Paper title

by Author 1, Author 2, etc

This paper has been submitted for publication in Some Journal.

Brief description of what this paper is about (2-3 sentences). Include a figure as well with the main result of your paper.

Brief figure caption.

Abstract

Paste here the abstract.

Reproducing the results

You can download a copy of all the files in this repository by cloning the git repository:

git clone https://github.com/pinga-lab/PAPER-REPO.git

or click here to download a zip archive.

Describe here the folder structure and what is in each folder. Suggested layout would be:

All source code used to generate the results and figures in the paper are in the code folder. The data used in this study is provided in data and the sources for the manuscript text and figures are in manuscript. See the README.md files in each directory for a full description.

The calculations and figure generation are all run inside Jupyter notebooks. You can view a static (non-executable) version of the notebooks in the nbviewer webservice:

http://nbviewer.jupyter.org/github/pinga-lab/PAPER-REPO

Also provided are read-only PDF versions of the notebooks.

See sections below for instructions on executing the code.

Setting up your environment

Describe what you need to install. Usually it's Anaconda with Python 2.7. Here is template for that:

You'll need a working Python 2.7 environment with all the standard scientific packages installed (numpy, scipy, matplotlib, etc). The easiest (and recommended) way to get this is to download and install the Anaconda Python distribution. Make sure you get the Python 2.7 version.

If you need Fatiando, use this:

You'll also need to install version X.Y of the Fatiando a Terra library. See the install instructions on the website.

If you provide a conda environment through an environment.yml file, use:

You can use conda package manager (included in Anaconda) to create a virtual environment with all the required packages installed. Run the following command in the repository folder (where environment.yml is located):

conda env create

To activate the conda environment, run

source activate moho

or, if you're on Windows,

activate moho

This will enable the environment for your current terminal session.

I would recommend having a bash shell with make installed in Windows to make life easier for everyone. Put these instructions if you want this:

Windows users: It is highly recommended that you install the bash shell to run code and produce the results here. You can download bash for Windows at http://git-for-windows.github.io/. Install the "Git for Windows SDK" that will come with bash and make as well.

Running the code

If using Jupyter notebooks, use this text:

To execute the code in the Jupyter notebooks, you must first start the notebook server by going into the repository folder and running:

jupyter notebook

Make sure you have the conda environment enabled first.

This will start the server and open your default web browser to the Jupyter interface. In the page, go into the code folder and select the notebook that you wish to view/run.

The notebook is divided cells (some have text while other have code). Each cell can be executed using Shift + Enter. Executing text cells does nothing and executing code cells runs the code and produces it's output. To execute the whole notebook, run all cells in order.

License

All source code is made available under a BSD 3-clause license. You can freely use and modify the code, without warranty, so long as you provide attribution to the authors. See LICENSE.md for the full license text.

The manuscript text is not open source. The authors reserve the rights to the article content, which is currently submitted for publication in the JOURNAL NAME.