new_contents: from sklearn import datasets
  import numpy as np
  
  def run(self, Input):
    number_of_timesteps = 21
    end_time = 40;
    self.Time = np.linspace(0, end_time, number_of_timesteps)
    
    id = int(Input['n'])
    
    print(id)
    print('/n')
    
    iris = datasets.load_iris()
    x1 = iris.data[id,0]
    x2 = iris.data[id,1]
    x3 = iris.data[id,2]
    x4 = iris.data[id,3]
    
    self.x1 = np.zeros(number_of_timesteps)
    self.x2 = np.zeros(number_of_timesteps)
    self.x3 = np.zeros(number_of_timesteps)
    self.x4 = np.zeros(number_of_timesteps)
    
    for j in range(number_of_timesteps):
      t = self.Time[j]
      self.x1[j] = x1*np.exp(-t/15)*1.0 + np.sin(2*np.pi*t/end_time)*1.0
      self.x2[j] = x2*np.exp(-t/15)*1.0 + np.cos(2*np.pi*t/end_time)*1.0+1.0
      self.x3[j] = x3*np.exp(-t/15)*1.0 - np.cos(2*np.pi*t/end_time)*1.0 + np.sin(2*np.pi*t/end_time)*1.0
      self.x4[j] = x4*np.exp(-t/15)*1.0 - np.cos(2*np.pi*t/end_time)*1.0 - np.sin(2*np.pi*t/end_time)*1.0
  
subject: add data generator for dimensionality reduction tests