')
scatter.add_yaxis("power", vanguard_power, symbol='diamond')
scatter.set_global_opts(
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-30)),
title_opts=opts.TitleOpts(title="各球队前锋数据"),
visualmap_opts=opts.VisualMapOpts(type_='size', max_=90, min_=60),
)
scatter.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
scatter.render_notebook()
# 中场
df_midfield = player_df[player_df['staff'] == '中场'][[
'staff', 'club', 'pass', 'speed', 'tape'
]]
data = []
for N in range(1,75):
Q = 0
for x in range(0,M):
bir=[(random.randint(1,365))for i in range(N)]
sbir=set(bir)
if(len(sbir)<len(bir)):Q+=1
mydict={}
mydict[N]=Q/M
# print(mydict)
data.append(Q/M)
# print(Q)
# print(Q/M)
# N+=1
# M += 1
line.add_xaxis(columns)
line.add_yaxis("%d个班级"%M,data,label_opts=opts.LabelOpts(is_show=False))
# print(data)
line.render(r"C:\Users\tony5\Desktop\pyclass\master\multi.html")
print('end')
except:
print("error")
from bisect import bisect_left
from random import randint
def make_word_list():
"""Reads lines from a file and builds a list using append."""
word_list = []
fin = open(r'C:\Users\tony5\Desktop\pyclass\master\words.txt','r')
# 设置饼图（环形图）半径范围，单位为百分比
radius=[0, 40]
)
pie.add(
"Cat2",
list(zip(Faker.choose(), Faker.values())),
rosetype="radius",
radius=[60, 100]
)
pie.render_notebook()
# %% [markdown]
# ### Scatter -- 散点图
scatter = Scatter()
scatter.add_xaxis(Faker.choose())
scatter.add_yaxis("cat1", Faker.values())
scatter.add_yaxis("cat2", Faker.values())
scatter.render_notebook()
# %% [markdown]
# #### Scatter -- 气泡图（大小标识数量）
scatter = Scatter()
scatter.add_xaxis(Faker.choose())
scatter.add_yaxis("cat1", Faker.values())
scatter.add_yaxis("cat2", Faker.values())
scatter.set_global_opts(
visualmap_opts=opts.VisualMapOpts(
type_="size"
)
class ScatterChart(base_chart.BaseChart):
chart = None
max_y = None
max_x = None
min_x = None
def __init__(self, title, xaxis_name, yaxis_name, xaxis_formatter):
base_chart.BaseChart.__init__(self,
title,
xaxis_name,
yaxis_name,
xaxis_formatter=xaxis_formatter)
def clear(self):
self.data.clear()
def set_data(self, **data):
self.clear()
if ('x' in data) & ('y' in data):
self.data.append([data['x'], data['y']])
self.max_x = max(data['x'])
self.max_y = max(data['y'])
self.min_x = min(data['x'])
if 'max_x' in data:
self.max_x = data['max_x']
if 'min_x' in data:
self.min_x = data['min_x']
if 'max_y' in data:
self.max_y = data['max_y']
return self
def show(self):
return self.chart
def plot(self):
self.chart = Scatter(init_opts=opts.InitOpts(
page_title=self.title, width='600px', height='500px'))
# load data
self.chart.add_xaxis(self.data[0][0])
self.chart.add_yaxis(self.yaxis_name, self.data[0][1])
# set options
self.chart.set_global_opts(
title_opts=opts.TitleOpts(title=self.title),
toolbox_opts=opts.ToolboxOpts(is_show=True),
datazoom_opts=opts.DataZoomOpts(is_show=True,
type_='slider',
range_start=0,
range_end=100),
xaxis_opts=opts.AxisOpts(
name=self.xaxis_name,
type_='time',
name_location='end',
name_gap=15,
splitline_opts=opts.SplitLineOpts(is_show=True),
min_=self.min_x,
max_=self.max_x),
yaxis_opts=opts.AxisOpts(
name=self.yaxis_name,
name_location='center',
name_gap=15,
splitline_opts=opts.SplitLineOpts(is_show=True),
max_=self.max_y),
visualmap_opts=opts.VisualMapOpts(max_=self.max_y))
self.chart.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
return self
def find_correlation_render(attributes, data, pearsonr, query, table_path,
answer):
dimensions = len(attributes)
if dimensions == 2:
data[0] = list(map(str, data[0]))
data[1] = list(map(float, data[0]))
l1_1 = Scatter()
l1_1.add_xaxis(data[0])
l1_1.add_yaxis("", data[1])
l1_1.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(name=attributes[0]),
yaxis_opts=opts.AxisOpts(name=attributes[1]),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
grid = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG,
))
grid.add(l1_1, grid_opts={'left': '15%', 'bottom': '34%'})
option1 = grid.dump_options_with_quotes()
option1 = json.loads(option1)
option = {"option": [option1], "query": query}
return option
elif dimensions == 3:
l1_1 = Scatter()
data[0] = list(map(str, data[0]))
data[1] = list(map(float, data[1]))
data[2] = list(map(float, data[2]))
l1_1.add_xaxis(data[0])
l1_1.add_yaxis("", data[1])
l1_1.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(
name=attributes[0],
axislabel_opts=opts.LabelOpts(rotate=50, interval=0),
grid_index=0,
),
yaxis_opts=opts.AxisOpts(
name=attributes[1],
grid_index=0,
),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
l1_2 = Scatter()
l1_2.add_xaxis(data[0])
l1_2.add_yaxis("", data[2])
l1_2.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(
name=attributes[0],
axislabel_opts=opts.LabelOpts(rotate=50, interval=0),
grid_index=1,
),
yaxis_opts=opts.AxisOpts(name=attributes[2], grid_index=1),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
z=100,
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
data[1] = list(map(str, data[1]))
l2_1 = Scatter()
l2_1.add_xaxis(data[1])
l2_1.add_yaxis("", data[2])
l2_1.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(name=attributes[0],
axislabel_opts=opts.LabelOpts(rotate=50,
interval=0),
grid_index=2),
yaxis_opts=opts.AxisOpts(name=attributes[1], grid_index=2),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
grid = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG,
))
grid.add(
chart=l1_1,
grid_opts=opts.GridOpts(pos_right="57%",
pos_bottom="20%",
pos_top="40%"),
grid_index=0,
)
grid.add(
chart=l1_2,
grid_opts=opts.GridOpts(pos_left="57%",
pos_bottom="20%",
pos_top="40%"),
grid_index=1,
)
grid.add(
chart=l2_1,
grid_opts=opts.GridOpts(pos_right="57%", pos_bottom="60%"),
grid_index=2,
)
option1 = grid.dump_options_with_quotes()
option1 = json.loads(option1)
option = {"option": [option1], "query": query}
return option
elif dimensions == 4:
data[0] = list(map(str, data[0]))
data[1] = list(map(float, data[1]))
data[2] = list(map(float, data[2]))
data[3] = list(map(float, data[3]))
l1_1 = Scatter()
l1_1.add_xaxis(data[0])
l1_1.add_yaxis("", data[1])
l1_1.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(
name=attributes[0],
axislabel_opts=opts.LabelOpts(rotate=50, interval=0),
grid_index=0,
),
yaxis_opts=opts.AxisOpts(
name=attributes[1],
grid_index=0,
),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
l1_2 = Scatter()
l1_2.add_xaxis(data[0])
l1_2.add_yaxis("", data[2])
l1_2.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(
name=attributes[0],
axislabel_opts=opts.LabelOpts(rotate=50, interval=0),
grid_index=1,
),
yaxis_opts=opts.AxisOpts(name=attributes[2], grid_index=1),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
l2_1 = Scatter()
l2_1.add_xaxis(data[0])
l2_1.add_yaxis("", data[3])
l2_1.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(name=attributes[0],
axislabel_opts=opts.LabelOpts(rotate=50,
interval=0),
grid_index=2),
yaxis_opts=opts.AxisOpts(name=attributes[3], grid_index=2),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
data[1] = list(map(str, data[1]))
l2_2 = Scatter()
l2_2.add_xaxis(data[1])
l2_2.add_yaxis("", data[2])
l2_2.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(name=attributes[1],
axislabel_opts=opts.LabelOpts(rotate=50,
interval=0),
grid_index=3),
yaxis_opts=opts.AxisOpts(name=attributes[2], grid_index=3),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
grid = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG,
))
grid.add(
chart=l1_1,
grid_opts=opts.GridOpts(pos_right="57%",
pos_bottom="20%",
pos_top="40%"),
grid_index=0,
)
grid.add(
chart=l1_2,
grid_opts=opts.GridOpts(pos_left="57%",
pos_bottom="20%",
pos_top="40%"),
grid_index=1,
)
grid.add(
chart=l2_1,
grid_opts=opts.GridOpts(pos_right="57%", pos_bottom="60%"),
grid_index=2,
)
grid.add(
chart=l2_2,
grid_opts=opts.GridOpts(pos_left="57%", pos_bottom="60%"),
grid_index=3,
)
r1_1 = Scatter()
r1_1.add_xaxis(data[1])
r1_1.add_yaxis("", data[3])
r1_1.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(name=attributes[1],
axislabel_opts=opts.LabelOpts(rotate=50,
interval=0),
grid_index=0),
yaxis_opts=opts.AxisOpts(name=attributes[3], grid_index=0),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
data[2] = list(map(str, data[2]))
r1_2 = Scatter()
r1_2.add_xaxis(data[2])
r1_2.add_yaxis("", data[3])
r1_2.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(name=attributes[2],
axislabel_opts=opts.LabelOpts(rotate=50,
interval=0),
grid_index=1),
yaxis_opts=opts.AxisOpts(name=attributes[3], grid_index=1),
graphic_opts=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=[
'\n' + "Q:" + ' ' + query + '\n' + 'A:' + ' ' +
answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
grid1 = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG,
))
grid1.add(
chart=r1_1,
grid_opts=opts.GridOpts(pos_right="57%", pos_bottom="30%"),
grid_index=0,
)
grid1.add(
chart=r1_2,
grid_opts=opts.GridOpts(pos_left="57%", pos_bottom="30%"),
grid_index=1,
)
option1 = grid.dump_options_with_quotes()
option1 = json.loads(option1)
option2 = grid1.dump_options_with_quotes()
option2 = json.loads(option2)
option = {"option": [option1, option2], "query": query}
return option
def Plot(self, jine: list, hushu: list, coef: list, date :str = None, title : str = None, size_def = lambda x: 50 if 10 + x > 50 else 10 + x):
##配置全局变量
j_list = [0 for _ in jine]
h_list = [0 for _ in hushu]
plot = Scatter(init_opts = opts.InitOpts(width = self.width, height = self.height, theme = self.theme))
plot.set_global_opts(
title_opts=opts.TitleOpts(title=title),
xaxis_opts = opts.AxisOpts(type_="value",
splitline_opts=opts.SplitLineOpts(is_show=False),
min_ = self.x_min, max_ = self.x_max,
name = self.data_name[self.x_index]),
yaxis_opts = opts.AxisOpts(type_="value",
splitline_opts=opts.SplitLineOpts(is_show=False),
min_ = self.y_min, max_ = self.y_max,
name = self.data_name[self.y_index]),
toolbox_opts = opts.ToolboxOpts(orient = 'horizontal', pos_top = 0,
feature = opts.ToolBoxFeatureOpts(
save_as_image = opts.ToolBoxFeatureSaveAsImageOpts(type_ = "jpeg", pixel_ratio = 4, background_color = 'white'),
restore = opts.ToolBoxFeatureRestoreOpts(),
data_zoom = opts.ToolBoxFeatureDataZoomOpts(),
data_view = opts.ToolBoxFeatureDataViewOpts(is_show = False),
magic_type = opts.ToolBoxFeatureMagicTypeOpts(is_show = False),
brush = opts.ToolBoxFeatureBrushOpts(type_=[]))),
tooltip_opts=opts.TooltipOpts(is_show=True, trigger="item", axis_pointer_type="cross")
)
##逐个添加点
for item in self.data_value:
#数据处理
local = str(item[self.local_index])
num = float(item[self.x_index])
gold = float(item[self.y_index])
name = str(item[self.name_index])
size = 0.
for s in range(len(self.size_index)):
size += item[self.size_index[s]]*self.size_coef[s]
tips = '日期:{}'.format(date)
for s in range(len(self.data_name)):
tips += '<br>'
tips += '{}:{}'.format(self.data_name[s], item[s])
#添加点及其tips
plot.add_xaxis([num])
plot.add_yaxis(local, [gold], symbol_size = size_def(size),
tooltip_opts=opts.TooltipOpts(formatter = tips),
label_opts=opts.LabelOpts(formatter = name))
#计算达标人数
for i in range(len(j_list)):
if gold >= jine[i]:
j_list[i] += 1
for i in range(len(h_list)):
if num >= hushu[i]:
h_list[i] += 1
##添加达标线及其注释点
for item in range(len(j_list)):
plot.add_xaxis([self.x_max])
plot.add_yaxis('达标线', [jine[item]], symbol_size = 25, symbol = 'pin',
label_opts = opts.LabelOpts(is_show = False),
tooltip_opts = opts.TooltipOpts(formatter = '达标人数:{}<br>未达标人数:{}'.format(j_list[item], self.num-j_list[item])),
markline_opts = opts.MarkLineOpts(data = [opts.MarkLineItem(y = jine[item], name = '金额达标线{}'.format(i+1))],
label_opts = opts.LabelOpts(is_show = False),
symbol_size = 0))
for item in range(len(h_list)):
plot.add_xaxis([hushu[item]])
plot.add_yaxis('达标线', [self.y_max], symbol_size = 25, symbol = 'pin',
label_opts = opts.LabelOpts(is_show = False),
tooltip_opts = opts.TooltipOpts(formatter = '奖励系数:x{}<br>达标人数:{}<br>未达标人数:{}'.format(coef[item], h_list[item], self.num-h_list[item])),
markline_opts = opts.MarkLineOpts(data = [opts.MarkLineItem(x = hushu[item], name = '户数达标线{}'.format(i+1))],
label_opts = opts.LabelOpts(is_show = False),
symbol_size = 0))
return plot
def generate_scatter_html_with_multi_tables(tables,
title="可转债分布情况",
subtitle=None,
select=None,
use_personal_features=True,
price_field_name='转债价格'):
chart_id = str(abs(hash(title)))
scatter = Scatter(
opts.InitOpts(height='700px',
width='1424px',
theme=ThemeType.LIGHT,
chart_id=chart_id))
scatter.add_js_funcs('chart_' + chart_id +
""".on('click', function(params){
// alert(params)
popWin.showWin("1200","600", params['data']['value'][3]);
})
""")
for label, table in tables.items():
if select is not None and label not in select:
continue
x = []
y = []
point_items = []
rows = table._rows
for row in rows:
record = get_record(table, row)
if record['溢价率'] is None:
continue
x1 = record[price_field_name]
x.append(x1)
y1 = record['溢价率'].replace('%', '') * 1
amount = record.get("持有数量", 0)
bond_name = record['名称'].replace('转债', '')
bond_code = record['bond_code']
bond_code = trade_utils.rebuild_bond_code(bond_code)
y.append([y1])
# todo symbol 轮出:triangle 轮入:diamond
if use_personal_features and record.get(
'hold_id') is not None and amount > 0:
point_items.append(
opts.MarkPointItem(
coord=[x1, y1],
symbol_size=amount,
itemstyle_opts=opts.ItemStyleOpts(
opacity=0.5,
border_color='#000',
border_width=1,
),
value=[bond_name, x1, y1, bond_code, amount]))
else:
point_items.append(
opts.MarkPointItem(
coord=[x1, y1],
# symbol_size=symbol_size,
itemstyle_opts=opts.ItemStyleOpts(
# color='#fff',
# border_color='#000'
),
value=[bond_name, x1, y1, bond_code]))
scatter.add_xaxis(x)
scatter.add_yaxis(
label,
y,
label_opts=opts.LabelOpts(is_show=False),
markpoint_opts=opts.MarkPointOpts(
symbol='circle',
symbol_size=10,
data=point_items,
label_opts=opts.LabelOpts(
position='bottom',
formatter=JsCode(
'function(params){return params.value[0]}'))),
markline_opts=opts.MarkLineOpts(
linestyle_opts=opts.LineStyleOpts(type_='dashed'),
is_silent=True,
label_opts=opts.LabelOpts(
position='end',
formatter=JsCode(
"function(params){return params.data['name'];}")),
data=[
opts.MarkLineItem(x=utils.trade_utils.MID_X,
name='中位数(' +
str(utils.trade_utils.MID_X) + '元)'),
opts.MarkLineItem(y=utils.trade_utils.MID_Y,
name='中位数(' +
str(utils.trade_utils.MID_Y) + '%)'),
]))
# scatter.add_xaxis(x)
scatter.set_global_opts(
title_opts=opts.TitleOpts(title=title,
subtitle=subtitle,
pos_left='center'),
tooltip_opts=opts.TooltipOpts(formatter=get_hover_js_code()),
legend_opts=opts.LegendOpts(pos_bottom=-5,
# selected_mode='single'
),
toolbox_opts=opts.ToolboxOpts(feature={
'dataZoom': {},
}),
# visualmap_opts=opts.VisualMapOpts(
# type_="color", max_=150, min_=20, dimension=1
# ),
xaxis_opts=opts.AxisOpts(
# data=None,
type_='value',
name='转债价格(元)',
name_gap=30,
is_scale=True,
name_location='middle',
splitline_opts=opts.SplitLineOpts(is_show=False),
axislabel_opts=opts.LabelOpts(formatter='{value}元'),
axisline_opts=opts.AxisLineOpts(is_on_zero=False,
symbol=['none', 'arrow'])),
yaxis_opts=opts.AxisOpts(
type_='value',
name='转股溢价率(%)',
name_rotate=90,
name_gap=35,
name_location='middle',
is_scale=True,
axislabel_opts=opts.LabelOpts(formatter='{value}%'),
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(is_on_zero=False,
symbol=['none', 'arrow'])))
scatter_html = scatter.render_embed('template.html', env)
return scatter_html
def create_scatter(title,
sub_title,
field_name,
label_y,
point_items,
x,
y,
hover_maker=None,
click_maker=None):
chart_id = str(abs(hash(title)))
scatter = Scatter(
opts.InitOpts(height='700px', width='1424px', chart_id=chart_id))
if click_maker is None:
click_maker = get_click_js_code
scatter.add_js_funcs(click_maker(chart_id))
scatter.add_xaxis(xaxis_data=x)
show_label = True
if len(point_items) > 100:
show_label = False
scatter.add_yaxis(
series_name="",
y_axis=y,
color=choice(colors),
label_opts=opts.LabelOpts(is_show=False, ),
markline_opts=opts.MarkLineOpts(
linestyle_opts=opts.LineStyleOpts(type_='dashed'),
is_silent=True,
label_opts=opts.LabelOpts(
position='end',
formatter=JsCode(
"function(params){return params.data['name'];}")),
data=[
opts.MarkLineItem(x=utils.trade_utils.MID_X,
name='中位数(' + str(utils.trade_utils.MID_X) +
'元)'),
opts.MarkLineItem(y=utils.trade_utils.MID_Y,
name='中位数(' + str(utils.trade_utils.MID_Y) +
'%)'),
]),
markpoint_opts=opts.MarkPointOpts(
symbol='circle',
symbol_size=12,
data=point_items,
label_opts=opts.LabelOpts(
is_show=show_label,
position='bottom',
formatter=JsCode('function(params){return params.value[0]}'))))
if title is not None and title.strip(' ') != '':
title = "=========" + title + "========="
if hover_maker is None:
hover_maker = get_hover_js_code
scatter.set_global_opts(
title_opts=opts.TitleOpts(title=title,
subtitle=sub_title,
pos_left='center'),
tooltip_opts=opts.TooltipOpts(formatter=hover_maker(field_name), ),
toolbox_opts=opts.ToolboxOpts(feature={
'dataZoom': {},
}),
xaxis_opts=opts.AxisOpts(
# data=None,
type_='value',
name='转债价格(元)',
name_gap=30,
is_scale=True,
name_location='middle',
splitline_opts=opts.SplitLineOpts(is_show=False),
axislabel_opts=opts.LabelOpts(formatter='{value}元'),
axisline_opts=opts.AxisLineOpts(is_on_zero=False,
symbol=['none', 'arrow'])),
yaxis_opts=opts.AxisOpts(
type_='value',
name=label_y,
name_rotate=90,
name_gap=35,
name_location='middle',
is_scale=True,
axislabel_opts=opts.LabelOpts(formatter='{value}%'),
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(is_on_zero=False,
symbol=['none', 'arrow'])),
)
scatter_html = scatter.render_embed('template.html', env)
return "<br/>" + scatter_html
def plt(key):
"""连接hbase"""
connection = happybase.Connection(host="localhost", port=9090)
"""打开传输"""
connection.open()
"""连接表"""
basicFeaturesTable = happybase.Table('basicFeaturesTable', connection)
socialAttributesTable = happybase.Table('socialAttributesTable',
connection)
consumptionFeaturesTable = happybase.Table('consumptionFeaturesTable',
connection)
internetFeaturesTable = happybase.Table('internetFeaturesTable',
connection)
consumptionCharacteristicsTable = happybase.Table(
'consumptionCharacteristicsTable', connection)
internetBehaviorTable = happybase.Table('internetBehaviorTable',
connection)
"""获取信息"""
try:
key_name = basicFeaturesTable.row(key, columns=["name"])
except:
"""连接hbase"""
connection = happybase.Connection(host="localhost", port=9090)
"""打开传输"""
connection.open()
"""连接表"""
basicFeaturesTable = happybase.Table('basicFeaturesTable', connection)
socialAttributesTable = happybase.Table('socialAttributesTable',
connection)
consumptionFeaturesTable = happybase.Table('consumptionFeaturesTable',
connection)
internetFeaturesTable = happybase.Table('internetFeaturesTable',
connection)
consumptionCharacteristicsTable = happybase.Table(
'consumptionCharacteristicsTable', connection)
internetBehaviorTable = happybase.Table('internetBehaviorTable',
connection)
key_name = basicFeaturesTable.row(key, columns=["name"])
key_name = list(key_name.values())
key_name = key_name[0].decode()
try:
sInfo = socialAttributesTable.row(key,
columns=["incLevel", "eduLevel"])
cInfo = consumptionFeaturesTable.row(key,
columns=["CMLevel", "CTLevel"])
iInfo = internetFeaturesTable.row(key, columns=["intLevel"])
consumptionCharacteristicsInfo = consumptionCharacteristicsTable.row(
key, columns=["commodity", "price", "date"])
internetBehaviorInfo = internetBehaviorTable.row \
(key, columns=
["date", "news", "communications", "entertainment", "domersticServices", "busApp", "toolUse"]
)
except:
"""连接hbase"""
connection = happybase.Connection(host="localhost", port=9090)
"""打开传输"""
connection.open()
"""连接表"""
basicFeaturesTable = happybase.Table('basicFeaturesTable', connection)
socialAttributesTable = happybase.Table('socialAttributesTable',
connection)
consumptionFeaturesTable = happybase.Table('consumptionFeaturesTable',
connection)
internetFeaturesTable = happybase.Table('internetFeaturesTable',
connection)
consumptionCharacteristicsTable = happybase.Table(
'consumptionCharacteristicsTable', connection)
internetBehaviorTable = happybase.Table('internetBehaviorTable',
connection)
sInfo = socialAttributesTable.row(key,
columns=["incLevel", "eduLevel"])
cInfo = consumptionFeaturesTable.row(key,
columns=["CMLevel", "CTLevel"])
iInfo = internetFeaturesTable.row(key, columns=["intLevel"])
consumptionCharacteristicsInfo = consumptionCharacteristicsTable.row(
key, columns=["commodity", "price", "date"])
internetBehaviorInfo = internetBehaviorTable.row \
(key, columns=
["date", "news", "communications", "entertainment", "domersticServices", "busApp", "toolUse"]
)
"""消费情况图"""
consumptionCharacteristicsValues = list(
consumptionCharacteristicsInfo.values())
consumptionCharacteristicsValues = list(
map(lambda x: x.decode(), consumptionCharacteristicsValues))
consumptionCharacteristicsValues[
int(len(consumptionCharacteristicsValues) / 3):-int(len(consumptionCharacteristicsValues) / 3)] \
= list(map(int, consumptionCharacteristicsValues[int(len(consumptionCharacteristicsValues) / 3):
-int(len(consumptionCharacteristicsValues) / 3)]))
consumptionCharacteristicsValues[-int(len(consumptionCharacteristicsValues) / 3):] \
= list(map(int, consumptionCharacteristicsValues[-int(len(consumptionCharacteristicsValues) / 3):]))
consumptionCharacteristicsData = []
consumptionCharacteristicsData.append(
consumptionCharacteristicsValues[:int(
len(consumptionCharacteristicsValues) / 3)])
consumptionCharacteristicsData.append(consumptionCharacteristicsValues[
int(len(consumptionCharacteristicsValues) /
3):-int(len(consumptionCharacteristicsValues) / 3)])
consumptionCharacteristicsData.append(consumptionCharacteristicsValues[
-int(len(consumptionCharacteristicsValues) / 3):])
consumptionCharacteristicsData = pd.DataFrame(
consumptionCharacteristicsData).T
consumptionCharacteristicsData.columns = ["commodity", "date", "price"]
consumptionCharacteristicsData.sort_values(by="date", inplace=True)
consumptionCharacteristicsData_y = consumptionCharacteristicsData.loc[:,
"date"].tolist(
)
consumptionCharacteristicsData_y = list(
map(str, consumptionCharacteristicsData_y))
consumptionCharacteristicsData_x = consumptionCharacteristicsData.loc[:,
"price"].tolist(
)
consumptionCharacteristicsData_commodity = consumptionCharacteristicsData.loc[:,
"commodity"].tolist(
)
quzhong_consumptionCharacteristicsData_y = list(
set(consumptionCharacteristicsData_y))
if len(quzhong_consumptionCharacteristicsData_y) != len(
consumptionCharacteristicsData_y):
for i in range(len(quzhong_consumptionCharacteristicsData_y)):
count_consumptionCharacteristicsData_y = consumptionCharacteristicsData_y. \
count(quzhong_consumptionCharacteristicsData_y[i])
if count_consumptionCharacteristicsData_y != 1:
index = consumptionCharacteristicsData_y.index(
quzhong_consumptionCharacteristicsData_y[i])
consumptionCharacteristicsData_y = consumptionCharacteristicsData_y[:index + 1] + \
consumptionCharacteristicsData_y[
index + count_consumptionCharacteristicsData_y:]
consumptionCharacteristicsData_x[index] = sum(
consumptionCharacteristicsData_x[
index:index + count_consumptionCharacteristicsData_y])
consumptionCharacteristicsData_x = consumptionCharacteristicsData_x[:index + 1] + \
consumptionCharacteristicsData_x[
index + count_consumptionCharacteristicsData_y:]
consumptionCharacteristicsData_commodity[index] = \
",".join(
consumptionCharacteristicsData_commodity[index:index + count_consumptionCharacteristicsData_y])
consumptionCharacteristicsData_commodity \
= consumptionCharacteristicsData_commodity[:index + 1] + \
consumptionCharacteristicsData_commodity[index + count_consumptionCharacteristicsData_y:]
consumptionCharacteristicsData_xx = \
[list(z) for z in zip(consumptionCharacteristicsData_x, consumptionCharacteristicsData_commodity)]
scatter = Scatter(init_opts=opts.InitOpts(width="850px", height="380px"))
scatter.add_xaxis(consumptionCharacteristicsData_y)
scatter.add_yaxis("", consumptionCharacteristicsData_xx, color="red")
scatter.set_global_opts(
tooltip_opts=opts.TooltipOpts(
trigger="item",
axis_pointer_type="cross",
formatter=JsCode(
"function (params) {return '消费日期：' + params.name + ' <br/>消费金额：' + params.value[1] + '元 <br/>消费产品：' + params.value[2];}"
)),
yaxis_opts=opts.AxisOpts(
name="消费金额",
type_="value",
name_textstyle_opts=opts.TextStyleOpts(color="white"), ###########
axislabel_opts=opts.LabelOpts(formatter="{value} 元",
border_color="white",
color="white"), ########
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
xaxis_opts=opts.AxisOpts(
name="消费日期",
type_="category",
name_textstyle_opts=opts.TextStyleOpts(color="white"), ###########
axislabel_opts=opts.LabelOpts(border_color="white",
color="white"), ##############
axispointer_opts=opts.AxisPointerOpts(is_show=True,
type_="shadow"),
),
legend_opts=opts.LegendOpts(is_show=False))
scatter.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
line = Line(init_opts=opts.InitOpts(width="850px", height="380px"))
line.add_xaxis(consumptionCharacteristicsData_y)
line.add_yaxis(series_name="",
y_axis=consumptionCharacteristicsData_x,
color="red")
scatter.overlap(line)
scatter.render("./static/html/pictureConsumptionCharacteristics.html")
"""互联网行为图"""
internetBehaviorInfoKeys = list(internetBehaviorInfo.keys())
internetBehaviorInfoKeys = list(
map(lambda x: x.decode(), internetBehaviorInfoKeys))
internetBehaviorInfoKeys = list(
map(lambda x: x[:x.index(':')], internetBehaviorInfoKeys))
internetBehaviorInfoValues = list(internetBehaviorInfo.values())
internetBehaviorInfoValues = list(
map(lambda x: x.decode(), internetBehaviorInfoValues))
internetBehaviorInfoValues = list(map(int, internetBehaviorInfoValues))
internetBehaviorData = []
splitNum = int(len(internetBehaviorInfoValues) / 7)
internetBehaviorData.append(internetBehaviorInfoValues[:splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[splitNum:2 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[2 * splitNum:3 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[3 * splitNum:4 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[4 * splitNum:5 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[5 * splitNum:6 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[6 * splitNum:7 *
splitNum])
internetBehaviorData = pd.DataFrame(internetBehaviorData).T
internetBehaviorData.columns = [
internetBehaviorInfoKeys[0], internetBehaviorInfoKeys[splitNum],
internetBehaviorInfoKeys[2 * splitNum],
internetBehaviorInfoKeys[3 * splitNum],
internetBehaviorInfoKeys[4 * splitNum],
internetBehaviorInfoKeys[5 * splitNum],
internetBehaviorInfoKeys[6 * splitNum]
]
internetBehaviorData.sort_values(by="date", inplace=True)
internetBehaviorData_y = internetBehaviorData.loc[:, "date"].tolist()
internetBehaviorData_y = list(map(str, internetBehaviorData_y))
bar = Bar(init_opts=opts.InitOpts(width="800px", height="380px"))
bar.add_xaxis(internetBehaviorData_y)
bar.add_yaxis(series_name="新闻资讯",
yaxis_data=internetBehaviorData.loc[:, "news"].tolist(),
stack="stack")
bar.add_yaxis(
series_name="通信交流",
yaxis_data=internetBehaviorData.loc[:, "communications"].tolist(),
stack="stack")
bar.add_yaxis(
series_name="娱乐休闲",
yaxis_data=internetBehaviorData.loc[:, "entertainment"].tolist(),
stack="stack")
bar.add_yaxis(
series_name="生活服务",
yaxis_data=internetBehaviorData.loc[:, "domersticServices"].tolist(),
stack="stack")
bar.add_yaxis(series_name="商务应用",
yaxis_data=internetBehaviorData.loc[:, "busApp"].tolist(),
stack="stack")
bar.add_yaxis(series_name="工具使用",
yaxis_data=internetBehaviorData.loc[:, "toolUse"].tolist(),
stack="stack")
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.set_global_opts(
tooltip_opts=opts.TooltipOpts(is_show=True,
trigger="axis",
axis_pointer_type="cross"),
xaxis_opts=opts.AxisOpts(
name="日期",
name_textstyle_opts=opts.TextStyleOpts(color="white"), ###########
type_="category",
axislabel_opts=opts.LabelOpts(border_color="white",
color="white"), #############
axispointer_opts=opts.AxisPointerOpts(is_show=True),
),
yaxis_opts=opts.AxisOpts(
name="时间",
name_textstyle_opts=opts.TextStyleOpts(color="white"),
type_="value",
min_=0,
max_=24,
interval=4,
axislabel_opts=opts.LabelOpts(formatter="{value} 小时",
border_color="white",
color="white"), ###########
axistick_opts=opts.AxisTickOpts(is_show=True),
),
datazoom_opts=opts.DataZoomOpts(type_="inside"),
legend_opts=opts.LegendOpts(is_show=True,
textstyle_opts=opts.TextStyleOpts(
border_color="white", color="wihte"),
orient='horizontal'))
bar.render("./static/html/pictureInternetBehavior.html")
"""个人特征图"""
sValue = list(sInfo.values())
sValue = list(map(lambda x: x.decode(), sValue))
cValue = list(cInfo.values())
cValue = list(map(lambda x: x.decode(), cValue))
iValue = list(iInfo.values())
iValue = list(map(lambda x: x.decode(), iValue))
value = sValue + cValue + iValue
value = list(map(int, value))
value = [value[1], value[2], value[3], value[0], value[4]]
value = [value]
rader = Radar(init_opts=opts.InitOpts(width="350px", height="350px"))
rader.add_schema(schema=[
opts.RadarIndicatorItem(name="收入指数", max_=5),
opts.RadarIndicatorItem(name="消费金\n额指数", max_=5),
opts.RadarIndicatorItem(name="消费次数指数", max_=5),
opts.RadarIndicatorItem(name="学历指数", max_=5),
opts.RadarIndicatorItem(name="网络依\n赖指数", max_=5),
],
shape='polygon')
rader.add(series_name=key_name, data=value)
rader.set_global_opts(legend_opts=opts.LegendOpts(is_show=False))
rader.render("./static/html/pictureCompositiveInfo.html")
def kline_pro(kline: List[dict],
fx: List[dict] = None,
xd=None,
bs: List[dict] = None,
title: str = "缠中说禅K线分析",
width: str = "1400px",
height: str = '580px') -> Grid:
"""绘制缠中说禅K线分析结果
:param kline: K线
:param fx: 分型识别结果
:param bi: 笔识别结果
:param xd: 线段识别结果
:param zs: 中枢
:param bs: 买卖点
:param title: 图表标题
:param width: 图表宽度
:param height: 图表高度
:return: 用Grid组合好的图表
"""
# 配置项设置
# ------------------------------------------------------------------------------------------------------------------
bg_color = "#1f212d" # 背景
up_color = "#F9293E"
down_color = "#00aa3b"
init_opts = opts.InitOpts(bg_color=bg_color,
width=width,
height=height,
animation_opts=opts.AnimationOpts(False))
title_opts = opts.TitleOpts(
title=title,
pos_top="1%",
title_textstyle_opts=opts.TextStyleOpts(color=up_color, font_size=20),
subtitle_textstyle_opts=opts.TextStyleOpts(color=down_color,
font_size=12))
label_not_show_opts = opts.LabelOpts(is_show=False)
legend_not_show_opts = opts.LegendOpts(is_show=False)
red_item_style = opts.ItemStyleOpts(color=up_color)
green_item_style = opts.ItemStyleOpts(color=down_color)
k_style_opts = opts.ItemStyleOpts(color=up_color,
color0=down_color,
border_color=up_color,
border_color0=down_color,
opacity=0.8)
legend_opts = opts.LegendOpts(is_show=True,
pos_top="1%",
pos_left="30%",
item_width=14,
item_height=8,
textstyle_opts=opts.TextStyleOpts(
font_size=12, color="#0e99e2"))
brush_opts = opts.BrushOpts(tool_box=["rect", "polygon", "keep", "clear"],
x_axis_index="all",
brush_link="all",
out_of_brush={"colorAlpha": 0.1},
brush_type="lineX")
axis_pointer_opts = opts.AxisPointerOpts(is_show=True,
link=[{
"xAxisIndex": "all"
}])
range_start = int(100 - 216 / len(kline) * 100)
dz_inside = opts.DataZoomOpts(False,
"inside",
xaxis_index=[0, 1, 2],
range_start=range_start,
range_end=100)
dz_slider = opts.DataZoomOpts(True,
"slider",
xaxis_index=[0, 1, 2],
pos_top="96%",
pos_bottom="0%",
range_start=range_start,
range_end=100)
yaxis_opts = opts.AxisOpts(is_scale=True,
axislabel_opts=opts.LabelOpts(
color="#c7c7c7",
font_size=8,
position="inside"))
grid0_xaxis_opts = opts.AxisOpts(
type_="category",
grid_index=0,
axislabel_opts=label_not_show_opts,
split_number=20,
min_="dataMin",
max_="dataMax",
is_scale=True,
boundary_gap=False,
axisline_opts=opts.AxisLineOpts(is_on_zero=False))
tool_tip_opts = opts.TooltipOpts(
trigger="axis",
axis_pointer_type="cross",
background_color="rgba(245, 245, 245, 0.8)",
border_width=1,
border_color="#ccc",
position=JsCode("""
function (pos, params, el, elRect, size) {
var obj = {top: 10};
obj[['left', 'right'][+(pos[0] < size.viewSize[0] / 2)]] = 30;
return obj;
}
"""),
textstyle_opts=opts.TextStyleOpts(color="#000"),
)
# 数据预处理
# ------------------------------------------------------------------------------------------------------------------
# dts = [x.get('dt', x['date']) for x in kline]
try:
dts = [x['date'] for x in kline]
except:
dts = [x['dt'] for x in kline]
# k_data = [[x['open'], x['close'], x['low'], x['high']] for x in kline]
k_data = [
opts.CandleStickItem(
name=i, value=[x['open'], x['close'], x['low'], x['high']])
for i, x in enumerate(kline)
]
vol = []
for i, row in enumerate(kline):
item_style = red_item_style if row['close'] > row[
'open'] else green_item_style
bar = opts.BarItem(name=i,
value=row['volume'],
itemstyle_opts=item_style,
label_opts=label_not_show_opts)
vol.append(bar)
close = np.array([x['close'] for x in kline], dtype=np.double)
diff, dea, macd = MACD(close)
ma5 = SMA(close, timeperiod=5)
ma34 = SMA(close, timeperiod=34)
ma55 = SMA(close, timeperiod=55)
ma233 = SMA(close, timeperiod=233)
macd_bar = []
for i, v in enumerate(macd.tolist()):
item_style = red_item_style if v > 0 else green_item_style
bar = opts.BarItem(name=i,
value=round(v, 4),
itemstyle_opts=item_style,
label_opts=label_not_show_opts)
macd_bar.append(bar)
diff = diff.round(4)
dea = dea.round(4)
# K 线主图
# ------------------------------------------------------------------------------------------------------------------
chart_k = Kline()
chart_k.add_xaxis(xaxis_data=dts)
chart_k.add_yaxis(series_name="Kline",
y_axis=k_data,
itemstyle_opts=k_style_opts)
chart_k.set_global_opts(legend_opts=legend_opts,
datazoom_opts=[dz_inside, dz_slider],
yaxis_opts=yaxis_opts,
tooltip_opts=tool_tip_opts,
axispointer_opts=axis_pointer_opts,
brush_opts=brush_opts,
title_opts=title_opts,
xaxis_opts=grid0_xaxis_opts)
if xd:
index = 0
zs_colors = [
"yellow", "white", '#f034c1', "#7944b7", "#468b58", "#c17f2f",
"#9EA0A1"
]
data = []
temp_xd = xd
while temp_xd:
zs_color = zs_colors[index % len(zs_colors)]
data = data + [
opts.MarkAreaItem(
name='XD{}'.format(index),
x=(x['xd_list'][0]['date'], x['xd_list'][-1]['date']),
y=(x['ZG']['value'], x['ZD']['value']),
label_opts=opts.LabelOpts(color=zs_color),
itemstyle_opts=opts.ItemStyleOpts(
color=zs_color,
opacity=0.2,
)) for x in temp_xd.zs_list
]
temp_xd = temp_xd.next
index = index + 1
chart_k.set_series_opts(
markarea_opts=opts.MarkAreaOpts(is_silent=True, data=data))
# 均线图
# ------------------------------------------------------------------------------------------------------------------
chart_ma = Line()
chart_ma.add_xaxis(xaxis_data=dts)
ma_keys = {"MA5": ma5, "MA34": ma34, "MA55": ma55, "MA233": ma233}
ma_colors = ["#39afe6", "#da6ee8", "#A02128", "#00940b"]
for i, (name, ma) in enumerate(ma_keys.items()):
chart_ma.add_yaxis(series_name=name,
y_axis=ma,
is_smooth=True,
is_selected=False,
symbol_size=0,
label_opts=label_not_show_opts,
linestyle_opts=opts.LineStyleOpts(
opacity=0.8, width=1.0, color=ma_colors[i]))
chart_ma.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_ma)
# 缠论结果
# ------------------------------------------------------------------------------------------------------------------
if fx:
try:
fx_dts = [x['date'] for x in fx]
except:
fx_dts = [x['dt'] for x in fx]
fx_val = [x['value'] for x in fx]
chart_fx = Scatter()
chart_fx.add_xaxis(fx_dts)
chart_fx.add_yaxis(series_name="FX",
y_axis=fx_val,
is_selected=False,
symbol="circle",
symbol_size=6,
label_opts=label_not_show_opts,
itemstyle_opts=opts.ItemStyleOpts(
color="rgba(152, 147, 193, 1.0)", ))
chart_fx.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_fx)
if xd:
index = 0
xd_colors = zs_colors
while xd:
xd_dts = [x['date'] for x in xd]
xd_val = [x['value'] for x in xd]
chart_xd = Line()
chart_xd.add_xaxis(xd_dts)
xd_color = xd_colors[index % len(xd_colors)]
chart_xd.add_yaxis(
series_name="XD{}".format(index),
y_axis=xd_val,
is_selected=True,
symbol="triangle",
symbol_size=10,
linestyle_opts=opts.LineStyleOpts(color=xd_color,
width=index + 1,
type_="solid"),
itemstyle_opts=opts.ItemStyleOpts(color=xd_color))
chart_xd.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_xd)
xd = xd.next
index = index + 1
if bs:
b_dts = [x['date'] for x in bs if x['bs'] == 'buy']
if len(b_dts) > 0:
b_val = [x['value'] for x in bs if x['bs'] == 'buy']
chart_b = Scatter()
chart_b.add_xaxis(b_dts)
chart_b.add_yaxis(series_name="BUY",
y_axis=b_val,
is_selected=False,
symbol="arrow",
symbol_size=8,
itemstyle_opts=opts.ItemStyleOpts(
color="#f31e1e", ))
chart_b.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_b)
s_dts = [x['date'] for x in bs if x['bs'] == 'sell']
if len(s_dts) > 0:
s_val = [x['value'] for x in bs if x['bs'] == 'sell']
chart_s = Scatter()
chart_s.add_xaxis(s_dts)
chart_s.add_yaxis(series_name="SELL",
y_axis=s_val,
is_selected=False,
symbol="pin",
symbol_size=12,
itemstyle_opts=opts.ItemStyleOpts(
color="#45b97d", ))
chart_s.set_global_opts(xaxis_opts=grid0_xaxis_opts,
legend_opts=legend_not_show_opts)
chart_k = chart_k.overlap(chart_s)
# 成交量图
# ------------------------------------------------------------------------------------------------------------------
chart_vol = Bar()
chart_vol.add_xaxis(dts)
chart_vol.add_yaxis(series_name="Volume", y_axis=vol, bar_width='60%')
chart_vol.set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=1,
axislabel_opts=opts.LabelOpts(is_show=True,
font_size=8,
color="#9b9da9"),
),
yaxis_opts=yaxis_opts,
legend_opts=legend_not_show_opts,
)
# MACD图
# ------------------------------------------------------------------------------------------------------------------
chart_macd = Bar()
chart_macd.add_xaxis(dts)
chart_macd.add_yaxis(series_name="MACD", y_axis=macd_bar, bar_width='60%')
chart_macd.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, color="#c7c7c7"),
),
legend_opts=opts.LegendOpts(is_show=False),
)
line = Line()
line.add_xaxis(dts)
line.add_yaxis(series_name="DIFF",
y_axis=diff,
label_opts=label_not_show_opts,
is_symbol_show=False,
linestyle_opts=opts.LineStyleOpts(opacity=0.8,
width=1.0,
color="#da6ee8"))
line.add_yaxis(series_name="DEA",
y_axis=dea,
label_opts=label_not_show_opts,
is_symbol_show=False,
linestyle_opts=opts.LineStyleOpts(opacity=0.8,
width=1.0,
color="#39afe6"))
chart_macd = chart_macd.overlap(line)
grid0_opts = opts.GridOpts(pos_left="0%",
pos_right="1%",
pos_top="12%",
height="58%")
grid1_opts = opts.GridOpts(pos_left="0%",
pos_right="1%",
pos_top="74%",
height="8%")
grid2_opts = opts.GridOpts(pos_left="0%",
pos_right="1%",
pos_top="86%",
height="10%")
grid_chart = Grid(init_opts)
grid_chart.add(chart_k, grid_opts=grid0_opts)
grid_chart.add(chart_vol, grid_opts=grid1_opts)
grid_chart.add(chart_macd, grid_opts=grid2_opts)
return grid_chart
def run_strategy(smaPeriod):
df_new = pd.DataFrame(columns=('shares_ID', 'total number of trades',
'Profit times number of trades',
'Profit Percentage',
'Final portfolio value'))
for (root, dirs, files) in os.walk("E:/Stock/Data_Day"):
z = 0
for x in range(len(files)):
z = z + 1
#K线图
df = pd.read_csv("E:/Stock/Data_Day/" + files[x])
df = df.sort_index(ascending=False).reset_index(drop=True)
print("进度：", z / len(files) * 100, "%")
date = df.xs('Date Time', axis=1).tolist()
data = []
vol = []
for idx in df.index:
row1 = [
df.iloc[idx]['Open'], df.iloc[idx]['Close'],
df.iloc[idx]['Low'], df.iloc[idx]['High']
]
row2 = df.iloc[idx]['Volume']
data.append(row1)
vol.append(row2)
kline1 = Kline()
line1 = Line()
line2 = Line()
line3 = Line()
scatter1 = Scatter()
scatter2 = Scatter()
kline1.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(is_scale=True),
datazoom_opts=[opts.DataZoomOpts()])
kline1.extend_axis(
yaxis=opts.AxisOpts(type_='value', position='right'))
kline1.extend_axis(
yaxis=opts.AxisOpts(type_='value', position='right'))
# 价格均线
line1.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(is_scale=True),
datazoom_opts=[opts.DataZoomOpts()])
# 成交量
line2.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(is_scale=True),
datazoom_opts=[opts.DataZoomOpts()])
#资金量
line3.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(is_scale=True),
datazoom_opts=[opts.DataZoomOpts()])
#买入点
scatter1.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(is_scale=True),
datazoom_opts=[opts.DataZoomOpts()])
#卖出点
scatter2.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(is_scale=True),
datazoom_opts=[opts.DataZoomOpts()])
kline1.add_xaxis(date)
kline1.add_yaxis(files[x], data)
line2.add_xaxis(date)
line2.add_yaxis("vol",
vol,
yaxis_index=1,
label_opts=opts.LabelOpts(is_show=False))
feed = GenericBarFeed(Frequency.DAY, None, None)
feed.addBarsFromCSV("fd", "E:/Stock/Data_Day/" + files[x])
global myStrategy
myStrategy = MyStrategy(feed, "fd", smaPeriod)
trade_situation = trades.Trades()
myStrategy.attachAnalyzer(trade_situation)
plt = plotter.StrategyPlotter(myStrategy)
# Include the SMA in the instrument's subplot to get it displayed along with the closing prices.
plt.getInstrumentSubplot("test").addDataSeries(
"SMA", myStrategy.getSMA())
# Plot the simple returns on each bar.
# plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
myStrategy.run()
scatter1.add_xaxis(myStrategy.Buyday)
scatter1.add_yaxis("Buy", myStrategy.Buyprice)
scatter2.add_xaxis(myStrategy.Sellday)
scatter2.add_yaxis("Sell", myStrategy.Sellprice)
line1.add_xaxis(myStrategy.Barday)
line1.add_yaxis("Price_SMA",
myStrategy.Sma_price,
label_opts=opts.LabelOpts(is_show=False))
line3.add_xaxis(date)
line3.add_yaxis("money",
myStrategy.money,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False))
plt.savePlot("E:/Stock/html_png_Total_day/" + files[x] + ".png")
print(files[x] + " Final portfolio value:$%.2f" %
myStrategy.getBroker().getEquity())
print("total number of trades", trade_situation.getCount())
print("Profit times number of trades ",
trade_situation.getProfitableCount())
if trade_situation.getCount() > 0:
Percentage = trade_situation.getProfitableCount(
) / trade_situation.getCount()
print("百分比", Percentage)
else:
Percentage = 0
print("百分比", 0)
df1 = pd.DataFrame({
"shares_ID": [files[x]],
'total number of trades': [trade_situation.getCount()],
'Profit times number of trades':
trade_situation.getProfitableCount(),
'Profit Percentage':
Percentage,
'Final portfolio value': [myStrategy.getBroker().getEquity()]
})
kline1.overlap(scatter1)
kline1.overlap(scatter2)
kline1.overlap(line1)
kline1.overlap(line2)
kline1.overlap(line3)
kline1.render(path='E:\\Stock/html_png_Total_day/' + files[x] +
'.html')
df_new = pd.concat([df1, df_new], ignore_index=True)
df_new.to_csv("E:/Stock/html_png_Total_day/Total_Min.csv", index=False)
