code: def _init_random_gaussians(self, X):
          
  
          n_samples = np.shape(X)[0]
          self.priors = (1 / self.k) * np.ones(self.k)
          for _ in range(self.k):
              params = {}
              params["mean"] = X[np.random.choice(range(n_samples))]
              params["cov"] = calculate_covariance_matrix(X)
              self.parameters.append(params)
docs: Initialize gaussian randomly