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Newnius 2020-05-01 18:13:06 +08:00
parent 7cd43511ac
commit 557ee80026
2 changed files with 31 additions and 23 deletions
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23
.idea/workspace.xml
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@ -375,11 +376,11 @@
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31
serve.py
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@ -142,28 +142,35 @@ def draw_yqy(config, origin_data, predict_norm_data, mean_yqy, std_yqy):
assert label_norm_data.shape[0] == predict_norm_data.shape[ assert label_norm_data.shape[0] == predict_norm_data.shape[
0], "The element number in origin and predicted data is different" 0], "The element number in origin and predicted data is different"
print("dasdsadsadas")
# label_norm_data=label_norm_data[:,1] # label_norm_data=label_norm_data[:,1]
label_name = 'high' label_names = ['pre', 'main', 'post']
label_column_num = 1 label_column_num = 1
loss = \ loss1 = \
np.mean((label_norm_data[config.predict_day:][:, 1] - predict_norm_data[:-config.predict_day][0:]) ** 2, np.mean((label_norm_data[config.predict_day:][:, 5] - predict_norm_data[:-config.predict_day][0:]) ** 2,
axis=0)[1] axis=0)[5]
print("The mean squared error of stock {} is ".format(label_name), loss) loss2 = \
np.mean((label_norm_data[config.predict_day:][:, 6] - predict_norm_data[:-config.predict_day][0:]) ** 2,
axis=0)[6]
loss3 = \
np.mean((label_norm_data[config.predict_day:][:, 7] - predict_norm_data[:-config.predict_day][0:]) ** 2,
axis=0)[7]
print("The mean squared error of stock {} is ".format(label_names[0]), loss1)
print("The mean squared error of stock {} is ".format(label_names[1]), loss2)
print("The mean squared error of stock {} is ".format(label_names[2]), loss3)
# label_X = range(origin_data.data_num - origin_data.train_num - origin_data.start_num_in_test) # label_X = range(origin_data.data_num - origin_data.train_num - origin_data.start_num_in_test)
# predict_X = [x + config.predict_day for x in label_X] # predict_X = [x + config.predict_day for x in label_X]
label_data = label_norm_data[:, 1] * std_yqy[1] + mean_yqy[1] label_datas = label_norm_data * std_yqy + mean_yqy
predict_data = predict_norm_data * std_yqy[1] + mean_yqy[1] predict_datas = predict_norm_data * std_yqy + mean_yqy
print(label_data) print(label_datas)
print(predict_data) print(predict_datas)
print(label_data[-1]) print(label_datas[-1])
print(predict_data[-1]) print(predict_datas[-1])
PORT_NUMBER = 8080 PORT_NUMBER = 8080