parameters: (scatter_matrix, eig_val_sc, eig_vec_sc)
return_statement: return True
docstring: Verify if the eigen values of the scatter matrix were made correctly.
          Test consists in asserting that the covariance and eigen vector product equals the eigen value and eigen vector.
docstring_summary: Verify if the eigen values of the scatter matrix were made correctly.
          Test consists in asserting that the covariance and eigen vector product equals the eigen value and eigen vector.
docstring_tokens: Verify if the eigen values of the scatter matrix were made correctly . Test consists in asserting that the covariance and eigen vector product equals the eigen value and eigen vector .
function: def verify_eigen_values(scatter_matrix, eig_val_sc, eig_vec_sc):
      """
          Verify if the eigen values of the scatter matrix were made correctly.
          Test consists in asserting that the covariance and eigen vector product equals the eigen value and eigen vector.
      """
      for i in range(len(eig_val_sc)):
          eigv = eig_vec_sc[:, i].reshape(1, 3).T
          np.testing.assert_array_almost_equal(
              scatter_matrix.dot(eigv),
              eig_val_sc[i] * eigv,
              decimal=6,
              err_msg="",
              verbose=True,
          )
      # test eigen vectors module to equal one
      for ev in eig_vec_sc:
          np.testing.assert_array_almost_equal(1.0, np.linalg.norm(ev))
      return True
function_tokens: def verify_eigen_values ( scatter_matrix , eig_val_sc , eig_vec_sc ) : for i in range ( len ( eig_val_sc ) ) : eigv = eig_vec_sc [ : , i ] . reshape ( 1 , 3 ) . T np . testing . assert_array_almost_equal ( scatter_matrix . dot ( eigv ) , eig_val_sc [ i ] * eigv , decimal = 6 , err_msg = "" , verbose = True , ) # test eigen vectors module to equal one for ev in eig_vec_sc : np . testing . assert_array_almost_equal ( 1.0 , np . linalg . norm ( ev ) ) return True