本文整理汇总了Java中org.sbml.jsbml.Model.getParameter方法的典型用法代码示例。如果您正苦于以下问题:Java Model.getParameter方法的具体用法?Java Model.getParameter怎么用?Java Model.getParameter使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.sbml.jsbml.Model
的用法示例。
在下文中一共展示了Model.getParameter方法的6个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: updateComplexCooperativity
import org.sbml.jsbml.Model; //导入方法依赖的package包/类
public static void updateComplexCooperativity(String reactantId, Reaction react, String CoopStr, Model model) {
SpeciesReference reactant = react.getReactantForSpecies(reactantId);
KineticLaw k = react.getKineticLaw();
LocalParameter p = k.getLocalParameter(GlobalConstants.COOPERATIVITY_STRING+"_"+reactantId);
if (CoopStr != null) {
if (p==null) {
p = k.createLocalParameter();
p.setId(GlobalConstants.COOPERATIVITY_STRING+"_"+reactantId);
}
double nc = Double.parseDouble(CoopStr);
p.setValue(nc);
reactant.setStoichiometry(nc);
} else {
if (p != null) {
k.getListOfLocalParameters().remove(GlobalConstants.COOPERATIVITY_STRING+"_"+reactantId);
}
Parameter gp = model.getParameter(GlobalConstants.COOPERATIVITY_STRING);
reactant.setStoichiometry(gp.getValue());
}
react.getKineticLaw().setMath(SBMLutilities.myParseFormula(createComplexKineticLaw(react)));
}
示例2: prependToVariableNodes
import org.sbml.jsbml.Model; //导入方法依赖的package包/类
/**
* recursively finds all variable nodes and prepends a string to the
* variable static version
*
* @param node
* @param toPrepend
*/
private static void prependToVariableNodes(ASTNode node, String toPrepend, Model model)
{
if (node.isName())
{
// only prepend to species and parameters
if (model.getSpecies(toPrepend + node.getName()) != null)
{
node.setVariable(model.getSpecies(toPrepend + node.getName()));
}
else if (model.getParameter(toPrepend + node.getName()) != null)
{
node.setVariable(model.getParameter(toPrepend + node.getName()));
}
}
else
{
for (ASTNode childNode : node.getChildren())
{
prependToVariableNodes(childNode, toPrepend, model);
}
}
}
示例3: parseParameterSBOL
import org.sbml.jsbml.Model; //导入方法依赖的package包/类
private void parseParameterSBOL(Model sbmlModel, HashMap<String, AssemblyNode2> idToNode) {
for (int i = 0; i < sbmlModel.getParameterCount(); i++) {
Parameter sbmlParameter = sbmlModel.getParameter(i);
AssemblyNode2 parameterNode = constructNode(sbmlParameter, sbmlParameter.getId());
if (parameterNode.getURIs().size() > 0)
containsSBOL = true;
idToNode.put(sbmlParameter.getId(), parameterNode);
if (sbmlParameter.getExtensionPackages().containsKey(CompConstants.namespaceURI))
parsePortMappings(sbmlParameter, parameterNode, idToNode);
}
}
示例4: getDimensionSize
import org.sbml.jsbml.Model; //导入方法依赖的package包/类
public static Map<String, Double> getDimensionSize(Model model, Map<String, String> dimNSize)
{
Map<String, Double> dimensionSizes = new HashMap<String, Double>();
for (String dimId : dimNSize.keySet())
{
String parameterId = dimNSize.get(dimId);
Parameter param = model.getParameter(parameterId);
if (param == null)
{
return null;
}
dimensionSizes.put(dimId, param.getValue());
}
return dimensionSizes;
}
示例5: normalExcecution
import org.sbml.jsbml.Model; //导入方法依赖的package包/类
/**
* Tests that correct execution produced fitted data that closely matches the function that
* was sampled to produce the external data. Here the sine function is used.
*/
@Test
public void normalExcecution() {
setSinData();
SBMLDocument doc = new SBMLDocument(3, 1);
Model model = doc.createModel("test_model");
SBMLTimeCourseDataHelper.addParameter(
model, "myParam", _times, _values, new PolynomialInterpolator(new SplineInterpolator()));
// Model must now have a parameter called myParam with specific properties
assertEquals("Model must have one parameter", 1, model.getParameterCount());
Parameter param = model.getParameter(0);
assertEquals("Parameter id: ", "myParam", param.getId());
assertEquals("Parameter name: ", "myParam", param.getName());
assertEquals("Parameter isConstant: ", false, param.isConstant());
// Model must have an assignment rule that is associated with the parameter
assertEquals("Model must have one rule", 1, model.getRuleCount());
Rule rule = model.getRule(0);
assertTrue("Rule must be assignment rule", rule instanceof AssignmentRule);
AssignmentRule assignmentRule = (AssignmentRule) rule;
assertEquals("Variable of assignment rule", "myParam", assignmentRule.getVariable());
// Now we can compare data with the fitted data - for the sine function the spline
// should fit quite well
for (double t = _times[0]; t<_times[_times.length-1]; t+=0.005) {
double sin = Math.sin(t);
double fitted = evaluateMathML(assignmentRule.getMath(), t);
assertTrue(
"Fitted must be close to actual, t=" + t + " sine="+sin +" fitted=" + fitted +
" diff=" + Math.abs(sin-fitted),
Math.abs(sin-fitted) < 0.01);
}
}
示例6: estimate
import org.sbml.jsbml.Model; //导入方法依赖的package包/类
/**
* This function is used to execute parameter estimation from a given SBML file. The input model serves
* as a template and the existing parameters in the model will set the bounds to which parameter estimation will use.
* <p>
* In addition, the SBML file is used for simulation when estimating the values of the parameters.
*
* @param SBMLFileName: the input SBML file
* @param root: the directory where the experimental data is located
* @param parameterList: the list of parameters that needs to have the value estimated.
* @param experiments: data object that holds the experimental data.
* @param speciesCollection: data object that holds the species in the model.
* @return A new SBMLDocument containing the new parameter values.
* @throws IOException - when a file cannot be read or written.
* @throws XMLStreamException - when an SBML file cannot be parsed.
* @throws BioSimException - when simulation encounters a problem.
*/
public static SBMLDocument estimate(String SBMLFileName, String root, List<String> parameterList, Experiments experiments, SpeciesCollection speciesCollection) throws IOException, XMLStreamException, BioSimException
{
int numberofparameters = parameterList.size();
int sp = 0;
int n = experiments.getExperiments().get(0).size() - 1;
double ep = experiments.getExperiments().get(0).get(n).get(0);
double[] lowerbounds = new double[numberofparameters];
double[] upperbounds = new double[numberofparameters];
HierarchicalSimulation sim = new HierarchicalODERKSimulator(SBMLFileName, root, 0);
sim.initialize(randomSeed, 0);
for (int i = 0; i < numberofparameters; i++)
{
lowerbounds[i] = sim.getTopLevelValue(parameterList.get(i)) / 100;
upperbounds[i] = sim.getTopLevelValue(parameterList.get(i)) * 100;
}
Modelsettings M1 = new Modelsettings(experiments.getExperiments().get(0).get(0), speciesCollection.size(), sp, (int) ep, lowerbounds, upperbounds, false);
// Objective objective1 = new ObjectiveSqureError(M1,0.1);
EvolutionMethodSetting EMS = new EvolutionMethodSetting();
ObjectiveSqureError TP = new ObjectiveSqureError(sim, experiments, parameterList, speciesCollection, M1, 0.1);
SRES sres = new SRES(TP, EMS);
SRES.Solution solution = sres.run(200).getBestSolution();
// TODO: report results: take average of error
// TODO: weight mean square error. Add small value
SBMLDocument doc = SBMLReader.read(new File(SBMLFileName));
Model model = doc.getModel();
for(int i = 0; i < parameterList.size(); i++)
{
Parameter parameter = model.getParameter(parameterList.get(i));
if(parameter != null)
{
parameter.setValue(solution.getFeatures()[i]);
}
}
System.out.println(solution.toString());
return doc;
}