def boll():
#??tushare??????
df=ts.get_k_data('300580',start='2017-01-12',end='2017-05-26')
#?????
closed=df['close'].values
upper,middle,lower=talib.BBANDS(closed,matype=talib.MA_Type.SMA)
print upper,middle,lower
plt.plot(upper)
plt.plot(middle)
plt.plot(lower)
plt.grid()
plt.show()
diff1=upper-middle
diff2=middle-lower
print diff1
print diff2
python类BBANDS的实例源码
def BOLL_CN(close,timeperiod=20, nbdev=2, isDEV=False):
stddev = nbdev
if not isDEV:
devfix = np.sqrt(1.0*timeperiod/(timeperiod-1))
stddev = nbdev * devfix
bollUPPER, bollMIDDLE, bollLOWER = tl.BBANDS(
#close narray
close,
#time default 20
timeperiod=timeperiod,
# number of non-biased standard deviations from the mean
nbdevup=stddev,
nbdevdn=stddev,
# Moving average type: simple moving average here
matype=0)
return bollUPPER, bollMIDDLE, bollLOWER
#WR%
def Bollinger_Bands(security_list, timeperiod=5, nbdevup=2, nbdevdn=2):
# ????????????
if isinstance(security_list, str):
security_list = [security_list]
# ?? Bollinger Bands
security_data = history(timeperiod * 2, '1d', 'close',
security_list, df=False, skip_paused=True)
upperband = {}
middleband = {}
lowerband = {}
for stock in security_list:
upperband[stock], middleband[stock], lowerband[stock] = talib.BBANDS(
security_data[stock], timeperiod, nbdevup, nbdevdn)
return upperband, middleband, lowerband
# ?????
def __recountBoll(self):
"""????"""
if self.inputBollLen < EMPTY_INT: return
l = len(self.lineBar)
if l < min(7, self.inputBollLen)+1:
self.debugCtaLog(u'?????,??Bar?????{0}???Boll???{1}'.
format(len(self.lineBar), min(7, self.inputBollLen)+1))
return
if l < self.inputBollLen+2:
bollLen = l-1
else:
bollLen = self.inputBollLen
# ????????Bar
listClose=[x.close for x in self.lineBar[-bollLen - 1:-1]]
#
upper, middle, lower = ta.BBANDS(numpy.array(listClose, dtype=float),
timeperiod=bollLen, nbdevup=self.inputBollStdRate,
nbdevdn=self.inputBollStdRate, matype=0)
self.lineUpperBand.append(upper[-1])
self.lineMiddleBand.append(middle[-1])
self.lineLowerBand.append(lower[-1])
# ----------------------------------------------------------------------
def cycle_process(event):
print(event.widget.get())
cycle = event.widget.get()
upperband, middleband, lowerband = ta.BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
fig, axes = plt.subplots(2, 1, sharex=True)
ax1, ax2 = axes[0], axes[1]
axes[0].plot(close, 'rd-', markersize=3)
axes[0].plot(upperband, 'y-')
axes[0].plot(middleband, 'b-')
axes[0].plot(lowerband, 'y-')
axes[0].set_title(cycle, fontproperties="SimHei")
if cycle == '??????——???????':
real = ta.HT_DCPERIOD(close)
axes[1].plot(real, 'r-')
elif cycle == '??????,??????????':
real = ta.HT_DCPHASE(close)
axes[1].plot(real, 'r-')
elif cycle == '??????——????':
inphase, quadrature = ta.HT_PHASOR(close)
axes[1].plot(inphase, 'r-')
axes[1].plot(quadrature, 'g-')
elif cycle == '??????——????':
sine, leadsine = ta.HT_SINE(close)
axes[1].plot(sine, 'r-')
axes[1].plot(leadsine, 'g-')
elif cycle == '??????——???????':
integer = ta.HT_TRENDMODE(close)
axes[1].plot(integer, 'r-')
plt.show()
# ????
def statistic_process(event):
print(event.widget.get())
statistic = event.widget.get()
upperband, middleband, lowerband = ta.BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
fig, axes = plt.subplots(2, 1, sharex=True)
ax1, ax2 = axes[0], axes[1]
axes[0].plot(close, 'rd-', markersize=3)
axes[0].plot(upperband, 'y-')
axes[0].plot(middleband, 'b-')
axes[0].plot(lowerband, 'y-')
axes[0].set_title(statistic, fontproperties="SimHei")
if statistic == '????':
real = ta.LINEARREG(close, timeperiod=14)
axes[1].plot(real, 'r-')
elif statistic == '??????':
real = ta.LINEARREG_ANGLE(close, timeperiod=14)
axes[1].plot(real, 'r-')
elif statistic == '??????':
real = ta.LINEARREG_INTERCEPT(close, timeperiod=14)
axes[1].plot(real, 'r-')
elif statistic == '??????':
real = ta.LINEARREG_SLOPE(close, timeperiod=14)
axes[1].plot(real, 'r-')
elif statistic == '???':
real = ta.STDDEV(close, timeperiod=5, nbdev=1)
axes[1].plot(real, 'r-')
elif statistic == '??????':
real = ta.TSF(close, timeperiod=14)
axes[1].plot(real, 'r-')
elif statistic == '??':
real = ta.VAR(close, timeperiod=5, nbdev=1)
axes[1].plot(real, 'r-')
plt.show()
# ????
def math_operator_process(event):
print(event.widget.get())
math_operator = event.widget.get()
upperband, middleband, lowerband = ta.BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
fig, axes = plt.subplots(2, 1, sharex=True)
ax1, ax2 = axes[0], axes[1]
axes[0].plot(close, 'rd-', markersize=3)
axes[0].plot(upperband, 'y-')
axes[0].plot(middleband, 'b-')
axes[0].plot(lowerband, 'y-')
axes[0].set_title(math_operator, fontproperties="SimHei")
if math_operator == '?????????':
real = ta.MAX(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif math_operator == '????????????':
integer = ta.MAXINDEX(close, timeperiod=30)
axes[1].plot(integer, 'r-')
elif math_operator == '?????????':
real = ta.MIN(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif math_operator == '????????????':
integer = ta.MININDEX(close, timeperiod=30)
axes[1].plot(integer, 'r-')
elif math_operator == '????????????':
min, max = ta.MINMAX(close, timeperiod=30)
axes[1].plot(min, 'r-')
axes[1].plot(max, 'r-')
elif math_operator == '???????????????':
minidx, maxidx = ta.MINMAXINDEX(close, timeperiod=30)
axes[1].plot(minidx, 'r-')
axes[1].plot(maxidx, 'r-')
elif math_operator == '??':
real = ta.SUM(close, timeperiod=30)
axes[1].plot(real, 'r-')
plt.show()
def expected_bbands(self, window_length, k, closes):
"""Compute the expected data (without adjustments) for the given
window, k, and closes array.
This uses talib.BBANDS to generate the expected data.
"""
lower_cols = []
middle_cols = []
upper_cols = []
ndates, nassets = closes.shape
for n in range(nassets):
close_col = closes[:, n]
if np.isnan(close_col).all():
# ta-lib doesn't deal well with all nans.
upper, middle, lower = [np.full(ndates, np.nan)] * 3
else:
upper, middle, lower = talib.BBANDS(
close_col,
window_length,
k,
k,
)
upper_cols.append(upper)
middle_cols.append(middle)
lower_cols.append(lower)
# Stack all of our uppers, middles, lowers into three 2d arrays
# whose columns are the sids. After that, slice off only the
# rows we care about.
where = np.s_[window_length - 1:]
uppers = np.column_stack(upper_cols)[where]
middles = np.column_stack(middle_cols)[where]
lowers = np.column_stack(lower_cols)[where]
return uppers, middles, lowers
def add_BBANDS(self, timeperiod=20, nbdevup=2, nbdevdn=2, matype=0,
types=['line_dashed_thin', 'line_dashed_thin'],
colors=['tertiary', 'grey_strong'], **kwargs):
"""Bollinger Bands.
Note that the first argument of types and colors refers to upper and lower
bands while second argument refers to middle band. (Upper and lower are
symmetrical arguments, hence only 2 needed.)
"""
if not self.has_close:
raise Exception()
utils.kwargs_check(kwargs, VALID_TA_KWARGS)
if 'kind' in kwargs:
kwargs['type'] = kwargs['kind']
if 'kinds' in kwargs:
types = kwargs['type']
if 'type' in kwargs:
types = [kwargs['type']] * 2
if 'color' in kwargs:
colors = [kwargs['color']] * 2
name = 'BBANDS({},{},{})'.format(str(timeperiod),
str(nbdevup),
str(nbdevdn))
ubb = name + '[Upper]'
bb = name
lbb = name + '[Lower]'
self.pri[ubb] = dict(type='line_' + types[0][5:],
color=colors[0])
self.pri[bb] = dict(type='area_' + types[1][5:],
color=colors[1], fillcolor='fill')
self.pri[lbb] = dict(type='area_' + types[0][5:],
color=colors[0], fillcolor='fill')
(self.ind[ubb],
self.ind[bb],
self.ind[lbb]) = talib.BBANDS(self.df[self.cl].values,
timeperiod, nbdevup, nbdevdn, matype)
def _boll(self, data, n):
""" ??????????? """
data = transform2ndarray(data)
upper, middle, lower = talib.BBANDS(data, n, 2, 2)
return (upper, middle, lower)
def calculate_bbands(self, period_name, close):
timeperiod = 20
upperband_1, middleband_1, lowerband_1 = talib.BBANDS(close, timeperiod=timeperiod, nbdevup=1, nbdevdn=1, matype=0)
self.current_indicators[period_name]['bband_upper_1'] = upperband_1[-1]
self.current_indicators[period_name]['bband_lower_1'] = lowerband_1[-1]
upperband_2, middleband_2, lowerband_2 = talib.BBANDS(close, timeperiod=timeperiod, nbdevup=2, nbdevdn=2, matype=0)
self.current_indicators[period_name]['bband_upper_2'] = upperband_2[-1]
self.current_indicators[period_name]['bband_lower_2'] = lowerband_2[-1]
def BOLL(closes, matype=MA_Type.EMA):
"""???
matype: ???????? ????????????? EMA??2??SMA?4?????????
return upper, middle, lower"""
closes = np.array(closes)
return talib.BBANDS(closes, timeperiod=20, matype=matype)
def bbands(df):
if len(df) > 100:
close = df.close.values
upperband, middleband, lowerband = tl.BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
return upperband, middleband, lowerband
def get_bbands_info(df):
"""
calculate bbands quotation.
:param df:
:return: close, upperband, middleband, lowerband
"""
close = get_close_data(df)
upperband, middleband, lowerband = ta.BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
return pd.DataFrame({u'close': df.close[-view_days:],
u'upperband': upperband[-view_days:],
u'middleband': middleband[-view_days:],
u'lowerband': lowerband[-view_days:]})
def get_bbands(sorted_data):
close,high,low,ma5,ma10,ma20 = get_case_data(sorted_data)
upperband, middleband, lowerband = ta.BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
#??%b???????????
operator = ''
# score = 0
index_b = (close[-1]-lowerband[-1]) / (upperband[-1]-lowerband[-1])
# print "%b is : " + str(index_b)
if index_b > 1:
operator += 'S%'
# score -= 10
elif index_b <= 0 :
operator += 'B%'
# score += 10
#??????????????
up = upperband[-1] - upperband[-2]
down = lowerband[-2] -lowerband[-1]
if up > 0 and down > 0:
if up > down:
operator += 'BO'
elif up < down:
operator += 'SO'
if ma5[-1] > ma10[-1] and ma10[-1] > ma20[-1]:
if upperband[-1] < upperband[-2]:
operator += 'S!'
return (operator,index_b)
#initial the date
def overlap_process(event):
print(event.widget.get())
overlap = event.widget.get()
upperband, middleband, lowerband = ta.BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
fig, axes = plt.subplots(2, 1, sharex=True)
ax1, ax2 = axes[0], axes[1]
axes[0].plot(close, 'rd-', markersize=3)
axes[0].plot(upperband, 'y-')
axes[0].plot(middleband, 'b-')
axes[0].plot(lowerband, 'y-')
axes[0].set_title(overlap, fontproperties="SimHei")
if overlap == u'???':
pass
elif overlap == u'????????':
real = ta.DEMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'??????? ':
real = ta.EMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'??????——?????':
real = ta.HT_TRENDLINE(close)
axes[1].plot(real, 'r-')
elif overlap == u'???????????':
real = ta.KAMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'?????':
real = ta.MA(close, timeperiod=30, matype=0)
axes[1].plot(real, 'r-')
elif overlap == u'MESA???????':
mama, fama = ta.MAMA(close, fastlimit=0, slowlimit=0)
axes[1].plot(mama, 'r-')
axes[1].plot(fama, 'g-')
elif overlap == u'????????':
real = ta.MAVP(close, periods, minperiod=2, maxperiod=30, matype=0)
axes[1].plot(real, 'r-')
elif overlap == u'???????':
real = ta.SMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'????????(T3)':
real = ta.T3(close, timeperiod=5, vfactor=0)
axes[1].plot(real, 'r-')
elif overlap == u'????????':
real = ta.TEMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'?????? ':
real = ta.TRIMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'???????':
real = ta.WMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
plt.show()
# ????
