As a note: The name gedipy seems to already be taken on pipy.

This means, in case this project will develop into a package we would need to distribute it under another name, or kindly ask the other team if it would be possible to get the name from them.

Distributing it via pip install gedipy is currently not an option.

Hello @armstonj

as discussed before I took some time investigating the use of dask/ xarray for data processing and integration into gedipy.

You can find insight I gathered about the integration into the current library in this notebook and general information about data processing with h5py, xarray and dask here.

Overall I would say xarray and dask

• could be useful for new functionality i.e. taking the output of read_shots() or with an addition for reading and writing data.
• still also have limitations for reshaping arrays i.e. 1D waveform to 2D (or require very specific expert knowledge)
  (As a side note I have not used dask too much before and there might be better way's of going about using it. I found it very interesting to get to know it more and I think it's overall benefit shows on distributed clusters not necessarily on small machines, which I used. More in the notebooks)

Let me know if you would find it interesting to merge my experiments and I'd be happy to set up a PR. There were also a couple general additions in my dask-integration branch I could extract if they are of interest. I hope this helps the library a little.

Numpy-docs doc string style as the recommended way of writing doc-strings. I'll start implementing a couple examples.

open() is a Python build in function. It is generally not recommended to use Python build in function names, like open as names for custom functions. def open() is currently used as function name in h5io.py. Is this intentional or by mistake? Maybe I can learn something new? :)

For documentation purposes: read_pgap_theta_z(), read_tx_waveform() and read_rx_waveform() all have very similar code.
There might be potential to create a separate class or create shareable functionality (i.e. read data, process data, write data).