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2. Configure the python environment

The code for calculating SPI is written in Python 3. It is recommended to use either the Miniconda3 (minimal Anaconda) or Anaconda3 distribution. The below instructions will be Anaconda specific (although relevant to any Python virtual environment), and assume the use of a bash shell.

A new Anaconda environment can be created using the conda environment management system that comes packaged with Anaconda. In the following examples, I’ll use an environment named climate_indices (any environment name can be used instead of climate_indices) which will be created and populated with all required dependencies through the use of the provided setup.py file.

Note

This step must only be done the first time. Once the environment has been created there is no need to do it again.

  • First, open your Terminal (in your macOS/Linux and Ubuntu Linux on WSL), create the Python environment with python3.7 as default:
conda create -n climate_indices python=3.7

Env CI

Proceed with y

  • The environment created can now be ‘activated’:
conda activate climate_indices
  • Install climate-indices package. Once the environment has been activated then subsequent Python commands will run in this environment where the package dependencies for this project are present. Now the package can be added to the environment along with all required modules (dependencies) via pip:
pip install climate-indices

Pip CI

  • Install netCDF Operator (NCO) using conda and proceed with y.
conda install -c conda-forge nco
  • Install Climate Data Operator (CDO) from Max-Planck-Institut für Meteorologie using conda and proceed with y.
conda install -c conda-forge cdo
  • Install jupyter and other package using conda and proceed with y.
conda install -c conda-forge jupyter numpy netCDF4
  • Deactivate an active environment climate_indices as I will create a new environment called gis to install gdal to clip the rainfall data using a shapefile, and proceed with y.
conda deactivate && conda create -n gis python=3.7

Env GIS1

  • The environment created can now be ‘activated’:
conda activate gis
  • Install gdal, nco and cdo in gis environment and proceed with y.
conda install -c conda-forge gdal nco cdo wget

Env GIS2