image_path = './new_image/Tr-{}_Va-{}12_Te-{}10.png'.format(train, valid, test) #image_path = './Tr-{}_Va-{}12_Te-{}10.png'.format(train, valid, test) #train_path = './Tainan/2010_1-1_to_2017_12-31.csv' #test_path = './Tainan/2018_1-1_to_2018_10-31.csv' #train_path = './Yongkang/2010_1-1_to_2017_12-31.csv' #test_path = './Yongkang/2018_1-1_to_2018_10-31.csv' train_path = './{}/2010_1-1_to_2017_12-31.csv'.format(train) test_path = './{}/2018_1-1_to_2018_10-31.csv'.format(test) validation_path = './{}/2010_1-1_to_2017_12-31.csv'.format(valid) #get data data_set = get_data.from_2010(train_path, 4, t_temp, t_temp, 24) data_time = get_data.get_time(train_path, t_temp, 24) data_set[0] /= 40 data_set[1] /= 40 data_set[0] = pd.concat([data_set[0], data_time[0], data_time[1]], axis=1).reset_index(drop=True) #get validation data data_set1 = get_data.from_2010(validation_path, 4, t_temp, t_temp, 24) data_time1 = get_data.get_time(validation_path, t_temp, 24) data_set1[0] /= 40 data_set1[1] /= 40
import sys from sklearn.decomposition import PCA import get_data now = time.time() #train_path = sys.argv[1] #test_path = sys.argv[2] components = int(sys.argv[1]) t_temp = 96 t_humd = 96 #int(sys.argv[2]) t_pres = 0 #int(sys.argv[3]) #get data data_set = get_data.from_2010('./Taoyuan/2010_1-1_to_2017_12-31.csv', 4, t_temp, t_temp, 24) data_set[0] /= 40 data_time = get_data.get_time('./Taoyuan/2010_1-1_to_2017_12-31.csv', t_temp, 24) #data_set = get_data.from_2010(train_path, 4, t_temp, t_temp, 24) #data_time = get_data.get_time(train_path, t_temp, 24) #data_humd = get_data.from_2010('./Tainan/2010_1-1_to_2017_12-31.csv', 6, t_temp, t_temp, 24) #data_set[0] = pd.concat([data_set[0], data_humd[0]], axis=1).reset_index(drop = True) pca_t1 = PCA(n_components=6) pca_t2 = PCA(n_components=6) pca_t3 = PCA(n_components=12) #pca_t4 = PCA(n_components = 12) #pca_h = PCA(n_components = 24) aPCA_temp1 = pd.DataFrame.from_records( pca_t1.fit_transform(data_set[0].iloc[:, :48]))
#image_path = './new_image/Tr-{}_Va-{}12_Te-{}10.png'.format(train, valid, test) #image_path = './Tr-{}_Va-{}12_Te-{}10.png'.format(train, valid, test) #train_path = './Tainan/2010_1-1_to_2017_12-31.csv' #test_path = './Tainan/2018_1-1_to_2018_10-31.csv' #train_path = './Yongkang/2010_1-1_to_2017_12-31.csv' #test_path = './Yongkang/2018_1-1_to_2018_10-31.csv' train_path = './{}/2010_1-1_to_2017_12-31.csv'.format(train) test_path = './{}/2018_1-1_to_2018_10-31.csv'.format(train) #validation_path = './{}/2010_1-1_to_2017_12-31.csv'.format(valid) #get data data_set = get_data.from_2010(train_path, 4, t_temp, t_temp, 24) data_time = get_data.get_time(train_path, t_temp, 24) data_set1 = get_data.from_2010(test_path, 4, t_temp, t_temp, 24) data_time1 = get_data.get_time(test_path, t_temp, 24) data_set[0] /= 40 data_set[1] /= 40 data_set1[0] /= 40 data_set1[1] /= 40 data_set[0] = pd.concat([data_set[0], data_time[0], data_time[1]], axis=1).reset_index(drop=True) data_set1[0] = pd.concat([data_set1[0], data_time1[0], data_time1[1]], axis=1).reset_index(drop=True) all_data = [
import time import sys import get_data #time.sleep(4000) now = time.time() #train_path = sys.argv[1] #test_path = sys.argv[2] t_temp = 96 t_humd = 0 #int(sys.argv[2]) t_pres = 0 #int(sys.argv[3]) #get data data_set = get_data.from_2010('./Tainan/2010_1-1_to_2017_12-31.csv', 4, t_temp, t_temp, 24) data_set1 = get_data.from_2010('./Tamsui/2010_1-1_to_2017_12-31.csv', 4, t_temp, t_temp, 24) data_set2 = get_data.from_2010('./Taoyuan/2010_1-1_to_2017_12-31.csv', 4, t_temp, t_temp, 24) data_set3 = get_data.from_2010('./Yongkang/2010_1-1_to_2017_12-31.csv', 4, t_temp, t_temp, 24) data_time = get_data.get_time('./Tainan/2010_1-1_to_2017_12-31.csv', t_temp, 24) #data_time1 = get_data.get_time('./Yongkang/2010_1-1_to_2017_12-31.csv', t_temp, 24) #data_time2 = get_data.get_time('./Taoyuan/2010_1-1_to_2017_12-31.csv', t_temp, 24) #data_set = get_data.from_2010(train_path, 4, t_temp, t_temp, 24) #data_time = get_data.get_time(train_path, t_temp, 24) data_set[0] /= 40