#!/usr/bin/env python3

# -*- coding: utf-8 -*-

"""

Created on Fri Nov  9 14:43:07 2018

@author: Josefine

"""

import numpy as np

import sys

import os

sys.path.append(os.path.join('.', '..')) 

import matplotlib.pyplot as plt

import matplotlib

import matplotlib.pylab as pylab

%matplotlib inline

#

a = np.load('Results/region_performance.npz')

dice2 = a['dice']

acc = a['acc']

spec = a['spec']

sens = a['sens']

rates = a['rates']

#params = {'legend.fontsize': 'x-large',

#          'figure.figsize': (15, 5),

#         'axes.labelsize': 'x-large',

#         'axes.titlesize':'x-large',

#         'xtick.labelsize':'x-large',

#         'ytick.labelsize':'x-large'}

#pylab.rcParams.update(params)

def epoch_average(a,size):

    new_a = []

    i = 0

    while i < len(a):

        val = np.mean(a[i:i+size])

        new_a.append(val)

        i+=size

    return new_a

dim = 128

# Load validation curves

n_test = int(2*dim)

acc_cor = epoch_average(np.load('Results/train_hist/region/valid_acc_cor.npy'),n_test)

loss_cor = epoch_average(np.load('Results/train_hist/region/valid_loss_cor.npy'),n_test)

acc_sag = epoch_average(np.load('Results/train_hist/region/valid_acc_sag.npy'),n_test)

loss_sag = epoch_average(np.load('Results/train_hist/region/valid_loss_sag.npy'),n_test)

acc_axial = epoch_average(np.load('Results/train_hist/region/valid_acc_axial.npy'),n_test)

loss_axial = epoch_average(np.load('Results/train_hist/region/valid_loss_axial.npy'),n_test)

acc_axial_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/valid_acc_axial.npy'),n_test)

loss_axial_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/valid_loss_axial.npy'),n_test)

acc_sag_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/valid_acc_sag.npy'),n_test)

loss_sag_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/valid_loss_sag.npy'),n_test)

acc_cor_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/valid_acc_cor.npy'),n_test)

loss_cor_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/valid_loss_cor.npy'),n_test)

acc_cor_noaug = epoch_average(np.load('Results/train_hist/region_noaug/valid_acc_cor.npy'),n_test)

loss_cor_noaug = epoch_average(np.load('Results/train_hist/region_noaug/valid_loss_cor.npy'),n_test)

acc_sag_noaug = epoch_average(np.load('Results/train_hist/region_noaug/valid_acc_sag.npy'),n_test)

loss_sag_noaug = epoch_average(np.load('Results/train_hist/region_noaug/valid_loss_sag.npy'),n_test)

acc_axial_noaug = epoch_average(np.load('Results/train_hist/region_noaug/valid_acc_axial.npy'),n_test)

loss_axial_noaug = epoch_average(np.load('Results/train_hist/region_noaug/valid_loss_axial.npy'),n_test)

acc_axial_nothing = epoch_average(np.load('Results/train_hist/region_nothing/valid_acc_axial.npy'),n_test)

loss_axial_nothing = epoch_average(np.load('Results/train_hist/region_nothing/valid_loss_axial.npy'),n_test)

acc_sag_nothing = epoch_average(np.load('Results/train_hist/region_nothing/valid_acc_sag.npy'),n_test)

loss_sag_nothing = epoch_average(np.load('Results/train_hist/region_nothing/valid_loss_sag.npy'),n_test)

acc_cor_nothing = epoch_average(np.load('Results/train_hist/region_nothing/valid_acc_cor.npy'),n_test)

loss_cor_nothing = epoch_average(np.load('Results/train_hist/region_nothing/valid_loss_cor.npy'),n_test)

plt.rcParams.update({'font.size': 13})

plt.figure(figsize=(8*4, 8*3))

plt.subplot(3,4,3)

matplotlib.ticker.MultipleLocator(0.01)

plt.plot(acc_cor, label = 'Both')

plt.plot(acc_cor_noaug, label = 'Only drop out')

plt.plot(acc_cor_nodrop, label = 'Only augmentation')

plt.plot(acc_cor_nothing, label = 'Nothing')

plt.legend(loc='lower right')

plt.xlabel('Epochs')

plt.ylabel('Accuracy')

axes = plt.gca()

axes.set_ylim([0.95,1])

plt.title('Validation accuracy coronal network')

plt.subplot(3,4,4)

plt.title('Validation loss coronal network')

plt.plot(loss_cor, label = 'Both')

plt.plot(loss_cor_noaug, label = 'Only drop out')

plt.plot(loss_cor_nodrop, label = 'Only augmentation')

plt.plot(loss_cor_nothing, label = 'Nothing')

plt.legend(loc='upper right')

axes = plt.gca()

axes.set_ylim([0.02,0.19])

plt.xlabel('Epochs')

plt.ylabel('Loss')

plt.subplot(3,4,7)

plt.plot(acc_sag, label = 'Both')

plt.plot(acc_sag_noaug, label = 'Only drop out')

plt.plot(acc_sag_nodrop, label = 'Only augmentation')

plt.plot(acc_sag_nothing, label = 'Nothing')

axes = plt.gca()

plt.xlabel('Epochs')

plt.ylabel('Accuracy')

axes.set_ylim([0.95,1])

plt.legend(loc='lower right')

plt.title('Validation accuracy sagittal network')

plt.subplot(3,4,8)

plt.title('Validation loss sigittal network')

plt.plot(loss_sag, label = 'Both')

plt.plot(loss_sag_noaug, label = 'Only drop out')

plt.plot(loss_sag_nodrop, label = 'Only augmentation')

plt.plot(loss_sag_nothing, label = 'Nothing')

plt.legend(loc='upper right')

plt.xlabel('Epochs')

plt.ylabel('Loss')

axes = plt.gca()

axes.set_ylim([0.02,0.19])

plt.subplot(3,4,11)

plt.plot(acc_axial, label = 'Both')

plt.plot(acc_axial_noaug, label = 'Only drop out')

plt.plot(acc_axial_nodrop, label = 'Only augmentation')

plt.plot(acc_axial_nothing, label = 'Nothing')

axes = plt.gca()

plt.xlabel('Epochs')

plt.ylabel('Accuracy')

axes.set_ylim([0.95,1])

plt.title('Validation accuracy axial network')

plt.legend(loc='lower right')

plt.subplot(3,4,12)

plt.plot(loss_axial, label = 'Both')

plt.plot(loss_axial_noaug, label = 'Only drop out')

plt.plot(loss_axial_nodrop, label = 'Only augmentation')

plt.plot(loss_axial_nothing, label = 'Nothing')

plt.title('Validation loss axial network')

plt.xlabel('Epochs')

plt.ylabel('Loss')

plt.legend(loc='upper right')

axes = plt.gca()

axes.set_ylim([0.02,0.19])

#% Load training curves

n_test = int(13*6*dim)

acc_cor = epoch_average(np.load('Results/train_hist/region/train_acc_cor.npy'),n_test)

loss_cor = epoch_average(np.load('Results/train_hist/region/train_loss_cor.npy'),n_test)

acc_sag = epoch_average(np.load('Results/train_hist/region/train_acc_sag.npy'),n_test)

loss_sag = epoch_average(np.load('Results/train_hist/region/train_loss_sag.npy'),n_test)

acc_axial = epoch_average(np.load('Results/train_hist/region/train_acc_axial.npy'),n_test)

loss_axial = epoch_average(np.load('Results/train_hist/region/train_loss_axial.npy'),n_test)

n_test = int(13*6*dim)

acc_axial_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/train_acc_axial.npy'),n_test)

loss_axial_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/train_loss_axial.npy'),n_test)

acc_sag_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/train_acc_sag.npy'),n_test)

loss_sag_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/train_loss_sag.npy'),n_test)

acc_cor_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/train_acc_cor.npy'),n_test)

loss_cor_nodrop = epoch_average(np.load('Results/train_hist/region_nodrop/train_loss_cor.npy'),n_test)

n_test = int(13*dim)

acc_cor_noaug = epoch_average(np.load('Results/train_hist/region_noaug/train_acc_cor.npy'),n_test)

loss_cor_noaug = epoch_average(np.load('Results/train_hist/region_noaug/train_loss_cor.npy'),n_test)

acc_sag_noaug = epoch_average(np.load('Results/train_hist/region_noaug/train_acc_sag.npy'),n_test)

loss_sag_noaug = epoch_average(np.load('Results/train_hist/region_noaug/train_loss_sag.npy'),n_test)

acc_axial_noaug = epoch_average(np.load('Results/train_hist/region_noaug/train_acc_axial.npy'),n_test)

loss_axial_noaug = epoch_average(np.load('Results/train_hist/region_noaug/train_loss_axial.npy'),n_test)

acc_axial_nothing = epoch_average(np.load('Results/train_hist/region_nothing/train_acc_axial.npy'),n_test)

loss_axial_nothing = epoch_average(np.load('Results/train_hist/region_nothing/train_loss_axial.npy'),n_test)

acc_sag_nothing = epoch_average(np.load('Results/train_hist/region_nothing/train_acc_sag.npy'),n_test)

loss_sag_nothing = epoch_average(np.load('Results/train_hist/region_nothing/train_loss_sag.npy'),n_test)

acc_cor_nothing = epoch_average(np.load('Results/train_hist/region_nothing/train_acc_cor.npy'),n_test)

loss_cor_nothing = epoch_average(np.load('Results/train_hist/region_nothing/train_loss_cor.npy'),n_test)

plt.subplot(3,4,1)

plt.plot(acc_cor, label = 'Both')

plt.plot(acc_cor_noaug, label = 'Only drop out')

plt.plot(acc_cor_nodrop, label = 'Only augmentation')

plt.plot(acc_cor_nothing, label = 'Nothing')

axes = plt.gca()

axes.set_ylim([0.95,1])

plt.legend(loc='lower right')

plt.xlabel('Epochs')

plt.ylabel('Accuracy')

plt.title('Train accuracy coronal network')

plt.subplot(3,4,2)

plt.title('Train loss coronal network')

plt.plot(loss_cor, label = 'Both')

plt.plot(loss_cor_noaug, label = 'Only drop out')

plt.plot(loss_cor_nodrop, label = 'Only augmentation')

plt.plot(loss_cor_nothing, label = 'Nothing')

plt.legend(loc='upper right')

plt.xlabel('Epochs')

plt.ylabel('Loss')

axes = plt.gca()

axes.set_ylim([0,0.05])

plt.subplot(3,4,5)

plt.plot(acc_sag, label = 'Both')

plt.plot(acc_sag_noaug, label = 'Only drop out')

plt.plot(acc_sag_nodrop, label = 'Only augmentation')

plt.plot(acc_sag_nothing, label = 'Nothing')

plt.legend(loc='lower right')

axes = plt.gca()

axes.set_ylim([0.95,1])

plt.xlabel('Epochs')

plt.ylabel('Accuracy')

plt.title('Train accuracy sagittal network')

plt.subplot(3,4,6)

plt.title('Train loss sigittal network')

plt.plot(loss_sag, label = 'Both')

plt.plot(loss_sag_noaug, label = 'Only drop out')

plt.plot(loss_sag_nodrop, label = 'Only augmentation')

plt.plot(loss_sag_nothing, label = 'Nothing')

plt.legend(loc='upper right')

plt.xlabel('Epochs')

plt.ylabel('Loss')

axes = plt.gca()

axes.set_ylim([0,0.05])

plt.subplot(3,4,9)

plt.plot(acc_axial, label = 'Both')

plt.plot(acc_axial_noaug, label = 'Only drop out')

plt.plot(acc_axial_nodrop, label = 'Only augmentation')

plt.plot(acc_axial_nothing, label = 'Nothing')

plt.legend(loc='lower right')

axes = plt.gca()

axes.set_ylim([0.95,1])

plt.xlabel('Epochs')

plt.ylabel('Accuracy')

plt.title('Train accuracy axial network')

plt.subplot(3,4,10)

plt.plot(loss_axial, label = 'Both')

plt.plot(loss_axial_noaug, label = 'Only drop out')

plt.plot(loss_axial_nodrop, label = 'Only augmentation')

plt.plot(loss_axial_nothing, label = 'Nothing')

plt.title('Train loss axial network')

plt.legend(loc='upper right')

plt.xlabel('Epochs')

plt.ylabel('Loss')

axes = plt.gca()

axes.set_ylim([0,0.05])