def draw_charts():
kline_data = [data[1:-1] for data in chart_data["values"]]
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"),
).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%"),
)
grid_chart.render("professional_kline_brush.html")
def draw_chart():
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 = split_data_part(),
symbol = ["circle","none"],
),
)
.set_series_opts(
markarea_opts = opts.MarkAreaOpts(is_silent = True,data = split_data_part())
)
.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 = True,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),
],
)
)
kline_line = (
Line()
.add_xaxis(xaxis_data = data["times"])
.add_yaxis(
series_name = "MA5",
y_axis = calculate_ma(day_count = 5),
is_smooth = True,
linestyle_opts = opts.LineStyleOpts(opacity = 0.5),
label_opts = opts.LabelOpts(is_show = False),
)
.set_global_opts(
xaxis_opts = opts.AxisOpts(
type_ = "category",
axislabel_opts = opts.LabelOpts(is_show = False),
),
yaxis_opts = opts.AxisOpts(
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 = kline.overlap(kline_line)
bar_1 = (
Bar()
.add_xaxis(xaxis_data = data["times"])
.add_yaxis(
series_name = "Volumn",
y_axis = data["vols"],
label_opts = opts.LabelOpts(is_show = False),
itemstyle_opts = opts.ItemStyleOpts(
color = JsCode(
"""
function(params){
var colorList;
if(barData[params.dataIndex][1] > barData[params.dataIndex][0]){
colorList = '#ef232a';
}else{
colorList = '#14b143';
}
return colorList;
}
"""
)
),
)
.set_global_opts(
xaxis_opts = opts.AxisOpts(
type_ = "category",
axislabel_opts = opts.LabelOpts(is_show = False),
),
legend_opts = opts.LegendOpts(is_show = False),
)
)
bar_2 = (
Bar()
.add_xaxis(xaxis_data = data["times"])
.add_yaxis(
series_name = "MACD",
y_axis = data["macds"],
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",
axislabel_opts = opts.LabelOpts(is_show = False),
),
yaxis_opts = opts.AxisOpts(
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"],
label_opts = opts.LabelOpts(is_show =False),
)
.set_global_opts(
legend_opts = opts.LegendOpts(is_show = False)
)
)
overlap_bar_line = bar_2.overlap(line_2)
grid_chart = Grid(init_opts = opts.InitOpts(width = "1400px",height = "800px",theme = ThemeType.ESSOS))
grid_chart.add_js_funcs("var barData={}".format(data["datas"]))
grid_chart.add(
overlap_kline_line,
grid_opts = opts.GridOpts(
pos_left="3%", pos_right="1%", height="60%"
),
)
grid_chart.add(
bar_1,
grid_opts = opts.GridOpts(
pos_left = "3%",pos_right = "1%",pos_top = "71%",height = "10%"
),
)
grid_chart.add(
overlap_bar_line,
grid_opts = opts.GridOpts(
pos_left = "3%",pos_right = "1%",pos_top = "82%",height = "14%"
)
)
grid_chart.render("professional_kline_chart.html")
def kline(stock_data: pd.DataFrame):
"""
@input: column name ('date', 'open', 'close', 'min', 'max', 'Trading_Volume')
"""
def calculate_ma(day_count: int, price: list):
result: List[Union[float, str]] = []
for i in range(len(price)):
if i < day_count:
result.append("-")
continue
sum_total = 0.0
for j in range(day_count):
sum_total += float(price[i - j])
result.append(abs(float("%.3f" % (sum_total / day_count))))
return result
def process_stock_data(data):
data = data[["date", "open", "close", "min", "max", "Trading_Volume"]]
data.columns = ["date", "open", "close", "low", "high", "volume"]
if is_datetime(data["date"]):
data_times = data["date"].dt.strftime("%Y-%m-%d").to_list()
else:
data_times = data["date"].to_list()
values = data.values.tolist()
volumes = []
for i, tick in enumerate(data.values.tolist()):
volumes.append([i, tick[5], 1 if tick[1] > tick[2] else -1])
return {
"categoryData": data_times,
"values": values,
"volumes": volumes,
}
chart_data = process_stock_data(stock_data)
kline_data = [data[1:-1] for data in chart_data["values"]]
kline = Kline(init_opts=opts.InitOpts(animation_opts=opts.AnimationOpts(
animation=False), ))
kline.add_xaxis(xaxis_data=chart_data["categoryData"])
kline.add_yaxis(
series_name="kline",
y_axis=kline_data,
itemstyle_opts=opts.ItemStyleOpts(color="#ec0000", color0="#00da3c"),
)
kline.set_global_opts(
legend_opts=opts.LegendOpts(is_show=True, pos_left="center"),
datazoom_opts=[
opts.DataZoomOpts(
is_show=False,
type_="inside",
xaxis_index=[0, 1],
range_start=85,
range_end=100,
),
opts.DataZoomOpts(
is_show=True,
xaxis_index=[0, 1],
type_="slider",
pos_top="85%",
range_start=85,
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",
),
)
close = np.array(chart_data["values"])[:, 2]
ma_items = [5, 10, 20, 60]
line = Line(init_opts=opts.InitOpts(animation_opts=opts.AnimationOpts(
animation=False), )).add_xaxis(xaxis_data=chart_data["categoryData"])
for ma in ma_items:
line.add_yaxis(
series_name="MA" + str(ma),
y_axis=calculate_ma(day_count=ma, price=close),
is_smooth=True,
is_symbol_show=False,
is_hover_animation=False,
linestyle_opts=opts.LineStyleOpts(width=3, opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
)
line.set_global_opts(xaxis_opts=opts.AxisOpts(type_="category"))
bar = Bar(init_opts=opts.InitOpts(animation_opts=opts.AnimationOpts(
animation=False), ))
bar.add_xaxis(xaxis_data=chart_data["categoryData"])
bar.add_yaxis(
series_name="Volume",
y_axis=chart_data["volumes"],
xaxis_index=1,
yaxis_index=1,
label_opts=opts.LabelOpts(is_show=False),
)
bar.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),
)
overlap_kline_line = kline.overlap(line)
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%"),
)
grid_chart.render("kline.html")
display(HTML(filename="kline.html"))
return grid_chart
def plot_kline(ka,
bs=None,
file_html="kline.html",
width="1400px",
height="680px"):
"""
:param ka: KlineAnalyze
:param bs: pd.DataFrame
买卖点，包含三个字段 ["操作提示", "交易时间", "交易价格"]
:param file_html: str
:param width: str
:param height: str
:return: None
"""
df = ka.to_df(use_macd=True, ma_params=(
5,
20,
))
x = df.dt.to_list()
title = "%s | %s 至 %s" % (ka.symbol, ka.start_dt, ka.end_dt)
kline = (
Kline().add_xaxis(xaxis_data=x).add_yaxis(
series_name="",
y_axis=df[['open', 'close', 'low', 'high']].values.tolist(),
itemstyle_opts=opts.ItemStyleOpts(
color="#ef232a",
color0="#14b143",
border_color="#ef232a",
border_color0="#14b143",
),
).set_series_opts(markarea_opts=opts.MarkAreaOpts(
is_silent=True)).set_global_opts(
title_opts=opts.TitleOpts(title=title, pos_left="0"),
xaxis_opts=opts.AxisOpts(
type_="category",
is_scale=True,
boundary_gap=False,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
split_number=20,
min_="dataMin",
max_="dataMax",
),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitline_opts=opts.SplitLineOpts(is_show=True),
axislabel_opts=opts.LabelOpts(is_show=True,
position="inside")),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="line"),
datazoom_opts=[
opts.DataZoomOpts(is_show=False,
type_="inside",
xaxis_index=[0, 0],
range_end=100),
opts.DataZoomOpts(is_show=True,
xaxis_index=[0, 1],
pos_top="96%",
range_end=100),
opts.DataZoomOpts(is_show=False,
xaxis_index=[0, 2],
range_end=100),
],
# 三个图的 axis 连在一块
axispointer_opts=opts.AxisPointerOpts(
is_show=True,
link=[{
"xAxisIndex": "all"
}],
label=opts.LabelOpts(background_color="#777"),
),
))
kline_line = (Line().add_xaxis(xaxis_data=x).add_yaxis(
series_name="笔",
y_axis=df.bi.tolist(),
is_smooth=False,
is_connect_nones=True,
symbol='diamond',
symbol_size=8,
linestyle_opts=opts.LineStyleOpts(opacity=1, type_='dotted', width=2),
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="线段",
y_axis=df.xd.tolist(),
is_smooth=False,
is_connect_nones=True,
symbol='triangle',
symbol_size=12,
linestyle_opts=opts.LineStyleOpts(opacity=1, type_='solid', width=2),
label_opts=opts.LabelOpts(is_show=True, position='right'),
).set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=1,
axislabel_opts=opts.LabelOpts(is_show=False),
),
yaxis_opts=opts.AxisOpts(
grid_index=1,
split_number=3,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
axistick_opts=opts.AxisTickOpts(is_show=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
axislabel_opts=opts.LabelOpts(is_show=True, position="inside"),
),
))
# Overlap Kline + Line
overlap_kline_line = kline.overlap(kline_line)
if isinstance(bs, pd.DataFrame) and len(bs) > 0:
c = (Scatter().add_xaxis(bs['交易时间'].to_list()).add_yaxis(
"买卖点",
bs['交易价格'].to_list(),
label_opts=opts.LabelOpts(
is_show=True,
position="left",
formatter=JsCode(
"function(params){return bsName[params.dataIndex][0];}")),
))
overlap_kline_line = overlap_kline_line.overlap(c)
# draw volume
bar_1 = (Bar().add_xaxis(xaxis_data=x).add_yaxis(
series_name="Volumn",
yaxis_data=df.vol.tolist(),
xaxis_index=1,
yaxis_index=1,
label_opts=opts.LabelOpts(is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color=JsCode("""
function(params) {
var colorList;
if (barData[params.dataIndex][1] > barData[params.dataIndex][0]) {
colorList = '#ef232a';
} else {
colorList = '#14b143';
}
return colorList;
}
""")),
).set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=1,
axislabel_opts=opts.LabelOpts(is_show=False),
),
yaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(is_show=True, position='inside')),
legend_opts=opts.LegendOpts(is_show=False),
))
# Bar-2 (Overlap Bar + Line)
bar_2 = (Bar().add_xaxis(xaxis_data=x).add_yaxis(
series_name="MACD",
yaxis_data=df.macd.tolist(),
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color=JsCode("""
function(params) {
var colorList;
if (params.data >= 0) {
colorList = '#ef232a';
} else {
colorList = '#14b143';
}
return colorList;
}
""")),
).set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=2,
axislabel_opts=opts.LabelOpts(is_show=False),
),
yaxis_opts=opts.AxisOpts(
grid_index=2,
split_number=4,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
axistick_opts=opts.AxisTickOpts(is_show=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
axislabel_opts=opts.LabelOpts(is_show=True, position="inside"),
),
legend_opts=opts.LegendOpts(is_show=False),
))
line_2 = (Line().add_xaxis(xaxis_data=x).add_yaxis(
series_name="DIF",
y_axis=df['diff'].tolist(),
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="DEA",
y_axis=df['dea'].tolist(),
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
).set_global_opts(legend_opts=opts.LegendOpts(is_show=False)))
# draw MACD
overlap_bar_line = bar_2.overlap(line_2)
# 最后的 Grid
grid_chart = Grid(
init_opts=opts.InitOpts(width=width, height=height, page_title=title))
grid_chart.add_js_funcs("var barData = {}".format(
df[['open', 'close', 'low', 'high']].values.tolist()))
if isinstance(bs, pd.DataFrame) and len(bs) > 0:
grid_chart.add_js_funcs("var bsName = {}".format(
bs[["操作提示", "交易价格"]].values.tolist()))
grid_chart.add(
overlap_kline_line,
grid_opts=opts.GridOpts(pos_left="3%", pos_right="1%", height="60%"),
)
grid_chart.add(
bar_1,
grid_opts=opts.GridOpts(pos_left="3%",
pos_right="1%",
pos_top="71%",
height="10%"),
)
grid_chart.add(
overlap_bar_line,
grid_opts=opts.GridOpts(pos_left="3%",
pos_right="1%",
pos_top="82%",
height="14%"),
)
grid_chart.render(path=file_html)
def draw_charts(stock_data,name):
x = stock_data['TIME'].values.tolist()
y = stock_data[name].values.tolist()
indexes_peaks, line_peaks=get_line_peaks(stock_data[name])
indexes_valleys, line_valleys=get_line_valleys(stock_data[name])
line = (
Line()
.add_xaxis(x)
.add_yaxis('收盘价', y, label_opts=opts.LabelOpts(is_show=False), is_symbol_show=False, )
.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
),
datazoom_opts=[opts.DataZoomOpts(type_="inside")],
title_opts=opts.TitleOpts(title="股票价格",
subtitle=ts_code,
pos_left='15%',
pos_top="40%"),
# 把所有的x轴连接在一起
axispointer_opts=opts.AxisPointerOpts(is_show=True,
link=[{"xAxisIndex": "all"}],
label=opts.LabelOpts(background_color="#777"),
),
)
)
# 极大值的散点图
scatter_peak = (
Scatter()
.add_xaxis(indexes_peaks)
.add_yaxis('Peaks', line_peaks, label_opts=opts.LabelOpts(is_show=False), symbol='triangle',
symbol_rotate=180, itemstyle_opts=opts.ItemStyleOpts(color='#ef232a'))
.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
),
datazoom_opts=[opts.DataZoomOpts(type_="inside")], )
)
scatter_valley = (
Scatter()
.add_xaxis(indexes_valleys)
.add_yaxis('Valleys', line_valleys, label_opts=opts.LabelOpts(is_show=False), symbol='triangle',
itemstyle_opts=opts.ItemStyleOpts(color='#14b143'))
.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
),
datazoom_opts=[opts.DataZoomOpts(type_="inside")], )
)
#绘制布林带
line_boll = (
Line()
.add_xaxis(x)
.add_yaxis(
series_name="MID",
y_axis=stock_data["MID"].values.tolist(),
linestyle_opts=opts.LineStyleOpts(opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
is_symbol_show=False,
)
.add_yaxis(
series_name="UPPER",
y_axis=stock_data["UPPER"].values.tolist(),
linestyle_opts=opts.LineStyleOpts(opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
is_symbol_show=False,
)
.add_yaxis(
series_name="LOWER",
y_axis=stock_data["LOWER"].values.tolist(),
linestyle_opts=opts.LineStyleOpts(opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
is_symbol_show=False,
)
.set_global_opts(datazoom_opts=[opts.DataZoomOpts(type_="inside", )],
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
), )
)
stock_basic_data = stock_data[["TIME", "OPEN", "CLOSE", "LOW", "HIGH"]]
# 绘制K线图
kline = (
Kline()
.add_xaxis(x)
.add_yaxis("K线图", stock_basic_data.iloc[:, 1:5].values.tolist(), itemstyle_opts=opts.ItemStyleOpts(
color="#ec0000",
color0="#00da3c"
), )
.set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True,
is_show=False),
# axis_opts=opts.AxisOpts(is_scale=True,min_=0), #y轴起始坐标可以设为0
yaxis_opts=opts.AxisOpts(is_scale=True,
splitarea_opts=opts.SplitAreaOpts(is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
), # y轴起始坐标可自动调整
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="line"),
legend_opts=opts.LegendOpts(is_show=True, orient='vertical', pos_right="5%", pos_top='20%'),
datazoom_opts=[ # 设置zoom参数后即可缩放
opts.DataZoomOpts(
is_show=True,
type_="inside",
),
],
)
)
line_close = (
Line()
.add_xaxis(x)
.add_yaxis('五日均线', stock_data["MA5"].values.tolist(), label_opts=opts.LabelOpts(is_show=False),
is_symbol_show=False, )
.set_global_opts(xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
),
datazoom_opts=[opts.DataZoomOpts(type_="inside")],
)
)
overlap_findpeak = line.overlap(scatter_peak)
overlap_findpeak = overlap_findpeak.overlap(scatter_valley)
overlap_findpeak = overlap_findpeak.overlap(line_boll)
overlap_findpeak = overlap_findpeak.overlap(kline)
overlap_findpeak = overlap_findpeak.overlap(line_close)
grid_chart = Grid(init_opts=opts.InitOpts(
width="1400px",
height="700px",
animation_opts=opts.AnimationOpts(animation=False),
))
grid_chart.add(
overlap_findpeak,
grid_opts=opts.GridOpts(pos_left="25%", pos_right="15%", pos_top="10%"),
)
grid_chart.render('stock_{}/find_peak.html'.format(ts_code))
def kline_pro(kline: 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",
t_seq: List[int] = None,
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
{'dt': Timestamp('2020-11-26 00:00:00'),
'fx_mark': 'd',
'start_dt': Timestamp('2020-11-25 00:00:00'),
'end_dt': Timestamp('2020-11-27 00:00:00'),
'fx_high': 144.87,
'fx_low': 138.0,
'bi': 138.0}
:param xd: 线段识别结果
:param bs: 买卖点
:param title: 图表标题
:param t_seq: 均线系统
: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], range_start=80, range_end=100)
dz_slider = opts.DataZoomOpts(True, "slider", xaxis_index=[0, 1, 2], pos_top="96%",
pos_bottom="0%", range_start=80, 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['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['vol'], 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)
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
)
# 均线图
# ------------------------------------------------------------------------------------------------------------------
chart_ma = Line()
chart_ma.add_xaxis(xaxis_data=dts)
if not t_seq:
t_seq = [10, 20, 60, 120, 250]
ma_keys = dict()
for t in t_seq:
ma_keys[f"MA{t}"] = SMA(close, timeperiod=t)
for i, (name, ma) in enumerate(ma_keys.items()):
chart_ma.add_yaxis(series_name=name, y_axis=ma, is_smooth=True,
is_selected=True, symbol_size=0, label_opts=label_not_show_opts,
linestyle_opts=opts.LineStyleOpts(opacity=0.8, width=1))
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 = Line()
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)", ),
linestyle_opts=opts.LineStyleOpts(width=1.5))
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 = Line()
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['price'] 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['price'] 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
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22],
]
c = (Kline().add_xaxis(["2017/7/{}".format(i + 1) for i in range(31)
]).add_yaxis("kline", data).set_global_opts(
yaxis_opts=opts.AxisOpts(is_scale=True),
xaxis_opts=opts.AxisOpts(is_scale=True),
title_opts=opts.TitleOpts(title="Kline-基本示例"),
).render("5.kline_base.html"))
def K(self) -> Kline:
data = self.data[self.prices_cols].values.tolist()
c = (Kline().add_xaxis(self.dateindex).add_yaxis(
"k线", data).set_global_opts(
title_opts=opts.TitleOpts(title=self.title, pos_left="0"),
legend_opts=opts.LegendOpts(is_show=False,
pos_bottom=10,
pos_left="center"),
datazoom_opts=[
opts.DataZoomOpts(
is_show=True,
xaxis_index=[0, 1],
type_="slider",
pos_top="85%",
range_start=0,
range_end=100,
),
],
xaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(is_show=False),
axistick_opts=opts.AxisTickOpts(is_show=False),
),
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=2,
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",
),
))
if len(self.klines) != 0:
kLine = Line().add_xaxis(self.dateindex)
for i in self.klines:
kLine.add_yaxis(
i,
round(self.data[i], self.precision).values.tolist(),
is_smooth=True,
is_symbol_show=False,
is_hover_animation=False,
label_opts=opts.LabelOpts(is_show=True),
linestyle_opts=opts.LineStyleOpts(type_='solid', width=2),
)
kLine.set_global_opts(
xaxis_opts=opts.AxisOpts(type_="category", is_show=False))
c.overlap(kLine)
if 'BUY' in self.data.columns:
v1 = self.data[self.data['BUY'] == True].index.strftime(
"%Y-%m-%d").tolist()
v2 = self.data[self.data['BUY'] == True]['close']
es_buy = (EffectScatter().add_xaxis(v1).add_yaxis(
"", v2, symbol=SymbolType.ARROW, is_selected=True))
c.overlap(es_buy)
if 'SELL' in self.data.columns:
v1 = self.data[self.data['SELL'] == True].index.strftime(
"%Y-%m-%d").tolist()
v2 = self.data[self.data['SELL'] == True]['low']
es_sell = (EffectScatter().add_xaxis(v1).add_yaxis("", v2))
c.overlap(es_sell)
return c
def draw_chart():
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=split_data_part(),
symbol=["circle", "none"],
),
).set_series_opts(markarea_opts=opts.MarkAreaOpts(
is_silent=True, data=split_data_part())).
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),
],
# 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"]).add_yaxis(
series_name="MA5",
y_axis=calculate_ma(day_count=5),
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(opacity=0.5),
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
print(data["vols"])
bar_1 = (
Bar().add_xaxis(xaxis_data=data["times"]).add_yaxis(
series_name="Volumn",
y_axis=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",
y_axis=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="DIF",
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)))
# 最下面的柱状图和折线图
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="3%", pos_right="1%", height="60%"),
)
# Volumn 柱状图
grid_chart.add(
bar_1,
grid_opts=opts.GridOpts(pos_left="3%",
pos_right="1%",
pos_top="71%",
height="10%"),
)
# MACD DIFS DEAS
grid_chart.add(
overlap_bar_line,
grid_opts=opts.GridOpts(pos_left="3%",
pos_right="1%",
pos_top="82%",
height="14%"),
)
grid_chart.render("1.professional_kline_chart.html")
2397.94], [2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76,
2330.88], [2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89,
2340.71], [2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92,
2366.16], [2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54], [2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6,
2351.44], [2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59,
2333.67], [2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83,
2333.29], [2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
c = (Kline().add_xaxis([
"2018/9/{}".format(i + 1) for i in range(31)
]).add_yaxis("kline",
v1,
markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(type_='max', value_dim="close")]))
).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1))),
datazoom_opts=[opts.DataZoomOpts(type_="inside")],
title_opts=opts.TitleOpts(title="K线图示例")).render(r'k.html')
def draw2(df: pd.DataFrame, ts_name: str):
kline = (
Kline().add_xaxis(df["trade_date"].values.tolist()).add_yaxis(
series_name=ts_name,
y_axis=df[["open", "close", "low", "high"]].values.tolist(),
itemstyle_opts=opts.ItemStyleOpts(color="#ec0000",
color0="#00da3c")).
set_global_opts(
legend_opts=opts.LegendOpts(is_show=False,
pos_bottom=10,
pos_left="center"),
datazoom_opts=[opts.DataZoomOpts(pos_bottom="-2%")],
# 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",
),
))
sma_5 = talib.SMA(np.array(df['close']), 5)
sma_10 = talib.SMA(np.array(df['close']), 10)
sma_20 = talib.SMA(np.array(df['close']), 20)
sma_30 = talib.SMA(np.array(df['close']), 30)
line = (Line().add_xaxis(xaxis_data=df["trade_date"]).add_yaxis(
series_name="MA5",
y_axis=sma_5,
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=sma_10,
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=sma_20,
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=sma_30,
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=df["trade_date"].values.tolist()).add_yaxis(
series_name="Volume",
y_axis=df["vol"].values.tolist(),
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),
))
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%"),
)
grid_chart.render("b.html")
name = 'jinshan'
data = []
datetime = []
for i in range(1, 30):
if i % 7 == 4 or i % 7 == 5:
continue
datetime.append(i)
date = '07-' + '{:02d}'.format(i)
path = os.getcwd() + '/stock/' + name + '/金山-07-' + '{:02d}'.format(
i) + '.csv'
df = pd.read_csv(path)
value = df.iloc[:, 2].values
open = value[0]
close = value[-1]
highest = max(value)
lowest = min(value)
data.append([open, close, lowest, highest])
c = (Kline().add_xaxis(["2017/07/{}".format(i) for i in datetime]).add_yaxis(
"kline", data).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
datazoom_opts=[opts.DataZoomOpts(type_="inside")],
title_opts=opts.TitleOpts(title="云计算第一组金山股7月k线图"),
).render("金山.html"))
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22],
]
c = (Kline().add_xaxis(
["2017/7/{}".format(i + 1) for i in range(31)]).add_yaxis(
"kline",
data,
markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(type_="max", value_dim="close")]),
).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
title_opts=opts.TitleOpts(title="Kline-MarkLine"),
).render("4.kline_markline.html"))
from pyecharts import options as opts
from pyecharts.charts import Kline
import os
import pandas as pd
name = 'yingbang'
path = os.getcwd() + '/' + name + '.csv'
df = pd.read_csv(path)
data = []
datetime = []
for i in reversed(range(23)):
data.append([df.iloc[i, 1], df.iloc[i, 2], df.iloc[i, 4], df.iloc[i, 3]])
datetime.append(df.iloc[i, 0])
c = (Kline().add_xaxis(datetime).add_yaxis("kline", data).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
datazoom_opts=[opts.DataZoomOpts(type_="inside")],
title_opts=opts.TitleOpts(title="云计算第一组人民币对英镑7月k线图"),
).render("英镑.html"))
def bar_base() -> Bar:
# c = (
# Bar()
# .add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
# .add_yaxis("商家A", [randrange(0, 100) for _ in range(6)])
# .add_yaxis("商家B", [randrange(0, 100) for _ in range(6)])
# .set_global_opts(title_opts=opts.TitleOpts(title="Bar-基本示例", subtitle="我是副标题"))
# )
data = [
[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22],
]
c = (Kline().add_xaxis(
["2017/7/{}".format(i + 1) for i in range(31)]).add_yaxis(
"kline",
data,
markline_opts=opts.MarkLineOpts(data=[
opts.MarkLineItem(type_="max", value_dim="close"),
opts.MarkLineItem(type_="min", value_dim="close"),
],
linestyle_opts=[]),
).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
title_opts=opts.TitleOpts(title="Kline-MarkLine"),
))
return c
def ohlc_kline_chart(df, x_axis_count=2, signal_infos=[]):
"""创建一个 OHLC K线图，并返回
:time_series 时间数组
:ohlc_data K线数据
:x_axis_count 控制要缩放的 X 轴数量
"""
time_series = pyecharts_time_data(df)
ohlc_data = pyecharts_ohlc_data(df)
kline = (Kline().add_xaxis(xaxis_data=time_series).add_yaxis(
series_name="K线",
y_axis=ohlc_data,
yaxis_index=2,
itemstyle_opts=opts.ItemStyleOpts(
color="#314555",
color0="#ec0000",
border_color="#314555",
border_color0="#ec0000",
),
markpoint_opts=opts.MarkPointOpts(data=[{
'value': info[2],
"coord": [info[0], info[1]],
"itemStyle": {
"color": info[3]
}
} for info in signal_infos]),
).set_global_opts(
legend_opts=opts.LegendOpts(
is_show=True,
pos_top=10,
pos_left="center",
),
title_opts=opts.TitleOpts(title=""),
datazoom_opts=[
opts.DataZoomOpts(
is_show=True,
xaxis_index=list(range(0, x_axis_count)),
type_="slider",
pos_top="90%",
range_start=50,
range_end=100,
),
],
xaxis_opts=opts.AxisOpts(
is_scale=True,
splitline_opts=opts.SplitLineOpts(
is_show=True,
linestyle_opts=opts.LineStyleOpts(type_='dotted')),
),
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": "#314555"
},
{
"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",
),
))
return kline
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22],
]
c = (
Kline()
.add_xaxis(["2017/7/{}".format(i + 1) for i in range(31)])
.add_yaxis("kline", data)
.set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
),
datazoom_opts=[opts.DataZoomOpts(pos_bottom="-2%")],
title_opts=opts.TitleOpts(title="Kline-DataZoom-slider-Position"),
)
)
c.width = "100%"
put_html(c.render_notebook())
def draw_Kline(self):
"""
画股票的K线图，需要传入四个数据
分别是["open", "close", "high", "low"]
:return: 画出图像
"""
Df_s1 = Read_One_Stock(self.SC).select_col("open", "high", "low",
"close", "vol", "amount")
length = Df_s1.shape[0]
Df_s1.sort_values("trade_date", inplace=True)
Df_s1.index = list(range(length))
price = np.array(Df_s1[["open", "close", "high", "low"]]).tolist()
date = np.array(Df_s1["trade_date"], dtype=np.string_).tolist()
ma_value_5 = calculate_ma_n(list(Df_s1['close']), 5)
ma_value_10 = calculate_ma_n(list(Df_s1['close']), 10)
ma_value = np.array([ma_value_5, ma_value_10]).tolist()
kline = Kline()
kline.set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
datazoom_opts=[opts.DataZoomOpts()],
title_opts=opts.TitleOpts(title="K-Line of {}".format(self.SC)),
)
kline.add_xaxis(date)
kline.add_yaxis('K-Line', price)
line = Line()
line.add_xaxis(date)
line.add_yaxis(series_name="ma5",
y_axis=ma_value[0],
label_opts=opts.LabelOpts(is_show=False))
line.add_yaxis(series_name="ma10",
y_axis=ma_value[1],
label_opts=opts.LabelOpts(is_show=False))
line.set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
datazoom_opts=[opts.DataZoomOpts()],
title_opts=opts.TitleOpts(title=""))
kline.overlap(line)
kline.render("./Plots/{} Candle Plot.html".format(self.SC))
def plot_kline(
df,
rendered=True,
ucolor="#ef232a",
dcolor="#14b143",
ucolorborder=None,
dcolorborder=None,
ucolorvolume=None,
dcolorvolume=None,
col="",
):
"""
针对 dataframe 直接画出标准看盘软件的上k线图下成交量图的形式
:param df:
:param rendered:
:param ucolor: str for color when going up, default red in A stock as "#ef232a"
:param dcolor: str for color when going down, default green in A stock as "#14b143"
:param col:
:return:
"""
# TODO: color changing seems to make no effect, possible issue with pyecharts
if ucolorborder is None:
ucolorborder = ucolor
if dcolorborder is None:
dcolorborder = dcolor
if ucolorvolume is None:
if ucolor != "#ffffff":
ucolorvolume = ucolor
else:
ucolorvolume = ucolorborder
if dcolorvolume is None:
if dcolor != "#ffffff":
dcolorvolume = dcolor
else:
dcolorvolume = dcolorborder
kline = (
Kline().add_xaxis(xaxis_data=list(df["date"])).add_yaxis(
series_name="",
itemstyle_opts=opts.ItemStyleOpts(
color=ucolor,
color0=dcolor,
border_color=ucolorborder, # ucolor,
border_color0=dcolorborder, # dcolor,
),
y_axis=list(zip(df["open"], df["close"], df["low"], df["high"])),
markpoint_opts=opts.MarkPointOpts(
data=[
opts.MarkPointItem(type_="max", name="最大值"),
opts.MarkPointItem(type_="min", name="最小值"),
],
symbol="pin",
symbol_size=[56, 40],
# label_opts=opts.LabelOpts(color="#CCFFFF",position=["top", "bottom"])
),
).set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(
is_show=True,
type_="slider",
range_start=50,
range_end=100,
xaxis_index=[0, 1],
),
opts.DataZoomOpts(
is_show=False,
type_="inside",
range_start=50,
range_end=100,
xaxis_index=1,
),
],
tooltip_opts=opts.TooltipOpts(
is_show=True,
trigger="axis",
trigger_on="mousemove",
axis_pointer_type="cross",
),
))
if col is not None:
for c in col:
line = (Line().add_xaxis(xaxis_data=list(df["date"])).add_yaxis(
series_name=c,
y_axis=list(df[c]),
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
))
kline = kline.overlap(line)
if "volume" in df.columns:
vl = list(df["volume"])
elif "amount" in df.columns:
vl = list(df["amount"])
else:
vl = [0 for _ in range(len(df))]
bar = (
Bar().add_js_funcs("var barData = {}".format(
list(df["close"] - df["open"]))).add_xaxis(
xaxis_data=list(df["date"])).add_yaxis(
series_name="",
yaxis_data=vl,
label_opts=opts.LabelOpts(is_show=False),
itemstyle_opts=opts.ItemStyleOpts(
color=JsCode("""
function(params) {{
var colorList;
if (barData[params.dataIndex]>0) {{
colorList = '{ucolor}';
}} else {{
colorList = '{dcolor}';
}}
return colorList;
}}
""".format(ucolor=ucolorvolume,
dcolor=dcolorvolume)) # escape {} when using format
),
).set_global_opts(tooltip_opts=opts.TooltipOpts(
is_show=True,
trigger="axis",
trigger_on="mousemove",
axis_pointer_type="cross",
), ))
grid_chart = Grid()
grid_chart.add_js_funcs("var barData = {}".format(
list(df["close"] - df["open"])))
grid_chart.add(
kline,
grid_opts=opts.GridOpts(pos_left="10%",
pos_right="1%",
pos_top="2%",
height="65%"),
)
grid_chart.add(
bar,
grid_opts=opts.GridOpts(pos_left="10%",
pos_right="1%",
pos_top="71%",
height="22%"),
)
if rendered:
return grid_chart.render_notebook()
else:
return grid_chart
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22],
]
c = (Kline().add_xaxis(
["2017/7/{}".format(i + 1)
for i in range(31)]).add_yaxis("kline", data).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
title_opts=opts.TitleOpts(title="Kline-显示分割区域"),
).render("10.kline_split_area.html"))
def kline(self):
""""""
kline = Kline(init_opts=opts.InitOpts(width="1400px", height="800px"))
kline.add_xaxis(xaxis_data=self.bar_data_datetime)
kline.add_yaxis(
series_name=f"{self.bar_data.symbol[0]}",
yaxis_index=0,
y_axis=self.bar_data[[
"open_price", "close_price", "low_price", "high_price"
]].values.tolist(),
itemstyle_opts=opts.ItemStyleOpts(color="#ec0000",
color0="#00da3c",
border_color="#8A0000",
border_color0="#008F28",
opacity=0.8),
)
if self.grid == True and self.grid_quantity == 1:
kline.set_global_opts(
# 多图组合
datazoom_opts=[
opts.DataZoomOpts(
is_show=False,
type_="inside",
xaxis_index=[0, 0],
range_start=0,
range_end=100,
),
opts.DataZoomOpts(
is_show=True,
type_="slider",
xaxis_index=[0, 1],
pos_top="95%",
range_start=0,
range_end=100,
),
],
xaxis_opts=opts.AxisOpts(
is_scale=True,
type_="category",
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,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=0.8)),
),
brush_opts=opts.BrushOpts(
tool_box=[
"rect", "polygon", "keep", "lineX", "lineY", "clear"
],
x_axis_index="all",
brush_link="all",
out_of_brush={"colorAlpha": 0.1},
brush_type="lineX",
),
tooltip_opts=opts.TooltipOpts(
is_show=True,
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",
font_size=12,
font_family="Arial",
font_weight="lighter",
),
),
toolbox_opts=opts.ToolboxOpts(orient="horizontal",
pos_left="right",
pos_top="0%"),
legend_opts=opts.LegendOpts(
is_show=True,
type_="scroll",
selected_mode="multiple",
pos_left="left",
pos_top="0%",
legend_icon="roundRect",
),
# 添加主标题和副标题
# title_opts = opts.TitleOpts(title = "主标题", subtitle = " 副标题"),
# 多图的 axis 连在一块
axispointer_opts=opts.AxisPointerOpts(
is_show=True,
link=[{
"xAxisIndex": "all"
}],
label=opts.LabelOpts(background_color="#777"),
),
)
elif self.grid == True and self.grid_quantity == 2:
kline.set_global_opts(
# 多图组合
datazoom_opts=[
opts.DataZoomOpts(
is_show=False,
type_="inside",
xaxis_index=[0, 0],
range_start=0,
range_end=100,
),
opts.DataZoomOpts(
is_show=True,
type_="slider",
xaxis_index=[0, 1],
pos_top="95%",
range_start=0,
range_end=100,
),
opts.DataZoomOpts(
is_show=False,
type_="inside",
xaxis_index=[0, 2],
range_start=0,
range_end=100,
),
],
xaxis_opts=opts.AxisOpts(
is_scale=True,
type_="category",
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,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=0.8)),
),
brush_opts=opts.BrushOpts(
tool_box=[
"rect", "polygon", "keep", "lineX", "lineY", "clear"
],
x_axis_index="all",
brush_link="all",
out_of_brush={"colorAlpha": 0.1},
brush_type="lineX",
),
tooltip_opts=opts.TooltipOpts(
is_show=True,
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",
font_size=12,
font_family="Arial",
font_weight="lighter",
),
),
toolbox_opts=opts.ToolboxOpts(orient="horizontal",
pos_left="right",
pos_top="0%"),
legend_opts=opts.LegendOpts(
is_show=True,
type_="scroll",
selected_mode="multiple",
pos_left="left",
pos_top="0%",
legend_icon="roundRect",
),
# 添加主标题和副标题
# title_opts = opts.TitleOpts(title = "主标题", subtitle = " 副标题"),
# 多图的 axis 连在一块
axispointer_opts=opts.AxisPointerOpts(
is_show=True,
link=[{
"xAxisIndex": "all"
}],
label=opts.LabelOpts(background_color="#777"),
),
)
else:
kline.set_global_opts(
# 单图形
datazoom_opts=opts.DataZoomOpts(
is_show=False,
type_="inside",
range_start=0,
range_end=100,
),
xaxis_opts=opts.AxisOpts(
is_scale=True,
type_="category",
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,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=0.8)),
),
brush_opts=opts.BrushOpts(
tool_box=[
"rect", "polygon", "keep", "lineX", "lineY", "clear"
],
x_axis_index="all",
brush_link="all",
out_of_brush={"colorAlpha": 0.1},
brush_type="lineX",
),
tooltip_opts=opts.TooltipOpts(
is_show=True,
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",
font_size=12,
font_family="Arial",
font_weight="lighter",
),
),
toolbox_opts=opts.ToolboxOpts(orient="horizontal",
pos_left="right",
pos_top="0%"),
legend_opts=opts.LegendOpts(
is_show=True,
type_="scroll",
selected_mode="multiple",
pos_left="left",
pos_top="0%",
legend_icon="roundRect",
),
# 添加主标题和副标题
# title_opts = opts.TitleOpts(title = "主标题", subtitle = " 副标题"),
# 多图的 axis 连在一块
axispointer_opts=opts.AxisPointerOpts(
is_show=True,
link=[{
"xAxisIndex": "all"
}],
label=opts.LabelOpts(background_color="#777"),
),
)
self.kline_chart = kline
x_data = []
y_data = []
for i in ret:
str_date = datetime.datetime.strftime(i['date'], '%Y-%m-%d')
x_data.append(str_date)
y_data.append(
[i['start_price'], i['max_price'], i['min_price'], i['stop_price']])
c = (Kline(init_opts=opts.InitOpts(width="1440px", height="800px")).add_xaxis(
xaxis_data=x_data).add_yaxis(
"kline",
y_data,
itemstyle_opts=opts.ItemStyleOpts(
color="#ec0000",
color0="#00da3c",
border_color="#8A0000",
border_color0="#008F28",
),
).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
datazoom_opts=[opts.DataZoomOpts(type_="inside")],
title_opts=opts.TitleOpts(title="abc005 K线走势图"),
).render("abc005kline.html"))
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22],
]
c=(
Kline()
.add_xaxis(["2017/7/{}".format(i + 1) for i in range(31)])
.add_yaxis("kline",
data,
itemstyle_opts=opts.ItemStyleOpts(
color="#ec0000",
color0="#00da3c",
border_color="#8A0000",
border_color0="#008F28",
)
)
.set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
),
datazoom_opts=[opts.DataZoomOpts(type_="inside")],
title_opts=opts.TitleOpts(title="K-line"),
)
)
c.render("k-line.html")
def stock_draw_welcome(labels, mode_combo, startdate, enddate, optInterval):
startdate = startdate.replace("/", "-") # 将参数日期转换为tushare的日期格式
enddate = enddate.replace("/", "-")
tl = Timeline(init_opts=opts.InitOpts(
width="1000px", height="500px", theme=ThemeType.WONDERLAND))
for label in labels: # 对于传入的labels一张张作图
label1 = re.split("-", label)
#print(label1[0])
#print(label1[1])
if mode_combo == "KLine":
array = ts.get_k_data(label1[1],
start=startdate,
end=enddate,
ktype=optInterval)
time = array['date'].tolist() # array.date
# 绘图方法
if label1[2] == 'Kline':
re_array = array[['open', 'close', 'high', 'low']]
data_li = list(row.tolist()
for index, row in re_array.iterrows())
close = array['close'].tolist()
#width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(labels)
kline = (Kline(init_opts=opts.InitOpts(
width="1100px", height="500px",
theme=ThemeType.WONDERLAND)).add_xaxis(time).add_yaxis(
label1[0], data_li).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(
opacity=1)),
),
datazoom_opts=[opts.DataZoomOpts(pos_top="10%")],
title_opts=opts.TitleOpts(title=label1[0] + "-" +
optInterval)))
# 计算移动平均
if len(close) > 10:
ma10 = CalculateMA(close, 10)
line1 = (
Line().add_xaxis(time).add_yaxis("MA10", ma10)
#.set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例"))
.set_series_opts(label_opts=opts.LabelOpts(
is_show=False)))
kline.overlap(line1)
if len(close) > 20:
ma20 = CalculateMA(close, 20)
line2 = (
Line().add_xaxis(time).add_yaxis("MA20", ma20)
# .set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例"))
.set_series_opts(label_opts=opts.LabelOpts(
is_show=False)))
kline.overlap(line2)
if len(close) > 30:
ma30 = CalculateMA(close, 30)
line3 = (
Line().add_xaxis(time).add_yaxis("MA30", ma30)
# .set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例"))
.set_series_opts(label_opts=opts.LabelOpts(
is_show=False)))
kline.overlap(line3)
tl.add(kline, label1[0] + "-" + optInterval)
else: # label1[2]==open/close/volume
if label1[2] == 'Open':
list_aft = array['open'].tolist()
elif label1[2] == 'Close':
list_aft = array['close'].tolist()
elif label1[2] == 'High':
list_aft = array['high'].tolist()
elif label1[2] == 'Low':
list_aft = array['low'].tolist()
elif label1[2] == 'Volume': # volume
list_aft = array['volume'].tolist()
else:
list_aft = array['amount'].tolist()
line = (Line().add_xaxis(time).add_yaxis(
label1[0] + "-" + label1[2], list_aft).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
datazoom_opts=[opts.DataZoomOpts(pos_bottom="-8%")],
title_opts=opts.TitleOpts(
title=label1[0] + "-" +
label1[2])).set_series_opts(
label_opts=opts.LabelOpts(is_show=False)))
return tl