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L-py: an L-system simulation framework for modeling plant architecture development based on a dynamic language.

Boudon F, Pradal C, Cokelaer T, Prusinkiewicz P, Godin C - Front Plant Sci (2012)

Bottom Line: In the last decade, the formalism of L-systems has emerged as a major paradigm for modeling plant development.We show that the use of dynamic language properties makes it possible to enhance the development of plant growth models: (i) by keeping a simple syntax while allowing for high-level programming constructs, (ii) by making code execution easy and avoiding compilation overhead, (iii) by allowing a high-level of model reusability and the building of complex modular models, and (iv) by providing powerful solutions to integrate MTG data-structures (that are a common way to represent plants at several scales) into L-systems and thus enabling to use a wide spectrum of computer tools based on MTGs developed for plant architecture.We then illustrate the use of L-Py in real applications to build complex models or to teach plant modeling in the classroom.

View Article: PubMed Central - PubMed

Affiliation: CIRAD, Virtual Plants INRIA Team Montpellier, France.

ABSTRACT
The study of plant development requires increasingly powerful modeling tools to help understand and simulate the growth and functioning of plants. In the last decade, the formalism of L-systems has emerged as a major paradigm for modeling plant development. Previous implementations of this formalism were made based on static languages, i.e., languages that require explicit definition of variable types before using them. These languages are often efficient but involve quite a lot of syntactic overhead, thus restricting the flexibility of use for modelers. In this work, we present an adaptation of L-systems to the Python language, a popular and powerful open-license dynamic language. We show that the use of dynamic language properties makes it possible to enhance the development of plant growth models: (i) by keeping a simple syntax while allowing for high-level programming constructs, (ii) by making code execution easy and avoiding compilation overhead, (iii) by allowing a high-level of model reusability and the building of complex modular models, and (iv) by providing powerful solutions to integrate MTG data-structures (that are a common way to represent plants at several scales) into L-systems and thus enabling to use a wide spectrum of computer tools based on MTGs developed for plant architecture. We then illustrate the use of L-Py in real applications to build complex models or to teach plant modeling in the classroom.

No MeSH data available.


The MAppleT model on L-Py: with (left) and without (right) computation of branch bending using mechanical simulation.
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Figure 12: The MAppleT model on L-Py: with (left) and without (right) computation of branch bending using mechanical simulation.

Mentions: We now illustrate the use of the above modular approach on a real complex FSPM, MAppleT, simulating the growth of an apple tree (Costes et al., 2008) and originally developed using L-studio/lpfg. This model mixes stochastic topological construction with a bio-mechanical model for the geometry (see Figure 12). Thanks to syntax compatibility between L-Py and L + C, the code port mainly consisted in translating and simplifying the C++ instructions into Python. Additionally, scientific tools from Python and OpenAlea were readily accessible from within the model (for instance, 2D plot with Matplotlib).


L-py: an L-system simulation framework for modeling plant architecture development based on a dynamic language.

Boudon F, Pradal C, Cokelaer T, Prusinkiewicz P, Godin C - Front Plant Sci (2012)

The MAppleT model on L-Py: with (left) and without (right) computation of branch bending using mechanical simulation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3362793&req=5

Figure 12: The MAppleT model on L-Py: with (left) and without (right) computation of branch bending using mechanical simulation.
Mentions: We now illustrate the use of the above modular approach on a real complex FSPM, MAppleT, simulating the growth of an apple tree (Costes et al., 2008) and originally developed using L-studio/lpfg. This model mixes stochastic topological construction with a bio-mechanical model for the geometry (see Figure 12). Thanks to syntax compatibility between L-Py and L + C, the code port mainly consisted in translating and simplifying the C++ instructions into Python. Additionally, scientific tools from Python and OpenAlea were readily accessible from within the model (for instance, 2D plot with Matplotlib).

Bottom Line: In the last decade, the formalism of L-systems has emerged as a major paradigm for modeling plant development.We show that the use of dynamic language properties makes it possible to enhance the development of plant growth models: (i) by keeping a simple syntax while allowing for high-level programming constructs, (ii) by making code execution easy and avoiding compilation overhead, (iii) by allowing a high-level of model reusability and the building of complex modular models, and (iv) by providing powerful solutions to integrate MTG data-structures (that are a common way to represent plants at several scales) into L-systems and thus enabling to use a wide spectrum of computer tools based on MTGs developed for plant architecture.We then illustrate the use of L-Py in real applications to build complex models or to teach plant modeling in the classroom.

View Article: PubMed Central - PubMed

Affiliation: CIRAD, Virtual Plants INRIA Team Montpellier, France.

ABSTRACT
The study of plant development requires increasingly powerful modeling tools to help understand and simulate the growth and functioning of plants. In the last decade, the formalism of L-systems has emerged as a major paradigm for modeling plant development. Previous implementations of this formalism were made based on static languages, i.e., languages that require explicit definition of variable types before using them. These languages are often efficient but involve quite a lot of syntactic overhead, thus restricting the flexibility of use for modelers. In this work, we present an adaptation of L-systems to the Python language, a popular and powerful open-license dynamic language. We show that the use of dynamic language properties makes it possible to enhance the development of plant growth models: (i) by keeping a simple syntax while allowing for high-level programming constructs, (ii) by making code execution easy and avoiding compilation overhead, (iii) by allowing a high-level of model reusability and the building of complex modular models, and (iv) by providing powerful solutions to integrate MTG data-structures (that are a common way to represent plants at several scales) into L-systems and thus enabling to use a wide spectrum of computer tools based on MTGs developed for plant architecture. We then illustrate the use of L-Py in real applications to build complex models or to teach plant modeling in the classroom.

No MeSH data available.