def draw_fig(self,datafile,start,save=0):
data = self.close_price
ma5 = []
for i in range(3):
ma5.append(0)
#
for i in range(3,len(data)):
mean_5 = np.mean(data[i-2:i+1])
ma5.append(mean_5)
#
#
data = ma5
data = self.close_price
my_emd = one_dimension_emd(data)
(imf, residual) = my_emd.emd(0.01,0.01)
imf = imf[2]
imf_buy_value = [imf[i] for i in self.buy_x_index]
imf_sell_value = [imf[i] for i in self.sell_x_index]
buy_x = [i-start for i in self.buy_x_index]
sell_x = [i-start for i in self.sell_x_index]
data1 = data
data = self.close_price
plt.figure(1)
plt.subplot(311).axis([start,len(data),min(data[start:]),max(data[start:])])
plt.plot([i for i in range(len(data))],data,'o',[i for i in range(len(data))],data,'b',self.buy_x_index,self.buy_y_index,'r*',self.sell_x_index,self.sell_y_index,'g*')
plt.subplot(312).axis([start,len(data),min(data1[start:]),max(data1[start:])])
plt.plot([i for i in range(len(data1))],data1,'o',[i for i in range(len(data1))],data1,'b')
plt.subplot(313).axis([start,len(imf),min(imf[start:]),max(imf[start:])])
plt.plot([i for i in range(len(imf))],imf,'o',[i for i in range(len(imf))],imf,'b',self.buy_x_index,imf_buy_value,'r*',self.sell_x_index,imf_sell_value,'g*')
#####
#####
asset_list=[]
x_spline_asset=[]
for i in range(1,len(self.total_asset_list)):
if abs(self.total_asset_list[i]-self.total_asset_list[i-1])>10:
x_spline_asset.append(i)
asset_list.append(self.total_asset_list[i])
spline_asset = linerestruct(x_spline_asset,asset_list)
plt.figure(2)
plt.plot([i for i in range(len(self.total_asset_list))],self.total_asset_list,'b',x_spline_asset,spline_asset,'r')
plt.show()
def profit_smooth(data):
x=[]
y=[]
for i in range(1,len(data)):
if abs(data[i]-data[i-1])>10:
x.append(i)
y.append(data[i])
yy = linerestruct(x,y)
cha= []
for i in range(len(y)):
cha.append((y[i]-yy[i])*(y[i]-yy[i]))
print "rss %s"%sum(cha)
print "increase %s"%((yy[-1]-yy[0])/(x[-1]-x[0]))
def draw_fig(self, datafile, start, save=0):
data = self.close_price
ma5 = []
for i in range(3):
ma5.append(0)
#
for i in range(3, len(data)):
mean_5 = np.mean(data[i - 2:i + 1])
ma5.append(mean_5)
#
#
data = ma5
#ma5 = []
#for i in range(3):
# ma5.append(0)
#
#for i in range(3,len(data)):
# mean_5 = np.mean(data[i-2:i+1])
# ma5.append(mean_5)
#
data = ma5
data = self.close_price
my_emd = one_dimension_emd(data)
(imf, residual) = my_emd.emd(0.01, 0.01)
imf = imf[2]
imf_buy_value = [imf[i] for i in self.buy_x_index]
imf_sell_value = [imf[i] for i in self.sell_x_index]
buy_x = [i - start for i in self.buy_x_index]
sell_x = [i - start for i in self.sell_x_index]
data1 = data
data = self.close_price
plt.figure(1)
plt.subplot(311).axis(
[start, len(data),
min(data[start:]),
max(data[start:])])
plt.plot([i for i in range(len(data))], data, 'o',
[i for i in range(len(data))], data, 'b', self.buy_x_index,
self.buy_y_index, 'r*', self.sell_x_index, self.sell_y_index,
'g*')
plt.subplot(312).axis(
[start, len(data),
min(data1[start:]),
max(data1[start:])])
plt.plot([i for i in range(len(data1))], data1, 'o',
[i for i in range(len(data1))], data1, 'b')
plt.subplot(313).axis(
[start, len(imf),
min(imf[start:]),
max(imf[start:])])
plt.plot([i for i in range(len(imf))], imf, 'o',
[i for i in range(len(imf))], imf, 'b', self.buy_x_index,
imf_buy_value, 'r*', self.sell_x_index, imf_sell_value, 'g*')
#####
#####
asset_list = []
x_spline_asset = []
for i in range(1, len(self.total_asset_list)):
if abs(self.total_asset_list[i] -
self.total_asset_list[i - 1]) > 10:
x_spline_asset.append(i)
asset_list.append(self.total_asset_list[i])
spline_asset = linerestruct(x_spline_asset, asset_list)
plt.figure(2)
plt.plot([i for i in range(len(self.total_asset_list))],
self.total_asset_list, 'b', x_spline_asset, spline_asset, 'r')
plt.show()
