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eeg storage in hdf5 + related functions

Project description

# eeghdf

Project to develop a easily accessible format for storing EEG in a way that is easy to access for machine learning.

## Simple install for developers - change to the desired python environment ` git clone pip install -e eeghdf ` - or if you just want to install as a requirement into a virtual env. Put this into your requirements.txt. The repo will be cloned into ./src/eeghdf and installed ` -e git+ ` ## To Do

  • [x] code to write file, target initial release version is 1000
  • [X] initial scripts to convert edf to eeghdf and floating point hdf5
  • [x] code to subsample and convert edf -> eeghdf
  • [ ] code to write back to edf
  • [ ] more visualization code -> push to eegvis
  • [x] add convenience interface to phys_signal with automagic conversion from digital->phys units
  • [ ] add study admin code to record info (do not seem to include this now, e.g. EEG No like V17-105)
  • [ ] code to clip and create subfiles - [ ] allow patient info to propagate - [ ] hash list/tree of history of file so that can track provenance of waveforms if desired - [ ] clip and maintain correct (relative) times
  • [ ] consider how to handle derived records: for example the downsampled float32 records “frecord200Hz”

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