============
Installation
============

Prerequisites
-------------
To install AMSIMP, you will need to utilise Python 3.7, or later.
Preferably, you will also want to have an installation of either
Anaconda, or Miniconda on your machine. For installation instructions,
please visit `Anaconda's documentation page`_.

.. _Anaconda's documentation page: https://docs.anaconda.com/anaconda/install/

Installing from Anaconda Cloud
------------------------------
Before installation via this particular method, TensorFlow needs to be installed through the Python Package Index (PyPI)
using the following command:

.. code:: sh

   $ pip install tensorflow

AMSIMP is distributed on `Anaconda Cloud <https://anaconda.org/amsimp/amsimp>`_ and can be installed using conda:

.. code:: sh

   $ conda install -c amsimp amsimp

If you run into any issues, you can either create an issue on
`GitHub <https://github.com/amsimp/amsimp/issues>`_ or
contact us by `email <support@amsimp.com>`_.

Installing from Source
----------------------

You can also install AMSIMP from the source code. First, clone
the repository off of GitHub:

.. code:: sh

   $ git clone https://github.com/amsimp/amsimp.git && cd amsimp

You will then need to install the software requirements, you can
do this via:

.. code:: sh

   $ conda env create -f environment.yml && conda activate amsimp

Further information about the required dependencies can be found here:

- **Python** 3.7.x (https://www.python.org/)
- **tqdm** (https://tqdm.github.io/) |
  A Fast, Extensible Progress Bar for Python and CLI.
- **NumPy** (https://numpy.org/) |
  Python package for scientific computing including a powerful N-dimensional array object.
- **Astropy** (https://www.astropy.org) |
  A Community Python Library for Astronomy.
- **Iris** (https://scitools.org.uk/iris/docs/latest/) |
  A powerful, format-agnostic, community-driven Python library for analysing and visualising Earth science data.
- **Tensorflow** 2.0 or later (https://www.tensorflow.org) |
  TensorFlow is an end-to-end open source platform for machine learning.

Finally, you can the software via install:

.. code:: sh

   $ python setup.py install