def DrawClosesAndVolumes(pl, closes, volumes, zz=None, avg=None, trade_index=None,\
title=None, closes_dp=None, closes_bankuai=None):
"""画closes，非df模式，
closes_dp: 大盘
closes_bankuai: 板块
"""
legend = []
pl.figure
pl.subplot(211)
if title != None:
pl.title(title, fontproperties=getFont())
pl.plot(closes)
legend.append('close')
if zz is not None:
DrawZZ(pl, zz, c='r')
if avg is not None:
pl.plot(avg)
if not agl.IsNone(closes_dp):
pl.plot(closes_dp)
legend.append('dapan')
if not agl.IsNone(closes_bankuai):
pl.plot(closes_bankuai)
legend.append('bankuai')
if trade_index != None:
pl, index, ts = pl, trade_index, closes
_DrawVLine(pl, index, ts)
pl.legend(legend, loc='upper left')
pl.subplot(212)
pl.plot(volumes)
pl.show()
pl.close()
def drawKline(pl,
df_code,
df_dp=None,
df_bk=None,
title=None,
df_syl=None,
legend2=None):
"""画个股k线图
pl: 自定义pl
df_code: 个股pd.DataFrame, ['holcv']
df_dp: 大盘
df_bk: 板块
df_syl: 历史市盈率
legend2: 标识, 不支持中文
"""
if 0: pl = plt
pl.figure
pl.subplot(211)
if title != None:
pl.title(title, fontproperties=getFont())
#画个股数据
df = copy.deepcopy(df_code)
df['c'] = df['c'] / max(df['c'])
df['v'] = df['v'] / max(df['v'])
df['c'].plot()
df2 = df['v']
legend = ['close']
if not isinstance(df_dp, type(None)) and len(df_dp) > 0:
df = copy.deepcopy(df_dp)
if isinstance(df, pd.Series):
df.plot()
else:
df['c'] = df['c'] / max(df['c'])
#df['v'] = df['v'] / max(df['v'])
df['c'].plot()
legend.append('dapan')
#df['v'].plot()
if not agl.IsNone(df_bk):
df_bk.plot()
legend.append('bankuai')
pl.legend(legend, loc='upper left')
pl.subplot(212)
df2.plot()
legend = ['volumns']
if not isinstance(df_syl, type(None)) and len(df_syl) > 0:
df = copy.deepcopy(df_syl)
#df['市盈率'] = df['市盈率'] / max(df['市盈率'])
#df['每股收益'] = df['每股收益'] / max(df['每股收益'])
##df['市盈率'].plot()
#df['每股收益'].plot()
#legend.append('mgsy')
df.plot()
legend.append('jll')
if legend2 is not None:
legend = legend2
pl.legend(legend, loc='upper left')
pl.show()
pl.close()
def is_dirty(self):
#return True
key = 'dirty'
key = self._genKey(key)
o = myredis.get_obj(key)
if agl.IsNone(o):
self.setDirty(True)
return True
return o
def get_obj(key):
"""用key取值 return: obj 或者 None"""
r = createRedis()
s = r.get(key)
if agl.IsNone(s):
return s
f = cStringIO.StringIO(s)
o = cPickle.load(f)
f.close()
return o
def TradeResult_Boll(code, bars, trade_positions, zhijin, changwei):
import backtest
signals = pd.DataFrame(index=bars.index)
signals['signal'] = 0.0
#signals['short_ma'] = stock.MA(closes=np.array(bars['c']), day=5)
#signals['long_ma'] = stock.MA(closes=np.array(bars['c']), day=20)
#signals['0'] = signals['short_ma']
#signals['1'] = signals['long_ma']
signals['signal'] = np.zeros(len(bars['c']))
if agl.IsNone(trade_positions):
signals['positions'] = signals['signal'].diff()
signals['positions'][10] = 1
signals['positions'][13] = 1
signals['positions'][20] = -1
else:
signals['positions'] = trade_positions
ShowTradeResult2(pl, bars, signals, zhijin, changwei, 0)
def TradeResult_Boll(pl, bars, trade_positions, zhijin,changwei, title=''):
"""显示策略结果
bars: df 包含有 c字段即可
trade_positions: np.darray or df 交易信号
zhijin: df index同bars
changwei: df index同bars
title: str 中文需要使用decode(utf8)
"""
signals = pd.DataFrame(index=bars.index)
signals['signal'] = 0.0
signals['signal'] = np.zeros(len(bars['c']))
if agl.IsNone(trade_positions):
signals['positions'] = signals['signal'].diff()
signals['positions'][10] = 1
signals['positions'][13] = 1
signals['positions'][20] = -1
else:
signals['positions'] = trade_positions
ShowTradeResult2(pl, bars, signals, zhijin,changwei , 0, title=title)
def drawKline(df, df_trades=None):
"""画k线图, 异步模式
需要注意的是如果df比较大的话，那么速度是相当的慢, 一般5日线10天的数据较好
df : 日线或5分钟线, cols('ohlcv')
df_trades : 交易点, 需要包含字段cols('trade_bSell', ['trade_price']), 见enum, []意思为不是必须
"""
def df_to_matplotformat(df):
"""
return: list[turpl(t,o,h,l,c)]
"""
data_list = []
for dates, row in df.iterrows():
# 将时间转换为数字
#date_time = datetime.datetime.strptime(dates,'%Y-%m-%d')
t = date2num(dates)
open, high, low, close = row[:4]
datas = (t, open, high, low, close)
data_list.append(datas)
return data_list
quotes = df_to_matplotformat(df)
plt.cla()
# 创建一个子图
#fig, ax = plt.subplots(facecolor=(0.5, 0.5, 0.5))
#fig.subplots_adjust(bottom=0.2)
ax = plt.gca()
if 0: ax = matplotlib.axes.Axes(fig, rect)
plt.subplots_adjust(bottom=0.2)
## 设置X轴刻度为日期时间
#ax.xaxis_date()
## X轴刻度文字倾斜45度
#plt.xticks(rotation=45)
#plt.title("code")
#plt.xlabel("time")
#plt.ylabel("price")
#mpf.candlestick_ohlc(ax,quotes,width=.001,colorup='r',colordown='green')
#调整下面日期显示的密度
freq = len(quotes) / 20
weekday_candlestick(quotes,
ax,
fmt='%b %d %H:%M',
freq=freq,
width=0.01,
colorup='r',
colordown='green')
#plt.grid(True)
#画交易点
if not agl.IsNone(df_trades):
if 0: df_trades = pd.DataFrame()
for index, row in df_trades.iterrows():
if AsynDrawKline.enum.trade_price in row.keys():
price = row[AsynDrawKline.enum.trade_price]
else:
price = row['c']
#交易点
trade_position = []
a = np.zeros(len(quotes))
a[:] = price
index = len(df[:index])
a[:index] = np.nan
bSell = int(row[AsynDrawKline.enum.trade_bSell])
clr = agl.where(bSell, 'g', 'r')
plt.plot(a, color=clr, linewidth=0.25)
plt.text(len(quotes), price, str(price), color=clr)
#左右两边都有坐标
#ax.yaxis.set_ticks_position('both')
#plt.tick_params(axis='y', which='both', labelleft='on', labelright='on')
plt.draw()
plt.pause(0.1)
def ExePolicy(self, code):
code = agl.unicode_to_utf8(code)
live_data = LiveData()
df_hisdat = live_data.getHisdat(code)
df_fenshi = live_data.getFenshi(code)
df_five_hisdat = live_data.getFiveMinHisdat(code)
if agl.IsNone(df_five_hisdat):
#print code ,'没有5分钟'
return
if len(df_fenshi) == 0:
return
if len(df_five_hisdat) < 30:
return
price = float(agl.FloatToStr(float(df_fenshi.tail(1)['p'])))
yclose = df_hisdat.ix[df_hisdat.index[-1]]['c']
zhangfu = stock.ZhangFu(price, yclose)
rsi = stock.RSI(df_five_hisdat['c'])
#ui.DrawClosesAndVolumes(pl, df_five_hisdat['c'], rsi)
upper, middle, lower = stock.TDX_BOLL(df_five_hisdat['c'])
#ui.DrawTs(pl, df_five_hisdat['c'],mid=middle, high=upper, low=lower)
highs, lows, closes = df_five_hisdat['h'], df_five_hisdat[
'l'], df_five_hisdat['c']
#atr = stock.ATR(highs, lows, closes)
adx = stock.TDX_ADX(highs, lows, closes)
closes = np.array(df_hisdat['c'])
if help.MyDate(agl.datetime_to_date(df_hisdat.index[-1])).d < \
help.MyDate(agl.CurDay()).d:
closes = agl.array_insert(closes, len(closes), price)
four = stock.FOUR(closes)
#print code, four[-1]
self._dict_four[code] = four[-1]
#return
#ui.DrawClosesAndVolumes(pl, df_five_hisdat['c'], adx)
boll_up = (price - upper[-1]) / upper[-1]
boll_mid = (price - middle[-1]) / middle[-1]
boll_down = (lower[-1] - price) / lower[-1]
boll_width = upper[-1] - lower[-1]
if abs(zhangfu) > 0.098 or boll_width < 0.01:
return
if code == '300033':
codename = stock.GetCodeName(code)
s = 'rsi = %d %s %s' % (rsi[-1], codename, str(price))
print s
if (rsi[-1] > 65 or rsi[-1] < 35) and adx[-1] > 60:
codename = stock.GetCodeName(code)
s = '%s %s' % (codename, str(price))
sign = False
#if code in ['300033','510050']:
#sign = True
#if adx[-1] > 55:
#s += ' ADX=%d'%(adx[-1])
#sign = True
if boll_up > -0.003:
s += ' 越过布林上轨'
#sign = True
if abs(boll_mid) < 0.003:
s += ' 布林中轨'
#sign = True
if boll_down > -0.003:
s += ' 越过布林下轨'
sign = True
if four[-1] > 0.1:
sign = False
#sign = False
if sign:
#ui.DrawTs(pl, df_five_hisdat['c'],mid=middle, high=upper, low=lower)
sInfo = self.calcInfo(code, price, zhangfu)
help.myprint(s, sInfo)
help.myprint(
'[%s,%s] %.3f,%.3f,%.3f,%.2f, four=%.2f, adx=%.2f' %
(code, stock.GetCodeName(code), boll_up, boll_mid,
boll_down, boll_width, four[-1], adx[-1]))
self.NotifyAutoxdShow(code)
self.Speak(s)
