def get_plot_base(self, _df, title_name='数据分布', subtitle_name=''):
'''
plot line & bar info
:param _df:
:return:
'''
bar = Bar()
line = Line()
bar.set_global_opts(
title_opts=opts.TitleOpts(title=title_name,
subtitle=subtitle_name),
yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(
formatter="{value}")),
datazoom_opts=opts.DataZoomOpts(), # 滑动条
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(
rotate=-15)), # label旋转
toolbox_opts=opts.ToolboxOpts(),
)
xaxis = list(map(str, _df.index))
bar.add_xaxis(xaxis)
line.add_xaxis(xaxis)
for field in _df.columns:
field = str(field)
bar.add_yaxis(series_name=field,
yaxis_data=_df[field].to_list(),
is_selected=True)
line.add_yaxis(series_name=field + self.series_name_add,
y_axis=_df[field].to_list(),
is_symbol_show=False)
bar.overlap(line)
return bar
def print_bar(self):
bar = Bar(init_opts=opts.InitOpts(width='1080px', height='480px'))
bar.add_xaxis(self.timedata)
# category 是同系列直接的距离，gap是不同系列之间的距离
bar.add_yaxis('治愈人数',
self.heal,
gap='100%',
label_opts=opts.LabelOpts(is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color='#90EE90'))
if self.name == '湖北':
bar.add_yaxis('死亡人数',
self.dead,
gap='100%',
label_opts=opts.LabelOpts(is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color='#696969'))
# 设置全局变量：x轴标签倾斜度，html主标题
bar.set_global_opts(datazoom_opts=[
opts.DataZoomOpts(),
opts.DataZoomOpts(type_='inside')
],
toolbox_opts=opts.ToolboxOpts(),
xaxis_opts=opts.AxisOpts(name_rotate=-15),
title_opts=opts.TitleOpts(self.name,
subtitle='数据来自inews'))
line = Line()
line.add_xaxis(self.timedata)
line.add_yaxis('确诊人数',
self.confirm,
label_opts=opts.LabelOpts(is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color='#F08080'))
print(self.name + '.html', '已成功生成到', os.getcwd())
# 在bar的基础上画line
bar.overlap(line).render(self.name + '.html')
def workarea_salary_chart(df):
# 转换类型为浮点型
df.low_salary, df.high_salary = df.low_salary.astype(
float), df.high_salary.astype(float)
# 分别求各地区平均最高薪资, 平均最低薪资
salary = df.groupby('workarea',
as_index=False)[['low_salary', 'high_salary'
]].mean() # 分别求各地区的岗位数量,并降序排列
print(salary)
workarea = df.groupby('workarea',
as_index=False)['name'].count().sort_values(
'name', ascending=False)
print(workarea)
workarea = pd.merge(workarea, salary, how='left', on='workarea') # 合并数据表
print(workarea)
workarea = workarea.head(20) # 用前20名进行绘图
grid = Grid()
bar = Bar()
grid.theme = themes
line = Line()
line1 = Line()
bar.add_xaxis(workarea.workarea.tolist())
bar.add_yaxis("岗位需求量", workarea.name.tolist())
bar.set_global_opts(
title_opts=opts.TitleOpts(
title="岗位需求量排名前20地区的平均薪资水平状况",
title_link='./chart/workarea_salary_chart.html',
title_target='blank',
pos_left='left',
),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="cross",
is_show=True), # 交叉指向工具
legend_opts=opts.LegendOpts(pos_left="80%",
orient="vertical",
pos_top="3%"),
)
# bar.set_series_opts(is_show=True, position='rightTop')
print((workarea.name).tolist())
print((round(workarea.high_salary * 1000)).tolist())
# 在bar上增加Y轴，在line图上选择对应的轴向
line.add_xaxis(workarea.workarea.tolist())
line.add_yaxis("平均最高薪资", (round(workarea.high_salary * 1000)).tolist(),
yaxis_index=0)
line1.add_xaxis(workarea.workarea.tolist())
line1.add_yaxis("平均最低薪资", (round(workarea.low_salary * 1000)).tolist(),
yaxis_index=0)
# 把line添加到bar上
bar.overlap(line)
bar.overlap(line1)
# 这里如果不需要grid也可以，直接设置bar的格式，然后显示bar即可
#bar.render_notebook()
grid.add(chart=bar, grid_opts=opts.GridOpts(), is_control_axis_index=True)
# grid.render("./chart/workarea_salary_chart.html")
return grid
def paintGraph(contestInfo, starttime='2017-09', endtime='2020-07'):
# 先根据指定的起始日期和截止日期构造需要的数据
x, cf, ac, nc, jsk, total = [], [], [], [], [], []
for key, value in sorted(contestInfo.items()):
if key >= starttime and key <= endtime:
x.append(key)
cf.append({'value': value.get('cf', 0)})
ac.append({'value': value.get('ac', 0)})
nc.append({'value': value.get('nc', 0)})
jsk.append({'value': value.get('jsk', 0)})
total.append(value.get('total', 0))
# print(total)
# 绘制图表
bar = Bar(
init_opts=opts.InitOpts(theme=ThemeType.LIGHT, page_title='各年月比赛数量统计'))
bar.set_global_opts(title_opts=opts.TitleOpts(title='各年月比赛数量统计'),
xaxis_opts=opts.AxisOpts(name='比赛年月'),
yaxis_opts=opts.AxisOpts(name='比赛数量统计'))
bar.add_xaxis(x)
bar.add_yaxis("CodeForces", cf, stack="stack1", category_gap="50%")
bar.add_yaxis("NowCoder", nc, stack="stack1", category_gap="50%")
bar.add_yaxis("AtCoder", ac, stack="stack1", category_gap="50%")
bar.add_yaxis("计蒜客", jsk, stack="stack1", category_gap="50%")
bar.set_series_opts(label_opts=opts.LabelOpts(
position="inside",
formatter=JsCode(
"function(x){return x.data.value ? Number(x.data.value) : '';}"),
))
line = Line()
line.set_global_opts(
tooltip_opts=opts.TooltipOpts(is_show=False),
xaxis_opts=opts.AxisOpts(type_="category"),
yaxis_opts=opts.AxisOpts(
type_="value",
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
)
line.add_xaxis(xaxis_data=x)
line.add_yaxis(
series_name="total",
y_axis=total,
symbol="Circle",
is_symbol_show=True,
label_opts=opts.LabelOpts(is_show=True),
)
# 将柱状图与折线图一起输出到html文件中
bar.overlap(line).render('acmersite02.html')
def workhour_get():
p = WorkhourInfo()
# 获取最近的12月
df = p.df.dropna()[-12:]
xdata = df['月份'].tolist()
# fig = Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
fig = Bar()
fig.add_xaxis(xdata)
fig.add_yaxis('总投入',
df['实际投入工时'].tolist(),
label_opts=opts.LabelOpts(position='inside'))
for v in df.columns[6:]:
fig.add_yaxis(v,
df[v].tolist(),
stack='detail',
is_selected=False,
label_opts=opts.LabelOpts(is_show=False))
fig.set_global_opts(
title_opts=opts.TitleOpts(title="最近12月工时投入"),
tooltip_opts=opts.TooltipOpts(is_show=True,
trigger="axis",
axis_pointer_type="shadow"),
yaxis_opts=opts.AxisOpts(name='工时'),
)
#"""
df['投入总工时比率'] = (df['投入总工时比率'] * 100).round(0)
maxratio = df['投入总工时比率'].max()
maxratio = 100 if maxratio <= 100 else maxratio
ratio = df['投入总工时比率'].tolist()
line = Line()
line.add_xaxis(xdata)
line.add_yaxis('投入工时率', ratio, yaxis_index=1)
fig.extend_axis(yaxis=opts.AxisOpts(name="投入工时率",
type_="value",
min_=0,
max_=maxratio,
axislabel_opts=opts.LabelOpts(
formatter="{value} %")))
fig.overlap(line)
#"""
return fig.dump_options_with_quotes()
def draw_balance_bar(xaxis,
yaxis,
difference=None,
title="消费统计",
markline=None,
width=2000) -> Bar:
"""
x = [月_日, 月_日, 月_日, ....]
y = [(title1, [num1, num2, num3, num4, ...]), (title2, [num1, num2, num3, num4, ...])]
:param difference: 差值 (比如：收入100，消费80，差值就是20) : ['title', [1,2,3,4]]
:param xaxis: x轴
:param yaxis: y轴
:param title: 标题
:param markline: 标记辅助线
:param width: 宽
:return: Bar
"""
bar = Bar()
bar.add_xaxis(xaxis)
for name, axis in yaxis:
bar.add_yaxis(name, axis, category_gap="20%", gap="0%")
bar.set_global_opts(title_opts=opts.TitleOpts(title=title, ),
datazoom_opts=[
opts.DataZoomOpts(range_start=0, range_end=100),
opts.DataZoomOpts(type_="inside")
],
tooltip_opts=opts.TooltipOpts(
trigger='axis', axis_pointer_type='shadow'))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
if difference:
name, diff_yaxis = difference
line = Line().add_xaxis(xaxis).add_yaxis(
name,
diff_yaxis,
symbol_size=15,
z_level=1,
is_symbol_show=False,
)
bar.overlap(line)
if markline is not None:
bar.set_series_opts(markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(y=markline, name='预算')]))
return bar
def dsp_her(): # 显示遗传力
# page = Page(layout=Page.DraggablePageLayout)
import xlrd
# file = "breeding.xlsx"
f1 = xlrd.open_workbook(file)
sheet1 = f1.sheet_by_name('Sheet1')
lst = her(file) # 接收计算的遗传力
y = []
colorArr = [
'1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C', 'D', 'E',
'F'
]
for i in range(len(lst)):
color = "#"
for j in range(6):
color += colorArr[random.randint(0, 14)]
y.append(
opts.BarItem(
value=lst[i],
itemstyle_opts=opts.ItemStyleOpts(color=str(color)),
# itemstyle_opts=opts.ItemStyleOpts(color=color[i])
))
x_ax = []
y_ax = []
start = load_profile()[0]
end = load_profile()[1]
for i in range(start, end + 1):
x_ax.append(sheet1.cell_value(0, i))
bar = Bar(init_opts=opts.InitOpts( #bg_color='rgba(155,250,205,0.2)',
width="1800px", height="800px"))
bar.set_colors(["#FF6347", "black"]) # FF6347
bar.add_xaxis(x_ax)
bar.add_yaxis("遗传力", y, category_gap="60%")
bar.set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
markpoint_opts=opts.MarkPointOpts(
data=[opts.MarkPointItem(type_="max", name="最大值")]))
# bar.add_yaxis("商家B", [57, 134, 137, 129, 145, 60, 49])
bar.set_global_opts(title_opts=opts.TitleOpts(title="显示已有数据遗传力"))
for i in range(sheet1.nrows - 1):
y_ax.append(i)
line = Line(init_opts=opts.InitOpts(width="1800px", height="800px"))
line.add_xaxis(y_ax)
line.add_yaxis(series_name="",
y_axis=lst,
label_opts=opts.LabelOpts(is_show=True))
picture = bar.overlap(line)
return render_template("display.html",
picture_options=picture.dump_options())
def paint_bar_stack_with_line(self, x: list, children: dict, parents: dict,
sub_title: str):
for (parent_name, unit), item in children.items():
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS))
bar.add_xaxis(x)
line = Line()
line.add_xaxis(x)
child_names = []
for child_name, data, overall in item:
bar.add_yaxis(child_name, data, stack='stack1')
line.add_yaxis(f'{child_name}占比', overall, yaxis_index=1)
child_names.append(child_name)
bar.add_yaxis(parent_name,
parents[parent_name],
stack='stack1',
yaxis_index=0)
bar.set_global_opts(
title_opts=opts.TitleOpts(title='，'.join(child_names),
subtitle=sub_title,
pos_left='5%'),
legend_opts=opts.LegendOpts(pos_bottom='0'))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False),
tooltip_opts=opts.TooltipOpts(
formatter=f'{{b}}年{{a}}：{{c}}{unit}'),
itemstyle_opts=opts.ItemStyleOpts(opacity=0.5))
bar.extend_axis(yaxis=opts.AxisOpts(
type_='value',
name='所占比例',
min_=0,
max_=1,
position='right',
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(
opacity=1))))
bar.overlap(line)
yield bar
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
line.set_global_opts()
.add_xaxis(xaxis_data=x_data)
.add_yaxis(
series_name="总数",
y_axis=y3_data,
symbol="circle",
symbol_size=10,
is_symbol_show=True,
itemstyle_opts=opts.ItemStyleOpts(
color="rgba(252,230,48,1)",
border_width=0,
),
label_opts=opts.LabelOpts(
is_show=True,
position="top"
),
linestyle_opts=opts.LineStyleOpts(
width=2,
)
)
)
bar.overlap(line)
(
Grid(opts.InitOpts(bg_color="#344b58"))
.add(
bar,
opts.GridOpts()
)
).render("pyecharts_bar.html")
def echarts_stackbar(
df, # 传入数据df，应该是一个行索引为date的时间序列面板数据
df_gr=None, # 传入同比增长率df，可以没有
datatype="ABS", # 主Y轴形式是绝对值，增长率还是份额，用来确定一些标签格式，默认为绝对值
) -> Bar:
axislabel_format = "{value}" # 主Y轴默认格式
max = df[df > 0].sum(axis=1).max() # 主Y轴默认最大值
min = df[df <= 0].sum(axis=1).min() # 主Y轴默认最小值
if datatype in ["SHARE", "GR"]: # 如果主数据不是绝对值形式而是份额或增长率如何处理
df = df.multiply(100).round(2)
axislabel_format = "{value}%"
max = 100
min = 0
if df_gr is not None:
df_gr = df_gr.multiply(100).round(2) # 如果有同比增长率，原始数*100呈现
if df.empty is False:
stackbar = Bar().add_xaxis(df.index.tolist())
for i, item in enumerate(df.columns): # 预留的枚举，这个方法以后可以根据输入对象不同从单一柱状图变成堆积柱状图
stackbar.add_yaxis(
item,
df[item].values.tolist(),
stack="总量",
label_opts=opts.LabelOpts(is_show=False),
z_level=1,
)
# .add_yaxis(series_name=df.index[-5].strftime("%Y-%m"),
# yaxis_data=df_ya.values.tolist(),
# stack='总量',
# label_opts=opts.LabelOpts(is_show=False)
# )
# .add_yaxis(series_name=df.index[-1].strftime("%Y-%m")+' vs '+df.index[-5].strftime("%Y-%m"),
# yaxis_data=df_diff.values.tolist(),
# stack='总量',
# label_opts=opts.LabelOpts(is_show=False)
# )
if df_gr is not None: # 如果有同比增长率数据则加入次Y轴
stackbar.extend_axis(
yaxis=opts.AxisOpts(
name=df_gr.columns.astype("str")[0],
type_="value",
axislabel_opts=opts.LabelOpts(formatter="{value}%"),
)
)
stackbar.set_global_opts(
legend_opts=opts.LegendOpts(pos_top="5%", pos_left="10%", pos_right="60%"),
# toolbox_opts=opts.ToolboxOpts(is_show=True),
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross",),
xaxis_opts=opts.AxisOpts(
type_="category",
boundary_gap=True,
axislabel_opts=opts.LabelOpts(rotate=90), # x轴标签方向rotate有时能解决拥挤显示不全的问题
splitline_opts=opts.SplitLineOpts(
is_show=False,
linestyle_opts=opts.LineStyleOpts(type_="dotted", opacity=0.5,),
),
),
yaxis_opts=opts.AxisOpts(
max_=max,
min_=min,
type_="value",
axislabel_opts=opts.LabelOpts(formatter=axislabel_format),
# axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(
is_show=True,
linestyle_opts=opts.LineStyleOpts(type_="dotted", opacity=0.5,),
),
),
)
if df_gr is not None:
line = (
Line()
.add_xaxis(xaxis_data=df_gr.index.tolist())
.add_yaxis(
series_name=df_gr.columns.astype("str")[0],
yaxis_index=1,
y_axis=df_gr.values.tolist(),
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=3),
symbol_size=8,
itemstyle_opts=opts.ItemStyleOpts(
border_width=1, border_color="", border_color0="white"
),
z_level=2,
)
)
else:
stackbar = Bar()
if df_gr is not None:
return stackbar.overlap(line) # 如果有次坐标轴最后要用overlap方法组合
else:
return stackbar
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
def to_grid(ka,
kline_mode: str = "new",
with_bi: bool = False,
with_xd: bool = False,
with_zs: bool = False,
with_bs: bool = False,
with_ma: bool = False,
with_vol: bool = False,
with_macd: bool = False,
title: str = "ChanLun In Practise",
width: str = "1440px",
height: str = '900px') -> Grid:
"""绘制缠中说禅K线分析结果
:param kline: K线 new / raw，new标识标准化后的k线，raw标识原始k线
:param with_bi: 是否显示笔识别结果，默认True，不输出False
:param with_xd: 是否显示线段识别结果
:param with_zs: 是否显示中枢识别结果
:param with_bs: 是否显示买卖点
:param with_ma: 是否显示均线，默认True，不输出False
:param with_macd: 是否显示macd，默认True，不输出False
:param with_vol: 是否显示成交量，默认True，不输出False
: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='1400px', height='800px')
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",
textstyle_opts=opts.TextStyleOpts(color="#000"),
)
# 数据预处理
# ------------------------------------------------------------------------------------------------------------------
kline = ka.kline_new if kline_mode == 'new' else ka.kline_raw
dts = [x['dt'] for x in kline]
k_data = [[x['open'], x['close'], x['low'], x['high']] for x in kline]
# seriesname
aggregation = len(ka.ka_list)>0
# {'freq': {'kline', 'ma', 'vol', 'macd'}}
agg_dict = {}
agg_dict[ka.freq] = {
"kline": k_data,
"ma": ka.ma,
"vol": kline,
"macd": ka.macd
}
if aggregation:
for high_ka in ka.ka_list:
agg_dict[high_ka.freq] = {}
_high_k_data = high_ka.kline_new if kline_mode == 'new' else high_ka.kline_raw
high_k_data = []
high_ma_data = []
high_vol_data = []
high_macd_data = []
for i in range(len(dts)):
high_k_data.append([])
high_ma_data.append({})
high_vol_data.append(None)
high_macd_data.append(None)
for ki in range(len(kline)):
k = kline[ki]
_start = 0
for h_ki in range(_start, len(_high_k_data)):
h_k = _high_k_data[h_ki]
if (h_k['dt'] == k['dt']):
high_k_data[ki] = [h_k['open'], h_k['close'], h_k['low'], h_k['high']]
high_ma_data[ki] = high_ka.ma[h_ki]
high_vol_data[ki] = h_k
high_macd_data[ki] = high_ka.macd[h_ki]
_start = h_ki+1
break
agg_dict[high_ka.freq] = {
"kline": high_k_data,
"ma": high_ma_data,
"vol": high_vol_data,
"macd": high_macd_data
}
# K 线主图
# ------------------------------------------------------------------------------------------------------------------
chart_k = Kline()
chart_k.add_xaxis(xaxis_data=dts)
for k, v in agg_dict.items():
chart_k.add_yaxis(series_name=k if aggregation else 'kline', y_axis=v['kline'], itemstyle_opts=k_style_opts)
is_selected = False
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 with_ma:
# 均线图
# ------------------------------------------------------------------------------------------------------------------
ma_keys = [x for x in agg_dict[ka.freq]['ma'][0].keys() if "ma" in x][:3]
ma_colors = ["#39afe6", "#da6ee8", "#00940b"]
chart_ma = Line()
chart_ma.add_xaxis(xaxis_data=dts)
for key, vals in agg_dict.items():
for i, k in enumerate(ma_keys):
y_data = [x[k] if k in x else None for x in v['ma']]
chart_ma.add_yaxis(series_name=key if aggregation else k.upper(), y_axis=y_data, is_smooth=True,
is_selected=True, is_connect_nones=True, 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
# ------------------------------------------------------------------------------------------------------------------
def __draw_bi_line(_ka):
bi_dts = [x['dt'] for x in _ka.bi_list]
bi_val = [x['bi'] for x in _ka.bi_list]
chart_bi = Line()
chart_bi.add_xaxis(bi_dts)
chart_bi.add_yaxis(series_name=_ka.freq if aggregation else "BI", y_axis=bi_val, is_selected=True,
symbol="diamond", symbol_size=10, label_opts=label_not_show_opts,)
chart_bi.set_global_opts(xaxis_opts=grid0_xaxis_opts, legend_opts=legend_not_show_opts)
return chart_bi
if with_bi:
chark_k = chart_k.overlap(__draw_bi_line(ka))
for _ka in ka.ka_list:
chark_k = chart_k.overlap(__draw_bi_line(_ka))
def __draw_xd_line(_ka):
xd_dts = [x['dt'] for x in _ka.xd_list]
xd_val = [x['xd'] for x in _ka.xd_list]
chart_xd = Line()
chart_xd.add_xaxis(xd_dts)
chart_xd.add_yaxis(series_name=_ka.freq if aggregation else "XD", y_axis=xd_val, is_selected=True, symbol="triangle", symbol_size=10,)
chart_xd.set_global_opts(xaxis_opts=grid0_xaxis_opts, legend_opts=legend_not_show_opts)
return chart_xd
if with_xd:
chark_k = chart_k.overlap(__draw_xd_line(ka))
for _ka in ka.ka_list:
chark_k = chart_k.overlap(__draw_xd_line(_ka))
def __draw_zs_area(_ka):
lines = []
scatters = []
for _zs in _ka.zs_list:
x_start = _zs['start_point']['dt']
if _zs['zs_finished']:# 中枢完成
x_end = _zs['end_point']['dt']
chart_b = EffectScatter()
if 'buy3' in _zs:
chart_b.add_xaxis([_zs['buy3']['dt']])
chart_b.add_yaxis(series_name=_ka.freq if aggregation else "B", y_axis=[_zs['buy3']['xd']], is_selected=False, symbol="circle", symbol_size=8,
itemstyle_opts=opts.ItemStyleOpts(color="red",))
chart_b.set_global_opts(xaxis_opts=grid0_xaxis_opts, legend_opts=legend_not_show_opts)
scatters.append(chart_b)
elif 'sell3' in _zs:
chart_b.add_xaxis([_zs['sell3']['dt']])
chart_b.add_yaxis(series_name=_ka.freq if aggregation else "S", y_axis=[_zs['sell3']['xd']], is_selected=False, symbol="circle", symbol_size=8,
itemstyle_opts=opts.ItemStyleOpts(color="green",))
chart_b.set_global_opts(xaxis_opts=grid0_xaxis_opts, legend_opts=legend_not_show_opts)
scatters.append(chart_b)
elif len(_zs['points'])>=5:# 中枢成立但未完成，有3笔或段以上
x_end = _zs['points'][-1]['dt']
else: # 中枢未完成，且未确定
continue
ZD = _zs['ZD']
ZG = _zs['ZG']
area_data=[[ {'xAxis': x_start, 'yAxis': ZD, 'value': ZD }, {'xAxis': x_end, 'yAxis': ZG, 'value': ZG }]]
line = (Line()
.add_xaxis([x_start, x_end])
.add_yaxis(series_name=_ka.freq if aggregation else "ZS", y_axis=[ZD, ZG], symbol='none'
"""
, markpoint_opts = opts.MarkPointOpts(
data=[
opts.MarkPointItem(type_="max", name="ZG"),
opts.MarkPointItem(type_="min", name="ZD"),
]
)
"""
, markline_opts=opts.MarkLineOpts(
label_opts=opts.LabelOpts(
position="middle", color="blue", font_size=15,
),
linestyle_opts=opts.LineStyleOpts(type_="dashed"),
data=area_data,
symbol=["none", "none"],
)
)
.set_series_opts(
markarea_opts=opts.MarkAreaOpts(data=area_data, itemstyle_opts=opts.ItemStyleOpts(color="#dcdcdc",opacity=0.1))
))
lines.append(line)
return lines, scatters
if with_zs:
_areas, _scatters = __draw_zs_area(ka)
for _ka in ka.ka_list:
_a, _s = __draw_zs_area(_ka)
_areas.extend(_a)
_scatters.extend(_s)
for _area in _areas:
chark_k = chart_k.overlap(_area)
for _scatter in _scatters:
chark_k = chart_k.overlap(_scatter)
# if with_vol:
# 成交量图
# ------------------------------------------------------------------------------------------------------------------
chart_vol = Bar()
chart_vol.add_xaxis(dts)
for k, v in agg_dict.items():
vol = []
for row in v['vol']:
if not row:
row = {'close': 0, 'open': 0, 'vol': 0}
item_style = red_item_style if row['close'] > row['open'] else green_item_style
bar = opts.BarItem(name=None, value=row['vol'], itemstyle_opts=item_style, label_opts=label_not_show_opts)
vol.append(bar)
chart_vol.add_yaxis(series_name=k if aggregation else "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,
)
#if with_macd:
# MACD图
# ------------------------------------------------------------------------------------------------------------------
chart_macd = Bar()
chart_macd.add_xaxis(dts)
for k, v in agg_dict.items():
macd_bar = []
for row in v['macd']:
if not row:
row = {'macd': 0}
item_style = red_item_style if row['macd'] > 0 else green_item_style
bar = opts.BarItem(name=None, value=round(row['macd'], 4), itemstyle_opts=item_style, label_opts=label_not_show_opts)
macd_bar.append(bar)
chart_macd.add_yaxis(series_name=k if aggregation else "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)
for k, v in agg_dict.items():
macd = v['macd']
diff = [round(x['diff'], 4) if x else None for x in macd]
dea = [round(x['dea'], 4) if x else None for x in macd]
line.add_yaxis(series_name=k if aggregation else "DIFF", y_axis=diff, label_opts=label_not_show_opts, is_symbol_show=False
, is_connect_nones=True, linestyle_opts=opts.LineStyleOpts(opacity=0.8, width=1.0, color="#EDCB89"))
line.add_yaxis(series_name=k if aggregation else "DEA", y_axis=dea, label_opts=label_not_show_opts, is_symbol_show=False
, is_connect_nones=True, linestyle_opts=opts.LineStyleOpts(opacity=0.8, width=1.0, color="#FFFFFF"))
chart_macd = chart_macd.overlap(line)
grid0_opts = opts.GridOpts(pos_left="3%", pos_right="1%", pos_top="12%", height="58%")
grid1_opts = opts.GridOpts(pos_left="3%", pos_right="1%", pos_top="74%", height="8%")
grid2_opts = opts.GridOpts(pos_left="3%", 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
linestyle_opts=opts.LineStyleOpts(width=1.2, color='#4b0101'))
# 添加其他折线图
line2 = Line()
line2.add_xaxis(time_data)
line2.add_yaxis(
series_name='疑似数',
y_axis=suspect_num,
color='#fed0fc',
# 标签配置
label_opts=opts.LabelOpts(is_show=False),
# 线
linestyle_opts=opts.LineStyleOpts(width=1.2, color='#fed0fc'))
# 合并两个图
sumx = bar.overlap(line1).overlap(line2)
# 组合
all_ = Grid(init_opts=opts.InitOpts(
width='1750px', # 宽度
height='654px', # 高度
theme=ThemeType.PURPLE_PASSION,
))
all_.add(
sumx,
grid_opts=opts.GridOpts(pos_left='5%', pos_top='20%', pos_right='40%'),
is_control_axis_index=True,
)
# 生成
def create_mixed_line_and_bar(type, title, x_list, data_list, data_unit1, data_unit2 = None):
"""
:param type: 1-折线用于表示变化率and单柱状图+单折线 2-折线用于表示变化率and多柱状图+多折线
3-折线表示占比and单柱状图+单折线 4-折线表示占比and多柱状图+多折线
5-折线用于描述另一维度指标（此时data_list中最后一个k-v为折线数据）
:param title: 图表名称
:param x_list: 横坐标内容为时间序列，纵坐标高度为多个(同级)指标的总和，具体各个指标的数值、比例以不同颜色标出
:param data_list: 字典{key1:value1,key2:value2...}，构成柱状图的多个不同类型的bar
:param data_unit1: 第一根y轴的数值单位
:param data_unit2: 第二根y轴的数值单位
:return:
"""
c = Bar(init_opts=opts.InitOpts(height="600px",width="900px",theme=ThemeType.MACARONS))
c.add_xaxis(x_list)
if type == 1: # 因为有overlap，所以需要自适应调整刻度范围，是的bar和line都能显示出来
all_rate_list = []
for key in data_list.keys(): # 单柱状图只有一个bar
change_rate_list = [0]
c.add_yaxis(key, data_list[key], bar_width="20%",label_opts=opts.LabelOpts(is_show=True))
for i in range(1,len(data_list[key])):
if data_list[key][i-1] == 0 or data_list[key][i-1] is None or data_list[key][i] is None: # 注意分母不为0
change_rate_list.append(None)
else:
change_rate_list.append(round((data_list[key][i]-data_list[key][i-1])/data_list[key][i-1]*100,2))
all_rate_list.append(change_rate_list)
c.extend_axis(yaxis=opts.AxisOpts(
name="变化率",
type_="value",
min_=int(round((getMinRate(all_rate_list)-(getMaxRate(all_rate_list)-getMinRate(all_rate_list)))/10)*10),
max_=int(round((getMaxRate(all_rate_list)/10)*10)),
interval=10,
axislabel_opts=opts.LabelOpts(formatter="{value} %"),
))
line = (
Line()
.add_xaxis(xaxis_data=x_list)
.add_yaxis(
series_name="增长率",
yaxis_index=1,
y_axis=all_rate_list[0],
label_opts=opts.LabelOpts(is_show=True, formatter=JsCode(
"function(x){console.log(x);return Number(x.data[1]).toFixed(2) + '%';}"
)),
)
)
c.set_global_opts(title_opts=opts.TitleOpts(title=title,# subtitle="数据来源国家统计局",
# pos_left="center",pos_bottom="0px",
# item_gap=2,
# subtitle_textstyle_opts=opts.TextStyleOpts(color="black")
),
legend_opts=opts.LegendOpts(pos_left="right"),
yaxis_opts=opts.AxisOpts(name="单位:" + data_unit1,
# name_location="end",
# name_gap=5,
# # name_rotate=45,
min_=0, # 基本上指标数据都是为正的
max_=int(round(getMaxData(data_list)/10)*10)*2,
interval=10,
))
c.overlap(line)
elif type == 2:
count = len(data_list.keys())
all_rate_list = []
keys_list = []
for key in data_list.keys():
keys_list.append(key)
change_rate_list = [0]
c.add_yaxis(key, data_list[key], label_opts=opts.LabelOpts(is_show=True))
for i in range(1,len(data_list[key])):
if data_list[key][i-1] == 0 or data_list[key][i-1] is None or data_list[key][i] is None: # 注意分母不为0
change_rate_list.append(None)
else:
change_rate_list.append(round((data_list[key][i]-data_list[key][i-1])/data_list[key][i-1]*100,2))
all_rate_list.append(change_rate_list)
c.extend_axis(yaxis=opts.AxisOpts(
name="变化率",
type_="value",
min_=int(
round((getMinRate(all_rate_list) - (getMaxRate(all_rate_list) - getMinRate(all_rate_list))) / 10) * 10),
max_=int(round((getMaxRate(all_rate_list) / 10) * 10)),
interval=10,
axislabel_opts=opts.LabelOpts(formatter="{value} %"),
))
all_line = []
for i in range(count):
line = (
Line()
.add_xaxis(xaxis_data=x_list)
.add_yaxis(
series_name=keys_list[i] + "增长率",
yaxis_index=1,
y_axis=all_rate_list[i],
label_opts=opts.LabelOpts(is_show=True, formatter=JsCode(
"function(x){console.log(x);return Number(x.data[1]).toFixed(2) + '%';}"
)),
)
)
all_line.append(line)
c.set_global_opts(title_opts=opts.TitleOpts(title=title, # subtitle="数据来源国家统计局",
pos_left="center",pos_bottom="0px",
# item_gap=2,
# subtitle_textstyle_opts=opts.TextStyleOpts(color="black")
),
legend_opts=opts.LegendOpts(pos_left="right"),
yaxis_opts=opts.AxisOpts(name="单位:" + data_unit1,
# name_location="end",
# name_gap=5,
# # name_rotate=45,
min_=0,
max_=int(round(getMaxData(data_list)/10)*10)*2,
interval=10,
))
for line in all_line:
c.overlap(line)
src_path = "./指标-年度-图片生成/"
html_file_name = src_path + title + ".html"
img_file_name = src_path + title + ".png"
make_snapshot(snapshot, c.render(html_file_name), img_file_name)
print(img_file_name+":生成完毕...")
