public static void main(String[] args) { new ExampleProjects(); try { File exsDir = new File("osb/showcase/neuroConstructShowcase"); File mainFile = new File("docs/XML/xmlForHtml/samples/index.xml"); logger.logComment("Going to create docs at: " + mainFile.getCanonicalPath(), true); generateMainPage(mainFile, exsDir); logger.logComment("Created doc at: " + mainFile.getCanonicalPath(), true); /* File modelsDir = new File("nCmodels"); mainFile = new File("docs/XML/xmlForHtml/models/index.xml"); generateMainPage(mainFile, modelsDir); logger.logComment("Created doc at: "+ mainFile.getCanonicalPath(), true); */ } catch (Exception e) { e.printStackTrace(); } }
public void parseGroup(Group g) throws Hdf5Exception, EndOfSequenceException { startGroup(g); java.util.List members = g.getMemberList(); // NOTE: parsing contents twice to ensure subgroups are handled before datasets // This is mainly because synapse_props groups will need to be parsed before dataset of // connections for (int j = 0; j < members.size(); j++) { HObject obj = (HObject) members.get(j); if (obj instanceof Group) { Group subGroup = (Group) obj; logger.logComment("--------- Found a sub group: " + subGroup.getName()); parseGroup(subGroup); } } for (int j = 0; j < members.size(); j++) { HObject obj = (HObject) members.get(j); if (obj instanceof Dataset) { Dataset ds = (Dataset) obj; logger.logComment("Found a dataset: " + ds.getName()); dataSet(ds); } } endGroup(g); }
/** * Transforms the given XML string using the XSL string. * * @param xmlString The String containg the XML to transform * @param xslString The XML Stylesheet String containing the transform instructions * @return String representation of the transformation */ public static String transform(String xmlString, String xslString) { String shortString = new String(xmlString); if (shortString.length() > 100) shortString = shortString.substring(0, 100) + "..."; try { TransformerFactory tFactory = TransformerFactory.newInstance(); logger.logComment("Transforming string: " + shortString); StreamSource xslFileSource = new StreamSource(new StringReader(xslString)); Transformer transformer = tFactory.newTransformer(xslFileSource); StringWriter writer = new StringWriter(); transformer.transform( new StreamSource(new StringReader(xmlString)), new StreamResult(writer)); String shortResult = writer.toString(); if (shortResult.length() > 100) shortResult = shortResult.substring(0, 100) + "..."; logger.logComment("Result: " + shortResult); return writer.toString(); } catch (TransformerException e) { GuiUtils.showErrorMessage(logger, "Error when transforming the XML: " + shortString, e, null); return null; } }
public void loadFromFile(File positionFile) throws java.io.IOException { logger.logComment("Loading position records from file: " + positionFile.getAbsolutePath()); this.reset(); Reader in = new FileReader(positionFile); LineNumberReader reader = new LineNumberReader(in); String nextLine = null; String currentInputRef = null; while ((nextLine = reader.readLine()) != null) { // logger.logComment("Parsing line: "+ nextLine); if (nextLine.endsWith(":")) { currentInputRef = nextLine.substring(0, nextLine.length() - 1); logger.logComment("currentInputRef: " + currentInputRef); } else { SingleElectricalInput input = new SingleElectricalInput(nextLine); this.addSingleInput(currentInputRef, input); } } in.close(); logger.logComment("Finished loading cell info. Internal state: " + this.toString()); }
/** This main function is used for the ant task helpdocs. Don't change for testing!! */ public static void main(String[] args) { if (args.length != 4) { System.out.println( "Usage: java ucl.physiol.neuroconstruct.utils.XMLUtils originalXMLFile xslFile targetFile\n"); System.out.println("with: "); System.out.println(" originalXMLFile the original XML file to be transformed"); System.out.println( " (Note: if it's a directory will generate all xml files in dir)"); System.out.println(" xslFile the XSL file used to generate the file(s)"); System.out.println(" targetDir the target directory for the XML/HTML/etc."); System.out.println( " extension filename extension for the new files (.xml, .html, etc.)\n"); return; } File origFile = new File(args[0]); File xslFile = new File(args[1]); File targetFile = new File(args[2]); String extension = args[3]; /* File origFile = new File ("docs/XML/xmlForHtml/docs"); File xslFile = new File ("docs/XML/helpViewer/helpdocs.xsl"); File targetFile = new File ("../temp/tmm"); String extension = ".html"; */ logger.logComment("Result: " + XMLUtils.transform(origFile, xslFile, targetFile, extension)); }
/** * Transforms the given XML file using the specified XSL file. * * @param origXmlFile The file containg the XML to transform * @param xslFile The XML Stylesheet conntaining the transform instructions * @return String representation of the transformation */ public static String transform(File origXmlFile, File xslFile) { if (!origXmlFile.exists()) { GuiUtils.showErrorMessage( logger, "Warning, XML file: " + origXmlFile + " doesn't exist", null, null); return null; } if (!xslFile.exists()) { GuiUtils.showErrorMessage( logger, "Warning, XSL file: " + xslFile + " doesn't exist", null, null); return null; } try { logger.logComment("The xslFile is " + xslFile + " *************"); TransformerFactory tFactory = TransformerFactory.newInstance(); StreamSource xslFileSource = new StreamSource(xslFile); Transformer transformer = tFactory.newTransformer(xslFileSource); StringWriter writer = new StringWriter(); transformer.transform(new StreamSource(origXmlFile), new StreamResult(writer)); return writer.toString(); } catch (Exception e) { GuiUtils.showErrorMessage(logger, "Error when loading the XML file: " + origXmlFile, e, null); return null; } }
// Gets the specified XML Schema doc if one is mentioned in the file public static File getSchemaFile(Document xmlDoc) { /** @todo Must be an easier way of doing this... */ logger.logComment("Getting schema file for: " + xmlDoc.getDocumentURI()); NodeList nl = xmlDoc.getChildNodes(); for (int j = 0; j < nl.getLength(); j++) { Node node = nl.item(j); logger.logComment("Type: " + node.getNodeType() + "Name: " + node.getNodeName()); if (node.getNodeName().equals(XML_STYLESHEET_NODE)) { String nodeVal = node.getNodeValue(); logger.logComment("Looking at: " + nodeVal); String xslFileName = nodeVal.substring(nodeVal.indexOf("href=\"") + 6, nodeVal.length() - 1); File xslFile = new File(xslFileName); return xslFile; } if (node.getAttributes().getLength() > 0) { logger.logComment("Attributes: " + node.getAttributes()); if (node.getAttributes().getNamedItem(XML_SCHEMA_LOC_ATTR) != null) { String locString = node.getAttributes().getNamedItem(XML_SCHEMA_LOC_ATTR).getNodeValue(); logger.logComment("Loc string: " + locString); String file = locString.split("\\s")[1]; return new File(file); } } } logger.logError("No node found with name: " + XML_STYLESHEET_NODE); return null; }
public static void main(String args[]) { try { logger.logComment("Sys prop: " + System.getProperty("java.library.path"), true); // File projFile = new File("../copyNcModels/NewGranCellLayer/NewGranCellLayer.neuro.xml"); // File projFile = new File("../nC_projects/Bignet/Bignet.neuro.xml"); File projFile = new File("testProjects/TestNetworkML/TestNetworkML.neuro.xml"); // Project testProj = Project.loadProject(new File("projects/Parall/Parall.neuro.xml"),null); // Project testProj = Project.loadProject(new // File("examples/Ex5-Networks/Ex5-Networks.neuro.xml"),null); Project testProj = Project.loadProject(projFile, null); // File h5File = new File(projFile.getParentFile().getAbsolutePath()+ // "/savedNetworks/hhh.h5"); // File h5File = new File(projFile.getParentFile().getAbsolutePath()+ // "/savedNetworks/nnnn.h5"); File h5File = new File("testProjects/TestNetworkML/savedNetworks/small.h5"); // logger.logComment("Loading netml cell from "+ h5File.getAbsolutePath(), true); NetworkMLReader nmlReader = new NetworkMLReader(testProj); nmlReader.parse(h5File); logger.logComment("Contents: " + testProj.generatedCellPositions); logger.logComment("Net conns: " + testProj.generatedNetworkConnections); logger.logComment("Inputs: " + testProj.generatedElecInputs.details(false)); } catch (Exception e) { e.printStackTrace(); System.exit(0); } }
/** * Transforms the given XML string using the specified XSL file. * * @param xmlString The String containg the XML to transform * @param xslFile The XML Stylesheet conntaining the transform instructions * @return String representation of the transformation */ public static String transform(String xmlString, File xslFile) { if (!xslFile.exists()) { GuiUtils.showErrorMessage( logger, "Warning, XSL file: " + xslFile + " doesn't exist", null, null); return null; } String shortString = new String(xmlString); if (shortString.length() > 100) shortString = shortString.substring(0, 100) + "..."; try { logger.logComment("The xslFile is " + xslFile.getAbsolutePath() + " *************"); TransformerFactory tFactory = TransformerFactory.newInstance(); logger.logComment("Transforming string: " + shortString); StreamSource xslFileSource = new StreamSource(xslFile); Transformer transformer = tFactory.newTransformer(xslFileSource); StringWriter writer = new StringWriter(); transformer.transform( new StreamSource(new StringReader(xmlString)), new StreamResult(writer)); String shortResult = writer.toString(); if (shortResult.length() > 100) shortResult = shortResult.substring(0, 100) + "..."; logger.logComment("Result: " + shortResult); return writer.toString(); } catch (TransformerException e) { GuiUtils.showErrorMessage(logger, "Error when transforming the XML: " + shortString, e, null); return null; } }
// Gets the specified XML Schema doc if one is mentioned in the file public static File getSchemaFile(File xmlDoc) { /** @todo Must be an easier way of doing this... */ logger.logComment("Getting schema file for: " + xmlDoc); try { // File xslFile = null; DocumentBuilderFactory dbf = DocumentBuilderFactory.newInstance(); DocumentBuilder db = dbf.newDocumentBuilder(); Document doc = db.parse(xmlDoc); return getSchemaFile(doc); } catch (Exception e) { GuiUtils.showErrorMessage(logger, "Error when looking at the XML file: " + xmlDoc, e, null); return null; } }
public void endGroup(Group g) throws Hdf5Exception { logger.logComment("----- Going out of a group: " + g.getFullName()); if (g.getName().equals(NetworkMLConstants.POPULATIONS_ELEMENT)) { inPopulations = false; } else if (g.getName().equals(NetworkMLConstants.PROJECTIONS_ELEMENT)) { inProjections = false; } else if (g.getName().equals(NetworkMLConstants.INPUTS_ELEMENT)) { inInputs = false; } else if (g.getName().equals(NetworkMLConstants.INPUT_ELEMENT) && inInputs) { currentInput = null; } else if (g.getName().startsWith(NetworkMLConstants.POPULATION_ELEMENT) && inPopulations) { currentCellGroup = null; } else if (g.getName().startsWith(NetworkMLConstants.PROJECTION_ELEMENT) && inProjections) { currentNetConn = null; globConnProps = new ArrayList<ConnSpecificProps>(); } else if (g.getName().startsWith(NetworkMLConstants.CONNECTION_ELEMENT)) { localConnProps = new ArrayList<ConnSpecificProps>(); localAPDelay = 0; } }
public void saveToFile(File inputsFile) throws java.io.IOException { logger.logComment( "Saving " + this.getNumberSingleInputs() + " inputs to file: " + inputsFile.getAbsolutePath()); // will create the parent dir if it doesn't exist. if (!inputsFile.exists()) { logger.logComment("File: " + inputsFile + " doesn't exist."); if (!inputsFile.getParentFile().exists()) { logger.logComment("Parent dir: " + inputsFile.getParentFile() + " doesn't exist."); // String parentDirName = inputsFile.getParentFile().getCanonicalPath(); File projectDir = inputsFile.getParentFile().getParentFile(); if (!projectDir.exists()) { throw new FileNotFoundException( "Project dir doesn't exist: " + projectDir.getAbsolutePath()); } // logger.logComment("Going to create dir: "+ parentDirName +" in dir :"+ projectDir); logger.logComment("Going to create dir: " + inputsFile.getParentFile()); inputsFile.getParentFile().mkdir(); logger.logComment("Success? " + inputsFile.getParentFile().exists()); } } FileWriter fw = new FileWriter(inputsFile); Enumeration keys = this.myElecInputs.keys(); while (keys.hasMoreElements()) { String input = (String) keys.nextElement(); ArrayList<SingleElectricalInput> inputs = getInputLocations(input); fw.write(input + ":\n"); for (int i = 0; i < inputs.size(); i++) { fw.write(inputs.get(i) + "\n"); } } logger.logComment("Finished saving data to file: " + inputsFile.getAbsolutePath()); fw.flush(); fw.close(); }
public void startGroup(Group g) throws Hdf5Exception { logger.logComment("----- Going into a group: " + g.getFullName()); ArrayList<Attribute> attrs = Hdf5Utils.parseGroupForAttributes(g); for (Attribute attribute : attrs) { // attribute. logger.logComment( "Group: " + g.getName() + " has attribute: " + attribute.getName() + " = " + Hdf5Utils.getFirstStringValAttr(attrs, attribute.getName())); } if (g.getName().equals(NetworkMLConstants.ROOT_ELEMENT)) { logger.logComment("Found the main group"); String simConfigName = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.NC_SIM_CONFIG); if (simConfigName != null) this.foundSimConfig = simConfigName; String randomSeed = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.NC_NETWORK_GEN_RAND_SEED); if (randomSeed != null) this.foundRandomSeed = Long.parseLong(randomSeed); } else if (g.getName().equals(NetworkMLConstants.POPULATIONS_ELEMENT)) { logger.logComment("Found the pops group"); inPopulations = true; } else if (g.getName().startsWith(NetworkMLConstants.POPULATION_ELEMENT) && inPopulations) { String name = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.POP_NAME_ATTR); logger.logComment("Found a population: " + name); currentCellGroup = name; } else if (g.getName().equals(NetworkMLConstants.PROJECTIONS_ELEMENT)) { logger.logComment("Found the projections group"); inProjections = true; String units = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.UNITS_ATTR); projUnitSystem = UnitConverter.getUnitSystemIndex(units); } else if (g.getName().startsWith(NetworkMLConstants.PROJECTION_ELEMENT) && inProjections) { String name = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.PROJ_NAME_ATTR); String source = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.SOURCE_ATTR); String target = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.TARGET_ATTR); logger.logComment("Found a projection: " + name + " from " + source + " to " + target); if (!project.morphNetworkConnectionsInfo.isValidSimpleNetConn(name) && !project.volBasedConnsInfo.isValidVolBasedConn(name)) { throw new Hdf5Exception( "Error: there is a network connection with name: " + name + " specified in " + "that file, but no such NetConn exists in the project. Add one to allow import of this file"); } /* TODO: Add checks on source & target!! */ if (project.morphNetworkConnectionsInfo.isValidSimpleNetConn(name)) { // if (project.morphNetworkConnectionsInfo) } currentNetConn = name; } else if (g.getName().startsWith(NetworkMLConstants.SYN_PROPS_ELEMENT + "_") && inProjections) { String name = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.SYN_TYPE_ATTR); ConnSpecificProps cp = new ConnSpecificProps(name); String internalDelay = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.INTERNAL_DELAY_ATTR); if (internalDelay != null) cp.internalDelay = (float) UnitConverter.getTime( Float.parseFloat(internalDelay), projUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); // Lump them in to the internal delay... String preDelay = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.PRE_DELAY_ATTR); if (preDelay != null) cp.internalDelay = cp.internalDelay + (float) UnitConverter.getTime( Float.parseFloat(preDelay), projUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); String postDelay = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.POST_DELAY_ATTR); if (postDelay != null) cp.internalDelay = cp.internalDelay + (float) UnitConverter.getTime( Float.parseFloat(postDelay), projUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); cp.weight = Float.parseFloat(Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.WEIGHT_ATTR)); String propDelay = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.PROP_DELAY_ATTR); if (propDelay != null) globAPDelay = (float) UnitConverter.getTime( Float.parseFloat(propDelay), projUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); logger.logComment("Found: " + cp); globConnProps.add(cp); } else if (g.getName().equals(NetworkMLConstants.INPUTS_ELEMENT)) { logger.logComment("Found the Inputs group"); inInputs = true; String units = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.UNITS_ATTR); inputUnitSystem = UnitConverter.getUnitSystemIndex(units); } else if (g.getName().startsWith(NetworkMLConstants.INPUT_ELEMENT) && inInputs) { // The table of input sites is within the input group so get sites from here String inputName = g.getName().substring(6); // String inputName = Hdf5Utils.getFirstStringValAttr(attrs, // NetworkMLConstants.INPUT_ELEMENT); logger.logComment("Found an Input: " + inputName); // inInput = true; if (project.elecInputInfo.getStim(inputName) == null) { throw new Hdf5Exception( "Error: there is an electrical input with name: " + inputName + " specified in " + "that file, but no such electrical input exists in the project. Add one to allow import of this file"); } // Get the atributes of the Input and compare them with the attributes within the project // Test to find out what type of input this is } else if (g.getName().startsWith("IClamp") && inInputs) { String inputName = g.getParent().getName().substring(6); // Get the input sites from the table String cellGroup = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.INPUT_TARGET_POPULATION_ATTR); if (cellGroup == null) { cellGroup = Hdf5Utils.getFirstStringValAttr( attrs, NetworkMLConstants.INPUT_TARGET_CELLGROUP_OLD_ATTR); // check old name } float readDelay = (float) UnitConverter.getTime( Float.parseFloat( Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.INPUT_DELAY_ATTR)), inputUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); float readDuration = (float) UnitConverter.getTime( Float.parseFloat( Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.INPUT_DUR_ATTR)), inputUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); float readAmp = (float) UnitConverter.getCurrent( Float.parseFloat( Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.INPUT_AMP_ATTR)), inputUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); StimulationSettings nextStim = project.elecInputInfo.getStim(inputName); ElectricalInput myElectricalInput = nextStim.getElectricalInput(); IClamp ic = (IClamp) myElectricalInput; logger.logComment("Found an IClamp Input"); float currDelay = -1, currDur = -1, currAmp = -1; /* try { ic.getDelay().reset(); currDelay = ic.getDelay().getNumber(); ic.getDuration().reset(); currDur = ic.getDuration().getNumber(); ic.getAmplitude().reset(); currAmp = ic.getAmplitude().getNumber(); } catch (Exception ex) { logger.logError("Legacy error getting iclamp params!!"); }*/ currDelay = ic.getDel().getNominalNumber(); currDur = ic.getDur().getNominalNumber(); currAmp = ic.getAmp().getNominalNumber(); if ((!project.elecInputInfo.getStim(inputName).getCellGroup().equals(cellGroup)) || (readDelay != currDelay) || (readDuration != currDur) || (readAmp != currAmp)) { throw new Hdf5Exception( "Error: the input properties of the file do not match those in the project for input " + inputName + "" + "\nreadDelay: " + readDelay + ", currDelay: " + currDelay + "\nreadDuration: " + readDuration + ", currDur: " + currDur + "\nreadAmp: " + readAmp + ", currAmp: " + currAmp + ", str: " + Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.INPUT_AMP_ATTR)); } currentInput = inputName; } else if (g.getName().startsWith("RandomSpikeTrain") && inInputs) { String inputName = g.getParent().getName().substring(6); // Get the input sites from the table String cellGroup = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.INPUT_TARGET_POPULATION_ATTR); if (cellGroup == null) { cellGroup = Hdf5Utils.getFirstStringValAttr( attrs, NetworkMLConstants.INPUT_TARGET_CELLGROUP_OLD_ATTR); // check old name } float frequency = (float) UnitConverter.getRate( Float.parseFloat( Hdf5Utils.getFirstStringValAttr( attrs, NetworkMLConstants.RND_STIM_FREQ_ATTR)), inputUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); String mechanism = Hdf5Utils.getFirstStringValAttr(attrs, NetworkMLConstants.RND_STIM_MECH_ATTR); StimulationSettings nextStim = project.elecInputInfo.getStim(inputName); ElectricalInput myElectricalInput = nextStim.getElectricalInput(); RandomSpikeTrain rs = (RandomSpikeTrain) myElectricalInput; logger.logComment("Found an Random Spike Train Input"); if ((!project.elecInputInfo.getStim(inputName).getCellGroup().equals(cellGroup)) || frequency != rs.getRate().getFixedNum() || !rs.getSynapseType().equals(mechanism)) { throw new Hdf5Exception( "Error: the input properties of the file do not match those in the project for input " + inputName); } currentInput = inputName; } }
public void dataSet(Dataset d) throws Hdf5Exception { logger.logComment("----- Looking through dataset: " + d); ArrayList<Attribute> attrs = Hdf5Utils.parseDatasetForAttributes(d); for (Attribute attribute : attrs) { logger.logComment( "Dataset: " + d.getName() + " has attribute: " + attribute.getName() + " = " + Hdf5Utils.getFirstStringValAttr(attrs, attribute.getName())); } float[][] data = Hdf5Utils.parse2Ddataset(d); logger.logComment("Data has size: (" + data.length + ", " + data[0].length + ")"); if (inPopulations && currentCellGroup != null) { for (int i = 0; i < data.length; i++) { int id = (int) data[i][0]; float x = data[i][1]; float y = data[i][2]; float z = data[i][3]; PositionRecord posRec = new PositionRecord(id, x, y, z); if (data[0].length == 5) { posRec.setNodeId((int) data[i][4]); } this.project.generatedCellPositions.addPosition(currentCellGroup, posRec); } } if (inProjections && currentNetConn != null) { logger.logComment("Adding info for NetConn: " + currentNetConn); int id_col = -1; int pre_cell_id_col = -1; int pre_segment_id_col = -1; int pre_fraction_along_col = -1; int post_cell_id_col = -1; int post_segment_id_col = -1; int post_fraction_along_col = -1; int prop_delay_col = -1; for (Attribute attribute : attrs) { String storedInColumn = Hdf5Utils.getFirstStringValAttr(attrs, attribute.getName()); if (storedInColumn.equals(NetworkMLConstants.CONNECTION_ID_ATTR)) { id_col = Integer.parseInt(attribute.getName().substring("column_".length())); logger.logComment("id col: " + id_col); } else if (storedInColumn.equals(NetworkMLConstants.PRE_CELL_ID_ATTR)) { pre_cell_id_col = Integer.parseInt(attribute.getName().substring("column_".length())); } else if (storedInColumn.equals(NetworkMLConstants.PRE_SEGMENT_ID_ATTR)) { pre_segment_id_col = Integer.parseInt(attribute.getName().substring("column_".length())); logger.logComment("pre_segment_id_col: " + pre_segment_id_col); } else if (storedInColumn.equals(NetworkMLConstants.PRE_FRACT_ALONG_ATTR)) { pre_fraction_along_col = Integer.parseInt(attribute.getName().substring("column_".length())); logger.logComment("pre_fraction_along_col: " + pre_fraction_along_col); } else if (storedInColumn.equals(NetworkMLConstants.POST_CELL_ID_ATTR)) { post_cell_id_col = Integer.parseInt(attribute.getName().substring("column_".length())); } else if (storedInColumn.equals(NetworkMLConstants.POST_SEGMENT_ID_ATTR)) { post_segment_id_col = Integer.parseInt(attribute.getName().substring("column_".length())); } else if (storedInColumn.equals(NetworkMLConstants.POST_FRACT_ALONG_ATTR)) { post_fraction_along_col = Integer.parseInt(attribute.getName().substring("column_".length())); } else if (storedInColumn.startsWith(NetworkMLConstants.PROP_DELAY_ATTR)) { prop_delay_col = Integer.parseInt(attribute.getName().substring("column_".length())); } for (String synType : getConnectionSynTypes()) { if (storedInColumn.endsWith(synType)) { ConnSpecificProps cp = null; for (ConnSpecificProps currCp : localConnProps) { if (currCp.synapseType.equals(synType)) cp = currCp; } if (cp == null) { cp = new ConnSpecificProps(synType); cp.internalDelay = -1; cp.weight = -1; localConnProps.add(cp); } if (storedInColumn.startsWith(NetworkMLConstants.INTERNAL_DELAY_ATTR)) { cp.internalDelay = Integer.parseInt( attribute .getName() .substring("column_".length())); // store the col num temporarily.. } if (storedInColumn.startsWith(NetworkMLConstants.WEIGHT_ATTR)) { cp.weight = Integer.parseInt( attribute .getName() .substring("column_".length())); // store the col num temporarily.. } } } } for (int i = 0; i < data.length; i++) { int pre_seg_id = 0; float pre_fract_along = 0.5f; int post_seg_id = 0; float post_fract_along = 0.5f; int id = (int) data[i][id_col]; int pre_cell_id = (int) data[i][pre_cell_id_col]; int post_cell_id = (int) data[i][post_cell_id_col]; float prop_delay = 0; if (pre_segment_id_col >= 0) pre_seg_id = (int) data[i][pre_segment_id_col]; if (pre_fraction_along_col >= 0) pre_fract_along = data[i][pre_fraction_along_col]; if (post_segment_id_col >= 0) post_seg_id = (int) data[i][post_segment_id_col]; if (post_fraction_along_col >= 0) post_fract_along = data[i][post_fraction_along_col]; // (float)UnitConverter.getTime(XXXXXXXXX, UnitConverter.NEUROCONSTRUCT_UNITS, // unitSystem)+""; if (prop_delay_col >= 0) prop_delay = (float) UnitConverter.getTime( data[i][prop_delay_col], projUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); ArrayList<ConnSpecificProps> props = new ArrayList<ConnSpecificProps>(); if (localConnProps.size() > 0) { for (ConnSpecificProps currCp : localConnProps) { logger.logComment("Pre cp: " + currCp); ConnSpecificProps cp2 = new ConnSpecificProps(currCp.synapseType); if (currCp.internalDelay > 0) // index was stored in this val... cp2.internalDelay = (float) UnitConverter.getTime( data[i][(int) currCp.internalDelay], projUnitSystem, UnitConverter.NEUROCONSTRUCT_UNITS); if (currCp.weight > 0) // index was stored in this val... cp2.weight = data[i][(int) currCp.weight]; logger.logComment("Filled cp: " + cp2); props.add(cp2); } } this.project.generatedNetworkConnections.addSynapticConnection( currentNetConn, GeneratedNetworkConnections.MORPH_NETWORK_CONNECTION, pre_cell_id, pre_seg_id, pre_fract_along, post_cell_id, post_seg_id, post_fract_along, prop_delay, props); } } if (inInputs && currentInput != null) { logger.logComment("Adding info for: " + currentInput); StimulationSettings nextStim = project.elecInputInfo.getStim(currentInput); ElectricalInput myElectricalInput = nextStim.getElectricalInput(); String electricalInputType = myElectricalInput.getType(); String cellGroup = nextStim.getCellGroup(); for (int i = 0; i < data.length; i++) { Float fileCellId = data[i][0]; Float fileSegmentId = data[i][1]; Float fractionAlong = data[i][2]; int cellId = fileCellId.intValue(); int segmentId = fileSegmentId.intValue(); SingleElectricalInput singleElectricalInputFromFile = new SingleElectricalInput( electricalInputType, cellGroup, cellId, segmentId, fractionAlong, null); this.project.generatedElecInputs.addSingleInput( currentInput, singleElectricalInputFromFile); } } }
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; }
public static boolean transform( File origXmlFileOrDir, File xslFile, File targetDir, String extension) { logger.logComment( "Going to transform " + origXmlFileOrDir + " into dir " + targetDir + " using: " + xslFile, true); if (!origXmlFileOrDir.exists()) { GuiUtils.showErrorMessage( logger, "Warning, XML file/directory: " + origXmlFileOrDir + " doesn't exist", null, null); return false; } if (!xslFile.exists()) { GuiUtils.showErrorMessage( logger, "Warning, XSL file: " + xslFile + " doesn't exist", null, null); return false; } if (!targetDir.exists()) { GuiUtils.showErrorMessage( logger, "Warning, target directory: " + targetDir + " doesn't exist", null, null); return false; } if (origXmlFileOrDir.isDirectory()) { logger.logComment("That file is a directory. Converting all of the XML files in it"); File[] files = origXmlFileOrDir.listFiles(); boolean totalSuccess = true; for (int i = 0; i < files.length; i++) { if (!files[i].isDirectory() && (files[i].getName().endsWith(".xml") || files[i].getName().endsWith(".XML"))) { boolean partialSuccess = transform(files[i], xslFile, targetDir, extension); totalSuccess = totalSuccess || partialSuccess; } else if (files[i].isDirectory() && !GeneralUtils.isVersionControlDir(files[i])) { File newFolder = new File(targetDir, files[i].getName()); newFolder.mkdir(); logger.logComment( "Found a sub folder. Going to convert all there into: " + newFolder + "..."); transform(files[i], xslFile, newFolder, extension); } } return totalSuccess; } String result = transform(origXmlFileOrDir, xslFile); String newName = origXmlFileOrDir.getName(); if (newName.endsWith(".xml") || newName.endsWith(".XML")) { newName = newName.substring(0, newName.length() - 4) + extension; } File targetFile = new File(targetDir, newName); try { FileWriter fw = new FileWriter(targetFile); fw.write(result); fw.close(); } catch (IOException ex) { GuiUtils.showErrorMessage(logger, "Exception writing to file: " + targetFile, ex, null); return false; } logger.logComment("The result is in " + targetFile + " *************"); return result != null; }