old_contents: """
  Simple example to vary streamline thickness based on the vector amplitudes
  =================================
  """
  import numpy as np
  import matplotlib.pyplot as plt
  
  from discretize import TensorMesh
  
  ###############################################################################
  # Create mesh
  # -----
  #
  # Minimum cell size in each direction
  dx = 1.
  dy = 1.
  dz = 1.
  
  # Number of core cells in each direction
  nCoreX = 43.
  nCoreY = 43.
  nCoreZ = 43.
  
  # Cell widths
  hx = [(dx,nCoreX)]
  hy = [(dy,nCoreY)]
  hz = [(dz,nCoreZ)]
  
  # Desired Core mesh origin (Bottom SW corner)
  x0 = -21.5
  y0 = -21.5
  z0 = -21.5
  
  mesh = TensorMesh([hx, hy, hz],[x0,y0,z0])
  print(mesh.nC)
  
  ###############################################################################
  #
  # Define arbitrary function to plot
  #
  
  X = mesh.gridCC[:,0]
  Y = mesh.gridCC[:,1]
  Z = mesh.gridCC[:,2]
  
  U = -1 - X**2 + Y + Z
  V = 1 + X - Y**2 + Z
  W = 1 + X + Y - Z**2
  
  ###############################################################################
  # Plot streamlines
  # ----------------------
  #
  # Create figure
  fig = plt.figure()
  ax = plt.subplot(111)
  fig.set_figheight(15)
  fig.set_figwidth(15)
  labelsize = 30.
  ticksize = 30.
  
  # Create data vector
  dataVec = np.hstack([U,V,W])
  print(dataVec.shape)
  
  # Set streamline plotting options
  streamOpts = {'color':'w', 'density':2.0}
  pcolorOpts = {"cmap":"viridis"}
  
  dat = mesh.plotSlice(dataVec, ax=ax, normal='Z', ind=5, vType='CCv', view='vec', streamOpts=streamOpts, gridOpts={"color":"k", "alpha":0.1}, grid=True, clim=None, stream_thickness=3)
  
  ###############################################################################
  # Print the version of SimPEG and dependencies
  # --------------------------------------------
  #
  
  versions()
  
  ###############################################################################
  # Moving Forward
  # --------------
  #
  # If you have suggestions for improving this example, please create a `pull request on the example in discretize
  
new_contents: """
  Simple example to vary streamline thickness based on the vector amplitudes
  =================================
  """
  import numpy as np
  import matplotlib.pyplot as plt
  
  from discretize import TensorMesh
  
  ###############################################################################
  # Create mesh
  # -----
  #
  # Minimum cell size in each direction
  dx = 1.
  dy = 1.
  dz = 1.
  
  # Number of core cells in each direction
  nCoreX = 43.
  nCoreY = 43.
  nCoreZ = 43.
  
  # Cell widths
  hx = [(dx,nCoreX)]
  hy = [(dy,nCoreY)]
  hz = [(dz,nCoreZ)]
  
  # Desired Core mesh origin (Bottom SW corner)
  x0 = -21.5
  y0 = -21.5
  z0 = -21.5
  
  mesh = TensorMesh([hx, hy, hz],[x0,y0,z0])
  print(mesh.nC)
  
  ###############################################################################
  #
  # Define arbitrary function to plot
  #
  
  X = mesh.gridCC[:,0]
  Y = mesh.gridCC[:,1]
  Z = mesh.gridCC[:,2]
  
  U = -1 - X**2 + Y + Z
  V = 1 + X - Y**2 + Z
  W = 1 + X + Y - Z**2
  
  ###############################################################################
  # Plot streamlines
  # ----------------------
  #
  # Create figure
  fig = plt.figure()
  ax = plt.subplot(111)
  fig.set_figheight(15)
  fig.set_figwidth(15)
  labelsize = 30.
  ticksize = 30.
  
  # Create data vector
  dataVec = np.hstack([U,V,W])
  print(dataVec.shape)
  
  # Set streamline plotting options
  streamOpts = {'color':'w', 'density':2.0}
  pcolorOpts = {"cmap":"viridis"}
  
  dat = mesh.plotSlice(dataVec, ax=ax, normal='Z', ind=5, vType='CCv', view='vec', streamOpts=streamOpts, gridOpts={"color":"k", "alpha":0.1}, grid=True, clim=None, stream_thickness=3)
  
  ###############################################################################
  # Moving Forward
  # --------------
  #
  # If you have suggestions for improving this example, please create a `pull request on the example in discretize
  
subject: Remove version printing