def bszone(data):
return opts.MarkAreaItem(
x=(data["begin"].strftime("%Y-%m-%d"),
data["end"].strftime("%Y-%m-%d")),
itemstyle_opts=opts.ItemStyleOpts(
color="#ec0000" if data["earnings_v"] > 0 else "#00da3c",
opacity=0.1),
)
def line_with_mark_area():
line = Line(
init_opts=opts.InitOpts(theme='light', width='1000px', height='600px'))
line.add_xaxis(x_data)
line.add_yaxis('', y_data)
line.set_series_opts(markarea_opts=opts.MarkAreaOpts(
data=[opts.MarkAreaItem(name="黄金周", x=("2020/10/1", "2020/10/8"))]))
return line
def line_with_mark_area():
line = Line(init_opts=opts.InitOpts(theme='essos', width='1600px', height='450px'))
line.add_xaxis(x_data)
line.add_yaxis('百天情感趋势图', y_data)
# 设置标记区域
line.set_series_opts(
markarea_opts=opts.MarkAreaOpts(
data=[
opts.MarkAreaItem(name="情绪低落期", x=("1.20", "2.8"))
]
)
)
return line
def bs(data):
if data["bcount"] > 0:
bspoints.append(
opts.MarkPointItem(
name="B",
coord=[data.name.strftime("%Y-%m-%d"), data["bprice"]],
symbol_size=20,
value=str(round(data["signal"], 2)),
itemstyle_opts=opts.ItemStyleOpts(
color="#ec0000",
color0="#ec0000",
area_color="#ec0000",
),
))
if data["scount"] > 0:
bspoints.append(
opts.MarkPointItem(
name="S",
coord=[data.name.strftime("%Y-%m-%d"), data["sprice"]],
symbol_size=20,
value=str(round(data["signal"], 2)),
itemstyle_opts=opts.ItemStyleOpts(color="#00da3c"),
))
global area
if data["position"] > 0:
if area == None:
area = {}
area["assets"] = data["assets"]
area["date"] = data.name.strftime("%Y-%m-%d")
else:
if area is not None:
shouyi = data["assets"] - area["assets"]
shouyiv = shouyi / area["assets"]
print(shouyi)
bsArea.append(
opts.MarkAreaItem(
'收益：{:.2f} 收益率：{:.2f}'.format(shouyi, shouyiv),
x=(area["date"], data.name.strftime("%Y-%m-%d")),
itemstyle_opts=opts.ItemStyleOpts(
color="#ec0000" if shouyi > 0 else "#00da3c",
opacity=0.1),
))
area = None
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
pieces=[
{
"lte": 6,
"color": "green"
},
{
"gt": 6,
"lte": 8,
"color": "red"
},
{
"gt": 8,
"lte": 14,
"color": "green"
},
{
"gt": 14,
"lte": 17,
"color": "red"
},
{
"gt": 17,
"color": "green"
},
],
),
).set_series_opts(markarea_opts=opts.MarkAreaOpts(data=[
opts.MarkAreaItem(name="早高峰", x=("07:30", "10:00")),
opts.MarkAreaItem(name="晚高峰", x=("17:30", "21:15")),
])).render("distribution_of_electricity.html"))
def positionsitem(data, begin="bdate", end="sdate", value="assetsv"):
return opts.MarkAreaItem(
x=(data[begin], data[end]),
itemstyle_opts=opts.ItemStyleOpts(
color="#ec0000" if data[value] > 0 else "#00da3c", opacity=0.1),
)
def draw_chart(df,
extend_field,
save_path="",
trade_list=None,
point_list=None,
area_list=None,
kline_title="买卖点K线图",
is_smooth=True,
is_connect_nones=False):
datetime_array = df.datetime.tolist()
volume_array = df.volume.tolist()
# open close low high
kline_data = df[["open", "close", "low", "high"]].values.tolist()
# 绘制买卖点
_point_list = []
# 绘制标志点
if point_list is not None and len(point_list) > 1:
for point in point_list:
if type(point["datetime"]) == str:
point_datetime = point["datetime"]
else:
point_datetime = point["datetime"].strftime(
"%Y-%m-%d %H:%M:%S.%f")
point_name = point.get("name", "")
_point_list.append(
opts.MarkPointItem(
name=point_name,
coord=[point_datetime, point["y"]],
value=point_name if point_name else point["y"],
itemstyle_opts=opts.ItemStyleOpts(
color=point.get("color", "#ef232a"))))
else:
if trade_list is not None and len(trade_list) > 1:
for trade in trade_list:
# 开多
if type(trade[0]) == str:
trade_datetime = trade[0]
else:
trade_datetime = trade[0].strftime(
"%Y-%m-%d %H:%M:%S.%f")
if trade_datetime < datetime_array[0]:
continue
if trade[1] == "多" and trade[4] == "开":
_point_list.append(
opts.MarkPointItem(
name="开多",
coord=[trade_datetime, trade[6]],
value="开多",
itemstyle_opts=opts.ItemStyleOpts(
color="#ef232a")))
# 开空
elif trade[1] == "空" and trade[4] == "开":
_point_list.append(
opts.MarkPointItem(
name="开空",
coord=[trade_datetime, trade[6]],
value="开空",
itemstyle_opts=opts.ItemStyleOpts(
color="#ef232a")))
# 平多
elif trade[1] == "多" and (trade[4] == "平" or trade[4]
== "平今" or trade[4] == "平昨"):
_point_list.append(
opts.MarkPointItem(
name="平空",
coord=[trade_datetime, trade[6]],
value="平空",
itemstyle_opts=opts.ItemStyleOpts(
color="#14b143")))
# 平空
elif trade[1] == "空" and (trade[4] == "平" or trade[4]
== "平今" or trade[4] == "平昨"):
_point_list.append(
opts.MarkPointItem(
name="平多",
coord=[trade_datetime, trade[6]],
value="平多",
itemstyle_opts=opts.ItemStyleOpts(
color="#14b143")))
# 绘制矩形
_area_list = []
if area_list is not None and len(area_list) > 1:
for item in area_list:
_area_list.append(
opts.MarkAreaItem(
x=item["x"],
y=item["y"],
itemstyle_opts=opts.ItemStyleOpts(
color="transparent",
border_color=item.get("border_color", "#4D0099"),
border_width=3,
border_type="dashed"),
))
kline = (Kline().add_xaxis(xaxis_data=datetime_array).add_yaxis(
series_name="Kline",
y_axis=kline_data,
itemstyle_opts=opts.ItemStyleOpts(
color="#ef232a",
color0="#14b143",
border_color="#ef232a",
border_color0="#14b143",
),
markpoint_opts=opts.MarkPointOpts(data=_point_list),
).set_series_opts(markarea_opts=opts.MarkAreaOpts(
data=_area_list, )).set_global_opts(
title_opts=opts.TitleOpts(title=kline_title,
pos_left="2%",
pos_top="1%"),
legend_opts=opts.LegendOpts(is_show=True,
pos_top=10,
pos_left="center"),
datazoom_opts=[
opts.DataZoomOpts(
is_show=False,
type_="inside",
xaxis_index=[0, 1],
range_start=0,
range_end=100,
),
opts.DataZoomOpts(
is_show=True,
xaxis_index=[0, 1],
type_="slider",
pos_top="88%",
range_start=0,
range_end=100,
),
],
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitline_opts=opts.SplitLineOpts(is_show=True)),
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"),
),
))
bar = (Bar().add_xaxis(xaxis_data=datetime_array).add_yaxis(
series_name="Volume",
y_axis=volume_array,
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),
))
if len(extend_field) > 0:
line = (Line().add_xaxis(
xaxis_data=datetime_array).set_global_opts(
xaxis_opts=opts.AxisOpts(type_="category"),
legend_opts=opts.LegendOpts(is_show=True),
))
for field in extend_field:
field_value_array = df[field].tolist()
line.add_yaxis(
series_name=field,
y_axis=field_value_array,
is_smooth=is_smooth,
is_hover_animation=False,
linestyle_opts=opts.LineStyleOpts(width=2, opacity=0.8),
label_opts=opts.LabelOpts(is_show=False),
is_connect_nones=is_connect_nones,
)
# Kline And Line
kline = kline.overlap(line)
# Grid Overlap + Bar
grid_chart = Grid(init_opts=opts.InitOpts(
width="100%",
height="760px",
animation_opts=opts.AnimationOpts(animation=False),
))
grid_chart.add(
kline,
grid_opts=opts.GridOpts(pos_left="3.5%",
pos_right="3.5%",
height="60%"),
)
grid_chart.add(
bar,
grid_opts=opts.GridOpts(pos_left="3.5%",
pos_right="3.5%",
pos_top="70%",
height="16%"),
)
grid_chart.render(os.path.join(save_path, "KLineChart.html"))
def line(delivery_dates, df):
# line the vix
FLINE_OPT = opts.LineStyleOpts(opacity=1, width=1.5)
OLINE_OPT = opts.LineStyleOpts(opacity=0.9, width=1.2, type_='dashed')
df['delivery'] = [10 + 5 * (idx in delivery_dates) for idx in df.index]
warning_areas = get_warning_areas(df)
# there is a bug in pyecharts, the colors are reversed
# line.colors = ['crimson', 'gold', 'green', 'fuchsia', 'orchid', 'plum']
line = (
Line().add_xaxis(xaxis_data=df.index).add_yaxis(
"vix",
df[0],
is_symbol_show=False,
areastyle_opts=opts.AreaStyleOpts(opacity=0.2),
linestyle_opts=FLINE_OPT,
color='powderblue',
markline_opts=opts.MarkLineOpts(data=[
opts.MarkLineItem(type_="min", name="ivl"),
opts.MarkLineItem(type_="max", name="ivh"),
])).add_yaxis('gvz',
df['gvz'],
is_symbol_show=False,
linestyle_opts=FLINE_OPT,
color='olive',
markline_opts=opts.MarkLineOpts(data=[
opts.MarkLineItem(type_="min", name="ivl"),
opts.MarkLineItem(type_="max", name="ivh"),
])).add_yaxis(
'ovx',
df['ovx'],
is_symbol_show=False,
linestyle_opts=FLINE_OPT,
color='tan',
# is_selected = False,
markline_opts=opts.MarkLineOpts(data=[
opts.MarkLineItem(type_="min", name="ivl"),
opts.MarkLineItem(type_="max", name="ivh"),
])).add_yaxis(
"1",
df[1],
is_symbol_show=False,
color='plum',
linestyle_opts=OLINE_OPT).add_yaxis(
"2",
df[2],
is_symbol_show=False,
color='orchid',
linestyle_opts=OLINE_OPT,
is_selected=False).add_yaxis(
"3",
df[3],
is_symbol_show=False,
color='fuchsia',
linestyle_opts=OLINE_OPT).add_yaxis(
"4",
df[4],
is_symbol_show=False,
color='green',
linestyle_opts=OLINE_OPT,
is_selected=False).add_yaxis(
"5",
df[5],
is_symbol_show=False,
color='gold',
linestyle_opts=OLINE_OPT)
# add delivery date mark, not a good idea, but worked.
.add_yaxis("delivery",
df['delivery'],
is_symbol_show=False,
color='crimson',
is_step=True).set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
markarea_opts=opts.MarkAreaOpts(
is_silent=True,
data=[
opts.MarkAreaItem(name="warn", x=(xs, xe))
for xs, xe in warning_areas
],
itemstyle_opts=opts.ItemStyleOpts(
color='#FFA54F10'))).set_global_opts(
title_opts=opts.TitleOpts(title="vix",
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(
type_="slider",
range_start=50,
range_end=100),
))
return line
def grid_vertical(xaxis, taixin_yaxis, yali_yaxis, td_yaxis):
max_taixin = max(taixin_yaxis) + 20
min_taixin = min(taixin_yaxis) - 60
if min_taixin <= 0:
min_taixin = 0
line1 = (Line().add_xaxis(xaxis).add_yaxis(
"胎心率",
taixin_yaxis,
label_opts=opts.LabelOpts(is_show=False),
is_symbol_show=False,
markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(type_="average", name="胎心率平均值")]),
markpoint_opts=opts.MarkPointOpts(data=[
opts.MarkPointItem(type_="max", name="胎心率最大值"),
]),
).add_yaxis("下限", [120, 120],
markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(type_="average")])).add_yaxis(
"上限", [160, 160],
markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(type_="average")])).
add_yaxis(
"胎动",
td_yaxis,
label_opts=opts.LabelOpts(is_show=False),
markpoint_opts=opts.MarkPointOpts(data=[
opts.MarkPointItem(type_="None", name="胎动"),
]),
).set_global_opts(
xaxis_opts=opts.AxisOpts(
type_='value',
interval=120,
splitline_opts=opts.SplitLineOpts(is_show=True),
axislabel_opts=opts.LabelOpts(formatter="{value}秒"),
),
yaxis_opts=opts.AxisOpts(
type_='value',
interval=10,
min_=min_taixin,
max_=max_taixin,
splitline_opts=opts.SplitLineOpts(is_show=True)),
title_opts=opts.TitleOpts(title="eFM-60超声多普勒胎儿监护仪监测曲线图"),
tooltip_opts=opts.TooltipOpts(trigger="axis"),
toolbox_opts=opts.ToolboxOpts(is_show=True, ),
).set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
markarea_opts=opts.MarkAreaOpts(data=[
opts.MarkAreaItem(name="合理区间",
y=(120, 160),
itemstyle_opts=opts.ItemStyleOpts(
color="#A0D897", opacity=0.2)),
])))
line2 = (
Line().add_xaxis(xaxis).add_yaxis(
"宫内压力",
yali_yaxis,
label_opts=opts.LabelOpts(is_show=False),
is_symbol_show=False).set_global_opts(
xaxis_opts=opts.AxisOpts(
type_='value',
interval=120,
splitline_opts=opts.SplitLineOpts(is_show=True),
axislabel_opts=opts.LabelOpts(formatter="{value}秒"),
),
yaxis_opts=opts.AxisOpts(
type_='value',
interval=10,
min_=0,
max_=100,
splitline_opts=opts.SplitLineOpts(is_show=True)),
# title_opts=opts.TitleOpts(title="")
tooltip_opts=opts.TooltipOpts(trigger="axis"),
toolbox_opts=opts.ToolboxOpts(is_show=True),
legend_opts=opts.LegendOpts(pos_top="50%"),
).set_series_opts(label_opts=opts.LabelOpts(is_show=False), ))
# 把上面生成的两个图放进grid中并通过pos_top，pos_bottom, pos_left, pos_right设置其位置
grid = (Grid(init_opts=opts.InitOpts(width="3000px", height="600px")).add(
line2, grid_opts=opts.GridOpts(pos_top='60%', pos_left='2%')).add(
line1, grid_opts=opts.GridOpts(pos_bottom="60%", pos_left='2%')))
# 生成到本地网页形式打开，也可自己设置保存成png图片，因为网页的使用更方便，自己按情况使用
grid.render('1.html')
# 输出保存为图片
make_snapshot(snapshot, grid.render(), "1.png")
print(">>图表生成完毕！")
def signal_overview(price,
trades=None,
supplements=None,
plot_options={},
f_name="1213.html"):
figs_counts = len(supplements)
legends_heights = (figs_counts * 5)
left = 90 - legends_heights
height = left / figs_counts
sub_plots = []
fig_size = plot_options.setdefault("fig_size", ("1000px", "600px"))
x_data = price.index.tolist()
y_data = price.values.tolist()
marks = supplements.get("marks")
with_marks = True if marks is not None else False
if with_marks:
_ = pd.Series(index=price.index, data=np.arange(len(price)))
marks_data = [
opts.MarkPointItem(coord=[(x_data[int(l)]), (y_data[int(l)])],
itemstyle_opts=opts.ItemStyleOpts(
color=plot_options.setdefault(
v[0], colors[i]),
opacity=0.6),
symbol_size=20,
symbol="pin")
for i, v in enumerate(marks.items())
for l in _.reindex(v[1]).dropna().values.tolist()
]
else:
marks_data = []
with_trades = True if isinstance(trades, pd.Series) else False
if with_trades:
e_loc = [
price.index.get_loc(i)
for i in trades.index.get_level_values(0).unique()
]
ex_loc = [
price.index.get_loc(i)
for i in trades.index.get_level_values(1).unique()
]
pairs_loc = list(zip(e_loc, ex_loc))
(pairs_loc)
_b = [{"gt": p[0], "lte": p[1], "color": "#CD6839"} for p in pairs_loc]
_c = [{
"gt": pairs_loc[i][-1],
"lte": p[0],
"color": "#4A708B"
} for i, p in enumerate(pairs_loc[1:])]
_a = [{
"lte": pairs_loc[0][0],
"color": "#4A708B"
}, {
"gt": pairs_loc[-1][-1],
"color": colors[0]
}]
pieces = _a + _b + _c
else:
pieces = []
ds = np.unique(price.index.date)
decor_ = price.groupby(
price.index.date).apply(lambda x: [x.index[0], x.index[-1]]).loc[[
l[1] for l in list(filter(lambda x: x[0] % 2 == 0, enumerate(ds)))
]]
data_zoom_axis = np.arange(figs_counts).astype(int).tolist()
line = (Line(
init_opts=opts.InitOpts(width=fig_size[0], height=fig_size[1])
).add_xaxis(xaxis_data=x_data).add_yaxis(
series_name="价格",
y_axis=y_data,
yaxis_index=0,
is_smooth=True,
is_symbol_show=False,
is_hover_animation=False,
linestyle_opts=opts.LineStyleOpts(width=2),
markpoint_opts=opts.MarkPointOpts(data=marks_data, ),
).set_global_opts(
title_opts=opts.TitleOpts(title="价格",
pos_left='center',
pos_top=str(figs_counts * 5) + "%"),
toolbox_opts=opts.ToolboxOpts(is_show=True),
tooltip_opts=opts.TooltipOpts(
trigger="axis",
axis_pointer_type="cross",
border_width=1,
),
legend_opts=opts.LegendOpts(pos_left="left"),
axispointer_opts=opts.AxisPointerOpts(is_show=True,
link=[{
"xAxisIndex": "all"
}]),
datazoom_opts=[
opts.DataZoomOpts(is_show=True,
is_realtime=True,
xaxis_index=data_zoom_axis,
pos_top="5%",
range_start=0,
range_end=100,
orient="horizontal",
type_="inside"),
opts.DataZoomOpts(type_="slider",
xaxis_index=data_zoom_axis,
pos_bottom="bottom"),
],
yaxis_opts=opts.AxisOpts(
is_scale=True,
axistick_opts=opts.AxisTickOpts(is_inside=False),
axispointer_opts=opts.AxisPointerOpts(is_show=True),
axisline_opts=opts.AxisLineOpts(symbol='none'),
splitline_opts=opts.SplitLineOpts(is_show=True)),
xaxis_opts=opts.AxisOpts(is_show=False, ),
visualmap_opts=opts.VisualMapOpts(
is_show=False,
is_piecewise=with_trades,
dimension=0,
pieces=pieces,
),
).set_series_opts(markarea_opts=opts.MarkAreaOpts(data=[
opts.MarkAreaItem(
name="",
x=(d[0], d[1]),
itemstyle_opts=opts.ItemStyleOpts(color="#A1A9AF", opacity=0.2),
) for d in decor_
])))
sub_plots.append(line)
if with_marks:
_ = supplements.pop("marks")
if len(supplements) > 0:
last_pic = list(supplements.keys())[-1]
for i, s_1 in enumerate(supplements.items()):
k, v = s_1[0], s_1[1]
print(k)
ls = Line(
init_opts=opts.InitOpts(width=fig_size[0], height=fig_size[1]))
ls = ls.add_xaxis(xaxis_data=price.index.tolist())
for j, s_2 in enumerate(v.items()):
n, l = s_2[0], s_2[1]
print(n)
num = i * len(s_1) + j
ls.add_yaxis(
series_name=n,
y_axis=l.tolist(),
yaxis_index=len(sub_plots),
linestyle_opts=opts.LineStyleOpts(
width=2, color=plot_options.setdefault(n,
colors[num])),
label_opts=opts.LabelOpts(is_show=False),
)
s = legends_heights + height * len(sub_plots)
ls = ls.set_global_opts(
title_opts=opts.TitleOpts(title=k,
pos_left='center',
pos_top=str(s) + "%"),
legend_opts=opts.LegendOpts(pos_left="left",
pos_top=str(len(sub_plots) * 5) +
"%"),
yaxis_opts=opts.AxisOpts(
is_scale=True,
axistick_opts=opts.AxisTickOpts(is_inside=False),
axispointer_opts=opts.AxisPointerOpts(is_show=True),
axisline_opts=opts.AxisLineOpts(symbol='none'),
splitline_opts=opts.SplitLineOpts(is_show=True)),
xaxis_opts=opts.AxisOpts(is_show=(k == last_pic), ),
).set_series_opts(markarea_opts=opts.MarkAreaOpts(
data=[
opts.MarkAreaItem(
name="",
x=(d[0], d[1]),
itemstyle_opts=opts.ItemStyleOpts(color="#A1A9AF",
opacity=0.2),
) for d in decor_
],
is_silent=False,
))
sub_plots.append(ls)
pos = [
i + "%" for i in (height * np.arange(len(sub_plots)) +
legends_heights + 4.3).astype(str)
]
g = (Grid(init_opts=opts.InitOpts(width=fig_size[0], height=fig_size[1])))
for i, v in enumerate(sub_plots):
g.add(
chart=v,
grid_opts=opts.GridOpts(pos_left=50,
pos_right=50,
pos_top=pos[i],
height=str(height - 5) + "%"),
)
g.render(f_name)
import datetime
import math
import pyecharts.options as opts
import random
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts.faker import POPULATION
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
# %%
# 直角坐标系图表
# 直方图
x_data = ['apple', 'huawei', 'xiaomi', 'oppo', 'vivo', 'meizu']
y_data = [123, 312, 89, 107, 82, 23]
bar = (Bar().add_xaxis(x_data).add_yaxis('', y_data))
bar.render()
# %%
# 折线图
x_data = ['apple', 'huawei', 'xiaomi', 'oppo', 'vivo', 'meizu']
y_data = [123, 312, 89, 107, 82, 23]
bar = (Line().add_xaxis(x_data).add_yaxis('', y_data))
bar.render()
# %%
# 折线图
x_data = ['apple', 'huawei', 'xiaomi', 'oppo', 'vivo', 'meizu']
y_data = [[random.randint(100, 200) for i in range(10)] for item in x_data]
Box = Boxplot()
Box.add_xaxis(x_data)
Box.add_yaxis('', Box.prepare_data(y_data))
bar.render()
axispointer_opts=opts.AxisPointerOpts(is_show=True)
# 分隔线
splitline_opts=opts.SplitLineOpts(is_show=True),
)
)
.set_series_opts(
# 区域标记
markarea_opts=opts.MarkAreaOpts(
is_silent=False,
data=[
opts.MarkAreaItem(
name='',
x=(year-0.5,year+0.5),
label_opts=opts.LabelOpts(is_show=False),
itemstyle_opts=opts.ItemStyleOpts(
color="#aaaaaa", opacity=0.1
),
)
]
)
)
)
#------------------------------------- 配件及其他常用格式详解 -------------------------------------#
line=(
Line( # 官方说明链接 下同
# 初始化 https://pyecharts.org/#/zh-cn/global_options?id=initopts%ef%bc%9a%e5%88%9d%e5%a7%8b%e5%8c%96%e9%85%8d%e7%bd%ae%e9%a1%b9
width = "900px",
height = "500px",
page_title = "Awesome-pyecharts",
),
title_opts=opts.TitleOpts(title="各时段的订单数量与销售额"),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="cross"),
))
line = (
Line().add_xaxis(x_data).add_yaxis(
"销售额",
t3["analyze_t3.sales"].values.tolist(),
yaxis_index=0,
#color="#ff5798",
#color="#BFEFFF",
label_opts=opts.LabelOpts(is_show=False),
).set_series_opts(markarea_opts=opts.MarkAreaOpts(data=[
opts.MarkAreaItem(name="午高峰", x=("12", "15")),
opts.MarkAreaItem(name="晚高峰", x=("17", "20")),
])))
# x_data = ["{}月".format(i) for i in range(1, 13)]
# line = (
# Line()
# .add_xaxis(x_data)
# .add_yaxis(
# "平均温度",
# [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2],
# # yaxis_index=2,
# # color="#675bba",
# # label_opts=opts.LabelOpts(is_show=False),
# )
# )