Installing spit¶
This document describes how to install the spit repository.
Installing Dependencies¶
There are a number of non-standard dependencies related to the CNN(s) that lie within SPIT.
In general, we recommend that you use Anaconda for the majority of these installations.
Detailed installation instructions are presented below:
Python Dependencies¶
specdb depends on the following list of Python packages.
We recommend that you use Anaconda to install and/or update these packages.
- python versions 2.7, or 3.6 or later [2.7 will be phased out]
- numpy version 1.13 or later
- astropy version 3.0 or later
- scipy version 0.19 or later
- tensorflow version 1.4.1 or later
- pillow version 4.2 or later
- prettytensor version 0.7.4 or later [This dependency may be eventually eliminated]
If you are using Anaconda, you can check the presence of these packages with:
conda list "^python|numpy|astropy|scipy|tensorflow|pillow|prettytensor"
If the packages have been installed, this command should print out all the packages and their version numbers.
If any of these packages are missing you can install them with a command like:
pip install tensorflow
If any of the packages are out of date, they can be updated with a command like:
conda update scipy
# orL
pip update tensorflow
Installing spit¶
Presently, you must download the code from github:
#go to the directory where you would like to install specdb.
git clone https://github.com/PYPIT/spit.git
From there, you can build and install with
cd spit python setup.py install # or use develop
This should install the package and scripts. Make sure that your PATH includes the standard location for Python scripts (e.g. ~/anaconda/bin)
Installing Architectures¶
SPIT needs a trained CNN architecture to perform its `magic’. At present, there is only one (trained on Kast images).
Kast¶
Trained on a set of Kast images as described in Jankov & Prochaska (2018). Appears to work relatively well on other instruments (not extensively tested).
kast_original (unpacks to 811Mb)
- Original CNN generated by Vik Jankov as described in Yankoff & Prochaska (2018)
- Download the folder from this Google Drive
- cd spit/data/checkpoints/
- Unpack the downloaded zip file
- It should be named kast_original