2019_physical_data_model

This repository contains a version of the LUE physical data model as presented in our 2019 manuscript, as well as example scripts and other files used in the preparation of that manuscript.

• de Jong, K., Karssenberg, D., A physical data model for spatio-temporal objects, Environmental Modelling and Software (2019), doi: https://doi.org/10.1016/j.envsoft.2019.104553.

directory	contents
example	Deer-biomass model referred to from manuscript
lue	Version of LUE described in manuscript
source	Scripts used for visualising example-model output

The most recent LUE source code can be found in LUE's own repository.

Build LUE Python package

LUE is currently developed and tested on Linux using GCC-7. All code should compile and run fine on other platforms too, but this is not regularly tested.

Here is an example session of building the version of LUE used for our manuscript and installing the LUE targets in $HOME/lue_install:

cd /tmp
# Recursive is used to also checkout submodules
git clone --recursive https://github.com/pcraster/paper_2019_physical_data_model
cd paper_2019_physical_data_model
mkdir build
cd build
cmake -DCMAKE_INSTALL_PREFIX=$HOME/lue_install ..
cmake --build . --target install

The LUE data model source code depends on 3rd party libraries and tools, that may or may not be installed already on your system. The following dependencies can usually be installed using your system's package manager.

package	version used
libboost-dev	1.65.1
libgdal-dev	2.2.3
hdf5-dev	1.10.0

These package names correspond with those used in Debian distributions and derivatives. Other versions of these packages might also work.

Unless provided by your system's package manager also, these prerequisites can be installed using Conan:

package	version used
fmt	5.2.1
gsl_microsoft	2.0.0
jsonformoderncpp	3.5.0
pybind11	2.2.4

Other versions of these packages might also work.

To install Conan, some additional Python packages, and the above prerequisites, Miniconda (or Conda) can be used:

conda env create -n test \
    -f ../lue/environment/configuration/conda_environment.yml
conda activate test
conan install ../conanfile.txt

Once LUE is installed, some commandline utilities can be found in $HOME/lue_install/bin and the Python package in $HOME/lue_install/python.

Use LUE Python package

To be able to use the LUE commandline utilities and Python package, the following environment variables must be set as follows:

export PATH=$PATH:$HOME/lue_install/bin
export PYTHONPATH=$PYTHONPATH:$HOME/lue_install/python

Now these commands should not result in errors:

lue_validate
python -c "import lue"

Here is an example session of using the LUE Python package. An empty dataset is created and validated.

Python script:

# create_dataset.py
import lue

dataset = lue.create_dataset("my_first_dataset.lue")

Shell commands:

python create_dataset.py
lue_validate my_first_dataset.lue

Run example model

The following commands can be used to run the example model referred to from the manuscript:

../example/deer/model/model.py --nr_timesteps=250 --nr_deer=25 deer.lue

To visualize the model output, Blender can be used. For information how this has been done when preparing the manuscript, see run_model.sh and visualize_lue_dataset.sh in the example model directory.