import scipy.io as sio

import matplotlib.pyplot as plt

import os

import glob

import numpy as np

Patient_id = np.unique(sio.loadmat("Sample Data/trials_subNums.mat")['subjectNum'][0]) #corresponding to the patient id

dir = "Results/"

models = ["Basic", "LSTM", "MaxCNN", "Mix", "TempCNN"]

Results = np.zeros((len(Patient_id), len(models),20))

inc = 0

for model in models:

    inc_patient = 0

    for patient in Patient_id:

        doc = glob.glob(dir+"*"+model+"*"+"t"+str(patient)+".mat")[0]

        file = sio.loadmat(doc)['res']

        Results[inc_patient,inc, :] = file[:,3]

        inc_patient += 1

    inc += 1

fig = plt.figure()

for i in range(len(models)):

    a = 5

    plt.plot(np.max(Results[:,i,:],axis=1), '.-', label = models[i])

plt.legend()

#plt.boxplot(Results[:,0,:])

#plt.boxplot(Results[:,1,:])

lstm = sio.loadmat("Results/result_LSTM.mat")['vacc']

plt.plot(np.mean(lstm, axis=0))

plt.show()