Installing the development version#

Note

Conda and pip are not available for this experimental research code.

Currently only the bleeding-edge developer version is available for beta testing. We currently use a custom-patched version of ccdproc for reading in datasets. You will need to install this patch-ed ccdproc before installing ynot:

Navigate the your source directory in the ynot repository:

$ conda env create -f environment_torch1p6.yml
$ conda activate environment_torch1p6
$ git clone https://github.com/gully/ccdproc.git
$ cd ccdproc
$ git checkout unfixable_hdr_key_workaround
$ python setup.py develop

Once that is complete, you can navigate to this project:

$ cd your-ynot-path
$ python setup.py develop

And voila! It should work. You can run the tests in tests to double-check and benchmark GPU/CPU performance:

$ py.test -vs

Requirements#

The project may work with a variety of Python 3 minor versions, though none have been tested. The project has been developed with:

  • Python: 3.8

  • PyTorch: 1.6 or later.

  • ccdproc (custom-patched on Nov 17, 2020)

  • CUDA 10.2