code: def _corr_tseries(tseries1, tseries2):
      """Compute the correlation between two sets of time series."""
      corr = np.zeros(tseries1.shape[1])
      for ind in range(tseries1.shape[1]):
          corr[ind], _ = pearsonr(tseries1[:, ind], tseries2[:, ind])
      return corr
  
imports: import re
  import numpy
  import pandas
  import pytest
  from nibabel import Nifti1Image
  from scipy.stats import pearsonr
  from sklearn.preprocessing import scale
  from nilearn._utils.data_gen import create_fake_bids_dataset
  from nilearn._utils.fmriprep_confounds import to_camel_case
  from nilearn.conftest import _rng
  from nilearn.interfaces.bids import get_bids_files
  from nilearn.interfaces.fmriprep import load_confounds
  from nilearn.interfaces.fmriprep.load_confounds import _check_strategy, _load_single_confounds_file
  from nilearn.interfaces.fmriprep.tests._testing import create_tmp_filepath, get_legal_confound
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 7 for calling a global function with example usage: _corr_tseries(tseries1, tseries2) and returns: corr