code: def swarm():
      """A contrived instance of the Swarm class at a certain timestep"""
      # fmt: off
      attrs_at_t = {
          "position": np.array([[40.95838686e-01, 5.87433429e-04, 6.49113772e-03],
                               [1.00559609e+00, 3.96477697e-02, 7.67205397e-01],
                               [8.87990950e-01, -3.64932609e-02, 1.89750725e-02],
                               [1.11646877e+00, 3.12037361e-03, 1.97885369e-01],
                               [8.96117216e-01, -9.79602053e-03, -1.66139336e-01],
                               [9.90423669e-01, 1.99307974e-03, -1.23386797e-02],
                               [2.06800701e-01, -1.67869387e-02, 1.14268810e-01],
                               [4.21786494e-01, 2.58755510e-02, 6.62254843e-01],
                               [9.90350831e-01, 3.81575154e-03, 8.80833545e-01],
                               [9.94353749e-01, -4.85086205e-02, 9.85313500e-03]]),
          "velocity": np.array([[2.09076818e-02, 2.04936403e-03, 1.06761248e-02],
                               [1.64940497e-03, 5.67924469e-03, 9.74902301e-02],
                               [1.50445516e-01, 9.11699158e-03, 1.51474794e-02],
                               [2.94238740e-01, 5.71545680e-04, 1.54122294e-02],
                               [4.10430034e-02, 6.51847479e-04, 6.25109226e-02],
                               [6.71076116e-06, 1.89615516e-04, 4.65023770e-03],
                               [4.76081378e-02, 4.24416089e-03, 7.11856172e-02],
                               [1.33832808e-01, 1.81818698e-02, 1.16947941e-01],
                               [1.22849955e-03, 1.55685312e-03, 1.67819003e-02],
                               [5.60617396e-03, 4.31819608e-02, 2.52217220e-02]]),
          "current_cost": np.array([1.07818462, 5.5647911, 19.6046078, 14.05300016, 3.72597614, 1.01169386,
                                    16.51846203, 32.72262829, 3.80274901, 1.05237138]),
          "pbest_cost": np.array([1.00362006, 2.39151041, 2.55208424, 5.00176207, 1.04510827, 1.00025284,
                                  6.31216654, 2.53873121, 2.00530884, 1.05237138]),
          "pbest_pos": np.array([[9.98033031e-01, 4.97392619e-03, 3.07726256e-03],
                                 [1.00665809e+00, 4.22504014e-02, 9.84334657e-01],
                                 [1.12159389e-02, 1.11429739e-01, 2.86388193e-02],
                                 [1.64059236e-01, 6.85791237e-03, -2.32137604e-02],
                                 [9.93740665e-01, -6.16501403e-03, -1.46096578e-02],
                                 [9.90438476e-01, 2.50379538e-03, 1.87405987e-05],
                                 [1.12301876e-01, 1.77099784e-03, 1.45382457e-01],
                                 [4.41204876e-02, 4.84059652e-02, 1.05454822e+00],
                                 [9.89348409e-01, -1.31692358e-03, 9.88291764e-01],
                                 [9.99959923e-01, -5.32665972e-03, -1.53685870e-02]]),
          "best_cost": 1.0002528364353296,
          "best_pos": np.array([9.90438476e-01, 2.50379538e-03, 1.87405987e-05]),
          "options": {'c1': 0.5, 'c2': 0.3, 'w': 0.9},
      }
      # fmt: on
      return Swarm(**attrs_at_t)
  
imports: import numpy
  import pytest
  from pyswarms.backend.swarms import Swarm
label_desc: Use image node_id 1 for calling a global function with example usage: swarm() and returns: Swarm