def cpeaks(cdf,sidx,linecords):
cpeak_out = []
maxtab, mintab = peakdet(cdf[-sidx:],1)
cxrange = np.arange(len(cdf) - sidx,len(cdf))
lst_regression = []
for cor in linecords:
regression = basic_linear_regression(cor[0],cor[1])
lst_regression.append(regression)
if maxtab.any() or mintab.any():
for m in enumerate(np.vstack((maxtab,mintab))):
m[1][0] = cxrange[m[1][0]]
for i,r in enumerate(lst_regression):
#new_y = r[1][0] * m[1][0] + r[1][1]
new_y = r[0] * m[1][0] + r[1]
#print (new_y - (new_y * 0.001)), m[1][1],(new_y + (new_y *
#0.001))
if (new_y - (new_y * 0.001)) <= m[1][1] <= (new_y + (new_y * 0.001)):
plt.scatter(m[1][0], m[1][1], color = 'green')
cpeak_out.append([m[1],linecords[i]])
#print cpeak_out
return cpeak_out
def run(self):
deltastop = 55
linecords = []
touch_down = []
percent_return = 0
for d in self.delta:
maxtab, mintab = peakdet(self.df['p'],d)
if len(maxtab) > 2 and len(mintab) > 2 :
#print 'delta stop -- {0}'.format(d)
deltastop = d
break
bothpeak = []
if len(maxtab) > 0 and len(mintab) > 0 :
if maxtab[0][1] > mintab[0][1]:
bothpeak = self.array_series(maxtab,mintab,-3)
else:
bothpeak = self.array_series(mintab,maxtab,-3)
if len(bothpeak) == 3:
rtn = self.gen_afp(bothpeak)
if rtn == 0:
rtn = self.gen_afp(bothpeak,Schiff = True)
if rtn <> 0:
self.is_Schiff = True
return rtn
return 0
def apf_draw(df,symbol):
pmin = df.p.min()
pmax = df.p.max()
formatter = MyFormatter(df.index)
touch_down = []
percent_return = 0
fig, ax = plt.subplots()
ax.xaxis.set_major_formatter(formatter)
ax.plot(np.arange(len(df)), df['p'])
#detect peak
# 1 1 2 3 5 8 13 21 34
maxtab = []
mintab = []
delta = [55,34,21,13,8,5,3,2,1]
#delta = [5,3,2,1]
deltastop = 55
for d in delta:
maxtab, mintab = peakdet(df['p'],d)
if len(maxtab) > 1 and len(mintab) > 1 :
print 'delta stop -- {0}'.format(d)
deltastop = d
break
#draw APF
if maxtab.any() and mintab.any():
#plot peak
plt.scatter(array(maxtab)[:,0], array(maxtab)[:,1], color = 'black')
plt.scatter(array(mintab)[:,0], array(mintab)[:,1], color='red')
sets = -3
if maxtab[0][1] > mintab[0][1]:
bothpeak = array_series(maxtab,mintab,sets)
else:
bothpeak = array_series(mintab,maxtab,sets)
for i,apoint in enumerate(bothpeak):
try:
if (i + 2) < len(bothpeak):
linecords = []
bpoint = bothpeak[i + 1]
cpoint = bothpeak[i + 2]
mnmidx = (cpoint[0] - bpoint[0]) / 2
mnmidy = (cpoint[1] - bpoint[1]) / 2
percent_return = 100 * ((bpoint[1] - cpoint[1]) / 2) / apoint[1]
plt.plot([bpoint[0],cpoint[0]],[bpoint[1],cpoint[1]],color='yellow')
mnpoint = [mnmidx + bpoint[0],mnmidy + bpoint[1]]
plt.plot(mnpoint[0],mnpoint[1],'om')
slope, intercept = np.polyfit([apoint[0],mnpoint[0]],[apoint[1],mnpoint[1]],1)
prdictY = slope * apoint[1] + intercept
plt.plot(apoint[1],prdictY,'om')
print slope, intercept
mnline = [[apoint[1],apoint[0]],[prdictY,apoint[1]]]
plt.plot(mnline[0],mnline[1],color='orange')
linecords.append(mnline)
plt.plot(apoint[1] - mnmidx,prdictY - mnmidy,'om')
bmnline = [[bpoint[0],apoint[1] - mnmidx],[bpoint[1],prdictY - mnmidy]]
plt.plot(bmnline[0],bmnline[1],color='blue')
linecords.append(bmnline)
plt.plot(apoint[1] + mnmidx,prdictY + mnmidy,'om')
cmnline = [[cpoint[0],apoint[1] + mnmidx],[cpoint[1],prdictY + mnmidy]]
plt.plot(cmnline[0],cmnline[1],color='purple')
linecords.append(cmnline)
mn2midx = (mnpoint[0] - bpoint[0]) / 2
mn2midy = (mnpoint[1] - bpoint[1]) / 2
plt.plot(mn2midx + bpoint[0],mn2midy + bpoint[1],'om')
plt.plot(mn2midx + mnpoint[0],mn2midy + mnpoint[1],'om')
mnbline = [[mn2midx + bpoint[0],apoint[1] - mn2midx],[mn2midy + bpoint[1],prdictY - mn2midy]]
plt.plot(mnbline[0],mnbline[1],'--',color='black')
linecords.append(mnbline)
mncline = [[mn2midx + mnpoint[0],apoint[1] + mn2midx],[mn2midy + mnpoint[1],prdictY + mn2midy]]
plt.plot(mncline[0],mncline[1],'--',color='black')
linecords.append(mncline)
plt.xlabel('slope:{0} intercept:{1} delta:{2} '.format(slope,intercept,deltastop))
#print cpoint
#touch_down = cpeaks(df['p'],int(len(df['p']) -
#cpoint[0]),linecords)
touch_down = cpeaks2(df['p'],int(len(df['p']) - cpoint[0]),linecords)
#print 'touch down',touch_down
#break
except Exception, e:
print e
def apf_draw(fn):
# fn = ".\\data\\lastweek\\HHM_20141219.csv"
# line_prepender(fn,"d,t,p,na")
df = pd.read_csv(fn, parse_dates={"Timestamp": ["d", "t"]}, index_col="Timestamp")
df = df.ix[1:, ["p"]]
# resample to 15 min
df = df.resample("20min", how="first")
# drop na
df = df.dropna()
# price min, max
pmin = df.p.min()
pmax = df.p.max()
formatter = MyFormatter(df.index)
fig, ax = plt.subplots()
ax.xaxis.set_major_formatter(formatter)
ax.plot(np.arange(len(df)), df.p)
# detect peak
# 1 1 2 3 5 8 13 21 34
maxtab = []
mintab = []
delta = [34, 21, 13, 8, 5, 3, 2, 1]
for d in delta:
maxtab, mintab = peakdet(df["p"], d)
if len(maxtab) > 1 and len(mintab) > 1:
print "delta stop -- {0}".format(d)
break
else:
print "min delta -- {0}".format(d)
# draw APF
if maxtab.any() and mintab.any():
# plot peak
plt.scatter(array(maxtab)[:, 0], array(maxtab)[:, 1], color="black")
plt.scatter(array(mintab)[:, 0], array(mintab)[:, 1], color="red")
sets = -3
if maxtab[0][1] > mintab[0][1]:
bothpeak = array_series(maxtab, mintab, sets)
else:
bothpeak = array_series(mintab, maxtab, sets)
for i, apoint in enumerate(bothpeak):
try:
if (i + 2) < len(bothpeak):
bpoint = bothpeak[i + 1]
cpoint = bothpeak[i + 2]
mnmidx = (cpoint[0] - bpoint[0]) / 2
mnmidy = (cpoint[1] - bpoint[1]) / 2
plt.plot([bpoint[0], cpoint[0]], [bpoint[1], cpoint[1]], color="yellow")
mnpoint = [mnmidx + bpoint[0], mnmidy + bpoint[1]]
mnline = [[apoint[0], mnpoint[0]], [apoint[1], mnpoint[1]]]
plt.plot(mnline[0], mnline[1], color="orange")
slope, intercept = np.polyfit(mnline[0], mnline[1], 1)
prdictY = slope * apoint[1] + intercept
plt.plot(apoint[1], prdictY, "om")
mnline = [[mnpoint[1], mnpoint[0]], [prdictY, mnpoint[1]]]
plt.plot(mnline[0], mnline[1], color="orange")
bmnline = [[bpoint[0], mnpoint[1] - mnmidx], [bpoint[1], prdictY - mnmidy]]
plt.plot(bmnline[0], bmnline[1], color="blue")
cmnline = [[cpoint[0], mnpoint[1] + mnmidx], [cpoint[1], prdictY + mnmidy]]
plt.plot(cmnline[0], cmnline[1], color="purple")
mn2midx = (mnpoint[0] - bpoint[0]) / 2
mn2midy = (mnpoint[1] - bpoint[1]) / 2
plt.plot(mn2midx + bpoint[0], mn2midy + bpoint[1], "om")
plt.plot(mn2midx + mnpoint[0], mn2midy + mnpoint[1], "om")
mnbline = [[mn2midx + bpoint[0], mnpoint[1] - mn2midx], [mn2midy + bpoint[1], prdictY - mn2midy]]
plt.plot(mnbline[0], mnbline[1], "--", color="black")
mncline = [[mn2midx + mnpoint[0], mnpoint[1] + mn2midx], [mn2midy + mnpoint[1], prdictY + mn2midy]]
plt.plot(mncline[0], mncline[1], "--", color="black")
break
except Exception, e:
print e
