clim-recal installation

clim-recal is a set of tools to manage UK climate data and projections, and running a range of correction methods in python and R. For ease of installation and use, we focus primarily on the python portion, but in principal the R notebooks should be useable via RStudio, which suggests packages necessary to install. We also provide docker configurations which include both R and python environments.

1 Quickstart

Note

There are several different ways to install clim-recal . We have used docker the most across different platforms

For users who already have conda (or mamba) installed:

git clone https://github.com/alan-turing-institute/clim-recal
cd clim-recal
pip install conda-lock
conda-lock install --name clim-recal conda-lock.yml
conda activate clim-recal
cd python
pdm install
clim-recal --help

For docker:

git clone https://github.com/alan-turing-institute/clim-recal
cd clim-recal
docker compose build jupyter
docker compose up jupyter
clim-recal --help
Warning

There are cases where pdm install raises a KeyError: '_PYPROJECT_HOOKS_BUILD_BACKEND'. Thus far, running pdm install again works.

2 Options

Once installed the clim-recal command can be run with files. The settings below are specific to a server

clim-recal --help

 Usage: clim-recal [OPTIONS]

 Crop and align UK climate projections and test debias methods.

╭─ Options ──────────────────────────────────────────────────────────────╮
│ --hads-input-path     -d      PATH                [default: .]         │
│ --cpm-input-path      -o      PATH                [default: .]         │
│ --output-path         -o      DIRECTORY           [default:            │
│                                                   clim-recal-runs]     │
│ --variable            -v      [tasmax|rainfall|t  [default: tasmax]    │
│                               asmin]                                   │
│ --region              -a      [Glasgow|Mancheste  [default:            │
│                               r|London|Scotland]  Manchester]          │
│ --run                 -r      [01|04|05|06|07|08  [default: 05]        │
│                               |09|10|11|12|13|14                       │
│                               |15]                                     │
│ --method              -m      [quantile_delta_ma  [default:            │
│                               pping|quantile_map  quantile_delta_mapp… │
│                               ping|variance_scal                       │
│                               ing|delta_method]                        │
│ --all-variables                                                        │
│ --all-regions                                                          │
│ --all-runs                                                             │
│ --default-runs                                                         │
│ --all-methods                                                          │
│ --project-cpm                                     [default: True]      │
│ --project-hads                                    [default: True]      │
│ --crop-cpm                                        [default: True]      │
│ --crop-hads                                       [default: True]      │
│ --execute                                                              │
│ --start-index         -s      INTEGER RANGE       [default: 0]         │
│                               [x>=0]                                   │
│ --total-from-index    -t      INTEGER RANGE       [default: 0]         │
│                               [x>=0]                                   │
│ --cpus                        INTEGER RANGE       [default: 2]         │
│                               [1<=x<=10]                               │
│ --use-multiprocessi…                                                   │
│ --install-completion                              Install completion   │
│                                                   for the current      │
│                                                   shell.               │
│ --show-completion                                 Show completion for  │
│                                                   the current shell,   │
│                                                   to copy it or        │
│                                                   customize the        │
│                                                   installation.        │
│ --help                                            Show this message    │
│                                                   and exit.            │
╰────────────────────────────────────────────────────────────────────────╯

3 Conda/Mamba Python

3.1 Conda / Mamba

More detailed examples using conda or mamba are below. Installation instructions for either these are available:

These options are primarily to ease use of GDAL and optionally rsync.

3.2 conda-lock

conda-lock provides a means of managing dependencies for conda/mamba environments on precise, reproducible levels, and can incorporated local pyproject.toml configurations.

There are many ways to install conda-lock (for most up to date options see README.md):

pipx install conda-lock
pip install conda-lock
conda install --channel=conda-forge --name=base conda-lock
mamba install --channel=conda-forge --name=base conda-lock

Once conda-lock is installed, clim-recal can be installed via

cd `clim-recal`
conda-lock install conda-lock.yml
cd `clim-recal`
conda-lock install conda-lock.yml
cd `clim-recal`
conda activate base
conda-lock install conda-lock.yml
cd `clim-recal`
mamba activate base
conda-lock install conda-lock.yml

4 Docker

It can take some time to build, but the following will build 3 docker volumes for

  • jupyter: a python environment
  • RServer: an R environment
  • quarto: documentation
cd clim-recal
docker compose build
cd clim-recal  # for python
docker compose build jupyter
cd clim-recal  # for R
docker compose build rstudio
cd clim-recal  # for documentation in quarto via R
docker compose build quarto

Once built, the environments built can be run via

docker compose up
docker compose jupyter up
docker compose rstudio up
docker compose quarto up
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