# -*- coding: utf-8 -*-
"""
Created on Thu Mar  7 11:14:23 2019

@author: Student
"""

#class VectorExample():
#    def __init__(self, input_list):
#        self.vector = input_list
#        
#    def foreach(self, other, input_function):
#        return VectorExample([input_function(self.vector[i], other.vector[i]) for i in range(len(self.vector))])
#        
#    def __add__(self,other):
#        return self.foreach(other, lambda a,b: a+b)
#    
#    def __sub__(self, other):
#        return self.foreach(other, lambda a,b: a-b)
#    
#    def __mul__(self, other):
#        return self.foreach(other, lambda a,b: a*b)
#    
#    def __truediv__(self,other):
#        return self.foreach(other, lambda a,b: a/b)
#    
#    def __str__(self):
#        return str(self.vector)
#
#
#def run():
#    vector_1 = VectorExample([1, 13, 4])
#    vector_2 = VectorExample([3, -2, 2])
#
#    print(vector_1 + vector_2)
#    print(vector_1 - vector_2)
#    print(vector_1 * vector_2)
#    print(vector_1 / vector_2)
#    
#if __name__== "__main__":
#   run()

import os
import numpy as np
from matplotlib  import pyplot as plt
from skimage import io
import random

#def run():
#    example_array = np.array([
#            [8,1,1,1],
#            [9,7,5,3],
#            [4,6,8,10],
#            [2,3,5,7]
#    
#    ])
#    
#    noise_1 = np.random.randn(128,256)
#    noise_2 = np.random.randn(128,256)
#    
#    vmin=-0.5;vmax=0.5
#    plt.figure()
#    plt.subplot(2,1,1)
#    plt.imshow(noise_1,cmap='gray', vmin=vmin, vmax=vmax)
#    plt.axis('off')
#    plt.subplot(2,1,2)
#    plt.imshow(noise_2, cmap='gray', vmin=vmin, vmax=vmax)
#    plt.axis('off')
#    plt.show()
#    
#    
#
#run()
    

#def run():
#    
#    x_size = 512
#    y_size = 512
#    number_of_points = 500
#    vector1 = np.random.uniform(0,x_size,number_of_points)
#    vector2 = np.random.uniform(0,y_size,number_of_points)
#    
#    x_origin=256
#    y_origin=256
#    radius=100
#    is_inside=np.square(vector1-x_origin) + np.square(vector2-y_origin) < radius*radius
#    
#    image = np.zeros((y_size,x_size))
#    grid_x, grid_y = np.meshgrid(np.arange(x_size), np.arange(y_size))
#    
#    image[np.square(grid_x - x_origin)+np.square(grid_y - y_origin)<radius*radius] = 1
#    
##    plt.figure()
##    plt.subplot(1,2,1)
##    plt.imshow(grid_x, cmap='gray')
##    plt.subplot(1,2,2)
##    plt.imshow(grid_y, cmap='gray')
##    plt.show()
#    
#    vector1_inside = vector1[is_inside]
#    vector2_inside = vector2[is_inside]
#    
#    vector1_outside = vector1[np.logical_not(is_inside)]
#    vector2_outside = vector2[np.logical_not(is_inside)]    
#    
#    plt.figure()
#    plt.imshow(image, cmap='gray')
#    plt.plot(vector1_inside, vector2_inside,"r.")
#    plt.plot(vector1_outside, vector2_outside, "b.")
#    plt.xlabel("X Coordinates")
#    plt.ylabel("Y Coordinates")
#    plt.xlin([0, x_size])
#    plt.ylin([0, y_size])
#    plt.legend(["Outside","Inside"])
#    plt.show()
#    
#run()
    
    
def run():

    current_path = os.path.abspath(os.path.dirname(__file__))
    image_folder=os.path.join(current_path, "sample_cifar")
    file_names = os.listdir(image_folder)
    
    random.shuffle(file_names)
    file_names = file_names[0:25]
    
    print(file_names)
    
    plt.figure()
    i=1
    for file_name in file_names:
        current_class = file_name.split('_')[1].split('.')[0].capitalize()
        plt.subplot(5,5,i)
        image_path = os.path.join(image_folder, file_name)
        image = io.imread(image_path)
        i+=1
        plt.axis('off')
        plt.title(current_class)
    plt.show()
    
run()