public static void generateMainPage(File mainFile, File sourceProjDir)
throws IOException, ProjectFileParsingException, NeuroMLException {
SimpleXMLElement root = new SimpleXMLElement("document");
SimpleXMLElement header = new SimpleXMLElement("header");
root.addChildElement(header);
SimpleXMLElement title = new SimpleXMLElement("title");
header.addChildElement(title);
SimpleXMLElement body = new SimpleXMLElement("body");
root.addChildElement(body);
SimpleXMLElement intro = new SimpleXMLElement("p");
body.addChildElement(intro);
if (!mainFile.getParentFile().exists()) mainFile.getParentFile().mkdir();
File targetDownloadDir = new File(mainFile.getParentFile(), "downloads");
if (!targetDownloadDir.exists()) targetDownloadDir.mkdir();
if (sourceProjDir.getName().indexOf("examples") >= 0) {
title.addContent("neuroConstruct example projects");
intro.addContent(
"Downloadable neuroConstruct example projects. These <strong>illustrate the core "
+ "functionality of neuroConstruct</strong>, as opposed to providing electrophysiologically accurate "
+ "models. Projects based on published conductance based models can be found <a href=\"../models/index.html\">here</a>");
}
if (sourceProjDir.getName().indexOf("models") >= 0) {
title.addContent("neuroConstruct projects based on published neuronal and network models");
intro.addContent(
"Downloadable neuroConstruct projects <strong>based on published conductance based models</strong>. "
+ "Some examples to illustrate the core functionality of neuroConstruct, as opposed to "
+ "providing electrophysiologically accurate models can be found <a href=\"../samples/index.html\">here</a>."
+ "<p>Note: These models are currently being moved to a repository to allow open source, collaborative development of NeuroML models.</p>"
+ "<p>See the <a href=\"http://www.opensourcebrain.org\">Open Source Brain</a> website for full details. "
+ "<img alt=\"Open Source Brain\" src=\"http://www.opensourcebrain.org/images/logo.png\"/></p>");
}
File[] fileArray = sourceProjDir.listFiles();
fileArray = GeneralUtils.reorderAlphabetically(fileArray, true);
ArrayList<File> files = GeneralUtils.toArrayList(fileArray);
// if (files.contains(""))
ArrayList<String> toIgnore = new ArrayList<String>();
// toIgnore.add("Thalamocortical"); // temporarily
// toIgnore.add("CA1PyramidalCell"); // temporarily
// toIgnore.add("SolinasEtAl-GolgiCell"); // temporarily
for (File exProjDir : files) {
File morphDir = new File(exProjDir, "cellMechanisms");
if (morphDir.isDirectory() && !toIgnore.contains(exProjDir.getName())) {
String projName = exProjDir.getName();
SimpleXMLElement section = new SimpleXMLElement("section");
body.addChildElement(section);
SimpleXMLElement secTitle = new SimpleXMLElement("title");
section.addChildElement(secTitle);
secTitle.addContent(projName);
SimpleXMLElement anchor = new SimpleXMLElement("anchor");
section.addChildElement(anchor);
anchor.addAttribute("id", projName);
SimpleXMLElement table = new SimpleXMLElement("table");
section.addChildElement(table);
SimpleXMLElement row = new SimpleXMLElement("tr");
table.addChildElement(row);
String largeImg = "large.png";
String smallImg = "small.png";
File targetImageDir = new File(mainFile.getParentFile(), "images");
if (!targetImageDir.exists()) targetImageDir.mkdir();
File targetProjImageDir = new File(targetImageDir, projName);
if (!targetProjImageDir.exists()) targetProjImageDir.mkdir();
File smallImgFile = new File(exProjDir, "images/" + smallImg);
File largeImgFile = new File(exProjDir, "images/" + largeImg);
if (smallImgFile.exists()) {
GeneralUtils.copyFileIntoDir(smallImgFile, targetProjImageDir);
SimpleXMLElement col2 = new SimpleXMLElement("td");
row.addChildElement(col2);
col2.addAttribute("width", "120");
SimpleXMLElement secImg = new SimpleXMLElement("p");
col2.addChildElement(secImg);
SimpleXMLElement img = new SimpleXMLElement("img");
img.addAttribute("src", "images/" + projName + "/small.png");
img.addAttribute("alt", "Screenshot of " + projName);
if (largeImgFile.exists()) {
GeneralUtils.copyFileIntoDir(largeImgFile, targetProjImageDir);
SimpleXMLElement imgRef = new SimpleXMLElement("a");
img.addAttribute("title", "Click to enlarge");
imgRef.addAttribute("href", "images/" + projName + "/" + largeImg);
imgRef.addChildElement(img);
secImg.addChildElement(imgRef);
} else {
secImg.addChildElement(img);
}
}
SimpleXMLElement secIntro = new SimpleXMLElement("p");
SimpleXMLElement colMid = new SimpleXMLElement("td");
SimpleXMLElement colRight = new SimpleXMLElement("td");
row.addChildElement(colMid);
row.addChildElement(colRight);
colRight.addAttribute("width", "150");
colMid.addChildElement(secIntro);
secIntro.addContent("Project name: <strong>" + projName + "</strong>");
File projFile = ProjectStructure.findProjectFile(exProjDir);
Project project = Project.loadProject(projFile, null);
String descFull = project.getProjectDescription();
String breakpoint = "\n\n";
String descShort = new String(descFull);
if (descFull.indexOf(breakpoint) > 0) {
descShort = descFull.substring(0, descFull.indexOf(breakpoint));
}
SimpleXMLElement desc = new SimpleXMLElement("p");
colMid.addChildElement(desc);
desc.addContent(GeneralUtils.parseForHyperlinks(descShort));
SimpleXMLElement modified = new SimpleXMLElement("p");
colMid.addChildElement(modified);
SimpleDateFormat formatter = new SimpleDateFormat("EEEE MMMM d, yyyy");
java.util.Date date = new java.util.Date(projFile.lastModified());
modified.addContent("Project last modified: " + formatter.format(date));
File zipFile = null;
String zipFileName =
targetDownloadDir.getAbsolutePath()
+ "/"
+ projName
+ ProjectStructure.getNewProjectZipFileExtension();
ArrayList<String> ignore = new ArrayList<String>();
ArrayList<String> ignoreNone = new ArrayList<String>();
ArrayList<String> ignoreExtns = new ArrayList<String>();
ignore.add("i686");
ignore.add("x86_64");
ignore.add(".svn");
ignore.add("simulations");
ignore.add("generatedNEURON");
ignore.add("generatedNeuroML");
ignore.add("generatedGENESIS");
ignore.add("generatedMOOSE");
ignore.add("generatedPyNN");
ignore.add("generatedPSICS");
ignore.add("dataSets");
ignoreExtns.add("bak");
zipFile = ZipUtils.zipUp(exProjDir, zipFileName, ignore, ignoreExtns);
logger.logComment(
"The zip file: "
+ zipFile.getAbsolutePath()
+ " ("
+ zipFile.length()
+ " bytes) contains all of the project files");
SimpleXMLElement downloads = new SimpleXMLElement("p");
colRight.addChildElement(downloads);
downloads.addContent("Downloads<a href=\"#downloadInfo\">*</a>:");
SimpleXMLElement downloadProj = new SimpleXMLElement("p");
colRight.addChildElement(downloadProj);
SimpleXMLElement link = new SimpleXMLElement("a");
link.addAttribute("href", "downloads/" + zipFile.getName());
link.addContent("neuroConstruct project");
link.addAttribute("title", "Download full project for loading into neuroConstruct");
downloadProj.addChildElement(link);
ArrayList<String> noNeuroML = new ArrayList<String>();
noNeuroML.add("Ex3_Morphology");
noNeuroML.add("DentateGyrus");
noNeuroML.add("RothmanEtAl_KoleEtAl_PyrCell");
if (!noNeuroML.contains(projName)) {
project.neuromlFileManager.generateNeuroMLFiles(
null, new OriginalCompartmentalisation(), 1234, false);
File neuroMLDir = ProjectStructure.getNeuroML1Dir(project.getProjectMainDirectory());
String nmlZipFileName =
targetDownloadDir.getAbsolutePath() + "/" + projName + "_NeuroML.zip";
zipFile = ZipUtils.zipUp(neuroMLDir, nmlZipFileName, ignoreNone, ignoreNone);
SimpleXMLElement downloadNml = new SimpleXMLElement("p");
colRight.addChildElement(downloadNml);
// downloadNml.addContent("Download project as pure NeuroML: ");
SimpleXMLElement img = new SimpleXMLElement("img");
img.addAttribute("src", "../images/NeuroMLSmall.png");
String info = "Download core project elements in NeuroML format";
img.addAttribute("alt", info);
SimpleXMLElement imgRef = new SimpleXMLElement("a");
img.addAttribute("title", info);
imgRef.addAttribute("href", "downloads/" + zipFile.getName());
imgRef.addChildElement(img);
downloadNml.addChildElement(imgRef);
}
}
}
SimpleXMLElement end = new SimpleXMLElement("p");
body.addChildElement(end);
end.addContent(" ");
SimpleXMLElement infoDlanchor = new SimpleXMLElement("anchor");
body.addChildElement(infoDlanchor);
end.addAttribute("id", "downloadInfo");
SimpleXMLElement infoDl = new SimpleXMLElement("p");
body.addChildElement(infoDl);
end.addContent(
"* Note: neuroConstruct project downloads (most of which are included with the standard software distribution) "
+ "can be loaded directly into neuroConstruct to generate cell and network scripts for NEURON, GENESIS, etc.,"
+ " but NeuroML downloads just consist of the core elements of the project"
+ " (morphologies, channels, etc.) which have been exported in NeuroML format. The latter can be useful for testing NeuroML compliant applications. "
+ "If no NeuroML download link is present, this usually indicates that the model is mainly implemented using channel/synapse mechanisms in a simulator's "
+ "native language (e.g. mod files) which have not fully been converted to ChannelML yet.");
SimpleXMLElement end2 = new SimpleXMLElement("p");
body.addChildElement(end2);
end2.addContent(" ");
FileWriter fw = null;
try {
fw = new FileWriter(mainFile);
fw.write("<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n"); // quick hack, todo: add to
// SimpleXMLDoc...
fw.write(
"<!DOCTYPE document PUBLIC \"-//APACHE//DTD Documentation V2.0//EN\" \"http://forrest.apache.org/dtd/document-v20.dtd\">\n\n");
fw.write(root.getXMLString("", false));
fw.flush();
fw.close();
} catch (IOException ex) {
logger.logError("Problem: ", ex);
fw.close();
}
/*
<header>
<title>Examples of neuroConstruct in use</title>
</header>
<body>
<p>Some screenshots of neuroConstruct in action are given below.
Click on the thumbnails to see a full size version of the screenshots</p>
<section>
<title>Examples included with distribution</title>*/
}
public ArrayList<SimpleXMLEntity> getNetworkMLEntities(
int unitSystem, NeuroMLConstants.NeuroMLVersion version, SimpleXMLElement topLevelCompElement)
throws NeuroMLException {
ArrayList<SimpleXMLEntity> entities = new ArrayList<SimpleXMLEntity>();
Units timeUnits = UnitConverter.timeUnits[unitSystem];
Units currentUnits = UnitConverter.currentUnits[unitSystem];
SimpleXMLElement inputsElement = null;
try {
logger.logComment(
"Going to save file in NeuroML format: "
+ this.getNumberSingleInputs()
+ " inputs in total");
if (getNumberSingleInputs() == 0) {
SimpleXMLComment comm =
new SimpleXMLComment("There are no electrical inputs present in the network");
entities.add(comm);
return entities;
}
boolean nml2 = version.isVersion2();
boolean nml2alpha = version.isVersion2alpha();
if (!nml2) {
inputsElement = new SimpleXMLElement(NetworkMLConstants.INPUTS_ELEMENT);
entities.add(inputsElement);
if (unitSystem == UnitConverter.GENESIS_PHYSIOLOGICAL_UNITS) {
inputsElement.addAttribute(
new SimpleXMLAttribute(
NetworkMLConstants.UNITS_ATTR, NetworkMLConstants.UNITS_PHYSIOLOGICAL));
} else if (unitSystem == UnitConverter.GENESIS_SI_UNITS) {
inputsElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.UNITS_ATTR, NetworkMLConstants.UNITS_SI));
}
}
Enumeration keys = myElecInputs.keys();
while (keys.hasMoreElements()) {
String inputReference = (String) keys.nextElement();
ArrayList<SingleElectricalInput> inputsHere = getInputLocations(inputReference);
logger.logComment("Adding " + inputsHere.size() + " inputs");
StimulationSettings nextStim = project.elecInputInfo.getStim(inputReference);
ElectricalInput myElectricalInput = nextStim.getElectricalInput();
SimpleXMLElement inputElement = new SimpleXMLElement(NetworkMLConstants.INPUT_ELEMENT);
inputElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.INPUT_NAME_ATTR, inputReference));
if (myElectricalInput instanceof IClamp) {
IClamp ic = (IClamp) myElectricalInput;
float delay = ic.getDel().getNominalNumber();
float duration = ic.getDur().getNominalNumber();
float amplitude = ic.getAmp().getNominalNumber();
SimpleXMLElement inputTypeElement =
new SimpleXMLElement(NetworkMLConstants.PULSEINPUT_ELEMENT);
float del =
(float) UnitConverter.getTime(delay, UnitConverter.NEUROCONSTRUCT_UNITS, unitSystem);
float dur =
(float)
UnitConverter.getTime(duration, UnitConverter.NEUROCONSTRUCT_UNITS, unitSystem);
float amp =
(float)
UnitConverter.getCurrent(
amplitude, UnitConverter.NEUROCONSTRUCT_UNITS, unitSystem);
inputTypeElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.INPUT_DELAY_ATTR, del + ""));
inputTypeElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.INPUT_DUR_ATTR, dur + ""));
inputTypeElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.INPUT_AMP_ATTR, amp + ""));
inputElement.addChildElement(inputTypeElement);
inputElement.addContent("\n ");
if (nml2) {
SimpleXMLElement pulseGenElement =
new SimpleXMLElement(NetworkMLConstants.NEUROML2_PULSE_GEN_ELEMENT);
pulseGenElement.addAttribute(NeuroMLConstants.NEUROML_ID_V2, inputReference);
pulseGenElement.addAttribute(
NetworkMLConstants.INPUT_DELAY_ATTR, del + timeUnits.getNeuroML2Symbol());
pulseGenElement.addAttribute(
NetworkMLConstants.INPUT_DUR_ATTR, dur + timeUnits.getNeuroML2Symbol());
pulseGenElement.addAttribute(
NetworkMLConstants.INPUT_AMP_ATTR, amp + currentUnits.getNeuroML2Symbol());
topLevelCompElement.addContent("\n\n ");
topLevelCompElement.addChildElement(pulseGenElement);
topLevelCompElement.addContent("\n\n ");
}
} else if (myElectricalInput instanceof RandomSpikeTrain) {
RandomSpikeTrain rst = (RandomSpikeTrain) myElectricalInput;
float stimFreq = rst.getRate().getNominalNumber();
String stimMech = rst.getSynapseType();
SimpleXMLElement inputTypeElement =
new SimpleXMLElement(NetworkMLConstants.RANDOMSTIM_ELEMENT);
float rate =
(float)
UnitConverter.getRate(stimFreq, UnitConverter.NEUROCONSTRUCT_UNITS, unitSystem);
inputTypeElement.addAttribute(
new SimpleXMLAttribute(
NetworkMLConstants.RND_STIM_FREQ_ATTR,
(float)
UnitConverter.getRate(
stimFreq, UnitConverter.NEUROCONSTRUCT_UNITS, unitSystem)
+ ""));
inputTypeElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.RND_STIM_MECH_ATTR, stimMech));
inputElement.addChildElement(inputTypeElement);
inputElement.addContent("\n ");
if (nml2 && !nml2alpha) {
SimpleXMLElement spikeGenElement =
new SimpleXMLElement(NetworkMLConstants.NEUROML2_SPIKE_GEN_POISSON_ELEMENT);
spikeGenElement.addAttribute(NeuroMLConstants.NEUROML_ID_V2, inputReference);
spikeGenElement.addAttribute(
NetworkMLConstants.NEUROML2_SPIKE_GEN_POISSON_RATE_ATTR,
rate
+ " "
+ UnitConverter.rateUnits[UnitConverter.NEUROCONSTRUCT_UNITS]
.getNeuroML2Symbol()
+ "");
topLevelCompElement.addContent("\n\n ");
topLevelCompElement.addChildElement(spikeGenElement);
topLevelCompElement.addContent("\n\n ");
}
} else {
throw new NeuroMLException(
"Error trying to save input "
+ inputReference
+ ". Cannot save in NeuroML an input of type: "
+ myElectricalInput.getType());
}
SimpleXMLElement inputTargetElement =
new SimpleXMLElement(NetworkMLConstants.INPUT_TARGET_ELEMENT);
inputTargetElement.addAttribute(
new SimpleXMLAttribute(
NetworkMLConstants.INPUT_TARGET_POPULATION_ATTR, nextStim.getCellGroup()));
inputElement.addChildElement(inputTargetElement);
inputTargetElement.addContent("\n ");
SimpleXMLElement inputTargetSitesElement =
new SimpleXMLElement(NetworkMLConstants.INPUT_TARGET_SITES_ELEMENT);
inputTargetSitesElement.addAttribute(
new SimpleXMLAttribute(
NetworkMLConstants.INPUT_SITES_SIZE_ATTR, inputsHere.size() + ""));
inputTargetElement.addChildElement(inputTargetSitesElement);
SimpleXMLElement stimProjElement = null;
if (version.isVersion2betaOrLater()) {
if (myElectricalInput instanceof IClamp) {
SimpleXMLElement inputListElement =
new SimpleXMLElement(NetworkMLConstants.NEUROML2_INPUT_LIST_ELEMENT);
entities.add(inputListElement);
inputListElement.addAttribute(NeuroMLConstants.NEUROML_ID_V2, nextStim.getReference());
inputListElement.addAttribute(
NetworkMLConstants.NEUROML2_INPUT_COMPONENT, inputReference);
inputListElement.addAttribute(
NetworkMLConstants.NEUROML2_INPUT_POPULATION, nextStim.getCellGroup());
// inputElement.addContent("\n ");
inputTargetSitesElement = inputListElement;
} else if (myElectricalInput instanceof RandomSpikeTrain) {
SimpleXMLElement popElement =
new SimpleXMLElement(NetworkMLConstants.POPULATION_ELEMENT);
entities.add(0, popElement);
popElement.addAttribute(
NeuroMLConstants.NEUROML_ID_V2, nextStim.getReference() + "_population");
popElement.addAttribute(
NetworkMLConstants.NEUROML2_POPULATION_COMPONENT,
nextStim.getReference() + "_population");
popElement.addAttribute(
NetworkMLConstants.NEUROML2_POPULATION_SIZE, inputsHere.size() + "");
stimProjElement = new SimpleXMLElement(NetworkMLConstants.PROJECTION_ELEMENT);
stimProjElement.addAttribute(
NeuroMLConstants.NEUROML_ID_V2, nextStim.getReference() + "_projection");
entities.add(stimProjElement);
}
}
// Iterate around the list of sites
for (int i = 0; i < inputsHere.size(); i++) {
inputTargetSitesElement.addContent("\n ");
SingleElectricalInput sei = inputsHere.get(i);
SimpleXMLElement inputTargetSiteElement =
new SimpleXMLElement(NetworkMLConstants.INPUT_TARGET_SITE_ELEMENT);
inputTargetSiteElement.addAttribute(
new SimpleXMLAttribute(
NetworkMLConstants.INPUT_SITE_CELLID_ATTR, sei.getCellNumber() + ""));
inputTargetSiteElement.addAttribute(
new SimpleXMLAttribute(
NetworkMLConstants.INPUT_SITE_SEGID_ATTR, sei.getSegmentId() + ""));
inputTargetSiteElement.addAttribute(
new SimpleXMLAttribute(
NetworkMLConstants.INPUT_SITE_FRAC_ATTR, sei.getFractionAlong() + ""));
if (!nml2) inputTargetSitesElement.addChildElement(inputTargetSiteElement);
if (nml2 && !nml2alpha) {
if (myElectricalInput instanceof RandomSpikeTrain) {
String connElName = NetworkMLConstants.CONNECTION_ELEMENT;
SimpleXMLElement connElement = new SimpleXMLElement(connElName);
connElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.CONNECTION_ID_ATTR, i + ""));
stimProjElement.addContent("\n ");
stimProjElement.addChildElement(connElement);
stimProjElement.addContent("\n ");
}
}
if (sei.getInstanceProps() != null) {
inputTargetSiteElement.addContent("\n ");
inputTargetSiteElement.addComment("Adding the site specific props");
if (sei.getInstanceProps() instanceof IClampInstanceProps) {
IClampInstanceProps ic = (IClampInstanceProps) sei.getInstanceProps();
float delay =
(float)
UnitConverter.getTime(
ic.getDelay(), UnitConverter.NEUROCONSTRUCT_UNITS, unitSystem);
float duration =
(float)
UnitConverter.getTime(
ic.getDuration(), UnitConverter.NEUROCONSTRUCT_UNITS, unitSystem);
float amp =
(float)
UnitConverter.getCurrent(
ic.getAmplitude(), UnitConverter.NEUROCONSTRUCT_UNITS, unitSystem);
if (!nml2) {
SimpleXMLElement inputTypeElement =
new SimpleXMLElement(NetworkMLConstants.PULSEINPUT_INSTANCE_ELEMENT);
inputTypeElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.INPUT_DELAY_ATTR, delay + ""));
inputTypeElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.INPUT_DUR_ATTR, duration + ""));
// System.out.println("Converted "+amp+" to "+ a);
inputTypeElement.addAttribute(
new SimpleXMLAttribute(NetworkMLConstants.INPUT_AMP_ATTR, amp + ""));
inputTargetSiteElement.addContent(" ");
inputTargetSiteElement.addChildElement(inputTypeElement);
inputTargetSiteElement.addContent("\n ");
} else {
SimpleXMLElement pulseGenElement =
new SimpleXMLElement(NetworkMLConstants.NEUROML2_PULSE_GEN_ELEMENT);
pulseGenElement.addAttribute(
NeuroMLConstants.NEUROML_ID_V2, inputReference + "__" + i);
pulseGenElement.addAttribute(
NetworkMLConstants.INPUT_DELAY_ATTR, delay + timeUnits.getNeuroML2Symbol());
pulseGenElement.addAttribute(
NetworkMLConstants.INPUT_DUR_ATTR, duration + timeUnits.getNeuroML2Symbol());
pulseGenElement.addAttribute(
NetworkMLConstants.INPUT_AMP_ATTR, amp + currentUnits.getNeuroML2Symbol());
topLevelCompElement.addContent("\n\n ");
topLevelCompElement.addChildElement(pulseGenElement);
topLevelCompElement.addContent("\n\n ");
if (version.isVersion2alpha()) {
String target = nextStim.getCellGroup() + "[" + sei.getCellNumber() + "]";
SimpleXMLElement expInputElement =
new SimpleXMLElement(NetworkMLConstants.NEUROML2_EXP_INPUT_ELEMENT);
expInputElement.addAttribute(
NetworkMLConstants.NEUROML2_EXP_INPUT_TARGET_ATTR, target);
expInputElement.addAttribute(
NetworkMLConstants.NEUROML2_EXP_INPUT_INPUT_ATTR, inputReference + "__" + i);
entities.add(expInputElement);
} else {
String target =
"../"
+ nextStim.getCellGroup()
+ "/"
+ sei.getCellNumber()
+ "/"
+ project.cellGroupsInfo.getCellType(nextStim.getCellGroup());
SimpleXMLElement expInputElement =
new SimpleXMLElement(NetworkMLConstants.NEUROML2_INPUT_LIST_ELEMENT);
expInputElement.addAttribute(
NetworkMLConstants.NEUROML2_EXP_INPUT_TARGET_ATTR, target);
expInputElement.addAttribute(
NetworkMLConstants.NEUROML2_EXP_INPUT_INPUT_ATTR, inputReference + "__" + i);
entities.add(expInputElement);
}
}
} else if (sei.getInstanceProps() instanceof RandomSpikeTrainInstanceProps) {
RandomSpikeTrainInstanceProps rst =
(RandomSpikeTrainInstanceProps) sei.getInstanceProps();
float stimFreq = rst.getRate();
// String stimMech = rst.get;
SimpleXMLElement inputTypeElement =
new SimpleXMLElement(NetworkMLConstants.RANDOMSTIM_INSTANCE_ELEMENT);
inputTypeElement.addAttribute(
new SimpleXMLAttribute(
NetworkMLConstants.RND_STIM_FREQ_ATTR,
(float)
UnitConverter.getRate(
stimFreq, UnitConverter.NEUROCONSTRUCT_UNITS, unitSystem)
+ ""));
// inputTypeElement.addAttribute(new
// SimpleXMLAttribute(NetworkMLConstants.RND_STIM_MECH_ATTR, stimMech));
inputTargetSiteElement.addContent(" ");
inputTargetSiteElement.addChildElement(inputTypeElement);
inputTargetSiteElement.addContent("\n ");
} else {
throw new NeuroMLException(
"Error trying to save input "
+ inputReference
+ ". Cannot save in NeuroML an input of type: "
+ myElectricalInput.getType());
}
} else {
if (nml2) {
if (version.isVersion2alpha()) {
String target = nextStim.getCellGroup() + "[" + sei.getCellNumber() + "]";
SimpleXMLElement expInputElement =
new SimpleXMLElement(NetworkMLConstants.NEUROML2_EXP_INPUT_ELEMENT);
expInputElement.addAttribute(
NetworkMLConstants.NEUROML2_EXP_INPUT_TARGET_ATTR, target);
expInputElement.addAttribute(
NetworkMLConstants.NEUROML2_EXP_INPUT_INPUT_ATTR, inputReference);
entities.add(expInputElement);
} else {
String target =
"../"
+ nextStim.getCellGroup()
+ "/"
+ sei.getCellNumber()
+ "/"
+ project.cellGroupsInfo.getCellType(nextStim.getCellGroup());
SimpleXMLElement expInputElement =
new SimpleXMLElement(NetworkMLConstants.NEUROML2_INPUT_ELEMENT);
expInputElement.addAttribute(NeuroMLConstants.NEUROML_ID_V2, i + "");
expInputElement.addAttribute(
NetworkMLConstants.NEUROML2_EXP_INPUT_TARGET_ATTR, target);
expInputElement.addAttribute(
NetworkMLConstants.NEUROML2_INPUT_DESTINATION,
NetworkMLConstants.NEUROML2_INPUT_DESTINATION_DEFAULT);
inputTargetSitesElement.addChildElement(expInputElement);
}
}
}
if (i == inputsHere.size() - 1) inputTargetSitesElement.addContent("\n ");
// Next Site
}
inputTargetElement.addContent("\n ");
if (!nml2) {
inputsElement.addChildElement(inputElement);
inputElement.addContent("\n ");
}
}
logger.logComment("Finished saving data to inputs element");
} catch (Exception ex) {
ex.printStackTrace();
throw new NeuroMLException("Problem creating inputs element file", ex);
}
return entities;
}