# 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()