add dockerfile

Dockerfile

@@ -0,0 +1,24 @@
+# syntax=docker/dockerfile:1
+FROM nvcr.io/nvidia/tensorflow:19.10-py3
+ENV DEBIAN_FRONTEND=noninteractive
+RUN apt update
+
+# install necessary latex packages
+RUN curl -L -o install-tl-unx.tar.gz https://ftp.math.utah.edu/pub/tex/historic/systems/texlive/2024/install-tl-unx.tar.gz
+RUN zcat < install-tl-unx.tar.gz | tar xf -
+RUN cd install-tl-2* && perl install-tl --no-interaction --scheme=small
+ENV PATH="/usr/local/texlive/2024/bin/x86_64-linux:${PATH}"
+RUN tlmgr install type1cm cm-super dvipng
+
+ENV MY_ASTRO_DATA=/astro_data
+ENV SDSS_LOCAL_SAS_MIRROR=$MY_ASTRO_DATA/sdss_mirror
+ENV GAIA_TOOLS_DATA=$MY_ASTRO_DATA/gaia_mirror
+ENV DUST_DIR=$MY_ASTRO_DATA/mwdust_mirror
+RUN mkdir $MY_ASTRO_DATA $SDSS_LOCAL_SAS_MIRROR $GAIA_TOOLS_DATA $DUST_DIR
+RUN git clone https://github.com/henrysky/astroNN_spectra_paper_figures.git
+WORKDIR /workspace/astroNN_spectra_paper_figures
+RUN pip install -r requirements.txt
+RUN mkdir data_files figs
+RUN curl --cookie zenodo-cookies.txt "https://zenodo.org/records/13290056/files/__train.h5.h5?download=1" --output __train.h5.h5
+RUN curl --cookie zenodo-cookies.txt "https://zenodo.org/records/13290056/files/_highsnr_test.h5?download=1" --output _highsnr_test.h5
+RUN curl --cookie zenodo-cookies.txt "https://zenodo.org/records/13290056/files/aspcap_training.h5?download=1" --output aspcap_training.h5

README.rst

@@ -18,6 +18,9 @@ entire APOGEE DR14 dataset. Simultaneously, we release ``astroNN``, a well-teste
 developed for this work, but that is also designed to be a general package for deep learning in astronomy. ``astroNN`` is
 available at https://github.com/henrysky/astroNN with extensive documentation at http://astroNN.readthedocs.io.
 
+.. contents:: **Table of Contents**
+    :depth: 3
+
 Getting Started
 =================
 
@@ -41,6 +44,35 @@ Some notebooks make use of my `milkyway_plot`_ to plot on milkyway.
 
 To continuum normalize arbitrary APOGEE spectrum with v1.0.0, see: https://astronn.readthedocs.io/en/v1.0.0/tools_apogee.html#continuum-normalization-of-apogee-spectra
 
+Docker Image
+----------------
+
+If you have `Docker`_ installed, you can use the `Dockerfile`_ to build a Docker image upon Pytorch container from `NVIDIA NGC Catalog`_ with all dependencies installed and data files downloaded.
+
+.. _NVIDIA NGC Catalog: https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch
+.. _Dockerfile: Dockerfile
+.. _Docker: https://www.docker.com/
+
+To build the Docker image called ``astronn_spectra_paper_figures``, run the following command in the root directory of this repository:
+
+.. code-block:: bash
+
+    docker build -t astronn_spectra_paper_figures .
+
+To run the Docker container with all GPU available to the container named ``testing123``, run the following command:
+
+.. code-block:: bash
+    
+    docker run --gpus all --name testing123 -it -e SHELL=/bin/bash --entrypoint bash astronn_spectra_paper_figures
+
+Then you can attach to the container by running:
+
+.. code-block:: bash
+
+    docker exec -it testing123 bash
+
+Now you can run all notebooks or training script inside the container
+
 Jupyter Notebook
 ------------------
 -   | `Datasets_Data_Reduction.ipynb`_
@@ -192,11 +224,11 @@ To load it with python
 Authors
 =================
 -  | **Henry Leung** - henrysky_
-   | Student, Department of Astronomy and Astrophysics, University of Toronto
+   | Department of Astronomy and Astrophysics, University of Toronto
    | Contact Henry: henrysky.leung [at] utoronto.ca
 
 -  | **Jo Bovy** - jobovy_
-   | Professor, Department of Astronomy and Astrophysics, University of Toronto
+   | Department of Astronomy and Astrophysics, University of Toronto
 
 .. _henrysky: https://github.com/henrysky
 .. _jobovy: https://github.com/jobovy

requirements.txt

@@ -0,0 +1,2 @@
+astroNN==1.0.1
+cryptography~=37.0.0