def __init__(self):
self.names = []
self.settings = []
self.settings_val = []
# ---Importation des donnees du .mat--- #
data_filename = 'U001ai.mat'
data_folder = 'SSVEP_Training/Dataset/'
data_path = data_folder + data_filename
data = loadmat(data_path)
success = 0
i = 0
verbose = False
self.registered_patients = []
self.patients = []
patients = []
suc_rate = []
self.success_by_freq = [0, 0, 0, 0, 0]
rank = 1
average_success = []
for i in range(rank):
average_success.append([0])
for filename in os.listdir(data_folder):
if filename[-5] != 'x':
verbose = False
if filename == 'U005aii.mat':
verbose = True
if filename[-6:-4] == 'ii':
seq = 1
else:
seq = 0
data = loadmat(data_folder + filename)
i += 1
if filename[:5] in self.registered_patients:
patient_idx = self.registered_patients.index(filename[:5])
self.patients[patient_idx].addNewData(data, seq)
for i in range(rank):
suc_rate = self.patients[
self.registered_patients.index(
filename[:5])].successRate(i + 1)
average_success[i] = np.add(average_success[i],
suc_rate)
# print("Patient {}, success rate : {} %".format(filename, suc_rate))
else:
self.registered_patients.append(filename[:5])
self.patients.append(
cl.Patient(filename[:5], data, seq, rank))
for i in range(rank):
n = average_success[i][0]
n /= len(self.registered_patients)
print("Sucess rate rank {} : {}%".format(i + 1, n))
self.successRate()
self.frame = GUI.MainApplication(self.registered_patients,
self.patients[0].getChannelsName(),
self.success_by_freq)
self.window = self.frame.frames[GUI.MainWindow]
LW = self.frame.frames[GUI.MainWindow].lengthw
mwindow_size = str(1260 + LW) + 'x' + str(350)
self.frame.geometry(mwindow_size)
self.frame.mainloop()
self.guiLoop()
