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  1. def getGaussian(xvect, mewk, sigmak):
  2.  
  3.     xi = np.zeros((l,1))
  4.     for i in range(len(xi)):
  5.         xi[i][0] = xvect[i]
  6.     #print(xi)
  7.  
  8.     det_sigmak = np.linalg.det(sigmak)
  9.     det_sigmak = np.absolute(det_sigmak)
  10.     # print("sigmak",sigmak)
  11.     # print("det_sigmak",det_sigmak)
  12.  
  13.     if(det_sigmak == 0):
  14.         print("determinant zero")
  15.         det_sigmak = 0.0000001
  16.  
  17.     inv_sigmak = np.linalg.inv(sigmak)
  18.     constant = 1.0 / (np.sqrt((np.power(2*np.pi,l)) * det_sigmak))
  19.     #print("deno const",np.sqrt((np.power(2*np.pi,dim)) * det_sigmak))
  20.     #print("constant:", constant)
  21.  
  22.     #print("xi", xi)
  23.     #print("mewk", mewk)
  24.  
  25.     xi_min_mewk = np.subtract(xi,mewk)
  26.  
  27.     # print(xi_min_mewk,"\nhh",inv_sigmak)
  28.  
  29.     #print("trans",np.transpose(xi_min_mewk))
  30.     #print("inve sigmak", inv_sigmak)
  31.     temp = np.dot(np.transpose(xi_min_mewk),inv_sigmak)
  32.     #print("temp",temp)
  33.     #print("ximinmewk", xi_min_mewk)
  34.     exp_val = np.dot(temp,xi_min_mewk)
  35.     exp_val = -0.5 * exp_val
  36.     #print("exp val:",exp_val)
  37.  
  38.     #print("sigmak",sigmak)
  39.  
  40.     #print(np.multiply(5,mewk))
  41.  
  42.     if(exp_val < -500):
  43.         exp_val = -500
  44.     elif (exp_val > 500):
  45.         exp_val = 500
  46.  
  47.     ans = constant*np.exp(exp_val)
  48.     #print("gaussian",ans)
  49.     return ans
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