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