code: def _get_transformer():
      n_steps = 100
      n_elec = 8
      label_map = {"rock": 0, "scissors": 1, "paper": 2, "ok": 3}
      margin = 1000
      data = load_emg()
      data = data[data.label != "rest"]
      emg_data = {
          "time_vec": gs.array(data.time),
          "raw_data": gs.array(data[[f"c{i}" for i in range(8)]]),
          "label": gs.array(data.label),
          "exp": gs.array(data.exp),
      }
  
      return TimeSeriesCovariance(
          emg_data, n_steps, n_elec, label_map, margin
      )
  
file_path: geomstats/tests/tests_geomstats/test_datasets/test_prepare_emg_data.py
imports: import pytest
  import geomstats.backend
  from geomstats.datasets.prepare_emg_data import TimeSeriesCovariance
  from geomstats.datasets.utils import load_emg
  from geomstats.test.parametrizers import DataBasedParametrizer
  from geomstats.test.test_case import TestCase, np_and_autograd_only, pytorch_backend
  from .data.prepare_emg_data import TimeSeriesCovarianceTestData
label_desc: Use image node_id 1 for calling a global function with example usage: _get_transformer() and returns: TimeSeriesCovariance