name: nedc_eval_eeg
synopsis: nedc_eval_eeg [options] ref.txt hyp.txt
descr: evaluates hypotheses using standard scoring metrics

options:
 -o, --odir: the output directory [$PWD/output]
 -p, --parameters: scoring parameters [nedc_eval_eeg_params_v00.txt]
 -c, --competition: use competition version of this software
 
arguments:
 ref.txt: a list of reference annotation files (see below)
 hyp.txt: a list of hypothesis files (see below)

example:
 nedc_eval_eeg -odir ./output/report ref.list hyp.list

  generates a scoring report and outputs it to the default directory.
  the report contains results of the following algorithms:
    (1) NEDC's dynamic programming alignment scoring algorithm (dpalign)
    (2) NEDC's epoch scoring algorithm: (epoch)
    (3) NEDC's overlap scoring algorithm (ovlp)
    (4) NEDC's time-aligned event scoring algorithm (taes)
    (5) NEDC's inter-rater agreement (ira) (not included in comp version)

notes:

(1) When run in competition mode, the inputs are single files
    containing all the data to be scored. When run in research
    mode (the default), this inputs are files lists of all the hypothesis
    files.

(2) When using competition version, --parameters may not be used.

(3) To learn more about these algorithms, see this publication:

    Shah, V., Golmohammadi, M., Obeid, I., & Picone,
    J. (2021). Objective Evaluation Metrics for Automatic
    Classification of EEG Events. In I. Obeid, I. Selesnick, &
    J. Picone (Eds.), Biomedical Signal Processing: Innovation and
    Applications (1st ed., pp. 1–26). Springer. (Download).