text: """
  Classes for easy interpolation of trajectories and Curves.
  Requires Scipy installed.
  """
  
  import numpy as np
  
  class Interpolator:
      """ Poorman's linear interpolator, doesn't require Scipy. """
      
      def __init__(self, tt=None, ss=None, ttss = None, left=None, right=None):
  
          if ttss is not None:
              tt, ss = zip(*ttss)
          
          self.tt = 1.0*np.array(tt)
          self.ss = 1.0*np.array(ss)
          self.left = left
          self.right = right
          self.tmin, self.tmax = min(tt), max(tt)
  
      def __call__(self, t):
          return np.interp(t, self.tt, self.ss, self.left, self.right)
  
  class Trajectory:
  
      def __init__(self, tt, xx, yy):
  
          self.tt = 1.0*np.array(tt)
          self.xx = np.array(xx)
          self.yy = np.array(yy)
          self.update_interpolators()
  
      def __call__(self, t):
          return np.array([self.xi(t), self.yi(t)])
  
      def addx(self, x):
          return Trajectory(self.tt, self.xx+x, self.yy)
  
      def addy(self, y):
          return Trajectory(self.tt, self.xx, self.yy+y)
  
      def update_interpolators(self):
          self.xi =  Interpolator(self.tt, self.xx)
          self.yi =  Interpolator(self.tt, self.yy)
      
      def txy(self, tms=False):
          return zip((1000 if tms else 1)*self.tt, self.xx, self.yy)
  
      def to_file(self, filename):
          np.savetxt(filename, np.array(self.txy(tms=True)),
                     fmt="%d", delimiter='\t')
  
      @staticmethod
      def from_file(filename):
          arr = np.loadtxt(filename, delimiter='\t')
          tt, xx, yy = arr.T
          return Trajectory(1.0*tt/1000, xx, yy)
  
      @staticmethod
      def save_list(trajs, filename):
          N = len(trajs)
          arr = np.hstack([np.array(list(t.txy(tms=True))) for t in trajs])
          np.savetxt( filename, arr, fmt="%d", delimiter='\t',
                      header = "\t".join(N*['t(ms)', 'x', 'y']))
      
      @staticmethod
      def load_list(filename):
          arr = np.loadtxt(filename, delimiter='\t').T
          Nlines = arr.shape[0]
          return [Trajectory(tt=1.0*a[0]/1000, xx=a[1], yy=a[2])
                  for a in np.split(arr, Nlines/3)]
  