'''
  Take a file and plot its data onto a 2d or 3d axis depending on the data. 
  '''
  
  import os
  import numpy as np
  from sklearn.cluster import KMeans
  import matplotlib.pyplot as plt
  import argparse
  import json
  
  # Defining argparse
  parser = argparse.ArgumentParser(prog='Plotter', description='Plot a file of 2d ou 3d dimension')
  parser.add_argument('filepath', type=str,
                      help='the path of the file you want to plot')
  parser.add_argument('-o-', '--output', type=str,
                      default='plot.pdf',
                      help='the path of the ploted file')
  parser.add_argument('-t', '--toy', action='store_true',
                      help='test the script on a toy example. Do not test all the file content')
  
  args = parser.parse_args()
  
  # Editing global variable
  FILE_PATH=args.filepath
  OUTFILE_PATH = args.output
  TOY_VERSION = args.toy
  
  # Defining vectors with default number of column
  vectors = np.empty((0, 64), np.float32)
  metas = np.empty((0, 4), np.float32)
  
  # READ DATA
  with open(os.path.join(FILE_PATH), "r") as f:
          for i, line in enumerate(f):
                  if TOY_VERSION == True and i > 100:
                          break
                  spl_line = line.split(" ")
                  if(len(vectors) == 0):
                          vectors = np.empty((0, len(spl_line[1:])), np.float32)
                  metas = np.append(
                          metas,
                          np.asarray([spl_line[0].split(",")]),
                          axis=0)
  
                  vectors = np.append(
                          vectors,
                          np.asarray([spl_line[1:]], dtype=np.float32),
                          axis=0)
  
  vectors_T = np.transpose(vectors)
  
  
  # Plot the file
  plt.plot(vectors, 'ro')
  fig, ax = plt.subplots()
  
  if(vectors_T.shape[0] == 2):
  	ax.scatter(vectors_T[0], vectors_T[1]) #c=close, s=volume, alpha=0.5)
  else:
  	ax.scatter(vectors_T[0], vectors_T[1], vectors_T[2])
  
  ax.set_xlabel('Axe 1', fontsize=15)
  ax.set_ylabel('Axe 2', fontsize=15)
  
  if(vectors_T.shape[0] == 3):
  	ax.set_zlabel('Axe 3', fontsize15=15)
  
  ax.set_title('Volume and percent change')
  plt.savefig(OUTFILE_PATH)