def draw_chart(cls, data):
kline = (
Kline().add_xaxis(xaxis_data=data["times"]).add_yaxis(
series_name="",
y_axis=data["datas"],
itemstyle_opts=opts.ItemStyleOpts(
color="#ef232a",
color0="#14b143",
border_color="#ef232a",
border_color0="#14b143",
),
markpoint_opts=opts.MarkPointOpts(data=[
opts.MarkPointItem(type_="max", name="最大值"),
opts.MarkPointItem(type_="min", name="最小值"),
]),
markline_opts=opts.MarkLineOpts(
label_opts=opts.LabelOpts(position="middle",
color="blue",
font_size=15),
data=cls.split_data_part(data),
symbol=["circle", "none"],
),
).set_series_opts(markarea_opts=opts.MarkAreaOpts(
is_silent=True, data=cls.split_data_part(data))).
set_global_opts(
title_opts=opts.TitleOpts(title="K线周期图表", pos_left="0"),
xaxis_opts=opts.AxisOpts(
type_="category",
is_scale=True,
boundary_gap=False,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
split_number=20,
min_="dataMin",
max_="dataMax",
),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitline_opts=opts.SplitLineOpts(is_show=True)),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="line"),
datazoom_opts=[
opts.DataZoomOpts(is_show=False,
type_="inside",
xaxis_index=[0,
0],
range_end=100),
opts.DataZoomOpts(is_show=True,
xaxis_index=[0,
1],
pos_top="97%",
range_end=100),
opts.DataZoomOpts(is_show=False,
xaxis_index=[0,
2],
range_end=100),
opts.DataZoomOpts(is_show=False,
xaxis_index=[0,
3],
range_end=100),
],
# 三个图的 axis 连在一块
# axispointer_opts=opts.AxisPointerOpts(
# is_show=True,
# link=[{"xAxisIndex": "all"}],
# label=opts.LabelOpts(background_color="#777"),
# ),
))
kline_line = (
Line().add_xaxis(xaxis_data=data["times"])
# # EMA10
# .add_yaxis(
# series_name="EMA10",
# y_axis=data["ema10"],
# xaxis_index=2,
# yaxis_index=2,
# label_opts=opts.LabelOpts(is_show=False),
# )
# EMA144
# .add_yaxis(
# series_name="EMA144",
# y_axis=data["ema144"],
# xaxis_index=2,
# yaxis_index=2,
# label_opts=opts.LabelOpts(is_show=False),
# )
# boll_median
.add_yaxis(
series_name="median",
y_axis=data["boll_median"],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
)
# boll_upper
.add_yaxis(
series_name="upper",
y_axis=data["boll_upper"],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
)
# boll_lower
.add_yaxis(
series_name="lower",
y_axis=data["boll_lower"],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
).set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=1,
axislabel_opts=opts.LabelOpts(is_show=False),
),
yaxis_opts=opts.AxisOpts(
grid_index=1,
split_number=3,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
axistick_opts=opts.AxisTickOpts(is_show=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
axislabel_opts=opts.LabelOpts(is_show=True),
),
))
# Overlap Kline + Line
overlap_kline_line = kline.overlap(kline_line)
# Bar-1
bar_1 = (
Bar().add_xaxis(xaxis_data=data["times"]).add_yaxis(
series_name="Volumn",
yaxis_data=data["vols"],
xaxis_index=1,
yaxis_index=1,
label_opts=opts.LabelOpts(is_show=False),
# 根据 echarts demo 的原版是这么写的
# itemstyle_opts=opts.ItemStyleOpts(
# color=JsCode("""
# function(params) {
# var colorList;
# if (data.datas[params.dataIndex][1]>data.datas[params.dataIndex][0]) {
# colorList = '#ef232a';
# } else {
# colorList = '#14b143';
# }
# return colorList;
# }
# """)
# )
# 改进后在 grid 中 add_js_funcs 后变成如下
itemstyle_opts=opts.ItemStyleOpts(color=JsCode("""
function(params) {
var colorList;
if (barData[params.dataIndex][1] > barData[params.dataIndex][0]) {
colorList = '#ef232a';
} else {
colorList = '#14b143';
}
return colorList;
}
""")),
).set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=1,
axislabel_opts=opts.LabelOpts(is_show=False),
),
legend_opts=opts.LegendOpts(is_show=False),
))
# Bar-2 (Overlap Bar + Line)
bar_2 = (Bar().add_xaxis(xaxis_data=data["times"]).add_yaxis(
series_name="MACD",
yaxis_data=data["macds"],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color=JsCode("""
function(params) {
var colorList;
if (params.data >= 0) {
colorList = '#ef232a';
} else {
colorList = '#14b143';
}
return colorList;
}
""")),
).set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=2,
axislabel_opts=opts.LabelOpts(is_show=False),
),
yaxis_opts=opts.AxisOpts(
grid_index=2,
split_number=4,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
axistick_opts=opts.AxisTickOpts(is_show=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
axislabel_opts=opts.LabelOpts(is_show=True),
),
legend_opts=opts.LegendOpts(is_show=False),
))
line_2 = (Line().add_xaxis(xaxis_data=data["times"]).add_yaxis(
series_name="DIF",
y_axis=data["difs"],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="DEA",
y_axis=data["deas"],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
).set_global_opts(legend_opts=opts.LegendOpts(is_show=False)))
rsi_line = (Line().add_xaxis(xaxis_data=data["times"]).add_yaxis(
series_name="rsi6",
y_axis=data["rsi6"],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="rsi12",
y_axis=data["rsi12"],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="rsi24",
y_axis=data["rsi24"],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
).set_global_opts(legend_opts=opts.LegendOpts(is_show=False)))
# MACD
overlap_bar_line = bar_2.overlap(line_2)
# 最后的 Grid
grid_chart = Grid(
init_opts=opts.InitOpts(width="1400px", height="800px"))
# 这个是为了把 data.datas 这个数据写入到 html 中,还没想到怎么跨 series 传值
# demo 中的代码也是用全局变量传的
grid_chart.add_js_funcs("var barData = {}".format(data["datas"]))
# K线图和 MA5 的折线图
grid_chart.add(
overlap_kline_line,
grid_opts=opts.GridOpts(pos_left="4%",
pos_right="1%",
height="45%"),
)
# Volumn 柱状图
grid_chart.add(
bar_1,
grid_opts=opts.GridOpts(pos_left="4%",
pos_right="1%",
pos_top="56%",
height="10%"),
)
# MACD DIFS DEAS
grid_chart.add(
overlap_bar_line,
grid_opts=opts.GridOpts(pos_left="4%",
pos_right="1%",
pos_top="68%",
height="14%"),
)
# rsi6
grid_chart.add(
rsi_line,
grid_opts=opts.GridOpts(pos_left="4%",
pos_right="1%",
pos_top="84%",
height="10%"),
)
return grid_chart.render_embed()
def draw_kline(chart_data):
# [open, close, lowest, highest]
kline_data = [data[1:-1] for data in chart_data["values"]]
markpoint_item = [
opts.MarkPointItem(name="AI", coord=coord, value=value, symbol='pin', symbol_size=[35, 20],
itemstyle_opts=opts.ItemStyleOpts(color='rgb(255,0,0)'))
for coord, value in zip(chart_data["ai_markpoint_coord"], chart_data["ai_markpoint_value"])
# ]
] + \
[
opts.MarkPointItem(name="每日周線談整突破", coord=coord, value=value, symbol='pin',
symbol_size=[35, 20],
itemstyle_opts=opts.ItemStyleOpts(color='rgb(0,255,0)'))
for coord, value in zip(chart_data["other1_markpoint_coord"], chart_data["other1_markpoint_value"])
] + \
[
opts.MarkPointItem(name="每日日線", coord=coord, value=value, symbol='pin',
symbol_size=[35, 20],
itemstyle_opts=opts.ItemStyleOpts(color='rgb(0,0,255)'))
for coord, value in zip(chart_data["other2_markpoint_coord"], chart_data["other2_markpoint_value"])
] + \
[
opts.MarkPointItem(name="每日日線盤整突破", coord=coord, value=value, symbol='pin',
symbol_size=[35, 20],
itemstyle_opts=opts.ItemStyleOpts(color='rgb(255,255,0)'))
for coord, value in zip(chart_data["other3_markpoint_coord"], chart_data["other3_markpoint_value"])
] + \
[
opts.MarkPointItem(name="每日日線布林條件", coord=coord, value=value, symbol='pin',
symbol_size=[35, 20],
itemstyle_opts=opts.ItemStyleOpts(color='rgb(0,255,255)'))
for coord, value in zip(chart_data["other4_markpoint_coord"], chart_data["other4_markpoint_value"])
]
kline = (Kline().add_xaxis(
xaxis_data=chart_data["categoryData"]).add_yaxis(
series_name="Dow-Jones index",
y_axis=kline_data,
itemstyle_opts=opts.ItemStyleOpts(color="#ec0000",
color0="#00da3c"),
markpoint_opts=opts.MarkPointOpts(data=markpoint_item),
).set_global_opts(
legend_opts=opts.LegendOpts(is_show=False,
pos_bottom=10,
pos_left="center"),
datazoom_opts=[
opts.DataZoomOpts(
is_show=False,
type_="inside",
xaxis_index=[0, 1],
range_start=98,
range_end=100,
),
opts.DataZoomOpts(
is_show=True,
xaxis_index=[0, 1],
type_="slider",
pos_top="85%",
range_start=98,
range_end=100,
),
],
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
tooltip_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"),
),
visualmap_opts=opts.VisualMapOpts(
is_show=False,
dimension=2,
series_index=5,
is_piecewise=True,
pieces=[
{
"value": 1,
"color": "#00da3c"
},
{
"value": -1,
"color": "#ec0000"
},
],
),
axispointer_opts=opts.AxisPointerOpts(
is_show=True,
link=[{
"xAxisIndex": "all"
}],
label=opts.LabelOpts(background_color="#777"),
),
brush_opts=opts.BrushOpts(
x_axis_index="all",
brush_link="all",
out_of_brush={"colorAlpha": 0.1},
brush_type="lineX",
),
))
line = (Line().add_xaxis(xaxis_data=chart_data["categoryData"]).add_yaxis(
series_name="MA5",
y_axis=calculate_ma(day_count=5, data=chart_data),
is_smooth=True,
is_hover_animation=False,
linestyle_opts=opts.LineStyleOpts(width=3, opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="MA10",
y_axis=calculate_ma(day_count=10, data=chart_data),
is_smooth=True,
is_hover_animation=False,
linestyle_opts=opts.LineStyleOpts(width=3, opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="MA20",
y_axis=calculate_ma(day_count=20, data=chart_data),
is_smooth=True,
is_hover_animation=False,
linestyle_opts=opts.LineStyleOpts(width=3, opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="MA30",
y_axis=calculate_ma(day_count=30, data=chart_data),
is_smooth=True,
is_hover_animation=False,
linestyle_opts=opts.LineStyleOpts(width=3, opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
).set_global_opts(xaxis_opts=opts.AxisOpts(type_="category")))
bar = (Bar().add_xaxis(xaxis_data=chart_data["categoryData"]).add_yaxis(
series_name="Volume",
y_axis=chart_data["volumes"],
xaxis_index=1,
yaxis_index=1,
label_opts=opts.LabelOpts(is_show=False),
).set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
is_scale=True,
grid_index=1,
boundary_gap=False,
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=False),
split_number=20,
min_="dataMin",
max_="dataMax",
),
yaxis_opts=opts.AxisOpts(
grid_index=1,
is_scale=True,
split_number=2,
axislabel_opts=opts.LabelOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(is_show=False),
axistick_opts=opts.AxisTickOpts(is_show=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
),
legend_opts=opts.LegendOpts(is_show=False),
))
# Kline And Line
overlap_kline_line = kline.overlap(line)
# Grid Overlap + Bar
grid_chart = Grid(init_opts=opts.InitOpts(
width="1000px",
height="800px",
animation_opts=opts.AnimationOpts(animation=False),
))
grid_chart.add(
overlap_kline_line,
grid_opts=opts.GridOpts(pos_left="10%", pos_right="8%", height="50%"),
)
grid_chart.add(
bar,
grid_opts=opts.GridOpts(pos_left="10%",
pos_right="8%",
pos_top="63%",
height="16%"),
)
return grid_chart.render_embed()
