code: def test_multi_mass_seeded():
      np.random.seed(5)
      T = np.random.uniform(-1000, 1000, [3, 10]).astype(np.float64)
      m = 5
  
      trivial_idx = 2
  
      Q = T[:, trivial_idx : trivial_idx + m]
  
      ref = naive.multi_mass(Q, T, m)
  
      T_subseq_isconstant = core.rolling_isconstant(T, m)
      M_T, Σ_T = core.compute_mean_std(T, m)
  
      Q_subseq_isconstant = np.expand_dims(
          T_subseq_isconstant[:, trivial_idx], 1
      )
  
      comp = _multi_mass(
          Q,
          T,
          m,
          M_T,
          Σ_T,
          M_T[:, trivial_idx],
          Σ_T[:, trivial_idx],
          T_subseq_isconstant=T_subseq_isconstant,
          Q_subseq_isconstant=Q_subseq_isconstant,
          query_idx=trivial_idx,
      )
  
      npt.assert_almost_equal(
          ref, comp, decimal=config.STUMPY_TEST_PRECISION
      )
  
imports: import functools
  import naive
  import numpy
  import numpy.testing
  import pandas
  import pytest
  from stumpy import config, core, mdl, mstump, subspace
  from stumpy.mstump import _get_first_mstump_profile, _get_multi_QT, _multi_mass, multi_distance_profile
label_desc: Use image node_id 2 for calling a global function with example usage: test_multi_mass_seeded() without return types