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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.


Data flow of the MAppleT simulation. The model has been decomposed into several independent processes that can be combined and parameterized by user to drive the simulation graphically.
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Figure 13: Data flow of the MAppleT simulation. The model has been decomposed into several independent processes that can be combined and parameterized by user to drive the simulation graphically.

Mentions: To better demonstrate the modularity of the code resulting from this decomposition of MAppleT, the L-system components were assembled graphically using a dataflow in OpenAlea (Figure 13). As opposed to code representation, dataflows give a visual representation of the logical dependency structure of the FSPM. The composition of the components can be made graphically by the modeler by linking input and output of the different L-systems components and making it possible for the system to pass on the L-string and the dictionary of global parameters. The resulting graph (dataflow) can be executed and runs the pipeline throughout.


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)

Data flow of the MAppleT simulation. The model has been decomposed into several independent processes that can be combined and parameterized by user to drive the simulation graphically.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 13: Data flow of the MAppleT simulation. The model has been decomposed into several independent processes that can be combined and parameterized by user to drive the simulation graphically.
Mentions: To better demonstrate the modularity of the code resulting from this decomposition of MAppleT, the L-system components were assembled graphically using a dataflow in OpenAlea (Figure 13). As opposed to code representation, dataflows give a visual representation of the logical dependency structure of the FSPM. The composition of the components can be made graphically by the modeler by linking input and output of the different L-systems components and making it possible for the system to pass on the L-string and the dictionary of global parameters. The resulting graph (dataflow) can be executed and runs the pipeline throughout.

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.