TUT Inverse Problems
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Bayes-Forest Toolbox 1.0

Overview flowchart

This pages provides for additional materials and original data for the article BayesForest: a data-intensive generator of morphological tree clones by I. Potapov, M. Järvenpää, M. Åkerblom, P. Raumonen, and M. Kaasalainen, in press.

The toolbox requires MATLAB and it is guaranteed to work with version R2015b.

BayesForest-1.0.zip contains the complete set of routines of the Toolbox. After unpacking the archive the folder BayesForest-1.0 appears in the current directory. Put the directory in MATLAB's path and the Toolbox is installed. Refer to the help-pages of the functions for further details (the main function BayesForest() is a good starting point).

The most recent version of the package can be obtained from the BayesForest GitHub page. Similarly, all contributions to BayesForest are welcomed. The Wiki pages of the toolbox contain the description of the approach, tutorial, and the user guide.

Data and materials for the publication

morpho-clones.zip archive contains the simulated data and all necessary information to repeat the simulations reported in the paper.

Repeat the simulations

The QSM data are located in EspooData.mat file. It contains several reconstruction models of the target tree, but we used only the model 1. Make sure the file is loaded into the MATLAB's workspace by:

load('EspooData.mat');

The above command will create a variable called EspooData, which is accessed by the function BayesForest. To run a specific simulation with the configuration in, say, input.txt file just type at the MATLAB prompt:

BayesForest('input.txt')

All configuration files are located in the folders named by date and time:

  • The rosette-shape tree simulation is in 12.11.2016_18.22
  • The best-fit SSM simulation is in 6.1.2017_19.15

Other simulations are available with their description in the lab-book README.

The usual simulation time is long (up to several days on a modest two core computer). One can use simpler test runs for the Toolbox: see the tutorial.

Software requirements

Besides MATLAB one needs LPFG. LPFG is a simulator based on the L+C language (L-system paradigm in C++ expressions). The simulator is available in the VLAB (Unix) or L-studio (Windows) packages from the Algorithmic Botany website. The version used in this study was 4.4.0-2424 for 64-bit Mac OS (OS X version 10.11.6 El Capitan).

LPFG simulates the growth of a tree (self-organizing tree model, from sot-dist-1.2.8.zip file).

Additional material

Other best-fit candidates obtained during this study
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