def get_bar_chart():
chart_data = Buy2LineChart.fund_line(get_conf()['基金']['基金购买记录'])
line_data = Line()
all_date = None
for _, chart_data_val in chart_data.items():
p1, p2, p3, p4, p5 = chart_data_val[0],chart_data_val[1],chart_data_val[2],chart_data_val[3],chart_data_val[4]
line_data = line_data.add_xaxis(p1).add_yaxis(p2, p3, markline_opts=p4, markpoint_opts=p5)
all_date = p1
# 双轴，副轴为上证指数
index_vals = IndexHistory.get_history(all_date[0])
# min_axis, max_axis = min(index_vals), max(index_vals)
# last_x, last_y, last_val = all_date[-1], int(index_vals[-1]-2900), index_vals[-1]
# print(last_x, last_y, last_val)
sh_index = Line().add_xaxis(all_date).add_yaxis('上证指数', [int(x-2900) for x in index_vals],
# markline_opts=[100],
# markpoint_opts=[opts.MarkPointItem(coord=[last_x, last_y], value=last_val, symbol=SymbolType.RECT)],
yaxis_index=1)
# .extend_axis(yaxis=opts.AxisOpts(min_=[min_axis], max_=[max_axis]))
line_data.extend_axis(yaxis=opts.AxisOpts(interval=50)).overlap(sh_index)
# see: http://pyecharts.org/#/zh-cn/rectangular_charts
c = (line_data)
return c.dump_options_with_quotes()
def plot_multiple_line(x_axis,
y_axis_dict,
title,
double_ylabel_str,
double_ylabel=False,
ylabel_smooth=False,
is_show=True):
# 由于全部展示图例时数字太多影响效果，is_show用于控制是否展示或者都不展示
line = Line()
line.add_xaxis(x_axis)
for _name in y_axis_dict.keys():
if _name != double_ylabel_str:
line.add_yaxis(_name,
y_axis_dict[_name],
label_opts=opts.LabelOpts(is_show=is_show))
line.set_global_opts(title_opts=opts.TitleOpts(title=title, pos_top=20),
toolbox_opts=opts.ToolboxOpts(pos_top=30),
legend_opts=opts.LegendOpts(pos_bottom=0,
orient="horizontal"))
if double_ylabel:
line.extend_axis(yaxis=opts.AxisOpts(
name=double_ylabel_str, axislabel_opts=opts.LabelOpts(interval=5)))
line.add_yaxis(double_ylabel_str,
y_axis_dict[double_ylabel_str],
yaxis_index=1,
is_smooth=ylabel_smooth)
return line
def gen_line(df1):
#df1['datetime'] = df1['date'] + ' ' + df1['time']
df1['datetime'] = df1['date']
dt_list1 = list(df1['datetime'])
# print( len(dt_list1) )
# dt_list1 = [s[5:10] for s in dt_list1]
close_list1 = df1.apply(lambda record: float(record['close1']),
axis=1).tolist()
close_list1 = np.array(close_list1)
# print(close_list1)
close_list2 = df1.apply(lambda record: float(record['close2']),
axis=1).tolist()
close_list2 = np.array(close_list2)
price_min = 9000
line1 = Line(init_opts=opts.InitOpts(width='1500px', height='600px'))
line1.set_global_opts(
yaxis_opts=opts.AxisOpts(
min_=price_min,
#max_=price_max,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
),
datazoom_opts=[
opts.DataZoomOpts(
is_show=True,
type_="slider",
range_start=0,
range_end=100,
),
],
)
line1.extend_axis(yaxis=opts.AxisOpts(axislabel_opts=opts.LabelOpts(
formatter="{value} °C")))
line1.add_xaxis(xaxis_data=dt_list1)
line1.add_yaxis(
'left',
y_axis=close_list1,
)
line1.add_yaxis('right', y_axis=close_list2, yaxis_index=1)
line1.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
return line1
data=[opts.MarkPointItem(type_="max",
name="最大值")], #最大值圆点配置
symbol_size=40),
label_opts=opts.LabelOpts(is_show=False) #不显示每个点的值
)
c.set_global_opts( #全局配置开始
# title_opts = opts.TitleOpts(title = "The Development of COVID-19 News"),
xaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(interval=30),
name="Date",
name_gap=30),
yaxis_opts=opts.AxisOpts(name_rotate=90,
name_location="center",
name_gap=30))
c.extend_axis(yaxis=opts.AxisOpts(name_rotate=90,
name_location="center",
name_gap=60)) #基于折线图扩展纵坐标，设置右边的纵坐标
b = Bar() #开始画底层的柱状图
b.add_xaxis(publish_date)
# for death_type in [publisher_dic[publisher], 'Global']:
for death_type in [publisher_dic[publisher]]: #开始加daily cases柱状图
y = []
for day in publish_date:
df_value = death_df[death_df['Date'] == day][
death_type] #death_type是不同的国家
if len(df_value) > 0: #57-60，把没有新闻量的日期设置为0
y.append(int(df_value))
else:
y.append(0)
b.add_yaxis(
death_type + " daily cases",
def draw_charts(kline_data ,canshu ={} ,canshu2={},vol_bar=False,markline_show1 =False ,markline_show2 =False, path = '0501'):
'''
df['candle_begin_time','open','high','low','close','volume']
[['candle_begin_time','open','high','low','close','volume']]
kdata = df[['open', 'high', 'low', 'close']].values.tolist()
df['candle_begin_time'].values.tolist()
:return:
'''
df = kline_data.copy()
df['candle_begin_time'] = pd.to_datetime(df['candle_begin_time'])
time_list = df['candle_begin_time'].apply(lambda x: x.strftime('%Y-%m-%d %H:%M:%S')).values.tolist()
vol = df['volume'].values.tolist()
kline = Kline()
kline.add_xaxis(xaxis_data=time_list)
signal_pos_list = []
if 'signal' in df.columns:
print('signal,存在！')
df['pos'] = df['signal'].shift(1)
for i in df[df['pos'] > 0].index:
bar0 = df.iloc[i]
sig_pos0 = opts.MarkPointItem(name="做多",
coord=[bar0['candle_begin_time'].strftime('%Y-%m-%d %H:%M:%S'),bar0.low -2],
value='买',
symbol ='circle',
symbol_size =[20,40],
itemstyle_opts = {'color': 'red'})
signal_pos_list.append(sig_pos0)
for i in df[df['pos'] < 0].index:
bar0 = df.iloc[i]
sig_pos0 = opts.MarkPointItem(name="做空",
coord=[bar0['candle_begin_time'].strftime('%Y-%m-%d %H:%M:%S'),bar0.high +3],
value='卖',
symbol='circle',
symbol_size=[20, 40],
itemstyle_opts={'color': 'blue'})
signal_pos_list.append(sig_pos0)
for i in df[df['pos'] == 0].index:
bar0 = df.iloc[i]
sig_pos0 = opts.MarkPointItem(name="平仓",
coord=[bar0['candle_begin_time'].strftime('%Y-%m-%d %H:%M:%S'),bar0.low - 2],
value='平',
symbol ='triangle',
symbol_size =[20,40],
itemstyle_opts = {'color': 'green'})
signal_pos_list.append(sig_pos0)
else :
df['pos'] =None
markline =[]
if markline_show1 and ('signal' in df.columns) :
area_index_list =[i for i in df[(df['pos'] ==0)|(df['pos'] >0)|(df['pos'] <0)].index]
for ix,i in enumerate(area_index_list):
if ix+1 > len(area_index_list)-1:
break
i_now = df.iloc[area_index_list[ix]]
i_next = df.iloc[area_index_list[ix+1]]
if (i_now['pos'] >0) or (i_now['pos'] <0) :
log_info = f"价差：={i_next['open']-i_now['open']}--({i_next['open']}-{i_now['open']})"
else :
log_info =f"平仓：{i_next['open']}---开仓：{i_now['open']}"
sig_area = [{"xAxis": i_now['candle_begin_time'].strftime('%Y-%m-%d %H:%M:%S'),
"yAxis": i_now['open'] ,
"value": None},
{"xAxis": i_next['candle_begin_time'].strftime('%Y-%m-%d %H:%M:%S'),
"yAxis": i_now['open'],
"value":log_info}]
sig_area_v = [{"xAxis": i_next['candle_begin_time'].strftime('%Y-%m-%d %H:%M:%S'),
"yAxis": i_now['open'] ,
"value": None},
{"xAxis": i_next['candle_begin_time'].strftime('%Y-%m-%d %H:%M:%S'),
"yAxis": i_next['open'],
"value":None}]
markline.append(sig_area)
markline.append(sig_area_v)
elif markline_show2 and ('signal' in df.columns):
area_index_list =[i for i in df[(df['pos'] ==0)|(df['pos'] >0)|(df['pos'] <0)].index]
for ix,i in enumerate(area_index_list):
i_now = df.iloc[area_index_list[ix]]
i_1_now = df.iloc[area_index_list[ix-1]] if ix != 0 else 0
if i_now['pos'] == 0:
log_info = f"交易价: {round(i_now['open'], 1)} +- 2__盈亏:{round(i_now['open'], 1) - round(i_1_now['open'], 1)}"
else:
log_info = f"交易价: {round(i_now['open'],1)} +- 2"
sig_area = [{"xAxis": i_now['candle_begin_time'].strftime('%Y-%m-%d %H:%M:%S'),
"yAxis": i_now['open'] ,
"value": None},
{"xAxis": (i_now['candle_begin_time']+timedelta(minutes=15)).strftime('%Y-%m-%d %H:%M:%S'),
"yAxis": i_now['open'],
"value":log_info}]
markline.append(sig_area)
colors = {'red': 'rgb((220,20,60)','red2': 'rgb((250,20,40)',
'yangzi': 'rgb(255,0,255)', 'zi': 'rgb(128,0,128)',
'sehnzi': 'rgb(148,0,211)', 'blue': 'rgb(0,0,255)',
'qing': 'rgb(0,255,255)', 'black': 'rgb(0,0,0)',
'shengreen': 'rgb(157,255,212)', 'green': 'rgb(0,255,0)',
'yellow': 'rgb(255,255,0)', 'glod': 'rgb(218,165,32)',
'orange': 'rgb(255,165,0)', 'brown': 'rgb(165,42,42)'}
kline.add_xaxis(xaxis_data=time_list)
kline.add_yaxis(series_name="oclh",
xaxis_index=1,
yaxis_index=1,
y_axis =df.loc[:, ['open', 'close', 'low', 'high']].values.tolist(),
markline_opts=opts.MarkLineOpts(data=markline,
linestyle_opts=opts.LineStyleOpts(type_='dotted',width=3,color='red',opacity=0.5),
label_opts=opts.LabelOpts(position="right", color="blue", font_size=13),),
#官网给出的样本
markpoint_opts=opts.MarkPointOpts(data=signal_pos_list),
itemstyle_opts=opts.ItemStyleOpts(color="#ec0090", color0="#00aa3c"), )
kline.set_global_opts(
legend_opts=opts.LegendOpts(is_show=True,pos_top=30, pos_left="left",orient='vertical'),
datazoom_opts=[ opts.DataZoomOpts(
is_show=False,
type_="inside",
xaxis_index=[0, 1],
range_start=90,
range_end=100,
orient='vertical'),
opts.DataZoomOpts(
is_show=True,
xaxis_index=[0, 1],
type_="slider",
pos_top="20%",
range_start=90,
range_end=100,orient='vertical'),],
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 = 'K_line',
pos_top='middle',
title_textstyle_opts=opts.TextStyleOpts(
color='black',font_weight='bold' ,font_size=20)),
tooltip_opts=opts.TooltipOpts(
trigger="axis",
trigger_on='"mousemove"',#click|mousemove
axis_pointer_type="cross",
is_show_content=True,
is_always_show_content=True,
background_color="rgba(20, 105, 245, 0.1)",
border_width=1,
border_color= "#ccc",
position = ['70%','30%'],
textstyle_opts=opts.TextStyleOpts(font_size=10,color="#000"),),
visualmap_opts=opts.VisualMapOpts(
is_show=True,
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(canshu.keys())>0:
cos = list(colors.values())
line = Line()
for k,v in canshu.items():
line.add_xaxis(xaxis_data=time_list)
line.set_global_opts(xaxis_opts=opts.AxisOpts(type_="category"))
co = cos.pop()
line.add_yaxis(
series_name=k,
y_axis = [y for y in v.values.tolist() if y != np.nan],
xaxis_index=1,
yaxis_index=1,
is_smooth=False,
is_connect_nones=False,# 是否连接空数据
is_symbol_show=False,#是否显示值的位置，默认显示。
color = co,
is_hover_animation = False, # 是否开启 hover 在拐点标志上的提示动画效果。
linestyle_opts=opts.LineStyleOpts(width=2, opacity=0.9,color=co),
label_opts=opts.LabelOpts(is_show =True,position='middle',distance=2,rotate=5,color = 'rgb(165,42,42)'),
itemstyle_opts=opts.ItemStyleOpts(color=co),)
kline = kline.overlap(line)
grid_chart = Grid(init_opts=opts.InitOpts(width = "1500px",height= "700px",theme=ThemeType.DARK))
grid_chart.add(kline,grid_opts=opts.GridOpts(pos_left="10%", pos_right="8%",pos_top='4%' ,height="70%"))
if( vol_bar == True) or (len(canshu2.keys())==0):
bar = Bar()
bar.add_xaxis(xaxis_data=time_list)
bar.add_yaxis(
series_name="volume",
y_axis=vol,
xaxis_index=1,
yaxis_index=2,
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=True), )
grid_chart.add(bar,grid_opts=opts.GridOpts(pos_left="10%", pos_right="8%", pos_top="80%", height="15%"),)
if len(canshu2.keys())>0 :
line2 = Line()
line2.add_xaxis(xaxis_data=time_list)
for i, k in enumerate(canshu2.keys()):
co = random.choice(list(colors.values()))
line2.add_yaxis(
series_name=k,
y_axis=[y for y in canshu2[k].values.tolist()],
xaxis_index=1,
yaxis_index=i + 1,
is_smooth=True,
is_symbol_show=False,
is_hover_animation=True,
color=co,
z_level=0,
linestyle_opts=opts.LineStyleOpts(width=2, opacity=0.5, color=co),
label_opts=opts.LabelOpts(is_show=False), )
if k == list(canshu2.keys())[-1]: continue
line2.extend_axis(yaxis=opts.AxisOpts(name=k, type_="value", position="right", min_=None, max_=None,
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color=co)),
axislabel_opts=opts.LabelOpts(formatter="{value}"), ))
line2.set_global_opts(xaxis_opts=opts.AxisOpts(
type_="category", is_scale=True, grid_index=1, split_number=20, min_="dataMin", max_="dataMax",
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), ),
yaxis_opts=opts.AxisOpts(name=k, grid_index=i + 1, position='right',
splitarea_opts=opts.SplitAreaOpts(is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
min_=None, max_=None, is_scale=True, offset=50, ), )
grid_chart.add(line2,grid_opts=opts.GridOpts(pos_left="10%", pos_right="8%", pos_top="75%", height="23%"),is_control_axis_index=True)
tab = Tab()
zijin_data = (kline_data['per_lr'].cumsum())
zijin_data.fillna(method='ffill', inplace=True)
zijin_line = Line(init_opts=opts.InitOpts(width = "1500px",height= "700px",theme=ThemeType.DARK)).add_xaxis(time_list)
zijin_line.add_yaxis(series_name="zijin_line:", y_axis=zijin_data.values, color="#FF0000")
zijin_line.set_global_opts(
datazoom_opts=[opts.DataZoomOpts(), opts.DataZoomOpts(type_="inside")],
title_opts=opts.TitleOpts(title="资金曲线变化"),
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
yaxis_opts = opts.AxisOpts(
is_scale=True,
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=True)
)
tab.add(grid_chart,'kline' )
tab.add(zijin_line,'资金曲线变化' )
tab.render(f"{path}.html")
html0 = tab.render(f"{path}.html")
if os.path.exists(html0):
print("ok!保存在：")
print(html0)
else:
print('保存失败！')
def draw_line_charts(input_data,input_data2,canshu =[],path=''):
canshu_list = []
max0 = int(max(input_data[canshu].max())*1.001)
min0 = int(min(input_data[canshu].min())*0.995)
print(max0,min0)
for i in canshu:
canshu_dict0 = {}
canshu_dict0[i] = input_data[i]
canshu_list.append(canshu_dict0)
print(input_data.keys())
print(input_data.tail(100))
input_data['candle_begin_time'] = pd.to_datetime(input_data['candle_begin_time'])
time_list = input_data['candle_begin_time'].apply(lambda x: x.strftime('%Y-%m-%d %H:%M:%S')).values.tolist()
tab = Tab()
line_base = Line(init_opts=opts.InitOpts(width="1500px", height="700px", theme=ThemeType.DARK)).add_xaxis(time_list)
line_base.add_yaxis(series_name="close:",
y_axis=input_data['close'].values,
is_symbol_show=False,
color="#FF0000")
line_base.set_global_opts(
datazoom_opts=[opts.DataZoomOpts(range_start=95,
range_end=100,), opts.DataZoomOpts(
type_="inside",
range_start=95,
range_end=100,
)],
title_opts=opts.TitleOpts(title="资金曲线变化"),
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
yaxis_opts=opts.AxisOpts(
is_scale=True,
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=True) )
for ix,v in enumerate(canshu_list):
v0:str
value0:dict
for k,v0 in v.items():
name =k
value0 = v0
data0 = pd.DataFrame(value0)
data0.fillna(method='bfill',inplace=True)
# print(data0)
line_base.add_yaxis(
series_name=name,
y_axis=data0.values.tolist(),
yaxis_index=2,
linestyle_opts=opts.LineStyleOpts(),
label_opts=opts.LabelOpts(is_show=False),
)
line_base.extend_axis(
yaxis=opts.AxisOpts(
name="资金情况",
name_location="start",
type_="value",
max_= max0,
min_= min0,
is_inverse=False,
axistick_opts=opts.AxisTickOpts(is_show=False),
splitline_opts=opts.SplitLineOpts(is_show=False),))
tab.add(line_base,'资金变化')
table0 = Table().add(list(input_data2.columns), input_data2.values.tolist()).set_global_opts(
title_opts=ComponentTitleOpts(title="策略统计", subtitle=str(dt.datetime.now())))
table0.add_js_funcs('''
document.write("<p style='color:#FF0000;'>
注释：none </p>"
''')
tab.add(table0,'策略统计表')
html0 =tab.render(path)
if os.path.exists(html0):
print("ok!保存在：")
print(html0)
else:
print('保存失败！')
from pyecharts import options as opts
# 连接数据库
connect = pymysql.Connect(
host='localhost',
port=3306,
user='******',
passwd='demo1029',
db='mysql',
charset='utf8'
)
# 获取游标
cursor = connect.cursor()
ItemName = input('输入需要搜索的物品名称：')
xaxis = []
yaxis = []
yaxis1 = []
sql = "select * from mysql.itemprice where itemname = '"+ItemName+"' order by updatetime"
cursor.execute(sql)
for i in cursor.fetchall():
xaxis.append(i[4])
yaxis.append(i[1])
yaxis1.append(i[3])
line = Line()
line.add_xaxis(xaxis)
line.add_yaxis(ItemName, yaxis)
line.add_yaxis(ItemName, yaxis1, yaxis_index =1)
line.extend_axis(yaxis=opts.AxisOpts())
line.render(path='d:/1.html')
cursor.close()
connect.close()
def v_tradecost_ktest(
self, unitcost=True, start=None, end=yesterdayobj(), rendered=True
):
"""
visualization giving the average cost line together with netvalue line as well as buy and sell points
:returns: pyecharts.line
"""
# funddata = []
# costdata = []
pprice = self.price[self.price["date"] <= end]
pcftable = self.cftable
if start is not None:
pprice = pprice[pprice["date"] >= start]
pcftable = pcftable[pcftable["date"] >= start]
# for _, row in pprice.iterrows():
# date = row["date"]
# funddata.append(row["netvalue"])
# if unitcost:
# cost = 0
# if (date - self.cftable.iloc[0].date).days >= 0:
# cost = self.unitcost(date)
# costdata.append(cost)
#
coords = []
# pcftable = pcftable[abs(pcftable["cash"]) > threhold]
# for i, r in pcftable.iterrows():
# coords.append([r.date, pprice[pprice["date"] <= r.date].iloc[-1]["netvalue"]])
def marker_factory(x, y):
buy = pcftable[pcftable["date"] <= x].iloc[-1]["cash"]
print("buy",buy)
if buy < 0:
color = "#ff7733"
else:
color = "#3366ff"
size = (abs(buy) - lower) / (upper - lower) * 5 + 5
print("size",size)
return opts.MarkPointItem(
coord=[x.date(), y],
itemstyle_opts=opts.ItemStyleOpts(color=color),
# this nested itemstyle_opts within MarkPointItem is only supported for pyechart>1.7.1
symbol="circle",
symbol_size=size,
)
def marker_factory3v(x, y):
buy = pcftable[pcftable["date"] <= x].iloc[-1]["cash"]
print("buy",buy)
if buy < 0:
color = "#ff7733"
else:
color = "#3366ff"
# size = (abs(buy) - lower) / (upper - lower) * 5 + 5
size = len(str(buy)) * 10
print("size",size)
return opts.MarkPointItem(
value = -buy,
coord=[x.date(), y],
itemstyle_opts=opts.ItemStyleOpts(color=color),
# this nested itemstyle_opts within MarkPointItem is only supported for pyechart>1.7.1
# symbol="circle",
symbol_size=size,
)
coords_cash = []
# print("pcftable",pcftable)
# print("pprice",pprice)
#cash begin
cashdata = []
valuedata = []
# partp = self.price[self.price["date"] >= self.cftable.iloc[0].date]
# 多基金账单时起点可能非该基金持有起点
# partp = partp[partp["date"] <= end]
# valuedata = [
# self.briefdailyreport(d).get("currentvalue", 0) for d in partp.date
# self.briefdailyreport(d).get("currentvalue", 0) for d in pprice.date
# ]
# print(pprice.date)
# print("begin to cal ccost")
for d in pprice.date:
ucost = self.unitcost(d)
cshare = self.briefdailyreport(d).get("currentshare")
if(ucost is None or cshare is None ):
valuedata.append(0)
cashdata.append(0)
else:
cashdata.append(ucost*cshare)
valuedata.append(self.briefdailyreport(d).get("currentvalue", 0))
# # self.unitcost(d)*self.briefdailyreport(d).get("currentshare") for d in partp.date
# self.unitcost(d)*self.briefdailyreport(d).get("currentshare") for d in pprice.date
# ]
#cash end
# date = [d.date() for d in partp.date]
date = [d.date() for d in pprice.date]
date_dict = {}
for i,d in enumerate(date):
date_dict[convert_date(d)]=i
# print("date_dict",date_dict)
# print("date",date)
# print("cashdata",cashdata)
# pcftable = pcftable[abs(pcftable["cash"]) > threhold]
# print("print offset")
offset = pcftable["date"]
# print("offset",offset)
offset = offset[0]
offsetdate = []
coords_markvalue = []
pos = 3
for i, r in pcftable.iterrows():
# print("i,r",i,r)
# print("r.date",type(r.date.date()))
# print("convert_date(r.date)",type(convert_date(r.date)))
# print("date_dict[r.date]",date_dict[convert_date(r.date.date())])
offset = r.date - offset
valuecoords = valuedata[date_dict[convert_date(r.date.date())]]
cashcoords = cashdata[date_dict[convert_date(r.date.date())]]
distance = valuecoords - cashcoords
if(pos == 3):
coords_markvalue.append([r.date,cashcoords,offset])
pos =0
elif(pos == 0 ):
coords_markvalue.append([r.date,cashcoords + distance/2,offset])
pos = 1
elif(pos == 1):
coords_markvalue.append([r.date,valuecoords,offset])
pos =2
elif(pos ==2 ):
coords_markvalue.append([r.date,cashcoords,offset])
pos = 0
# if(distance>2000):
# pos = 1
# coords_markvalue.append([r.date,cashcoords + distance/2,offset])
# elif(distance<-2000):
#coords_markvalue.append([r.date,valuecoords - distance/2,offset])
# coords_markvalue.append([r.date,valuecoords - distance/2,offset])
# else:
#coords_markvalue.append([r.date,valuecoords,offset])
# coords_markvalue.append([r.date,cashcoords,offset])
coords_cash.append([r.date, cashdata[date_dict[convert_date(r.date.date())]],offset])
coords.append([r.date,cashdata[date_dict[convert_date(r.date.date())]]])
offsetdate.append(offset)
offset = r.date
# offsetdate[0] = pd.Timedelta(1,unit = "D")
print("coords_cash",coords_cash)
print("len(coords_cash)",len(coords_cash))
# print("offsetdate",offsetdate)
print("len(offsetdate)",len(offsetdate))
upper = pcftable.cash.abs().max()
lower = pcftable.cash.abs().min()
if upper == lower:
upper = 2 * lower + 1 # avoid zero in denominator
global previous
global direction
previous = 0
direction = 1
def marker_factory1v(x, y,offsetday):
offset = 0
buy = pcftable[pcftable["date"] <= x].iloc[-1]["cash"]
markvalue = 0
ycoor = y
global direction
global previous
print("previous before:",previous)
# loc = (abs(buy) - lower) / (upper - lower) * 5000 + 5000
loc = len(str(buy)) * 1000 + 1000
if buy < 0:
color = "#ff7733"
markvalue = -buy
if(offsetday < pd.Timedelta(7,unit = "D")):
offset = -100
ycoor = y + loc*previous*direction
previous = 1
direction =-direction
else:
previous = 0
else:
color = "#3366ff"
markvalue = -buy
if(offsetday < pd.Timedelta(7,unit = "D")):
ycoor = y + loc*previous*direction
direction = -direction
previous = 1
else:
previous = 0
print("previous after",previous)
# size = (abs(buy) - lower) / (upper - lower) * 50 + 50
size = len(str(buy)) * 10
return opts.MarkPointItem(name="test",
coord=[x.date(), ycoor],
value = -buy,
itemstyle_opts=opts.ItemStyleOpts(color=color),
# this nested itemstyle_opts within MarkPointItem is only supported for pyechart>1.7.1
# symbol="circle",
# symbol="rectangle",
symbol_size=size,
)
def marker_factory2v(x, y,offsetday):
offset = 0
buy = pcftable[pcftable["date"] <= x].iloc[-1]["cash"]
markvalue = 0
ycoor = y
global direction
global previous
print("previous before:",previous)
print("offsetday",offsetday)
print("day",x.date())
# loc = (abs(buy) - lower) / (upper - lower) * 5000 + 5000
loc = len(str(buy)) * 100
if buy < 0:
color = "#ff7733"
markvalue = -buy
if(offsetday < pd.Timedelta(5,unit = "D")):
offset = -100
#ycoor = y + loc*previous*direction
ycoor = y +loc*previous*direction
previous = 1
direction =-direction
else:
previous = 0
else:
color = "#3366ff"
markvalue = -buy
if(offsetday < pd.Timedelta(5,unit = "D")):
#ycoor = y + loc*previous*direction
ycoor = y + loc*previous*direction
direction = -direction
previous = 1
else:
previous = 0
print("previous after",previous)
# size = (abs(buy) - lower) / (upper - lower) * 50 + 50
size = len(str(round(-buy))) * 12
return opts.MarkPointItem(name="test",
coord=[x.date(), ycoor],
value = -round(buy),
itemstyle_opts=opts.ItemStyleOpts(color=color),
# this nested itemstyle_opts within MarkPointItem is only supported for pyechart>1.7.1
# symbol="circle",
# symbol="rectangle",
symbol_size=size,
)
# print("getting cashdata,pprice",pprice.date)
# print("2cashdata",cashdata)
# print("funddata",funddata)
print("len(2chashdata)",len(cashdata))
# print("funddata",len(funddata))
# print("valuedata",valuedata)
print("len(valuedata)",len(valuedata))
line = Line()
#line.add_xaxis([d.date() for d in pprice.date])
line.add_xaxis(date)
line.add_yaxis(
series_name="持仓总值1",
y_axis=valuedata,
# is_symbol_show=False,
# )
# y_axis=funddata,
is_symbol_show=False,
markpoint_opts=opts.MarkPointOpts(
data=[marker_factory2v(*c) for c in coords_markvalue],
),
)
line.extend_axis(
yaxis = opts.AxisOpts(
axislabel_opts = opts.LabelOpts(formatter="{value}%",)))
print("xianjinzhi")
line.add_yaxis(
series_name="现金值",
y_axis=cashdata,
is_symbol_show=False,
markpoint_opts=opts.MarkPointOpts(
# data=[marker_factory(*c) for c in coords_cash],
data=[marker_factory(*c) for c in coords],
# symbol = "circle",
# symbol_size =size,
),
)
def tooltip_factory(coords):
for x,y in coords:
return opts.TooltipOpts(
is_show=True,
trigger="axis",
trigger_on="mousemove",
axis_pointer_type="cross",
formatter = str(y)
)
line.set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(
is_show=True, type_="slider", range_start=50, range_end=100
),
opts.DataZoomOpts(
is_show=True,
type_="slider",
orient="vertical",
range_start=50,
range_end=100,
),
],
tooltip_opts=opts.TooltipOpts(
is_show=True,
trigger="axis",
# trigger_on="mousemove",
trigger_on="click",
axis_pointer_type="cross",
# formatter = [tooltip_factory(*c) for c in coords]
formatter = JsCode(
"""function(params){
if(params.dataIndex){
return params.dataIndex
}
else{
return params
}
}
"""
)
),
# tooltip_opts=tooltip_factory(coords)
# tooltip_opts=tooltip_factory(coords)
)
if rendered:
return line.render_notebook()
def generate_line_html2(rows, select=None):
line = Line(
opts.InitOpts(height='500px', width='1424px', theme=ThemeType.LIGHT))
x = []
y1 = []
y2 = []
min_y = 10000
max_y = 0
for row in rows:
x.append(row['date'])
mid_price = row['mid_price']
avg_premium = row['avg_premium']
if mid_price > max_y:
max_y = mid_price
elif mid_price < min_y:
min_y = mid_price
y1.append(mid_price)
y2.append(avg_premium)
delta = max_y - min_y
interval = round(delta / 5, 2)
star_up1 = round(min_y + interval * 1, 2)
star_up2 = round(min_y + interval * 2, 2)
star_up3 = round(min_y + interval * 3, 2)
star_up4 = round(min_y + interval * 4, 2)
line.add_xaxis(x)
line.extend_axis(
yaxis=opts.AxisOpts(type_='value',
name='溢价率平均值(%)',
name_rotate=90,
name_gap=55,
name_location='middle',
is_scale=True,
axislabel_opts=opts.LabelOpts(
formatter='{value}%'),
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
is_on_zero=False, symbol=['none', 'arrow'])))
line.add_yaxis("价格中位数", y1, yaxis_index=0)
line.add_yaxis("溢价率平均值", y2, yaxis_index=1)
line.set_global_opts(
title_opts=opts.TitleOpts(title="用价格中位数估值",
pos_left='center',
pos_top=-5),
tooltip_opts=opts.TooltipOpts(trigger='axis', ),
legend_opts=opts.LegendOpts(
is_show=True,
pos_top=20,
# pos_bottom=-50,
selected_mode='multiple'),
datazoom_opts={
'start': 0,
'end': 100
},
toolbox_opts=opts.ToolboxOpts(feature={
'dataZoom': {},
}),
xaxis_opts=opts.AxisOpts(
# data=None,
type_='time',
name='时间',
name_gap=30,
is_scale=True,
name_location='middle',
splitline_opts=opts.SplitLineOpts(is_show=False),
# axislabel_opts=opts.LabelOpts(formatter="{value}"), #echarts.format.formatTime('yy-MM-dd', value*1000)
axisline_opts=opts.AxisLineOpts(is_on_zero=False,
symbol=['none', 'arrow'])),
yaxis_opts=opts.AxisOpts(
type_='value',
name='价格中位数(元)',
name_rotate=90,
name_gap=55,
name_location='middle',
is_scale=True,
axislabel_opts=opts.LabelOpts(formatter='{value}元'),
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(is_on_zero=False,
symbol=['none', 'arrow'])),
visualmap_opts=opts.VisualMapOpts(is_show=True,
type_='color',
pos_top='50',
pos_left='5',
min_=min_y,
max_=max_y,
is_piecewise=True,
split_number=5,
series_index=0,
pieces=[
{
'min': min_y,
'max': star_up1,
'color': '#93CE07',
'label': '★★★★★'
},
{
'min': star_up1,
'max': star_up2,
'color': '#FBDB0F',
'label': '★★★★'
},
{
'min': star_up2,
'max': star_up3,
'color': '#FC7D02',
'label': '★★★'
},
{
'min': star_up3,
'max': star_up4,
'color': '#FD0100',
'label': '★★'
},
{
'min': star_up4,
'max': max_y,
'color': '#AC3B2A',
'label': '★'
},
]),
)
line.set_colors(['lightcoral', 'lightskyblue'])
line.set_series_opts(
symbol='none',
smooth=False,
linestyle_opts=opts.LineStyleOpts(width=2, ),
label_opts=opts.LabelOpts(is_show=False),
markline_opts=opts.MarkLineOpts(
is_silent=True,
symbol='none',
label_opts=opts.LabelOpts(
position='end',
is_show=False,
formatter=JsCode("function (params){return params.name}")),
linestyle_opts=opts.LineStyleOpts(
color='#333',
type_='dashed',
),
data=[
opts.MarkLineItem(y=min_y, name='0%'),
opts.MarkLineItem(y=star_up1, name='20%'),
opts.MarkLineItem(y=star_up2, name='40%'),
opts.MarkLineItem(y=star_up3, name='60%'),
opts.MarkLineItem(y=star_up4, name='80%'),
opts.MarkLineItem(y=max_y, name='100%'),
]),
)
line_html = line.render_embed('template.html', env)
return line_html