I'm following the vegan tutorial on procrustes analysis:

Now with Python I can choose either:

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  CodePudding user response：

  The manner in which the vegan package runs through monoMDS doesn't seem to align with any of the methods that Python uses. The code in vegan is all based on Fortran. You could link the Fortan to Python, just like you can in R.

  While the scaling is different, the rotation matrix within vare.proc is exactly the same as the rotation matrix (array?) in the Python coded object above vare_proc. I found that to be interesting.

  If I bring in the pieces of the content in R for your object vare.proc, I can make the exact graph.

  First, I used R Markdown to share objects between Python and R.

  # compare to R
  # vpR = vareProc$rotation
  vpR_py = r.vpR    
  # vpYrot = vareProc$Yrot
  vpYrot_py = r.vpYrot
  # vpX = vareProc$X
  vpX_py = r.vpX
  

  Then I used these objects to make the replica

  # build the plot exactly like vegan 
  # using https://github.com/vegandevs/vegan/blob/master/R/plot.procrustes.R
  tails = vpYrot_py
  heads = vpX_py
  
  # find the ranges
  xMax = max(abs(np.hstack((tails[:,0], heads[:,0]))))
  yMax = max(abs(np.hstack((tails[:,1], heads[:,1]))))
  
  plt.figure(dpi = 100) 
  fig, ax = plt.subplots()
  ax.set_aspect('equal')
  ax.set_xlim(-xMax, xMax)
  ax.set_ylim(-yMax, yMax)
  
  # add points
  ax.scatter(x = tails[:,0],
             y = tails[:,1],
             facecolors = 'none',
             edgecolors = 'k')
  
  # add origin axes
  ax.axhline(y = 0, color='k', ls = '--', linewidth = 1) # using dashed for origin
  ax.axvline(x = 0, color='k', ls = '--', linewidth = 1)
  
  # add rotation axes
  ax.axline(xy1 = (0, 0), color = 'k',
            slope = vpR_py[0, 1]/vpR_py[0, 0])
  ax.axline(xy1 = (0, 0), color = 'k',
            slope = vpR_py[1, 1]/vpR_py[1, 0])
  
  # add arrows
  for i in range(0, len(tails)):
    ax.annotate("", xy = heads[i,:],
                xycoords = 'data',
                xytext = tails[i,:], 
                arrowprops=dict(arrowstyle="->",
                                color = 'blue'))
  
  plt.tight_layout(pad = 2)
  plt.show()
  

  From matplotlib

  

  From vegan