code: def optical_density(raw, *, verbose=None):
      r"""Convert NIRS raw data to optical density.
  
      Parameters
      ----------
      raw : instance of Raw
          The raw data.
      %(verbose)s
  
      Returns
      -------
      raw : instance of Raw
          The modified raw instance.
      """
      raw = raw.copy().load_data()
      _validate_type(raw, BaseRaw, "raw")
      picks = _validate_nirs_info(raw.info, fnirs="cw_amplitude")
  
      # The devices measure light intensity. Negative light intensities should
      # not occur. If they do it is likely due to hardware or movement issues.
      # Set all negative values to abs(x), this also has the benefit of ensuring
      # that the means are all greater than zero for the division below.
      if np.any(raw._data[picks] <= 0):
          warn("Negative intensities encountered. Setting to abs(x)")
          min_ = np.inf
          for pi in picks:
              np.abs(raw._data[pi], out=raw._data[pi])
              min_ = min(min_, raw._data[pi].min() or min_)
          # avoid == 0
          for pi in picks:
              np.maximum(raw._data[pi], min_, out=raw._data[pi])
  
      for pi in picks:
          data_mean = np.mean(raw._data[pi])
          raw._data[pi] /= data_mean
          np.log(raw._data[pi], out=raw._data[pi])
          raw._data[pi] *= -1
          raw.info["chs"][pi]["coil_type"] = FIFF.FIFFV_COIL_FNIRS_OD
  
      return raw
  
imports: import numpy
  from ..._fiff.constants import FIFF
  from ...io import BaseRaw
  from ...utils import _validate_type, verbose, warn
  from ..nirs import _validate_nirs_info
label_desc: Use image node_id 1 for calling a global function with example usage: optical_density(raw) and returns: raw