def add_data(table): """ Add several values to a row in the table. Values to add are: last ticker in several exchanges like bitstamp, GDAX, gemini, kraken, deribit order book (from GDAX) time (epoch seconds) """ output = get_data.last() output['time'] = get_data.get_time() ob = get_data.order_book() output['bids'] = ob['bids'] output['asks'] = ob['asks'] response = table.put_item(Item={ 'symbol': 'BTC-USD', 'time': int(output['time']), 'bids': output['bids'], 'asks': output['asks'], 'bitstamp': Decimal(output['bitstamp']), 'GDAX': Decimal(output['GDAX']), 'kraken': Decimal(output['kraken']), 'gemini': Decimal(output['gemini']) }) return response
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 data_set1[0] = pd.concat([data_set1[0], data_time1[0], data_time1[1]],
#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 = [ pd.concat([data_set[0], data_set1[0]], axis=0).reset_index(drop=True),
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])) aPCA_temp2 = pd.DataFrame.from_records( pca_t2.fit_transform(data_set[0].iloc[:, 48:72])) aPCA_temp3 = pd.DataFrame.from_records(