{"id":45990472,"url":"https://github.com/pcraster/paper_2019_physical_data_model","last_synced_at":"2026-02-28T20:02:31.998Z","repository":{"id":89542734,"uuid":"181657239","full_name":"pcraster/paper_2019_physical_data_model","owner":"pcraster","description":"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.","archived":false,"fork":false,"pushed_at":"2023-06-27T15:09:42.000Z","size":375,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2024-01-25T10:16:25.185Z","etag":null,"topics":["agent-based","data-model","field-based","hdf5","modeling","paper","research","simulation"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pcraster.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2019-04-16T09:23:47.000Z","updated_at":"2023-06-27T15:09:49.000Z","dependencies_parsed_at":null,"dependency_job_id":"22166f93-6609-458b-aea3-73c3e1da8fed","html_url":"https://github.com/pcraster/paper_2019_physical_data_model","commit_stats":{"total_commits":19,"total_committers":1,"mean_commits":19.0,"dds":0.0,"last_synced_commit":"024ee8aaafabcf6143c4600acde0045d11fbefa0"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/pcraster/paper_2019_physical_data_model","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pcraster%2Fpaper_2019_physical_data_model","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pcraster%2Fpaper_2019_physical_data_model/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pcraster%2Fpaper_2019_physical_data_model/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pcraster%2Fpaper_2019_physical_data_model/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pcraster","download_url":"https://codeload.github.com/pcraster/paper_2019_physical_data_model/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pcraster%2Fpaper_2019_physical_data_model/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29951071,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-28T18:42:55.706Z","status":"ssl_error","status_checked_at":"2026-02-28T18:42:48.811Z","response_time":90,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["agent-based","data-model","field-based","hdf5","modeling","paper","research","simulation"],"created_at":"2026-02-28T20:02:31.388Z","updated_at":"2026-02-28T20:02:31.990Z","avatar_url":"https://github.com/pcraster.png","language":"Python","readme":"# 2019_physical_data_model\nThis repository contains a version of the LUE physical data model as\npresented in our 2019 manuscript, as well as example scripts and other\nfiles used in the preparation of that manuscript.\n\n- de Jong, K., Karssenberg, D., A physical data model for spatio-temporal\nobjects, Environmental Modelling and Software (2019), doi:\nhttps://doi.org/10.1016/j.envsoft.2019.104553.\n\n| directory | contents |\n| --------- | -------- |\n| `example` | Deer-biomass model referred to from manuscript |\n| `lue` | Version of LUE described in manuscript |\n| `source` | Scripts used for visualising example-model output |\n\nThe most recent LUE source code can be found in LUE's [own\nrepository](https://github.com/pcraster/lue).\n\n![Deer tracks](deer_tracks.png)\n\n\n## Build LUE Python package\nLUE is currently developed and tested on Linux using GCC-7. All code\nshould compile and run fine on other platforms too, but this is not\nregularly tested.\n\nHere is an example session of building the version of LUE used for our\nmanuscript and installing the LUE targets in `$HOME/lue_install`:\n\n```bash\ncd /tmp\n# Recursive is used to also checkout submodules\ngit clone --recursive https://github.com/pcraster/paper_2019_physical_data_model\ncd paper_2019_physical_data_model\nmkdir build\ncd build\ncmake -DCMAKE_INSTALL_PREFIX=$HOME/lue_install ..\ncmake --build . --target install\n```\n\nThe LUE data model source code depends on 3rd party libraries and tools,\nthat may or may not be installed already on your system. The following\ndependencies can usually be installed using your system's package manager.\n\n| package | version used |\n| ------- | ------------ |\n| libboost-dev | 1.65.1 |\n| libgdal-dev | 2.2.3 |\n| hdf5-dev | 1.10.0 |\n\nThese package names correspond with those used in Debian distributions\nand derivatives. Other versions of these packages might also work.\n\nUnless provided by your system's package manager also, these prerequisites\ncan be installed using [Conan](https://conan.io/):\n\n| package | version used |\n| ------- | ------------ |\n| fmt | 5.2.1 |\n| gsl_microsoft | 2.0.0 |\n| jsonformoderncpp | 3.5.0 |\n| pybind11 | 2.2.4 |\n\nOther versions of these packages might also work.\n\nTo install Conan, some additional Python packages, and the above\nprerequisites, [Miniconda](https://docs.conda.io/en/latest/miniconda.html)\n(or Conda) can be used:\n\n```bash\nconda env create -n test \\\n    -f ../lue/environment/configuration/conda_environment.yml\nconda activate test\nconan install ../conanfile.txt\n```\n\nOnce LUE is installed, some commandline utilities can be found in\n`$HOME/lue_install/bin` and the Python package in\n`$HOME/lue_install/python`.\n\n\n# Use LUE Python package\nTo be able to use the LUE commandline utilities and Python package,\nthe following environment variables must be set as follows:\n\n```bash\nexport PATH=$PATH:$HOME/lue_install/bin\nexport PYTHONPATH=$PYTHONPATH:$HOME/lue_install/python\n```\n\nNow these commands should not result in errors:\n\n```bash\nlue_validate\npython -c \"import lue\"\n```\n\nHere is an example session of using the LUE Python package. An empty\ndataset is created and validated.\n\nPython script:\n```python\n# create_dataset.py\nimport lue\n\ndataset = lue.create_dataset(\"my_first_dataset.lue\")\n```\n\nShell commands:\n```bash\npython create_dataset.py\nlue_validate my_first_dataset.lue\n```\n\n\n# Run example model\nThe following commands can be used to run the example model referred to\nfrom the manuscript:\n\n```bash\n../example/deer/model/model.py --nr_timesteps=250 --nr_deer=25 deer.lue\n```\n\nTo visualize the model output, [Blender](https://www.blender.org) can\nbe used. For information how this has been done when preparing the\nmanuscript, see `run_model.sh` and `visualize_lue_dataset.sh` in the\nexample model directory.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpcraster%2Fpaper_2019_physical_data_model","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpcraster%2Fpaper_2019_physical_data_model","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpcraster%2Fpaper_2019_physical_data_model/lists"}