old_contents: #!/usr/env python
  
  import pprocess  # parallel computing module
  import os  # os utilitites
  import time  # 
  
  import astropy.io.fits as fits  # FITS manipulating library
  import matplotlib.pyplot as plt
  import numpy as np  # numeric python for array manipulation
  
  import myscitools # my personal tools
  
  
  #input file informations and variables atributions----------------------
  inptname = str(raw_input('Input file (with extension): '))
  outptname = os.path.splitext(inptname)[0]+'_z2n_output_t.fits'
  inpt = fits.open(inptname)
  times = inpt[1].data.field('TIME')
  inpt.close()
  
  startf = float(raw_input('Enter the start frequency: '))
  endf = float(raw_input('Enter the last frequency: '))
  deltaf = float(raw_input('Enter the frequency interval: '))
  freqs = np.arange(startf, endf, deltaf)
  
  harm = int(raw_input('The Harmonic to be considered:'))
  
  #----------------- The parallelism starts here ------------------------
  nproc = int(raw_input('Enter the number of processor to use: '))
  if nproc < 1:
      nproc = 1  # default number of cpus = 1
  
  freqlist = np.array_split(freqs, nproc)
  
  
  results = pprocess.Map(limit=nproc, reuse=1)
  parallel_z2n = results.manage(pprocess.MakeReusable(myscitools.z2n))
  
  print "\n Calculating with ", nproc, " processor(s)\n"
  
  tic = time.time()
  [parallel_z2n(somefreqs, times, harm) for somefreqs in freqlist]
  
  print 'time = {0}'.format(time.time() - tic)
  z2n = []
  for result in results:
      for value in result:
          z2n.append(value)
  
  print z2n
  
  plt.plot(freqs, z2n)
  plt.show()
  plt.plot(freqs, z2n)
  plt.savefig('teste.png')
  
  #create and write the output.fits file
  col1 = [freqs, 'Frequency', 'E', 'Hz']
  col2 = [z2n, 'Z2nPower', 'E', 'arbitrary']
  myscitools.makefits(outptname, col1, col2)
  
new_contents: #!/usr/env python
  
  import pprocess  # parallel computing module
  import os  # os utilitites
  import time  # keep track of time
  
  import astropy.io.fits as fits  # FITS manipulating library
  import matplotlib.pyplot as plt
  import numpy as np  # numeric python for array manipulation
  
  import myscitools # my personal tools
  
  
  #input file informations and variables atributions----------------------
  inptname = str(raw_input('Input file (with extension): '))
  outptname = os.path.splitext(inptname)[0]+'_z2n_output_t.fits'
  inpt = fits.open(inptname)
  times = inpt[1].data.field('TIME')
  inpt.close()
  
  startf = float(raw_input('Enter the start frequency: '))
  endf = float(raw_input('Enter the last frequency: '))
  deltaf = float(raw_input('Enter the frequency interval: '))
  freqs = np.arange(startf, endf, deltaf)
  
  harm = int(raw_input('The Harmonic to be considered:'))
  
  #----------------- The parallelism starts here ------------------------
  nproc = int(raw_input('Enter the number of processor to use: '))
  if nproc < 1:
      nproc = 1  # default number of cpus = 1
  
  freqlist = np.array_split(freqs, nproc)
  
  
  results = pprocess.Map(limit=nproc, reuse=1)
  parallel_z2n = results.manage(pprocess.MakeReusable(myscitools.z2n))
  
  print "\n Calculating with ", nproc, " processor(s)\n"
  
  tic = time.time()
  [parallel_z2n(somefreqs, times, harm) for somefreqs in freqlist]
  
  z2n = []
  for result in results:
      for value in result:
          z2n.append(value)
  
  print 'time = {0}'.format(time.time() - tic)
  
  plt.plot(freqs, z2n)
  plt.show()
  plt.plot(freqs, z2n)
  plt.savefig('z2n.png')
  
  #create and write the output.fits file
  col1 = [freqs, 'Frequency', 'E', 'Hz']
  col2 = [z2n, 'Z2nPower', 'E', 'arbitrary']
  myscitools.makefits(outptname, col1, col2)
  
subject: delete bugtracker move time marker