update doc reqs and banner

docs/conf.py

@@ -94,7 +94,7 @@
     "logo_only": True,
     "display_version": False,
     "navbar_align": "left",
-    # "announcement": "S2WAV is currently in pre-release",
+    "announcement": "s2wav is currently in an open alpha, please provide feedback on GitHub",
     "show_toc_level": 2,
     "show_nav_level": 1,
     "header_links_before_dropdown": 5,

docs/index.rst

@@ -22,11 +22,10 @@ properties, and has been successfully adopted for various applications e.g.
 scattering transforms on the sphere `McEwen et al 2022 <https://arxiv.org/pdf/2102.02828.pdf>`_. 
 The wavelet dictionary is constructed by tiling the harmonic line with infinitely 
 differentiable Cauchy-Schwartz functions, which can straightforwardly be performed 
-in an efficient multiresolution manner, as in the Euclidean case. For example the 
-directional wavelet decomposition of a topographic map of the Earth can be seen 
-below
+in an efficient multiresolution manner, as in the Euclidean case. This is what the directional 
+wavelet filters look like in pixel space.
 
-.. image:: ./assets/figures/wavelet_decomposition.png
+.. image:: ./assets/figures/spherical_wavelets.png
    :width: 700
    :align: center
 

docs/user_guide/install.rst

@@ -1,25 +1,23 @@
+:html_theme.sidebar_secondary.remove:
+
 .. _install:
 
 Installation
-============
-Link to `PyPi <https://pypi.org>`_ and provide link for source install.
+=========================
+There are two primary ways to install ``S2WAV``. One can either build the project from 
+the most recent GitHub source, which comes with the added benefit of being able to 
+locally execute the unit testing. Alternately, one may simply install the package directly 
+from PyPi, an online python package manager.
 
 Quick install (PyPi)
 --------------------
-Install ``S2WAV`` from PyPi with a single command
+The simplest way to pick up ``S2WAV`` is to install it directly from PyPi by running 
 
 .. code-block:: bash
+    
+    pip install s2wav 
 
-    pip install s2wav
-
-Check that the package has installed by running 
-
-.. code-block:: bash 
-
-	pip list 
-
-and locate ``S2WAV``.
-
+after which ``S2WAV`` may be imported and run as outlined in the associated notebooks and collab tutorials.
 
 Install from source (GitHub)
 ----------------------------
@@ -28,26 +26,42 @@ When installing from source we recommend working within an existing conda enviro
 
 .. code-block:: bash
 
-    conda create -n s2wav_env python>=3.8
-    conda activate s2wav_env
+    conda create -n "env_name" python>=3.9
+    conda activate "env_name"
 
-Once within a fresh environment ``S2WAV`` may be installed by cloning the GitHub repository
+Once within a fresh environment ``S2WAV`` may be installed by cloning the GitHub repository 
+and pip installing locally
 
 .. code-block:: bash
 
     git clone https://github.com/astro-informatics/s2wav
     cd s2wav
+    pip install .
 
-and running the install script, within the root directory, with one command 
+from the root directory of the repository. Unit tests can then be executed to ensure the 
+installation was successful by running 
 
-.. code-block:: bash
+.. code-block:: bash 
 
-    bash build_s2wav.sh
+    pytest tests/ 
 
-To check the install has worked correctly run the unit tests with 
+Installing JAX for NVIDIA GPUs
+------------------------------
+We include both ``jax`` and ``jaxlib`` as dependencies in ``requirements/requirements-core.txt`` 
+however to get things running on GPUs can be a bit more involved. We strongly recommend 
+this installation `guide <https://github.com/google/jax#installation>`_ provided by 
+Google. To summarise you will first need to install NVIDIA drivers for 
+`CUDA <https://developer.nvidia.com/cuda-downloads>`_ and `CuDNN <https://developer.nvidia.com/CUDNN>`_, 
+following which a pre-built CUDA-compatible wheels shoulld be installed by running 
 
-.. code-block:: bash
+.. code-block:: bash 
+
+    pip install --upgrade pip 
+
+    # Wheels only built for linux
+    pip install --upgrade "jax[cuda]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
 
-	pytest --black tests/ 
+    # Wheels built for many machine architectures 
+    pip install "jax[cuda11_cudnn86]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
 
-.. note:: For installing from source a conda environment is required by the installation bash script, which is recommended, due to a pandoc dependency.
+where the versions of CUDA and CuDNN should match those you have installed on the machine.

requirements/requirements-docs.txt

@@ -1,18 +1,16 @@
-sphinx==4.2.0
-nbsphinx-link==1.3.0
-pydata-sphinx-theme==0.12.0
-sphinx_toolbox==2.15.0
-sphinx-tabs==3.2.0
-sphinxcontrib-bibtex==2.4.1
-sphinx-git==11.0.0
-sphinxcontrib-texfigure==0.1.3
+# Documentation
+sphinx>=5.0.0
+nbsphinx-link>=1.3.0
+pydata-sphinx-theme>=0.12.0
+sphinx_toolbox>=2.15.0
+sphinx-tabs>=3.2.0
+sphinxcontrib-bibtex>=2.4.1
+sphinx-git>=11.0.0
+sphinxcontrib-texfigure>=0.1.3
 sphinx-copybutton
 sphinxemoji
 sphinx_rtd_theme
 
 # Notebooks
-ipython==7.16.1
-jupyter==1.0.0
-
-# Markup converter
-pandoc 
+ipython>=7.16.1
+jupyter>=1.0.0