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#!/usr/bin/python3
# @file createNormalExample.py
# @brief SBML distrib example
# @author Sarah Keating
#
#
# <!--------------------------------------------------------------------------
# This file is part of libSBML. Please visit http:#sbml.org for more
# information about SBML, and the latest version of libSBML.
#
# Copyright (C) 2009-2013 jointly by the following organizations:
# 1. California Institute of Technology, Pasadena, CA, USA
# 2. EMBL European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
#
# Copyright (C) 2006-2008 by the California Institute of Technology,
# Pasadena, CA, USA
#
# Copyright (C) 2002-2005 jointly by the following organizations:
# 1. California Institute of Technology, Pasadena, CA, USA
# 2. Japan Science and Technology Agency, Japan
#
# This library is free software; you can redistribute it and/or modify it
# under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation. A copy of the license agreement is provided
# in the file named "LICENSE.txt" included with this software distribution
# and also available online as http:#sbml.org/software/libsbml/license.html
# ------------------------------------------------------------------------ -->
from libsbml import *
sbmlns = SBMLNamespaces(3, 1, "distrib", 1);
document = SBMLDocument(sbmlns);
# set the required attribute to true
docPlug = document.getPlugin("distrib");
docPlug.setRequired(True);
# create the Model
model = document.createModel();
# create the FunctionDefintion
fd = model.createFunctionDefinition();
fd.setId("mynormal");
math = libsbml.parseFormula("lambda(param1, param2, 0)");
fd.setMath(math);
#
# Get a DistribFunctionDefinitionPlugin object plugged in the fd object.
#
fdPlugin = fd.getPlugin("distrib");
# create a DrawFromDistribution object
draw = fdPlugin.createDrawFromDistribution();
# create the distribInputs
input1 = draw.createDistribInput();
input1.setId("mu");
input1.setIndex(0);
input2 = draw.createDistribInput();
input2.setId("sigma");
input2.setIndex(1);
# create the UncertMLNode object
uncert = libsbml.createDistributionNode("NormalDistribution", "mean, variance", "mu,sigma");
draw.setUncertML(uncert);
writeSBMLToFile(document, "distrib_example1.xml");
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