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The scripts in this repository coded in Python,
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but use several dependencies which can be installed by the following
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instructions.
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All the required packages should work on any platform and on linux based systems.
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The code has been tested in Python v.3.8
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Install dependencies with conda (all platforms)
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-----------------------------------------------
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This is the recommended way to install all the dependencies.
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**Prerequisites**
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You should have a recent version of the [conda](https://docs.conda.io/en/latest/)
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package manager. You can get [conda](https://docs.conda.io/en/latest/) by installing
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[miniconda](https://docs.conda.io/en/latest/miniconda.html), if you want a light version of the package manager.
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**Conda environment**
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Once conda is installed on your system you can easily create a fixed python environment
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to use in every run by:
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~~~
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conda create --name sst_env python=3.8
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~~~
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Then activate it:
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~~~
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conda activate sst_env
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~~~
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To install the code dependencies you must have activated your environment. You
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will know is activated once you see the name of the environment (e.g sst_env)
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in () at the beginning of your bash alias:
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~~~
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(sst_env) [brecinos@jasmin-sci2 ~]$
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~~~
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Make sure conda-forge channel is your default channel to install dependencies:
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~~~
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conda config --add channels conda-forge
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~~~
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To install dependencies simply do:
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~~~
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conda install -c conda-forge numpy pyreadr pandas xarray scipy cartopy pyproj configobj seaborn
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~~~
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We then need to install [netCDF4](https://github.com/Unidata/netcdf4-python) and the library [salem](https://salem.readthedocs.io/en/stable/), to use such libraries we need to install some dependencies with pip:
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~~~
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pip install shapely rasterio Pillow geopandas netcdf4 scikit-image joblib motionless dask descartes
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~~~
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Now we can install netCDF4 and joblib:
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~~~
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conda install -c conda-forge netCDF4 joblib
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~~~
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Finally, we can install salem:
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~~~
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pip install git+https://github.com/fmaussion/salem.git
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~~~
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If you want to run the jupyter-notebooks in the repository make sure you also install those tools in your environment:
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~~~
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conda install -c conda-forge ipykernel
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~~~
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You can add to your jupyter notebook installation a kernel to select this environment every time you activate the notebook.
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~~~
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python -m ipykernel install --user --name sst_env --display-name "sst_env"
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~~~
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**Install the repository itself**
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----------------------------------
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For this to work you'll need to have the [git](https://git-scm.com/) software installed on your system. Then, clone the latest repository version:
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~~~
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git clone git@git.noc.ac.uk:brecinosrivas/orchestra-sst.git
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~~~
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If you are inside [JASMIN](https://help.jasmin.ac.uk/article/185-generate-ssh-key-pair),
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you might have to configure your **Gitlab** ssh keys (under **Gitlab Profile >> Settings > Ssh keys**).
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And add a JASMIN pub key to your profile (generated from within a JASMIN's sci-server).
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This in order to enable access from JASMIN sci servers to your NOC gitlab platform and
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to clone the repository within one of JASMIN's sci servers.
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For more information on gitlab ssh keys [click here](https://git.noc.ac.uk/help/ssh/README.md). |