old_contents: import numpy as np
  import matplotlib.pyplot as plt
  import matplotlib
  from mpl_toolkits.mplot3d import Axes3D
  import sys
  
  import numpy.ma as ma
  
  fuz = 1/4.;
  if (len(sys.argv) < 2) :
  	print("Usage: \n dataplot.py path_to_binfile [clamp value]")
  	sys.exit()
  elif (len(sys.argv) > 2) :
  	fuz = float(sys.argv[2])
  binfile = sys.argv[1]
  linedata = []
  minLength = 200.0
  tend = 151
  tbegin = 80
  for i in np.linspace(tbegin,tend,15) :
      lengthdata=np.fromfile(binfile+str(int(i))+'_lengths.bin', dtype="float32")
      winddata=np.fromfile(binfile+str(int(i))+'_windings.bin', dtype="float32")
      datasize = int(np.sqrt(lengthdata.shape[0]))
      lengthdata=lengthdata.reshape(datasize, datasize)
      winddata=winddata.reshape(datasize, datasize)
      masked= ma.masked_where(lengthdata<minLength,winddata)
  #    masked = masked.filled(0)
      linedata.append((masked[datasize/2,:],str(int(i))))
  fig = plt.figure()
  ax = fig.add_subplot(111)
  matplotlib.rcParams['legend.numpoints'] = 1
  cmap = matplotlib.cm.get_cmap('jet')
  #Wist je dat dit ook zonder forloop kan?
  for dataset,i in linedata :
      x = np.linspace(0,np.pi,datasize)
      ax.plot(x,-1.*dataset,'.',label='t='+i, color=cmap((int(i)-tbegin)/float(tend-tbegin)))
  #ax.set_ylim([-0.5,4.0])
  #ax.set_xlim([x[0],x[800]])
  ax.set_ylabel('Winding number')
  ax.set_xlabel(r'$\sim r$')
  #plt.colorbar()
  plt.legend(loc=1)
  sizes = fig.get_size_inches()
  fig.set_size_inches(sizes[0]*2,sizes[1]*2)
  plt.savefig('tobiastestdingen.png')
  
new_contents: import numpy as np
  import matplotlib.pyplot as plt
  import matplotlib
  from mpl_toolkits.mplot3d import Axes3D
  import sys
  
  import numpy.ma as ma
  
  fuz = 1/4.;
  if (len(sys.argv) < 2) :
  	print("Usage: \n dataplot.py path_to_binfile [clamp value]")
  	sys.exit()
  elif (len(sys.argv) > 2) :
  	fuz = float(sys.argv[2])
  binfile = sys.argv[1]
  linedata = []
  minLength = 400.0
  tend = 290
  tbegin = 0
  for i in np.linspace(tbegin,tend,30) :
      lengthdata=np.fromfile(binfile+str(int(i))+'_lengths.bin', dtype="float32")
      winddata=np.fromfile(binfile+str(int(i))+'_windings.bin', dtype="float32")
      datasize = int(np.sqrt(lengthdata.shape[0]))
      lengthdata=lengthdata.reshape(datasize, datasize)
      winddata=winddata.reshape(datasize, datasize)
      masked= ma.masked_where(lengthdata<minLength,winddata)
  #    masked = masked.filled(0)
      linedata.append((masked[datasize/2,:],str(int(i))))
  fig = plt.figure()
  ax = fig.add_subplot(111)
  matplotlib.rcParams['legend.numpoints'] = 1
  cmap = matplotlib.cm.get_cmap('jet')
  #Wist je dat dit ook zonder forloop kan?
  for dataset,i in linedata :
      x = np.linspace(0,np.pi,datasize)
      ax.plot(x,-1.*dataset,'.',label='t='+i, color=cmap((int(i)-tbegin)/float(tend-tbegin)))
  #ax.set_ylim([-0.5,4.0])
  #ax.set_xlim([x[0],x[800]])
  ax.set_ylabel('Winding number')
  ax.set_xlabel(r'$\sim r$')
  #plt.colorbar()
  plt.legend(loc=1)
  sizes = fig.get_size_inches()
  fig.set_size_inches(sizes[0]*2,sizes[1]*2)
  plt.savefig('tobiastestdingen.png')
  
subject: Correct parameters for the paper