code: def design_matrix_light(
      frame_times,
      events=None,
      hrf_model="glover",
      drift_model="cosine",
      high_pass=0.01,
      drift_order=1,
      fir_delays=None,
      add_regs=None,
      add_reg_names=None,
      min_onset=-24,
  ):
      """Same as make_first_level_design_matrix, \
      but only returns the computed matrix and associated name."""
      fir_delays = fir_delays or [0]
      dmtx = make_first_level_design_matrix(
          frame_times,
          events,
          hrf_model,
          drift_model,
          high_pass,
          drift_order,
          fir_delays,
          add_regs,
          add_reg_names,
          min_onset,
      )
      _, matrix, names = check_design_matrix(dmtx)
      return matrix, names
  
imports: from os import path
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from nilearn._utils.data_gen import basic_paradigm
  from nilearn.glm.first_level.design_matrix import _convolve_regressors, check_design_matrix, create_cosine_drift, make_first_level_design_matrix, make_second_level_design_matrix
  from ._testing import block_paradigm, design_with_negative_onsets, modulated_block_paradigm, modulated_event_paradigm, spm_paradigm
label_desc: Use image node_id 1 for calling a global function with example usage: design_matrix_light(frame_times, events, hrf_model, drift_model, high_pass, drift_order, fir_delays, add_regs, add_reg_names, min_onset) and returns: matrix,  names