content: from mylib import *
  import os,sys
  import numpy as np
  import matplotlib.pyplot as plt
  import math
  import random
  from time import time
  
  if __name__ == '__main__':
  	DIR_PATH = sys.path[0] + '\\'
  
  	# normal distribution vector file
  	nvctr_file1 = DIR_PATH + 'normal_500_1.txt'
  	nvctr_file2 = DIR_PATH + 'normal_500_2.txt'
  	# uniform distribution vector file
  	uvctr_file1 = DIR_PATH + 'uniform_500_1.txt'
  	uvctr_file2 = DIR_PATH + 'uniform_500_2.txt'
  
  	# normal distribution matrix
  	nmtrx = fget_mtrx(nvctr_file1) + fget_mtrx(nvctr_file2)
  	# uniform distribution matrix
  	umtrx = fget_mtrx(uvctr_file1) + fget_mtrx(uvctr_file2)
  
  	# plist is list the numbers of dimensions after DCT compression
  	# nplist is for normal distribution data set
  	# uplist is for uniform distribution data set
  	nplist = []
  	uplist = []
  	for vector in nmtrx:
  		u, p = my_DCT_compression(vector, 0.01)
  		nplist.append(p)
  
  	for vector in umtrx:
  		u, p = my_DCT_compression(vector, 0.01)
  		uplist.append(p)
  
  	# draw histogram
  	plt.figure(1)
  	plt.subplot(2,1,1)
  	my_hist(nplist, bucket_size = 1, flat_edge = False, title = "For normal distribution data set")
  	plt.subplot(2,1,2)
  	my_hist(uplist, bucket_size = 1, flat_edge = False, title = "For uniform distribution data set")
  	plt.show()
  	
  	