sensAccCoeff = 8 * 9.81 / 32768 sensGyrCoeff = 2000 / 32768 sensMagCoeff = 0.007629 sensfsamp = 100 data = tools.load_file(filename, sep=',', header=1) data = tools.downsampling(data, 50) t = tools.selectCol(data, columns_in, "TIME") acc = tools.selectCol(data, columns_in, col_acc) gyr = tools.selectCol(data, columns_in, col_gyr) mag = tools.selectCol(data, columns_in, col_mag) lab = tools.selectCol(data, columns_in, "LAB") acc = inertial.convert_units(acc, coeff=sensAccCoeff) gyr = inertial.convert_units(gyr, coeff=sensGyrCoeff) mag = inertial.convert_units(mag, coeff=sensMagCoeff) # tools.array_labels_to_csv(np.column_stack([t, acc]), np.array(columns_in), "./output/preproc_"+filename[7:-4]+".csv") #-----EXTRACT FEATURES----- windows, winlab = win.get_windows_no_mix(t, lab, 1, 0.5) feats_acc, fcol_acc = inertial.extract_features_acc(acc, t, col_acc, windows) feats_gyr, fcol_gyr = inertial.extract_features_gyr(gyr, t, col_gyr, windows) feats_mag, fcol_mag = inertial.extract_features_mag(mag, t, col_mag, windows) feats = np.column_stack([feats_acc, feats_gyr, feats_mag, winlab]) columns_out = np.r_[fcol_acc, fcol_gyr, fcol_mag, np.array(["LAB"])] # print feats.shape # print columns.shape, columns
lables_acc=["accX", "accY", "accZ"]
lables_gyr=["gyrX", "gyrY", "gyrZ"]
lables_mag=["magX", "magY", "magZ"]
empaticaAccCoeff=2*9.81/128
empaticafsamp=32
sensAccCoeff=8*9.81/32768
sensGyrCoeff=2000/32768
sensMagCoeff=0.007629
sensfsamp=100
data=tools.load_file_pd(filename, sep=",", names=lables)
data=inertial.convert_units(data, lables_acc, coeff=sensAccCoeff)
data=inertial.convert_units(data, lables_gyr, coeff=sensGyrCoeff)
data=inertial.convert_units(data, lables_mag, coeff=sensMagCoeff)
plt.figure(1)
plt.plot(data.timestamp, data[lables_acc])
plt.legend(lables_acc)
plt.xlabel("Time (ms)")
plt.ylabel("Acceleration (m/s^2)")
plt.title("Accelerometer")
plt.figure(2)
plt.plot(data.timestamp, data[lables_gyr])
plt.legend(lables_gyr)
plt.xlabel("Time (ms)")
plt.ylabel("Angular Speed (degree/s)")
plt.title("Gyroscope")
sensAccCoeff=8*9.81/32768 sensGyrCoeff=2000/32768 sensMagCoeff=0.007629 sensfsamp=100 data = tools.load_file(filename, sep=',', header=1) data=tools.downsampling(data, 50) t=tools.selectCol(data, columns_in, "TIME") acc=tools.selectCol(data, columns_in, col_acc) gyr=tools.selectCol(data, columns_in, col_gyr) mag=tools.selectCol(data, columns_in, col_mag) lab=tools.selectCol(data, columns_in, "LAB") acc= inertial.convert_units(acc, coeff=sensAccCoeff) gyr= inertial.convert_units(gyr, coeff=sensGyrCoeff) mag= inertial.convert_units(mag, coeff=sensMagCoeff) # tools.array_labels_to_csv(np.column_stack([t, acc]), np.array(columns_in), "./output/preproc_"+filename[7:-4]+".csv") #-----EXTRACT FEATURES----- windows, winlab=win.get_windows_no_mix(t,lab , 1, 0.5) feats_acc, fcol_acc= inertial.extract_features_acc(acc, t, col_acc, windows) feats_gyr, fcol_gyr= inertial.extract_features_gyr(gyr, t, col_gyr, windows) feats_mag, fcol_mag= inertial.extract_features_mag(mag, t, col_mag, windows) feats=np.column_stack([feats_acc, feats_gyr, feats_mag, winlab]) columns_out=np.r_[fcol_acc, fcol_gyr, fcol_mag, np.array(["LAB"])] # print feats.shape # print columns.shape, columns
