code: def _tseries_std(
      img,
      mask_img,
      confounds,
      sample_mask,
      standardize_signal=False,
      standardize_confounds=True,
      detrend=False,
  ):
      """Get the std of time series in a mask."""
      masker = NiftiMasker(
          mask_img=mask_img,
          standardize=standardize_signal,
          standardize_confounds=standardize_confounds,
          detrend=detrend,
      )
      tseries = masker.fit_transform(
          img, confounds=confounds, sample_mask=sample_mask
      )
      return tseries.std(axis=0)
  
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 5 for calling a global function with example usage: _tseries_std(img, mask_img, confounds, sample_mask, standardize_signal, standardize_confounds, detrend) and returns: tseries