def bar_histogram_color() -> Bar:
x = Faker.dogs + Faker.animal
xlen = len(x)
y = []
for idx, item in enumerate(x):
if idx <= xlen / 2:
y.append(
opts.BarItem(
name=item,
value=(idx + 1) * 10,
itemstyle_opts=opts.ItemStyleOpts(color="#749f83"),
))
else:
y.append(
opts.BarItem(
name=item,
value=(xlen + 1 - idx) * 10,
itemstyle_opts=opts.ItemStyleOpts(color="#d48265"),
))
c = (Bar().add_xaxis(x).add_yaxis(
"series0", y, category_gap=0,
color=Faker.rand_color()).set_global_opts(title_opts=opts.TitleOpts(
title="Bar-直方图（颜色区分）")))
return c
def bar_histogram():
x = Faker.dogs + Faker.animal
xlen = len(x)
y = []
for idx, item in enumerate(x):
if idx <= xlen / 2:
bar_item = opts.BarItem(
name=item,
value=(idx + 1) * 10,
itemstyle_opts=opts.ItemStyleOpts(color="#749f83")
)
else:
bar_item = opts.BarItem(
name=item,
value=(xlen + 1 - idx) * 10,
itemstyle_opts=opts.ItemStyleOpts(color="#d48265"),
)
y.append(bar_item)
obj_bar = Bar()
obj_bar.add_xaxis(x)
#直方图就是紧挨着的系列柱category_gap=0调节系列柱之间距离，
# color=Faker.rand_color()因为上面设置了柱的颜色，这里只对图例legend的颜色起作用
obj_bar.add_yaxis("series0", y, category_gap=0,color=Faker.rand_color())
obj_bar.set_global_opts(
title_opts=opts.TitleOpts(title="Bar-直方图（颜色区分）", subtitle="副标题")
)
return obj_bar
def draw_bar_like(data,user_id,title="偏爱曲风统计"):
"""
柱状图 偏爱统计
:param data:
:param user_id:
:param title:
:return:
"""
file_name = "user_data/" + str(user_id) + "_bar_like.html"
x = ["古风", "古典", "电子", "民谣", "流行", "说唱", "摇滚"]
color = ["#C43C3C", "#7D573E", "#E6E65D", "#69DA69", "#70D4D4", "#9B7CC7", "#A2A2A2"]
xlen = len(x)
y = []
for idx, item in enumerate(x):
y.append(
opts.BarItem(
name=item,
value=data[idx][1],
itemstyle_opts=opts.ItemStyleOpts(color=color[idx]),
)
)
c = (
Bar()
.add_xaxis(x)
.add_yaxis("", y, color=Faker.rand_color())
.set_global_opts(title_opts=opts.TitleOpts(title=title),
toolbox_opts=opts.ToolboxOpts()
)
#.render(file_name)
)
return c
def get_XY(bins, pct, label, color):
# 分箱获取Y轴的数据
result = pd.cut(pct, bins, ordered=True, labels=label)
v = pd.value_counts(result)
result_dict = {}
for i in label:
if i == "-90":
j = '-20+'
else:
j = i
result_dict[j] = v.loc[i]
gte_20 = pct[pct >= 20].count()
result_dict.update({'20+': gte_20})
y_list = []
for k, v in result_dict.items():
if k.startswith('-'):
color_ = color[0]
else:
color_ = color[1]
y_list.append(
opts.BarItem(
name=str(v),
value=int(v),
itemstyle_opts=opts.ItemStyleOpts(color=color_),
))
return result_dict, y_list
def charts():
fp = open('./oldData.txt', 'r')
# Timeline
timeline = Timeline(init_opts=opts.InitOpts(
width="1660px",
height="708px",
))
# 48 bar charts
for i in range(48):
X, Y, Color = getSta(fp)
# y-axle with color
y = []
for j in range(22):
y.append(
opts.BarItem(
name=X[j],
value=Y[j],
itemstyle_opts=opts.ItemStyleOpts(color=Color[j])))
# single bar chart
bar = (
Bar().add_xaxis(X).add_yaxis(
"Youbike 使用率", y).reversal_axis().set_global_opts(
title_opts=opts.TitleOpts(
title="南港區Youbike的一天",
pos_left="center",
),
legend_opts=opts.LegendOpts(pos_left="left"),
graphic_opts=[
opts.GraphicGroup( # add a block
graphic_item=opts.GraphicItem(left="80%",
top="80%"),
children=[
opts.GraphicText( # add text into the block
graphic_item=opts.GraphicItem(
left="center",
top="center",
# z=100
),
graphic_textstyle_opts=opts.
GraphicTextStyleOpts(
text="{}".format(invTime[i]),
font="48px Verdana",
),
)
])
]).set_series_opts( # number showed at right of the bar
label_opts=opts.LabelOpts(position="right",
color="#333")))
timeline.add(bar, "") # add single bar chart into timeline
timeline.add_schema(play_interval=1000,
is_loop_play=True) # play settings
# export into HTML
timeline.render("YoubikeUsingRate.html")
fp.close()
def draw_bar_plays(data,user_id,title="听歌方式"):
"""
两种听歌方式
:param plays:
:param user_id:
:param title:
:return:
"""
file_name = "user_data/" + str(user_id) + "_bar_plays.html"
x = ["片段播放", "完整播放"]
color = ["#749f83", "#d48265"]
xlen = len(x)
y = []
for idx, item in enumerate(x):
y.append(
opts.BarItem(
name=item,
value=data[idx],
itemstyle_opts=opts.ItemStyleOpts(color=color[idx]),
)
)
c = (
Bar()
.add_xaxis(x)
.add_yaxis("用户："+str(user_id), y,color=Faker.rand_color())
.set_global_opts(title_opts=opts.TitleOpts(title=title),toolbox_opts=opts.ToolboxOpts())
#.render(file_name)
)
return c
def draw_bar_recoder(data,user_id,title = "用户行为统计"):
"""
用户行为统计
:param data:
:param user_id:
:param title:
:return:
"""
file_name = "user_data/" + str(user_id) + "_bar_recoder.html"
x = ["循环播放","片段播放","查看评论","点赞评论","收藏歌曲"]
color = ["#F79709","#749f83", "#d48265","#33CCCC","#82C182"]
xlen = len(x)
y = []
for idx, item in enumerate(x):
y.append(
opts.BarItem(
name=item,
value=data[idx][1],
itemstyle_opts=opts.ItemStyleOpts(color=color[idx]),
)
)
c = (
Bar()
.add_xaxis(x)
.add_yaxis("" , y, color=Faker.rand_color())
.set_global_opts(title_opts=opts.TitleOpts(title=title),
toolbox_opts=opts.ToolboxOpts()
)
# .render(file_name)
)
return c
def test_bar_item_base(fake_writer):
x_axis = ["A", "B", "C"]
bar_item_1 = [
opts.BarItem(name=d[0], value=d[1])
for d in list(zip(x_axis, [1, 2, 3]))
]
bar_item_2 = [
opts.BarItem(name=d[0], value=d[1])
for d in list(zip(x_axis, [4, 5, 6]))
]
c = (Bar().add_xaxis(x_axis).add_yaxis("series0", bar_item_1).add_yaxis(
"series1", bar_item_2))
c.render()
_, content = fake_writer.call_args[0]
assert_greater(len(content), 2000)
assert_equal(c.theme, "white")
assert_equal(c.renderer, "canvas")
def draw_degree():
degree = nx.degree(G)
degree_sort = sorted(degree, key=lambda x: x[1], reverse=True)
e0 = [
opts.BarItem(name=G.nodes[degree_sort[0][0]], value=degree_sort[0][1])
]
e1 = [
opts.BarItem(name=G.nodes[x[0]]['name'], value=x[1])
for x in degree_sort if G.nodes[x[0]]['E_numbers'] == 1
][:50]
e2 = [
opts.BarItem(name=G.nodes[x[0]]['name'], value=x[1])
for x in degree_sort if G.nodes[x[0]]['E_numbers'] == 2
][:50]
xaxis = [x + 1 for x in range(50)]
c = (Bar().add_xaxis(xaxis).add_yaxis(
"Erdos_number is 0",
e0,
category_gap=0,
itemstyle_opts=opts.ItemStyleOpts(color='#d48265'),
gap="0%").add_yaxis(
"Erdos_number is 1",
e1,
category_gap=0,
itemstyle_opts=opts.ItemStyleOpts(color='#749f83'),
gap="0%").add_yaxis(
"Erdos_number is 2", e2, category_gap=0,
gap="0%").set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
axisline_opts=opts.AxisOpts(interval=1),
markline_opts=opts.MarkLineOpts(data=[
opts.MarkLineItem(type_="average", name="Average"),
]),
).set_global_opts(
title_opts=opts.TitleOpts(title="Top 50 degree authors"),
datazoom_opts=opts.DataZoomOpts(),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
).render("bar_stack1.html"))
def format_yaxis(self, y_set, offset=0, sign=1, opacity: float = 1):
while len(self.y_axiss) < len(y_set) + offset:
self.y_axiss.append([])
for idx, item in enumerate(y_set.items()):
country, value = item
color = self.get_country_color(country)
self.y_axiss[idx + offset].append(
opts.BarItem(name=country,
value=value * sign,
itemstyle_opts=opts.ItemStyleOpts(
color=color, opacity=opacity)))
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 select_data(year):
film_list = select_film(year)
colors = [
"#546570", "#c4ccd3", "#bda29a", "#ca8622", "#d48265", "#6e7074",
"#749f83", "#61a0a8", "#2f4554", "#c23531", "#6e7074", "#749f83",
"#61a0a8", "#2f4554", "#c23531"
]
y = []
for n in range(len(film_list[1])):
y.append(
opts.BarItem(
name=film_list[0][n],
value=film_list[1][n],
itemstyle_opts=opts.ItemStyleOpts(color=colors[n]),
))
return y
def dsp_cbv(): # 显示综合育种值
import xlrd
# file = "breeding.xlsx"
f1 = xlrd.open_workbook(file)
sheet1 = f1.sheet_by_name('Sheet1')
lst = cbv(file)[0] # 接收计算的早选指数
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 = cbv(file)[1]
# y_ax = []
bar = Bar(init_opts=opts.InitOpts( #bg_color='rgba(255,250,205,0.2)',
width="1800px", height="800px"))
bar.set_colors(["#FF6347", "black"])
bar.add_xaxis(x_ax)
bar.add_yaxis("综合育种值", y, category_gap="80%")
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="显示已有数据综合育种值"))
# 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
return render_template("display.html",
picture_options=picture.dump_options())
def change_data(dataframe):
global date_list, price_list, ma5_list, ma10_list, ma20_list, volume_list
# 转成列表
try:
for i in range(0, len(dataframe)):
alist = []
date_list.append(dataframe['date'].iloc[i])
# alist.append(tsData['date'].iloc[i])
alist.append(dataframe['open'].iloc[i])
alist.append(dataframe['close'].iloc[i])
alist.append(dataframe['low'].iloc[i])
alist.append(dataframe['high'].iloc[i])
ma5_list.append(dataframe['ma5'].iloc[i])
ma10_list.append(dataframe['ma10'].iloc[i])
ma20_list.append(dataframe['ma20'].iloc[i])
high_list.append(dataframe['high'].iloc[i])
low_list.append(dataframe['low'].iloc[i])
# 柱状图数据处理
color = ''
if dataframe['open'].iloc[i] > dataframe['close'].iloc[i]:
color = '#ADFF2F'
else:
color = '#FF4500'
volume_list.append(
opts.BarItem(name='volume',
value=dataframe['volume'].iloc[i],
itemstyle_opts=opts.ItemStyleOpts(color=color)))
price_list.append(alist)
print('股票数据已成功转换')
except:
print('股票数据转换失败！')
draw()
def find_aggregation_render(x, y, flag, query, table_path, answer, y_name):
colorList = ['#f36c6c', '#e6cf4e', '#20d180', '#0093ff']
x_sum = ["Sum"]
Sum = []
Sum.append(sum(y))
mean = np.mean(y)
y1 = []
y2 = []
for i in range(len(y)):
if y[i] >= mean:
y1.append(round(mean, 2))
y2.append(
opts.BarItem(name=x[i],
value=round(y[i] - mean, 2),
label_opts=opts.LabelOpts(formatter="+{c}"),
itemstyle_opts=opts.ItemStyleOpts(color="red")))
else:
y1.append(round(y[i], 2))
y2.append(
opts.BarItem(name=x[i],
value=round(mean - y[i], 2),
label_opts=opts.LabelOpts(formatter="-{c}"),
itemstyle_opts=opts.ItemStyleOpts(color="green",
opacity=0.3)))
if flag == "mean":
bar = Bar()
bar.add_xaxis(x)
bar.add_yaxis(
'',
y_axis=y1,
stack='stack1',
label_opts=opts.LabelOpts(is_show=False),
color="white",
markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(name="mean:", y=round(mean, 2))],
label_opts=opts.LabelOpts(formatter="Mean:{c}", color="black"),
linestyle_opts=opts.LineStyleOpts(color="gray")),
)
bar.add_yaxis('', y_axis=y2, stack='stack1')
bar.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(rotate=40, font_size='100%'),
name_textstyle_opts=opts.TextStyleOpts(font_size="100%")),
yaxis_opts=opts.AxisOpts(
min_=int(min(y) - (max(y) - min(y)) / 10),
name=y_name,
axislabel_opts=opts.LabelOpts(font_size="100%"),
name_textstyle_opts=opts.TextStyleOpts(font_size="100%")),
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' + "\n" + 'A:' +
' ' + answer
],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333")))
])
bar.render("aggregation.html")
grid = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG,
))
grid.add(bar, grid_opts={'left': '15%', 'bottom': '34%'})
grid1 = Grid()
grid1.add(bar, grid_opts={'left': '15%', 'bottom': '34%'})
grid1.render("mean.html")
option1 = grid.dump_options_with_quotes()
option1 = json.loads(option1)
option = {"option": [option1], "query": query}
return option
elif flag == "sum":
bar = Bar()
bar.add_xaxis(x_sum)
bar.add_yaxis('',
Sum,
label_opts=opts.LabelOpts(position="inside",
formatter="Sum:{c}"),
color=colorList[0])
for i in range(len(y)):
Y = []
Y.append(y[i])
r = str(x[i])
bar.add_yaxis('',
Y,
stack='stack1',
label_opts=opts.LabelOpts(position="inside",
formatter=r + ":{c}"),
tooltip_opts=opts.TooltipOpts(is_show=False))
bar.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10,
range_end=90,
orient="vertical"),
opts.DataZoomOpts(type_="inside")
],
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(bar, grid_opts={'left': '15%', 'bottom': '34%'})
option1 = grid.dump_options_with_quotes()
option1 = json.loads(option1)
option = {"option": [option1], "query": query}
return option
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 find_proportion_render(x, y, z, part_name, main_name, query, table_path,
answer):
x = list(map(str, x))
y = list(map(float, y))
z = list(map(float, z))
colorList = ['#f36c6c', '#e6cf4e', '#20d180', '#0093ff']
y_part = []
y_main = []
for i in range(len(y)):
percentage = y[i] / z[i] * 100
percentage = str(percentage).split('.')[0] + '.' + str(
percentage).split('.')[1][:2]
y_part.append(
opts.BarItem(
name=x[i],
value=y[i],
label_opts=opts.LabelOpts(position="insideTop",
formatter=str(percentage) + "%"),
itemstyle_opts=opts.ItemStyleOpts(color=colorList[2])))
y_main.append(opts.BarItem(
name=x[i],
value=z[i] - y[i],
))
bar = Bar()
bar.add_xaxis(x)
bar.add_yaxis('',
y_axis=y_part,
stack='stack1',
label_opts=opts.LabelOpts(position="insideTop"),
itemstyle_opts=opts.ItemStyleOpts(color=colorList[2]),
tooltip_opts=opts.TooltipOpts(formatter=part_name + ':{c}')),
bar.add_yaxis('',
y_axis=y_main,
stack='stack1',
label_opts=opts.LabelOpts(is_show=False),
color="gray",
tooltip_opts=opts.TooltipOpts(formatter=main_name + ':{c}'))
bar.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")
],
legend_opts=opts.LegendOpts(is_show=False),
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")))
])
bar.render("aggregation.html")
grid = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG,
))
grid.add(bar, grid_opts={'left': '20%', 'bottom': '34%'})
option1 = grid.dump_options_with_quotes()
option1 = json.loads(option1)
option = {"option": [option1], "query": query}
return option
# 直方图
import random
import pyecharts.options as opts
from pyecharts.charts import Bar
x_vals = ['衬衫', '羊毛衫', '雪纺衫', '裤子', '高跟鞋', '袜子']
xlen = len(x_vals)
# 设置成两种颜色
y_vals = []
for idx, item in enumerate(x_vals):
if idx % 2 == 0:
y_vals.append(
opts.BarItem(
name=item,
value=random.randint(10, 100),
itemstyle_opts=opts.ItemStyleOpts(color="#749f83"),
))
else:
y_vals.append(
opts.BarItem(
name=item,
value=random.randint(10, 100),
itemstyle_opts=opts.ItemStyleOpts(color="#d48265"),
))
bar_histogram = (
Bar().add_xaxis(x_vals).add_yaxis('商家A', y_vals, category_gap=0)
# .add_yaxis('商家A', [random.randint(10, 100) for _ in range(6)], category_gap=0)
.set_series_opts(
label_opts=opts.LabelOpts(is_show=True, font_size=14)).set_global_opts(
def salary_pie_chart(self):
"""薪酬分布"""
salary_xaxis = [
'0', '5000', '10000', '15000', '20000', '30000', '40000', '50000',
'60000', '70000', '80000', '90000', '100000'
]
salary_yaxis = []
kd = self.frame.salary.value_counts()
salary_dict = {
0: 0,
5000: 0,
10000: 0,
15000: 0,
20000: 0,
30000: 0,
40000: 0,
50000: 0,
60000: 0,
70000: 0,
80000: 0,
90000: 0,
100000: 0
}
for k, v in dict(kd).items():
min_salary = float(
k.split('-')[0].split('·')[0].replace(
'以上', '').rstrip('k').rstrip('K')) * 1000
try:
max_salary = float(
k.split('-')[1].split('·')[0].replace(
'以上', '').rstrip('k').rstrip('K')) * 1000
except:
max_salary = min_salary
salary = 0.5 * (min_salary + max_salary)
if salary in range(0, 5000): salary = 0
if salary in range(5000, 10000): salary = 5000
if salary in range(10000, 15000): salary = 10000
if salary in range(15000, 20000): salary = 15000
if salary in range(20000, 30000): salary = 20000
if salary in range(30000, 40000): salary = 30000
if salary in range(40000, 50000): salary = 40000
if salary in range(50000, 60000): salary = 50000
if salary in range(60000, 70000): salary = 60000
if salary in range(70000, 80000): salary = 70000
if salary in range(80000, 90000): salary = 80000
if salary in range(90000, 100000): salary = 90000
if salary in range(100000, 10000000000): salary = 100000
if salary_dict.get(salary, ''):
salary_dict[salary] = salary_dict[salary] + v
else:
salary_dict[salary] = v
salary_dict = dict(collections.OrderedDict(sorted(
salary_dict.items())))
for salary_key, salary_value in salary_dict.items():
salary_yaxis.append(
opts.BarItem(
name=str(salary_key),
value=int(salary_value),
itemstyle_opts=opts.ItemStyleOpts(color="#d48265"),
))
html_path = os.path.join(
create_or_get_directory(os.path.join('report', 'single')),
'salary_pie_chart.html')
c = (Bar(init_opts=opts.InitOpts(
width="60%")).add_xaxis(salary_xaxis).add_yaxis(
"", salary_yaxis, category_gap=-1).set_series_opts(
label_opts=opts.LabelOpts(is_show=False)).set_global_opts(
yaxis_opts=opts.AxisOpts(
name="岗位数量",
axislabel_opts=opts.LabelOpts(color='red'),
name_textstyle_opts=opts.TextStyleOpts(
color='#d48265')),
xaxis_opts=opts.AxisOpts(
name="薪酬",
axislabel_opts=opts.LabelOpts(color='red'),
name_textstyle_opts=opts.TextStyleOpts(
color='#d48265')),
tooltip_opts=opts.TooltipOpts(
trigger="item",
formatter=JsCode("""function (params) {
var name='';
if (params.name < 5000){
name='小于5K'
}
else if (params.name < 10000) {
name='5K-10K'
}
else if (params.name < 15000) {
name='10K-15K'
}
else if (params.name < 20000) {
name='15K-20K'
}
else if (params.name < 30000) {
name='20K-30K'
}
else if (params.name < 40000) {
name='30K-40K'
}
else if (params.name < 50000) {
name='40K-50K'
}
else if (params.name < 60000) {
name='50K-60K'
}
else if (params.name < 70000) {
name='60K-70K'
}
else if (params.name < 80000) {
name='70K-80K'
}
else if (params.name < 90000) {
name='80K-90K'
}
else if (params.name < 100000) {
name='90K-100K'
}
else {
name='大于100K'
}
return name+':'+params.value;
}
""")),
).render(html_path))
script_string = self.get_javascript_string(html_path)
self.set_report_javascript(script_string, 'salary_pie_chart')
self.middle_charts.append({
'title': '薪资分布',
'name': 'salary_pie_chart'
})
)
# map.render('全球温度地图.html')
print("全球温度地图已生成！！")
# 绘制最高温度前十位国家的平均温度情况（条形图）
# print(top_ten_country)
country = [x[0] for x in top_ten_country] # 前十个国家
temperature = [x[1] for x in top_ten_country] # 前十个国家对应温度
x = [] # 空列表存温度
color_series = randomcolor(len(country))
for i in range(10):
x.append(
opts.BarItem(
name=country[i],
value=round(temperature[i], 2),
itemstyle_opts=opts.ItemStyleOpts(
color=color_series[i]) # 设置每根柱子的颜色
))
# 绘制柱形图
bar = Bar()
bar.add_xaxis(country)
bar.add_yaxis(series_name='温度',
y_axis=x,
is_selected=True,
label_opts=opts.LabelOpts(is_show=True))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=True, position='right'))
bar.set_global_opts(
title_opts=opts.TitleOpts(title="排行榜前十名温度最高国家"),
tooltip_opts=opts.TooltipOpts(is_show=True,
trigger="axis",
axis_pointer_type="shadow"),
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
area = [x[0] for x in area_count]
nums = [y[1] for y in area_count]
# 使用风格
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS))
colors = [
'red', '#0000CD', '#000000', '#008000', '#FF1493', '#FFD700', '#FF4500',
'#00FA9A', '#191970', '#9932CC'
]
random.shuffle(colors)
# 配置y轴数据 Baritem
y = []
for i in range(10):
y.append(
opts.BarItem(
name=area[i],
value=nums[i],
itemstyle_opts=opts.ItemStyleOpts(color=colors[i]) # 设置每根柱子的颜色
))
bar.add_xaxis(xaxis_data=area)
bar.add_yaxis("上榜美女数", y)
bar.set_global_opts(
xaxis_opts=opts.AxisOpts(name='国家',
axislabel_opts=opts.LabelOpts(rotate=45)),
yaxis_opts=opts.AxisOpts(
name='上榜美女数',
min_=0,
max_=55, # y轴刻度的最小值 最大值
),
title_opts=opts.TitleOpts(title="各地区上榜美女数",
title_textstyle_opts=opts.TextStyleOpts(
font_family="KaiTi",
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
# -*- coding:utf-8 -*-
from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Faker
x = Faker.dogs + Faker.animal
xlen = len(x)
y = []
for idx, item in enumerate(x):
if idx <= xlen / 2:
y.append(
opts.BarItem(
name=item,
value=(idx + 1) * 10,
itemstyle_opts=opts.ItemStyleOpts(color="#749f83"),
))
else:
y.append(
opts.BarItem(
name=item,
value=(xlen + 1 - idx) * 10,
itemstyle_opts=opts.ItemStyleOpts(color="#d48265"),
))
c = (
Bar().add_xaxis(x)
#category_gap: 同一系列的柱间距离，默认为类目间距的 20%，可设固定值
.add_yaxis(
"series0", y, category_gap=0,
color=Faker.rand_color()).set_global_opts(title_opts=opts.TitleOpts(
