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