This is L-Grass model, a model of rye grass morphogenesis.
See Migault V. 2015. Insertion de la morphogenèse racinaire dans L grass, un modèle structure-fonction de graminées fourragères. Verdenal A. 2009. De la simulation de la morphogénèse de l’appareil aérien du ray-grass anglais (Lolium perenne L.). Exploration d’un schéma cybernétique inspiré du concept d’auto-organisation et applications. Verdenal A, Combes D, Escobar-Gutiérrez AJ. 2008. A study of ryegrass architecture as a self-regulated system, using functional-structural plant modelling. Functional Plant Biology 35: 911–924.
These instructions will get you a copy of L-grass up and running on your local machine.
To install and use L-grass, you need first to install the dependencies.
L-grass has been tested on Windows.
-
Install Python
- go to https://www.python.org/downloads/windows/download,
- click on "Latest Python 2 Release [...]",
- download "Windows x86-64 MSI installer" and install it selecting the following options:
- install for all users,
- default destination directory,
- install all subfeatures, including subfeature "Add python.exe to Path".
-
Install OpenAlea Vplants:
- go to http://openalea.gforge.inria.fr/dokuwiki/doku.php?id=download:windows,
- download
OpenAlea 1.2
andVplants 1.2
, - install both installers:
-
Install NumPy:
- go to http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy,
- download
NumPy+MKL
for Python 2 64 bit, - install it using
pip
installer:- open a command line interpreter,
- go to the directory where you saved
NumPy+MKL
for Python 2 64 bit, - install
NumPy+MKL
from the downloaded wheel file.
For example, if you downloaded file "numpy-1.13.1+mkl-cp27-cp27m-win_amd64.whl", type:pip install "numpy-1.13.1+mkl-cp27-cp27m-win_amd64.whl"
.
-
Install Pandas
- go to http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas,
- download
Pandas
for Python 2 64 bit, - install it using
pip
installer:- open a command line interpreter,
- go to the directory where you saved
Pandas
for Python 2 64 bit, - install
Pandas
from the downloaded wheel file.
For example, if you downloaded file "pandas-0.20.3-cp27-cp27m-win_amd64.whl", type:pip install "pandas-0.20.3-cp27-cp27m-win_amd64.whl"
.
-
Install Sphinx
- go to http://www.lfd.uci.edu/~gohlke/pythonlibs/#misc,
- download
Sphinx
for Python 2, - install it using
pip
installer:- open a command line interpreter,
- go to the directory where you saved
Sphinx
for Python 2, - install
Sphinx
from the downloaded wheel file.
For example, if you downloaded file "Sphinx-1.6.3-py2.py3-none-any.whl", type:pip install "Sphinx-1.6.3-py2.py3-none-any.whl"
.
Note: We suppose you already installed the dependencies for your operating system. Otherwise follow these instructions.
You can install L-grass either in "install" or "develop" mode.
Install L-grass in "install" mode if you're not going to develop, edit or debug it, i.e. you just want to used it as third party package.
To install L-grass in "end-user" mode:
- open a command line interpreter,
- go to your local copy of project L-grass,
- run command:
python setup.py install --user
.
Install L-grass in "develop" mode if you want to get L-grass installed and then be able to frequently edit the code and not have to re-install L-grass to have the changes to take effect immediately.
To install L-grass in "develop" mode:
- open a command line interpreter,
- go to your local copy of project L-grass,
- run command:
python setup.py develop --user
.
To run a simulation example, two options:
-
- open Lpy platform, load lgrass.lpy file from lgrass folder, Use Run or animate button to launch a simulation
- Run lgrass from a python script (see main.py in test folder for an example)
See the user guide for a step by step explanation of how to set and run model L-grass.
To build the user and reference guides:
- install the model (see Installation of the model),
- open a command line interpreter,
- go to the top directory of your local copy of the project,
- run this command:
python setup.py build_sphinx
, - and direct your browser to file
doc/_build/html/index.html
.
The test allows to verify that the model implementation accurately represents the developer’s conceptual description of the model and its solution.
The test:
- runs the model on 200 steps,
- concatenates the outputs of the model in pandas dataframes,
- writes the outputs dataframes to CSV files,
- compares actual to expected outputs,
- raises an error if actual and expected outputs are not equal up to a given tolerance.
To run the test :
- install the model (see Installation of the model),
- open a command line interpreter,
- go to the directory
test
of your local copy of the project, - and run this command:
python test_lgrass.py
.
First, send an email to [email protected] to be added to the project.
Then,
- check for open issues or open a fresh issue to start a discussion around a feature idea or a bug: https://sourcesup.renater.fr/tracker/?group_id=3957.
- If you feel uncomfortable or uncertain about an issue or your changes, feel free to email [email protected].
For any question, send an email to [email protected].
We use a Git repository on SourceSup for
versioning: https://sourcesup.renater.fr/projects/lgrass/.
If you need an access to the current development version of the model, please send
an email to [email protected].
For versionning, use a git client and get git clone git+ssh://[email protected]:2222/lgrass.git. SSH will is required
Alban VERDENAL, Didier COMBES and Vincent MIGAULT - see file AUTHORS for details
This project is licensed under the CeCILL-C License - see file LICENSE for details