old_contents: # -*- coding: utf-8 -*-
  """
  Created on Fri Mar 08 09:43:02 2013
  
  @author: jgostick
  """
  
  import OpenPNM
  import numpy as np
  import matplotlib.pyplot as plt
  from time import clock
  
  params = {
  #'domain_size': [0.001,0.001,0.0004],  #physical network size [meters]
  #'divisions': [10,10,10], #Number of pores in each direction
  #'lattice_spacing': 1.0,  #spacing between pores [meters]
  #'num_pores': 1000, #This is used for random networks where spacing is irrelevant
  #'btype': [0,0,0],  #boundary type to apply to opposing faces [x,y,z] (1=periodic)
  #The following parameters are for the statistical functions used to generate
  #pore and throat size distributions.  See scipy.stats for options and parameters.
  'psd_dist': 'weibull_min',  #distribution to be used
  'psd_shape': 1.5,  #spread or skew of distribution
  'psd_loc': 6e-6,  #minimum pore diameter [meters]
  'psd_scale': 2e-5,  #controls maximum pore size
  'tsd_dist': 'weibull_min',  #distribution to be used
  'tsd_shape': 1.5,  #spread or skew of distribution
  'tsd_loc': 6e-6,  #minimum throat diameter [meters]
  'tsd_scale': 2e-5  #controls maximum throat size
  }
  
  start=clock()
  pn = OpenPNM.Geometry.Cubic(loglevel=10,**params).generate()
  
  #pn = OpenPNM.Geometry.Delaunay(loglevel=10,**params).generate()
  
  pn.throat_properties['Pc_entry'] = OpenPNM.Physics.CapillaryPressure.Washburn(pn,0.072,110)
  inlets = [0]
  #exp1 = OpenPNM.Algorithms.InvasionPercolation(pn, loglevel=10, npts=100, inlets=inlets, outlets=outlets).run()
  exp2 = OpenPNM.Algorithms.OrdinaryPercolation(pn, loglevel=10, npts=50, inv_sites=inlets).run()
  pn.update()
  
  #Write network to vtk file for visualization in Paraview
  #import os
  #OpenPNM.Visualization.NetToVtp(pn,os.path.abspath(os.path.dirname(__file__))+'\OpenPNM\\IO\\test.vtk')
  
  print clock()-start,"seconds."
  
  #vis = OpenPNM.Algorithms.Vis2D()
  #vis.overview(pn)
  
new_contents: # -*- coding: utf-8 -*-
  """
  Created on Fri Mar 08 09:43:02 2013
  
  @author: jgostick
  """
  
  import OpenPNM
  import numpy as np
  import matplotlib.pyplot as plt
  from time import clock
  
  params = {
  'domain_size': [0.001,0.001,0.0004],  #physical network size [meters]
  'divisions': [10,10,10], #Number of pores in each direction
  #'lattice_spacing': 1.0,  #spacing between pores [meters]
  'num_pores': 1000, #This is used for random networks where spacing is irrelevant
  'btype': [0,0,0],  #boundary type to apply to opposing faces [x,y,z] (1=periodic)
  #The following parameters are for the statistical functions used to generate
  #pore and throat size distributions.  See scipy.stats for options and parameters.
  'psd_dist': 'weibull_min',  #distribution to be used
  'psd_shape': 1.5,  #spread or skew of distribution
  'psd_loc': 6e-6,  #minimum pore diameter [meters]
  'psd_scale': 2e-5,  #controls maximum pore size
  'tsd_dist': 'weibull_min',  #distribution to be used
  'tsd_shape': 1.5,  #spread or skew of distribution
  'tsd_loc': 6e-6,  #minimum throat diameter [meters]
  'tsd_scale': 2e-5  #controls maximum throat size
  }
  
  start=clock()
  pn = OpenPNM.Geometry.Cubic(loglevel=10,**params).generate()
  
  #pn = OpenPNM.Geometry.Delaunay(loglevel=10,**params).generate()
  
  pn.throat_properties['Pc_entry'] = OpenPNM.Physics.CapillaryPressure().Washburn(pn,0.072,110)
  inlets = [0]
  #exp1 = OpenPNM.Algorithms.InvasionPercolation(pn, loglevel=10, npts=100, inlets=inlets, outlets=outlets).run()
  exp2 = OpenPNM.Algorithms.OrdinaryPercolation(pn, loglevel=10, npts=50, inv_sites=inlets).run()
  pn.update()
  
  #Write network to vtk file for visualization in Paraview
  #import os
  #OpenPNM.Visualization.NetToVtp(pn,os.path.abspath(os.path.dirname(__file__))+'\OpenPNM\\IO\\test.vtk')
  
  print clock()-start,"seconds."
  
  #vis = OpenPNM.Algorithms.Vis2D()
  #vis.overview(pn)
  
subject: Update to my script file to work with new Physics module conventions