import numpy as np import matplotlib.pyplot as plt import os, sys currentdir = os.path.dirname(os.path.realpath(__file__)) parentdir = os.path.dirname(currentdir) sys.path.append(parentdir) from s_data_loader import data_path plt.style.use('bmh') x_acc_raw_file = open(data_path('train/InertialSignals/body_acc_x_train.txt'), 'r') y_acc_raw_file = open(data_path('train/InertialSignals/body_acc_y_train.txt'), 'r') z_acc_raw_file = open(data_path('train/InertialSignals/body_acc_z_train.txt'), 'r') # Create empty lists x_acc_raw = [] for x in x_acc_raw_file: x_acc_raw.append([float(ts) for ts in x.split()]) y_acc_raw = [] for x in y_acc_raw_file: y_acc_raw.append([float(ts) for ts in x.split()]) z_acc_raw = [] for x in z_acc_raw_file: z_acc_raw.append([float(ts) for ts in x.split()]) x_acc_raw = np.array(x_acc_raw) y_acc_raw = np.array(y_acc_raw)
import numpy as np import matplotlib.pyplot as plt from s_knn_dtw import KnnDtw from s_data_loader import data_path plt.style.use('bmh') print("-------------------------------- section 7") # Import the HAR dataset x_train_file = open(data_path('train/X_train.txt'), 'r') y_train_file = open(data_path('train/y_train.txt'), 'r') x_test_file = open(data_path('test/X_test.txt'), 'r') y_test_file = open(data_path('test/y_test.txt'), 'r') # Create empty lists x_train = [] y_train = [] x_test = [] y_test = [] # Mapping table for classes labels = { 1: 'WALKING', 2: 'WALKING UPSTAIRS', 3: 'WALKING DOWNSTAIRS', 4: 'SITTING', 5: 'STANDING', 6: 'LAYING' }