forked from moonnejs/PythonLab
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathvisFunction.py
More file actions
158 lines (143 loc) · 5.71 KB
/
visFunction.py
File metadata and controls
158 lines (143 loc) · 5.71 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
# encoding: UTF-8
"""
包含一些CTA因子的可视化函数
"""
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib
matplotlib.use('Qt4Agg')
#import matplotlib as mpl
#mpl.rcParams["font.sans-serif"] = ["Microsoft YaHei"]#
#mpl.rcParams['axes.unicode_minus'] = False
import matplotlib.pyplot as plt
from calcFunction import get_capital_np,calcPerf,formatNumber
#----------------------------------------------------------------------
def showBtResult(d):
"""
显示回测结果
"""
name = d.get('name')
timeList = d['timeList']
pnlList = d['pnlList']
capitalList = d['capitalList']
drawdownList = d['drawdownList']
print(u'显示回测结果')
# 输出
if len(timeList)>0:
print('-' * 30)
print(u'第一笔交易：\t%s' % d['timeList'][0])
print(u'最后一笔交易：\t%s' % d['timeList'][-1])
print(u'总交易次数：\t%s' % formatNumber(d['totalResult']))
print(u'总盈亏：\t%s' % formatNumber(d['capital']))
print(u'最大回撤: \t%s' % formatNumber(min(d['drawdownList'])))
print(u'平均每笔盈亏：\t%s' %formatNumber(d['capital']/d['totalResult']))
print(u'平均每笔佣金：\t%s' %formatNumber(d['totalCommission']/d['totalResult']))
print(u'胜率\t\t%s%%' %formatNumber(d['winningRate']))
print(u'平均每笔盈利\t%s' %formatNumber(d['averageWinning']))
print(u'平均每笔亏损\t%s' %formatNumber(d['averageLosing']))
print(u'盈亏比：\t%s' %formatNumber(d['profitLossRatio']))
print(u'显示回测结果')
# 绘图
import matplotlib.pyplot as plt
from matplotlib.dates import AutoDateLocator, DateFormatter
autodates = AutoDateLocator()
yearsFmt = DateFormatter('%m-%d')
pCapital = plt.subplot(3, 1, 1)
pCapital.set_ylabel("capital")
pCapital.plot(timeList,capitalList)
plt.gcf().autofmt_xdate() #设置x轴时间外观
plt.gcf().subplots_adjust(bottom=0.1)
plt.gca().xaxis.set_major_locator(autodates) #设置时间间隔
plt.gca().xaxis.set_major_formatter(yearsFmt) #设置时间显示格式
pDD = plt.subplot(3, 1, 2)
pDD.set_ylabel("dd")
pDD.bar(range(len(drawdownList)), drawdownList)
pPnl = plt.subplot(3, 1, 3)
pPnl.set_ylabel("pnl")
pPnl.hist(pnlList, bins=20)
plt.subplots_adjust(bottom=0.05,hspace=0.3)
plt.show()
#----------------------------------------------------------------------
def plotSigCaps(timeList,signals,markets,climit=4,wlimit=2,size=1,rate=0.0001,op=True):
"""
打印某一个信号的资金曲线
"""
plt.close()
pnls,poss,fees = get_capital_np(markets,signals,size,rate,\
climit=climit, wlimit=wlimit,op=op)
d = calcPerf(timeList,pnls,fees)
showBtResult(d)
#----------------------------------------------------------------------
def plotFactors(datas,factors=None):
"""打印因子数据到一张图上"""
plt.close()
factors = datas.columns.tolist() if factors is None else factors
if 'pnl' in factors:
factors.remove('pnl')
sns.pairplot(datas, vars=factors, hue="pnl", size=1.5)
plt.show()
#----------------------------------------------------------------------
def plotSigHeats(signals,markets,start=0,step=2,size=1,iters=6):
"""
打印信号回测盈损热度图,寻找参数稳定岛
"""
sigMat = pd.DataFrame(index=range(iters),columns=range(iters))
for i in range(iters):
for j in range(iters):
climit = start + i*step
wlimit = start + j*step
pnls,poss,fees = get_capital_np(markets,signals,size,0.0001,climit=climit,wlimit=wlimit,op=False)
caps = np.cumsum(pnls[pnls!=0])
sigMat[i][j] = caps[-1]
#ratioDict = {}
#for i in range(iters):
# for j in range(iters):
# climit = start + i*step
# wlimit = start + j*step
# ratio = wlimit/climit
# if ratio in ratioDict:
# ratioDict[ratio] += sigMat[i][j]
# else:
# ratioDict[ratio] = sigMat[i][j]
#ratioList = []
#capList = []
#ratioDict0 = sorted(ratioDict.iteritems(),key=lambda d:d[0])
#for k,v in ratioDict0:
# ratioList.append(k)
# capList.append(v)
#plt.plot(ratioList,capList)
#plt.xlabel(u'盈亏比')
#plt.ylabel(u'盈利')
sns.heatmap(sigMat.values.astype(np.float64),annot=True,fmt='.2f',annot_kws={"weight": "bold"})
xTicks = [i+0.5 for i in range(iters)]
yTicks = [iters-i-0.5 for i in range(iters)]
xyLabels = [str(start+i*step) for i in range(iters)]
_, labels = plt.yticks(yTicks,xyLabels)
plt.setp(labels, rotation=0)
_, labels = plt.xticks(xTicks,xyLabels)
plt.setp(labels, rotation=90)
plt.xlabel('LossStop @')
plt.ylabel('ProfitTarget @')
return sigMat
#----------------------------------------------------------------------
def plotVarVPnl(pdData,s):
"""
展示策略状态的10分位盈亏
"""
data = pdData.copy()
minV = min(data[s])
maxV = max(data[s])
data[s+'_split'] = data[s].apply(lambda x:round(x*10/(maxV-minV))*(maxV-minV)/10)
data.groupby(s+'_split').pnl.sum().plot(kind='bar')
plt.show()
#------------------------------------------------
def plotPortfolioCurve(cap_table,weis):
"""输出策略组合的资金曲线"""
plt.close()
names = weis.index.tolist()
cap_table['tol']=1
for n in names:
cap_table['tol'] += cap_table[n]*weis['weight'][n]
cap_table['tol'].plot()
plt.show()