content: """
  Author: Chukwubuikem Ume-Ugwa
  Email: chubiyke@gmail.com
  
  MIT License
  
  Copyright (c) 2017 CleverChuk
  
  Permission is hereby granted, free of charge, to any person obtaining a copy
  of this software and associated documentation files (the "Software"), to deal
  in the Software without restriction, including without limitation the rights
  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  copies of the Software, and to permit persons to whom the Software is
  furnished to do so, subject to the following conditions:
  
  The above copyright notice and this permission notice shall be included in all
  copies or substantial portions of the Software.
  
  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  SOFTWARE.
  """
  
  
  import matplotlib.pyplot as plt
  from mpl_toolkits.mplot3d import Axes3D    
  from dataparser import *
  
  from multiprocessing import Pool, Manager
  import os
  import time
  
  manager = Manager()
  heightD = manager.dict() # holds values for minimum height of each particle
  
  TSIZE = 8 # data type size in bytes
  N_OFFSETS = 44 # number of data
  FCOLOR = genColor(N_OFFSETS, manager)
  
  # Dimension of the simulation bed
  xsize = 78
  ysize = 112
  zsize = 104
  
  hOut = "HeightData"
  def startChild(fname):
  	# DISALLOWED IN PYTHON
  	iam.fn = fname
  	dictn = iam.manager.dict()
  	mylist = iam.manager.list()
  
  	pool = Pool()
  	# passing offset multiplier to the producer task
  	pool.map(iam.producer, [i for i in range(1 , iam.N_OFFSETS)], 1)
  
  	# Feeds task from producers into the list
  	for i, j in self.dictn.items():
  		mylist.append(j[0])
  
  
  	# single process to handle plotting
  	proc = Process(target=iam.consumer, args=(mylist, ))
  	proc.start()
  	proc.join()
  
  
  
  def multijob(fname):
  	"""
  	Handles reading and plotting of data in file with name fname
  	"""
  
  	print("Starting multijob from process: %d" % os.getpid())
  	
  	fig = plt.figure()
  	axis = Axes3D(fig)
  	heightL = manager.list()
  	
  	axis = Axes3D(fig)
  	axis.set_xlim([0,ysize])
  	axis.set_ylim([0,ysize])
  	axis.set_zlim([0,ysize])
  	axis.view_init(elev = 40, azim = 50)
  
  	coords = manager.list()
  	rho = readsingle(fname)
  
  	for i in range(1, N_OFFSETS):
  		
  		eta_s = readsingle(fname, i * TSIZE)
  #		eta_s = process(rho, filter_eta(eta_s))
  		coords.append(getcoords(eta_s, xsize, ysize, zsize))
  		heightL.append(max(coords[-1][-2]) - min(coords[-1][-2]))
  
  	
  	writtable(hOut,str(heightL).strip('[]'))
  		
  	plot(coords, fig, axis, count = "ALL", fcolor = FCOLOR, multijob = (True,fname))		
  	print("Finished multijob from process: %d" % os.getpid())
  
  
  
  
  if __name__ == "__main__":
  	print("Starting mutiple jobs in a process task")
  	import timeit, sys
  	start_time = timeit.default_timer()
  	if(os.path.exists(hOut)):
  		os.remove(hOut)
  
  	
  	pool = Pool()	
  	files = list()
  
  	MAXCOUNT = 4
  	STEP = 2
  	START = 0
  	FNAME = "fullT{0}.dat"
  	
  
  	## file with filesname to work on
  	for i in range(START, MAXCOUNT, STEP):		
  		files.append(FNAME.format(i))
  
  	
  	pool.map(multijob, files, 1)
  	elapsed = timeit.default_timer() - start_time
  	
  	print("total time %d seconds" % elapsed)
  	print("Finished multiple job in a process task")
  
  
  
  
  
  
  
  
  
  
  
  
  
  