class_docstr: Classify ICA components using a specific training dataset (<thresh> is in the range 0-100, typically 5-20).
class_docstr_tok: ["Classify","ICA","components","using","a","specific","training","dataset","(","<","thresh",">","is","in","the","range","0-100",",","typically","5-20",")","."]
code: def _gen_artifacts_list_file(self, mel_ica, thresh):
      _, trained_wts_file = os.path.split(self.inputs.trained_wts_file)
      trained_wts_filestem = trained_wts_file.split(".")[0]
      filestem = "fix4melview_" + trained_wts_filestem + "_thr"
  
      fname = os.path.join(mel_ica, filestem + str(thresh) + ".txt")
      return fname
  
imports: from ..base import TraitedSpec, CommandLineInputSpec, CommandLine, InputMultiPath, OutputMultiPath, BaseInterface, BaseInterfaceInputSpec, traits, Directory, File, isdefined
  import os
label_desc: Use image node_id 1 for calling the Classifier obj's underlying member method code with example usage: obj._gen_artifacts_list_file(mel_ica, thresh) and returns: fname