code: def vclose(L, V):
      
      lam, X = 0, []
      for k in range(3):
          lam = lam + V[k] * L[k]
      beta = np.sqrt(1. - lam**2)
      for k in range(3):
          X.append((old_div((V[k] - lam * L[k]), beta)))
      return X
docs: gets the closest vector