Merge pull request #49 from flindersuni/feature/odc-update

Feature/odc update

docs/source/software/jupyter.rst

@@ -43,23 +43,24 @@ Python 3.10 *will* **not** *work*, due to dependency incompatibility. Specifical
 Conda Environment Preparation
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-1. Ensure you have a named Conda environment that is loadable by ``conda activate <ENVIRONMENT_NAME>``
-2. Ensure that the python version used by the environment is Python 3.9 or less.'
-3. Log onto the HPC via SSH and activate your Conda environment ``conda activate <ENVIRONMENT_NAME>`` (You can also use the JupyterHub 'Terminal' to do this)
-4. Execute the following commands: 
-    a. ``python3 -m pip install cm-jupyter-eg-kernel-wlm`` 
+1. If you have not performed an initial ``conda init bash``, issue ``module load Miniconda3`` followed by ``conda init bash``, the log-out and log-in the HPC.
+2. Ensure you have a named Conda environment that is loadable by ``conda activate <ENVIRONMENT_NAME>``
+3. Ensure that the python version used by the environment is Python 3.9 or less.'
+4. Log onto the HPC via SSH and activate your Conda environment ``conda activate <ENVIRONMENT_NAME>`` (You can also use the JupyterHub 'Terminal' to do this)
+5. Execute the following commands: 
+    a. ``python3 -m pip install cm-jupyter-eg-kernel-wlm bash-kernel`` 
     b. ``conda install ipython ipython_genutils``
-5. Log into Jupyter Hub with your FAN and password at the `Jupyter URL`_
-6. Using the bar on the Left-hand side, select small green symbol
-7. Create a new Kernel based on the 'CONDA via SLURM' template. 
+6. Log into Jupyter Hub with your FAN and password at the `Jupyter URL`_
+7. Using the bar on the Left-hand side, select small green symbol
+8.  Create a new Kernel based on the 'CONDA via SLURM' template. 
     a. Ensure you select any additional modules you need, like GDAL 
     b. Ensure that you select the correct Conda environment to initialise 
-8. Use the Kernel in your Jupyter Notebooks
+9.  Use the Kernel in your Jupyter Notebooks
 
 For Reference, the below image shows the Kernel Template Screen. 
 
 .. figure:: ../_static/jupyter-kernel-template.png
-    :align: left
+    :align: center
     :alt: Jupyter Hub Kernel Template Screen
 
 

docs/source/software/opendatacube.rst

@@ -50,7 +50,7 @@ The Open Data Cube is best installed into a Conda Environment, allowing you to u
 1. Follow the Jupyter Conda Setup, if you wish to use the ODC via the JupyterHub instance
 2. ``conda install datacube``. If this step hangs for more that 5 minutes, then follow the 'Advanced Installation Guide' further down this page to get split the install into smaller parts
 3. Raise a ServiceOne request for 'Access to the Open Data Cube'
-4. Place the provided configuration file in the following location on the HPC /home/<FAN>/.datacube.conf 
+4. Place the provided configuration file in the following location on the HPC: ``/home/<FAN>/.datacube.conf``
 5. Activate your Conda environment, and run ``datacube system check`` to verify that your ODC connects correctly
 
 
@@ -59,13 +59,15 @@ Open Data Cube Advanced Installation Guide
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 As the Open Data Cube is quite complicated, sometimes Conda can have trouble resolving the dependencies. In this case, we can manually install many of them, before we install the Data Cube itself. 
 
-1. ``conda create --name=odc python=3.9``
-2. ``conda install affine pyproj shapely cachetools click``
-3. ``conda install cloudpickle dask[array] distributed jsonschema netcdf4``
-4. ``conda install numpy psycopg2 lark-parser pandas python-dateutil``
-5. ``conda install pyyaml rasterio sqlalchemy toolz xarray\``
-6. ``conda install datacube``
-7. Raise a ServiceOne request for 'Access to the Open Data Cube'
-8. Place the provided configuration file in the following location on the HPC /home/<FAN>/.datacube.conf 
-9. Activate your Conda environment, and run ``datacube system check`` to verify that your ODC connects correctly 
-10. 
+1. 1. If you have not performed an initial ``conda init bash``, issue ``module load Miniconda3`` followed by ``conda init bash``, then log-out and log back in to the HPC.
+2. ``conda create --name=odc python=3.9``
+3. ``conda activate odc``
+4. ``conda config --add channels conda-forge``
+5. ``conda install affine pyproj shapely cachetools click``
+6. ``conda install cloudpickle dask[array] distributed jsonschema netcdf4``
+7. ``conda install numpy psycopg2 lark-parser pandas python-dateutil``
+8. ``conda install pyyaml rasterio sqlalchemy toolz xarray``
+9. ``conda install datacube``
+10. Raise a ServiceOne request for 'Access to the Open Data Cube'
+11. Place the provided configuration file in the following location on the HPC /home/<FAN>/.datacube.conf 
+12. Activate your Conda environment, and run ``datacube system check`` to verify that your ODC connects correctly