code: def dmtx_light(
      frametimes,
      paradigm=None,
      hrf_model="canonical",
      drift_model="cosine",
      hfcut=128,
      drift_order=1,
      fir_delays=[0],
      add_regs=None,
      add_reg_names=None,
      min_onset=-24,
      path=None,
  ):
      """Make a design matrix while avoiding framework
  
      Parameters
      ----------
      see make_dmtx, plus
      path: string, optional: a path to write the output
  
      Returns
      -------
      dmtx array of shape(nreg, nbframes):
          the sampled design matrix
      names list of strings of len (nreg)
          the names of the columns of the design matrix
      """
      dmtx_ = make_dmtx(
          frametimes,
          paradigm,
          hrf_model,
          drift_model,
          hfcut,
          drift_order,
          fir_delays,
          add_regs,
          add_reg_names,
          min_onset,
      )
      if path is not None:
          dmtx_.write_csv(path)
      return dmtx_.matrix, dmtx_.names
  
file_path: nipy/nipy/modalities/fmri/design_matrix.py
imports: from warnings import warn
  import numpy
  from .hemodynamic_models import _orthogonalize, compute_regressor
label_desc: Use image node_id 9 for calling a global function with example usage: dmtx_light(frametimes, paradigm, hrf_model, drift_model, hfcut, drift_order, fir_delays, add_regs, add_reg_names, min_onset, path) and returns: dmtx_,  dmtx_