# model.add(SimpleRNN(32))
# model.add(Dense(4, activation='softmax'))
#
# model.compile(loss='categorical_crossentropy', optimizer='adadelta', metrics=['accuracy'])
if os.path.exists(cf.GENERAL_MODEL_NAME):
model = load_model(cf.GENERAL_MODEL_NAME)
return model
else:
return None
mongo_engine = MongoEngine()
list = mongo_engine.getAllData()
x_l, y_l, t_l, i_l = dd.list_data2train_data(list)
x_list = np.array(x_l)
y_list = np.array(y_l)
t_list = np.array(t_l)
i_list = np.array(i_l)
n_initial = 1000
idx = []
up_and_down_count = 0
not_order_count = 0
for i in range(len(y_list)):
if y_list[i] == 1 or y_list[i] == -1 or y_list[i] == 2:
up_and_down_count += 1
idx.append(i)
order_idx = idx
not_order_idx = []
plt.yticks()
plt.title(self.instrumentID)
plt.xlabel("time")
plt.ylabel("price")
self.draw_button_up(self.up_buttion)
self.draw_button_down(self.down_buttion)
self.draw_button_damped(self.damped_buttion)
self.draw_button_not_order(self.not_order_buttion)
# fig.set_facecolor('green')
# mpf.index_bar(ax,data_list)
mpf.candlestick_ohlc(ax,
self.data_list,
width=0.8,
colorup='r',
colordown='b')
plt.grid()
plt.show()
if __name__ == '__main__':
a = {'instrumentID': 'ag1812'}
mongo_engine = MongoEngine()
list = mongo_engine.findLast(a, cf.ROW_LENGTH)
x_list, y_list, t_list, i_list = dd.list_data2train_data(list)
data = (x_list[0], y_list[0], t_list[0], i_list[0])
histogram = Histogram(data)
histogram.createImage()