From Molecules To Landscapes: Rule-based FSPMs in the Language XL Winfried Kurth

From Molecules To Landscapes: Rule-based FSPMs in the Language XL

Winfried Kurth

Brandenburg University of Technology at Cottbus, Chair for Graphics Systems

1. Strengths and weaknesses of traditional approaches in plant modelling

2. Relational Growth Grammars (RGGs) as a generic tool on a formal level

3. The language XL

4. Future perspectives

Cottbus, 10. 3. 2008

Cottbus, 10. 3. 2008

1. Strengths and weaknesses of traditional approaches in plant modelling

Challenges:

• connection of structure and function in a coherent model framework

• bridging the gap between different scales

bio-/geosphere

region

ecosystem

population

individual

organ

tissue

cell

organell / genome

molecule

GEOINFORMATICS

BIOINFORMATICS /SYSTEMS BIOLOGY

Cottbus, 10. 3. 2008

bio-/geosphere

region

ecosystem

population

individual

organ

tissue

cell

organell / genome

molecule

GEOINFORMATICS

BIOINFORMATICS /SYSTEMS BIOLOGY

Cottbus, 10. 3. 2008

ECOLOGICALINFORMATICS

Transfer of the Systems Biology viewpoint to higher scale levels

Tools for modelling and simulation:

(a) classical PBM (process-based models)

- pools of substrates in compartments

- fluxes between pools

Example:

STELLAflowcharts

mathematical formalisms:

- qualitative: Petri nets

- quantitative: systems of differential equations

tools:

- numerics software

- graphical modelling environments (e.g., STELLA)

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PBM – drawbacks:

• spatial structure often poorly represented

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PBM – drawbacks:


• no representation of the objects with which the user really works

PBM – drawbacks:


• no representation of the objects with which the user really works

• parameters partially difficult to measure and to interpret

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(b) structural models

- entities: organs / modules (biologically senseful and visualizable entities)

- effects of interaction occur emergently

- parameters: relatively few, measurable

barley model

(Buck-Sorlin et al. 2005)

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(b) structural models

- entities: organs / modules (biologically senseful and visualizable entities)

- effects of interaction occur emergently

- parameters: relatively few, measurable

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most important approach from computer science for this type of models (until recently):

Lindenmayer systems (L-systems)

Examples of L-system based plant models:

Prusinkiewicz & Lindenmayer 1990

K. 1998, 1999

Applications:

virtual plant structures as a basis for simulations, e.g.,

light interception in a tree stand (Knyazikhin, Ibrom, K. 1997)

water flow in a tree (Früh & K. 1999)

structure has impact on function – example of xylem sap flow

(Früh & K. 1999)

spruce (L-system model)

spruce (3D measurement)

Thuja (3D measurement)

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structural models – drawbacks:

• no (or very sparse) taking into acount of the functional aspects of organisms

• no metabolism, no linkage with lower scale levels

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structural models – drawbacks:

• no (or very sparse) taking into acount of the functional aspects of organisms

• no metabolism, no linkage with lower scale levels

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combination of model types

(c) Functional-structural plant models, FSPM

Idea: distribution of the processes to the modules



Tool: object-oriented programming

example of ALMIS

(Eschenbach 2000)



Tool: object-oriented programming

example of ALMIS

(Eschenbach 2000)

FSPM example LIGNUM (Perttunen et al. 1996, 1998, Dzierzon & K. 2002;Sievänen et al. 2006)

Drawbacks of ad hoc FSPMs from the last years:

isolated solutions, often strongly specialized

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large, complex source code, containing technical details mixed with fundamental features of the model

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low compatibility of the models with each other

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low compatibility of the models with each other

complexity of the tool (for the user) has to be reduced

a further challenge:

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traditional, commonly-used programming languages obviously not optimal for the purpose

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formal basis for tools in ecological informatics?

grammars

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Eric Mjolsness, Univ. of California 2006:

"Future multiscale models must be able to integrate all the major different types of dynamical systems models, ...

These goals are achieved by the modelling framework of... grammars."

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formal basis for tools in ecological informatics?

grammars

2. Relational Growth Grammars (RGG) as a generic tool on a formal level

point from where to start:

L systems

(parallel string rewriting)

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Limitations of L-systems:

• in L-systems, only 2 possible relations between objects: "direct successor" und "branching"

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• multiscaled models are not supported

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• object-oriented programming is not supported (only symbols, resp. "modules" = parameterized symbols, no objects, no classes)

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• structures must be serialized to strings

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transgression to graph grammars





• structures must be serialized to strings

"Relational Growth Grammars" (RGG) as generic tool on a formal level

= graph grammars with parallel application

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"Relational Growth Grammars" (RGG) as generic tool on a formal level

= graph grammars with parallel application

• graph model:- with node attributes and types (type hierarchy for inheritance)- with edge labels (finitely many)- no multiple edges with the same label

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Nodes:

correspond to the symbols in L-systems

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Nodes:


simultaneously objects sensu OOP

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Nodes:


simultaneously objects sensu OOP

e.g., plant organs, geometric transformations

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Edges:

their labels can represent different sorts of relations:

• is successor of

• contains

• bears as a lateral shoot

• reacts with

• encodes (genetically)

• is mating with

• (...)

also possible: representation of multiscaled structures

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multiscaled structures

(different geometric levels of resolution in one model)

relation of refinement

(AMAPmod software description, CIRAD Montpellier, 1998)

multiscaled structures

(different geometric levels of resolution in one model)

relation of refinement

(AMAPmod software description, CIRAD Montpellier, 1998)

in computer graphics: "Level of Detail"

● embedding model:Single-Pushout approach from algebraic graph grammartheory, extended by so-called connection transformations

● right-hand sides of rules are dynamically generated

RGG replacement mechanism

left-hand side of rule right-hand side of rule

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an RGG rule and its application in graphical form:

rule:

application:

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an RGG rule and its application in graphical form:

rule:

application:

rule in text form: i -b-> j -a-> k -a-> i = => j

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original graph: A B C

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implicit use of "connection edges" for the desired embedding:

a:A ==>> a C (SPO rule)

B ==> D E (rules of L-system type)

C ==> A

A B C

D E A

connection edges (auxiliary edges)

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C ==> A

A B C

D E A

a:

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C ==> A




C ==> A

A AD Ea:

C

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Advantages:

L-systems as a special case

Strings correspond to special graphs

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example: crossing over

Two homologous chromosome strands, encoded as strings with "successor" relation

RGG rule:

application:

alignment of homologous alleles

pure SPO rules as a special case

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further special case: rules which change only parameters

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Example from barley model:

Cell [lue1:LUE1] ::>

lue1[concentration] :+= 0.5 * par.DELTA_T;

Realization of RGGs in a programming language:

XL (eXtended L-system language)

(Kniemeyer 2007)

• extension of Java

• nodes are Java objects

• additional constructions

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3. The language XL

• Queries in the generated graphs

possibility to link structure and function

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Example: look for all leaves which are successor of node c and sum up their areas

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transitive closure

aggregation operator

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transitive closure

aggregation operator

result can be transferred to procedural calculation (e.g., PBM)

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Query in a plant / herbivore model:

p:Plant,

(* a:Animal, (distance(a,p) < p[radius]) *)

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Query in a plant / herbivore model:

p:Plant,

(* a:Animal, (distance(a,p) < p[radius]) *)

looks for all animals in the radius of p

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dynamics of networks

(e.g., neighbourship relation in a tree stand)

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generally:

dynamical systems with a dynamical structure

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Interactive 3D platform GroIMP (Growth-grammar related Interactive

Modelling Platform) with XL compiler

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Interactive 3D platform GroIMP (Growth-grammar related Interactive

Modelling Platform) with XL compiler

• GroIMP is an Open Source project (http://www.grogra.de)

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XL compiler

(time series of) structure(s)(attributed graphs)

modelspecification

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XL compiler descriptionparser


modelspecification

descriptions of real organisms

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renderer

visual representation

modelspecification


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XL console renderer


statistical analysis software

request for analysis (query)

modelspecification


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XL console renderer interfaces

special simulation software


statistical analysis software

request for analysis (query)

modelspecification


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GroIMP provides complete XL libraries

e.g., node classes for the emulation of Xfrog graphs (cf. Deussen, Lintermann)

Diploma thesis Henke 2006, Henke et al. (submitted)

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(Henke 2006)

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extension of the Xfrognode classes by an „arrange“ node

(Henke 2006)

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Input: „fields“ (given by image files) for spatial parameters

heights densities tree parameters



Input: „fields“ (given by image files) for spatial parameters

(Henke 2006)

heights densities tree parameters

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4. Future perspectives

Improvement of rendering / radiation simulation

currently under construction:

- Metropolis raytracing

- GPU-based raytracer

- Radiosity calculation

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(Veach 1998)

Weakness of bidirectional raytracing in case of indirect illumination:

Improvement:

Metropolis algorithm (mutation of an already detected ray path)

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e.g., molecule models (GroIMP filter for pdb files)

Extension of the possibilities for 3D modelling

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exchange platform "OpenAlea" (Pradal 2007)

modular platform to improve the interoperability of plant models and analysis tools

Making XL available for this international project

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3D data acquisition from real organisms

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3D data acquisition from real organisms

and linked to that:

solution of the inference problem for RGGs

Aim: automatize the pipeline

real object 3D model RGG abstract model visualization of the abstract model

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ongoing project:

development of a low-cost system for the acquisition of 3D data with structured light

(Jiang & Bunke 1997)

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aerial photo + elevation model(ArcGIS)

aerial photo + elevation model(ArcGIS)

view into simulated stand

(Knauft 2001)

shadow calculation at forest soil level at different times of the day

(Knauft 2001)

"ViWa" (Virtueller Wald = virtual forest) –

landscape in the Solling region (Germany) (Knauft & K. 2001)

elevation model + forest inventory data + structural model of stand + structural model of tree + rendering:

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Modelling of park landscapes

(Rogge & Moschner 2007, for Branitzer Park Foundation, Cottbus)

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Thank you for your attention!

Cottbus, 10. 3. 2008

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From Molecules To Landscapes: Rule-based FSPMs in the Language XL Winfried Kurth

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