mirror of
https://github.com/PAMGuard/PAMGuard.git
synced 2025-04-15 21:46:33 +00:00
Merge branch 'main' of https://github.com/PAMGuard/PAMGuard
This commit is contained in:
Douglas Gillespie
commit
0126ff83c6
@ -6,7 +6,7 @@
|
||||
<attribute name="maven.pomderived" value="true"/>
|
||||
</attributes>
|
||||
</classpathentry>
|
||||
<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/ojdk-21.0.1">
|
||||
<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/java-21-openjdk-amd64">
|
||||
<attributes>
|
||||
<attribute name="module" value="true"/>
|
||||
<attribute name="maven.pomderived" value="true"/>
|
||||
|
||||
@ -11,9 +11,9 @@ org.eclipse.jdt.core.codeComplete.staticFinalFieldPrefixes=
|
||||
org.eclipse.jdt.core.codeComplete.staticFinalFieldSuffixes=
|
||||
org.eclipse.jdt.core.compiler.codegen.inlineJsrBytecode=enabled
|
||||
org.eclipse.jdt.core.compiler.codegen.methodParameters=do not generate
|
||||
org.eclipse.jdt.core.compiler.codegen.targetPlatform=17
|
||||
org.eclipse.jdt.core.compiler.codegen.targetPlatform=21
|
||||
org.eclipse.jdt.core.compiler.codegen.unusedLocal=preserve
|
||||
org.eclipse.jdt.core.compiler.compliance=17
|
||||
org.eclipse.jdt.core.compiler.compliance=21
|
||||
org.eclipse.jdt.core.compiler.debug.lineNumber=generate
|
||||
org.eclipse.jdt.core.compiler.debug.localVariable=generate
|
||||
org.eclipse.jdt.core.compiler.debug.sourceFile=generate
|
||||
@ -23,4 +23,4 @@ org.eclipse.jdt.core.compiler.problem.enumIdentifier=error
|
||||
org.eclipse.jdt.core.compiler.problem.forbiddenReference=warning
|
||||
org.eclipse.jdt.core.compiler.problem.reportPreviewFeatures=warning
|
||||
org.eclipse.jdt.core.compiler.release=enabled
|
||||
org.eclipse.jdt.core.compiler.source=17
|
||||
org.eclipse.jdt.core.compiler.source=21
|
||||
|
||||
BIN
build/deb/PAMGuardIcon2.png
Normal file
BIN
build/deb/PAMGuardIcon2.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 99 KiB |
13
build/deb/control
Normal file
13
build/deb/control
Normal file
@ -0,0 +1,13 @@
|
||||
Package: PAMGuard
|
||||
Version: 2.0.1
|
||||
Section: java
|
||||
Priority: optional
|
||||
Architecture: all
|
||||
Maintainer: Jamie Macaulay <jdjm@st-andrews.ac.uk>
|
||||
Description: Process passive acoustic data for whales, dolphins and other species.
|
||||
Icon: pamguard_icon.png
|
||||
Depends: openjdk-21-jre
|
||||
postinst script:
|
||||
#!/bin/bash
|
||||
# Set JVM options for the application
|
||||
export JAVA_OPTS="-Xmx4g -Xms512m -Dsun.java2d.uiScale=2 -Dawt.useSystemAAFontSettings=on -Dswing.aatext=true"
|
||||
8
build/deb/pamguard.desktop
Executable file
8
build/deb/pamguard.desktop
Executable file
@ -0,0 +1,8 @@
|
||||
[Desktop Entry]
|
||||
Name=PAMGuard
|
||||
Comment=Application for passive acoustic monitoring v1
|
||||
Exec=java -jar /usr/share/pamguard/Pamguard -c
|
||||
Icon=/usr/share/pamguard/PAMGuardIcon2.png
|
||||
Terminal=true
|
||||
Type=Application
|
||||
Categories=Application;
|
||||
8
build/deb/set-java-propery.sh
Normal file
8
build/deb/set-java-propery.sh
Normal file
@ -0,0 +1,8 @@
|
||||
[Desktop Entry]
|
||||
Name=PAMGuard
|
||||
Comment=Application for passive acoustic monitoring
|
||||
Exec=java -jar /usr/share/pamguard/Pamguard-2.02.14a.jar -c
|
||||
Icon=/path/to/your/icon.png
|
||||
Terminal=true
|
||||
Type=Application
|
||||
Categories=Application;
|
||||
@ -26,6 +26,71 @@
|
||||
</resources>
|
||||
</build>
|
||||
<profiles>
|
||||
<profile>
|
||||
<id>linux-profile</id>
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.vafer</groupId>
|
||||
<artifactId>jdeb</artifactId>
|
||||
<version>1.11</version>
|
||||
<executions>
|
||||
<execution>
|
||||
<phase>package</phase>
|
||||
<goals>
|
||||
<goal>jdeb</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<controlDir>${basedir}/build/deb</controlDir>
|
||||
<dataSet>
|
||||
<data>
|
||||
<src>${project.build.directory}/${project.build.finalName}.jar</src>
|
||||
<type>file</type>
|
||||
<mapper>
|
||||
<type>perm</type>
|
||||
<prefix>/usr/share/pamguard</prefix>
|
||||
</mapper>
|
||||
</data>
|
||||
<data>
|
||||
<src>${basedir}/liblinux</src>
|
||||
<type>directory</type>
|
||||
<includes>*.txt</includes>
|
||||
<includes>*.so</includes>
|
||||
<mapper>
|
||||
<type>perm</type>
|
||||
<prefix>/usr/share/pamguard/liblinux</prefix>
|
||||
</mapper>
|
||||
</data>
|
||||
<data>
|
||||
<src>${basedir}/build/deb/PAMGuardIcon2.png</src>
|
||||
<type>file</type>
|
||||
<mapper>
|
||||
<type>perm</type>
|
||||
<prefix>/usr/share/pamguard</prefix>
|
||||
</mapper>
|
||||
</data>
|
||||
<data>
|
||||
<src>${basedir}/build/deb/pamguard.desktop</src>
|
||||
<type>file</type>
|
||||
<mapper>
|
||||
<type>perm</type>
|
||||
<prefix>/usr/share/applications</prefix>
|
||||
</mapper>
|
||||
</data>
|
||||
<data>
|
||||
<type>link</type>
|
||||
<linkName>/usr/share/pamguard/Pamguard</linkName>
|
||||
<linkTarget>/usr/share/pamguard/${project.build.finalName}.jar</linkTarget>
|
||||
<symlink>true</symlink>
|
||||
</data>
|
||||
</dataSet>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
</profile>
|
||||
<profile>
|
||||
<id>macos-profile</id>
|
||||
<build>
|
||||
@ -145,36 +210,11 @@
|
||||
<plugin>
|
||||
<artifactId>maven-compiler-plugin</artifactId>
|
||||
<version>3.12.1</version>
|
||||
<executions>
|
||||
<execution>
|
||||
<id>default-compile</id>
|
||||
<phase>compile</phase>
|
||||
<goals>
|
||||
<goal>compile</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<release>21</release>
|
||||
<compilerId>jdt</compilerId>
|
||||
</configuration>
|
||||
</execution>
|
||||
<execution>
|
||||
<id>default-testCompile</id>
|
||||
<phase>test-compile</phase>
|
||||
<goals>
|
||||
<goal>testCompile</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<release>21</release>
|
||||
<compilerId>jdt</compilerId>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>org.eclipse.tycho</groupId>
|
||||
<artifactId>tycho-compiler-jdt</artifactId>
|
||||
<version>1.5.1</version>
|
||||
<scope>compile</scope>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
<configuration>
|
||||
@ -207,17 +247,6 @@
|
||||
</transformer>
|
||||
<transformer />
|
||||
</transformers>
|
||||
<filters>
|
||||
<filter>
|
||||
<artifact>*:*</artifact>
|
||||
<excludes>
|
||||
<exclude>META-INF/*.SF</exclude>
|
||||
<exclude>META-INF/*.DSA</exclude>
|
||||
<exclude>META-INF/*.RSA</exclude>
|
||||
<exclude>test/resources/**</exclude>
|
||||
</excludes>
|
||||
</filter>
|
||||
</filters>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
@ -254,7 +283,7 @@
|
||||
<goal>copy-dependencies</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<outputDirectory>C:\Users\dg50\source\repos\PAMGuardPAMGuard\target/tempDependencies</outputDirectory>
|
||||
<outputDirectory>${project.build.directory}/tempDependencies</outputDirectory>
|
||||
<overWriteReleases>false</overWriteReleases>
|
||||
<overWriteSnapshots>false</overWriteSnapshots>
|
||||
<overWriteIfNewer>true</overWriteIfNewer>
|
||||
|
||||
162
pom.xml
162
pom.xml
@ -51,7 +51,106 @@
|
||||
earlier. Most OS specific profiles are for generating executables and code signing.
|
||||
Note use help:active-profiles to see which profiles are active -->
|
||||
<profiles>
|
||||
|
||||
|
||||
<!-- The Linux profile creates a DMG package for installing PAMGuard on
|
||||
Linux Ubuntu based systems-->
|
||||
<!--Note: There is a Maven bug/feature when using profiles when the plugin order is messed up and seemingly quite random.
|
||||
In PAMGuard it essential that the shade plugin is called before the linux plugin. Therefore explicately call
|
||||
the package phase using mvn package shade:shade jdeb:jdeb. Note that although a deb file can be created in Windows it
|
||||
will not have the correct JavaFX libraries and therefore will not work when riun -->
|
||||
<profile>
|
||||
<id>linux-profile</id>
|
||||
<activation>
|
||||
<os>
|
||||
<family>linux</family>
|
||||
</os>
|
||||
</activation>
|
||||
<build>
|
||||
<plugins>
|
||||
<!--Creates a deb file for Linux-->
|
||||
<plugin>
|
||||
<artifactId>jdeb</artifactId>
|
||||
<groupId>org.vafer</groupId>
|
||||
<version>1.11</version>
|
||||
<executions>
|
||||
<execution>
|
||||
<phase>package</phase>
|
||||
<goals>
|
||||
<goal>jdeb</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<controlDir>${basedir}/build/deb</controlDir>
|
||||
<dataSet>
|
||||
<data>
|
||||
<!--TODO-really the jar file should be named properly but thos would mean we would
|
||||
have to change the name in the desktop file too. For now create a link to the jar file
|
||||
with correct version number-->
|
||||
<src>
|
||||
${project.build.directory}/${project.build.finalName}.jar</src>
|
||||
<type>file</type>
|
||||
<mapper>
|
||||
<type>perm</type>
|
||||
<prefix>/usr/share/pamguard</prefix>
|
||||
</mapper>
|
||||
</data>
|
||||
<data>
|
||||
<src>${basedir}/liblinux</src>
|
||||
<type>directory</type>
|
||||
<includes>*.txt</includes>
|
||||
<includes>*.so</includes>
|
||||
<mapper>
|
||||
<type>perm</type>
|
||||
<prefix>
|
||||
/usr/share/pamguard/liblinux</prefix>
|
||||
</mapper>
|
||||
</data>
|
||||
<data>
|
||||
<src>
|
||||
${basedir}/build/deb/PAMGuardIcon2.png</src>
|
||||
<type>file</type>
|
||||
<mapper>
|
||||
<type>perm</type>
|
||||
<prefix>/usr/share/pamguard</prefix>
|
||||
</mapper>
|
||||
</data>
|
||||
<!---THe desktop file will create a PAMGuard icon in the applications tray-->
|
||||
<data>
|
||||
<src>
|
||||
${basedir}/build/deb/pamguard.desktop</src>
|
||||
<type>file</type>
|
||||
<mapper>
|
||||
<type>perm</type>
|
||||
<prefix>/usr/share/applications</prefix>
|
||||
</mapper>
|
||||
</data>
|
||||
<!---Create a link which is just called Pamguard. This means the .desktop file does not need
|
||||
to be altered depending on the build name-->
|
||||
<data>
|
||||
<type>link</type>
|
||||
<linkName>
|
||||
/usr/share/pamguard/Pamguard</linkName>
|
||||
<linkTarget>
|
||||
/usr/share/pamguard/${project.build.finalName}.jar</linkTarget>
|
||||
<symlink>true</symlink>
|
||||
</data>
|
||||
<!--<data>
|
||||
<src>${project.basedir}/build/deb/set-java-property.sh</src>
|
||||
<type>file</type>
|
||||
<mapper>
|
||||
<type>perm</type>
|
||||
<prefix>/usr/bin</prefix>
|
||||
<filemode>755</filemode>
|
||||
</mapper>
|
||||
</data>-->
|
||||
</dataSet>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
</profile>
|
||||
|
||||
<!-- The MacOS profile creates a DMG package for installing PAMGuard on MacOS-->
|
||||
<!--Note: There is a Maven bug when using profiles when the plugin order is messed up and seemingly quite random.
|
||||
In PAMGuard it essential that the shade plugin is called before the macos plugin and so the phase of the
|
||||
@ -311,11 +410,10 @@
|
||||
</execution>
|
||||
-->
|
||||
</executions>
|
||||
</plugin>
|
||||
|
||||
</plugin>
|
||||
|
||||
</plugins>
|
||||
|
||||
|
||||
<pluginManagement>
|
||||
<plugins>
|
||||
<!--This plugin's configuration is used to store Eclipse m2e settings only. It has no influence on the Maven build itself.-->
|
||||
@ -358,7 +456,52 @@
|
||||
</profile>
|
||||
|
||||
</profiles>
|
||||
|
||||
|
||||
<!-- Plugin which creates a .dmg file for MacOS.
|
||||
<plugin>
|
||||
<groupId>de.perdian.maven.plugins</groupId>
|
||||
<artifactId>macosappbundler-maven-plugin</artifactId>
|
||||
<version>1.21.1</version>
|
||||
<configuration>
|
||||
<plist>
|
||||
<JVMMainClassName>pamguard.Pamguard</JVMMainClassName>
|
||||
<CFBundleIconFile>src/Resources/PamguardIcon2.icns</CFBundleIconFile>
|
||||
<CFBundleDisplayName>PAMGuard</CFBundleDisplayName>
|
||||
<CFBundleDevelopmentRegion>English</CFBundleDevelopmentRegion>
|
||||
<CFBundleURLTypes>
|
||||
<string>msa</string>
|
||||
</CFBundleURLTypes>
|
||||
<JVMVersion>21+</JVMVersion>
|
||||
<JVMArguments>
|
||||
<string>-c</string>
|
||||
</JVMArguments>
|
||||
</plist>
|
||||
<dmg>
|
||||
<generate>true</generate>
|
||||
<additionalResources>
|
||||
<additionalResource>
|
||||
<directory>src/target/bundle/</directory>
|
||||
</additionalResource>
|
||||
</additionalResources>
|
||||
</dmg>
|
||||
<jdk>
|
||||
<include>false</include>
|
||||
<location>/Library/Java/JavaVirtualMachines/amazon-corretto-21.jdk</location>
|
||||
</jdk>
|
||||
</configuration>
|
||||
<executions>
|
||||
<execution>
|
||||
<phase>package</phase>
|
||||
<goals>
|
||||
<goal>bundle</goal>
|
||||
</goals>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>-->
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<reporting>
|
||||
@ -442,7 +585,7 @@
|
||||
<groupId>io.github.macster110</groupId>
|
||||
<artifactId>jpamutils</artifactId>
|
||||
<version>0.0.59f</version>
|
||||
<!-- com.github.psambit9791:wavfile:jar:0.1 pulls in various junit dependencies which breaks our own testing -->
|
||||
<!-- com.github.psambit9791:wavfile:jar:0.1 pulls in various junit dependencies which breaks our own testing -->
|
||||
<!--<exclusions>
|
||||
<exclusion>
|
||||
<groupId>org.junit.platform</groupId>
|
||||
@ -610,7 +753,7 @@
|
||||
</exclusions>
|
||||
</dependency>
|
||||
|
||||
<!-- html to markdown conversion https://github.com/furstenheim/copy-down -->
|
||||
<!-- html to markdown conversion https://github.com/furstenheim/copy-down -->
|
||||
<dependency>
|
||||
<groupId>io.github.furstenheim</groupId>
|
||||
<artifactId>copy_down</artifactId>
|
||||
@ -997,7 +1140,7 @@
|
||||
<version>2.1.1</version>
|
||||
</dependency>
|
||||
|
||||
<!--
|
||||
<!--
|
||||
<dependency>
|
||||
<groupId>javax.xml.bind</groupId>
|
||||
<artifactId>jaxb-api</artifactId>
|
||||
@ -1065,7 +1208,7 @@
|
||||
-->
|
||||
<dependency>
|
||||
<groupId>org.pamguard</groupId>
|
||||
<artifactId>x3</artifactId>
|
||||
<artifactId>X3</artifactId>
|
||||
<version>2.2.8</version>
|
||||
</dependency>
|
||||
|
||||
@ -1154,7 +1297,6 @@
|
||||
</dependency>
|
||||
|
||||
|
||||
|
||||
<!-- Test dependencies -->
|
||||
<dependency>
|
||||
<groupId>org.junit.jupiter</groupId>
|
||||
|
||||
@ -106,10 +106,6 @@ public class GroupLocResult implements Comparable<GroupLocResult>, LocalisationC
|
||||
this.chi2 = chi2;
|
||||
}
|
||||
|
||||
public GroupLocResult(double[] result, double[] resultErrors, int side, double chi2) {
|
||||
// TODO Auto-generated constructor stub
|
||||
}
|
||||
|
||||
/**
|
||||
* @return the latLong
|
||||
*/
|
||||
|
||||
@ -1381,7 +1381,25 @@ public class PamArrayUtils {
|
||||
}
|
||||
|
||||
|
||||
|
||||
/**
|
||||
* Convert a matrix to a
|
||||
* @param matrix - the MAT file matrix
|
||||
* @return double[][] array of results
|
||||
*/
|
||||
public static float[][] matrix2arrayF(Matrix matrix) {
|
||||
if (matrix==null) return null;
|
||||
|
||||
float[][] arrayOut = new float[matrix.getNumRows()][];
|
||||
float[] arrayRow;
|
||||
for (int i=0; i<matrix.getNumRows(); i++) {
|
||||
arrayRow=new float[matrix.getNumCols()];
|
||||
for (int j=0; j<matrix.getNumCols(); j++) {
|
||||
arrayRow[j] = matrix.getFloat(i, j);
|
||||
}
|
||||
arrayOut[i]=arrayRow;
|
||||
}
|
||||
return arrayOut;
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
@ -54,13 +54,18 @@ public class DataModelConnectPane extends ConnectionPane {
|
||||
@Override
|
||||
public void handle(DragEvent event)
|
||||
{
|
||||
|
||||
// System.out.println("START drag over node drag dropped" + dataModelPaneFX.getDraggingStructure());
|
||||
|
||||
final Dragboard dragboard = event.getDragboard();
|
||||
if (dragboard.hasString()
|
||||
&& dataModelPaneFX.getModuleDragKey().equals(dragboard.getString())
|
||||
&& dataModelPaneFX.getDraggingModule().get() != null || dataModelPaneFX.getDraggingStructure()!=null)
|
||||
{
|
||||
event.acceptTransferModes(TransferMode.MOVE);
|
||||
event.consume();
|
||||
// System.out.println("ACCEPT drag over node drag dropped" + dataModelPaneFX.getDraggingStructure());
|
||||
|
||||
event.acceptTransferModes(TransferMode.ANY);
|
||||
//event.consume(); //causesd issues with dropping nodes not being detected
|
||||
}
|
||||
}
|
||||
});
|
||||
@ -70,6 +75,9 @@ public class DataModelConnectPane extends ConnectionPane {
|
||||
@Override
|
||||
public void handle(DragEvent event)
|
||||
{
|
||||
|
||||
System.out.println("Add Some Node drag dropped: " + dataModelPaneFX.getDraggingStructure());
|
||||
|
||||
final Dragboard dragboard = event.getDragboard();
|
||||
if (dragboard.hasString()
|
||||
&& dataModelPaneFX.getModuleDragKey().equals(dragboard.getString())
|
||||
@ -80,6 +88,7 @@ public class DataModelConnectPane extends ConnectionPane {
|
||||
|
||||
ModuleRectangle moduleRect = dataModelPaneFX.getDraggingModule().get();
|
||||
|
||||
// System.out.println("Add Connection Node drag dropped");
|
||||
dataModelPaneFX.getDraggingModule().set(null);
|
||||
dataModelPaneFX.getConnectionNodeFactory().addNewModule(moduleRect.getPamModuleInfo(), event.getX(), event.getY());
|
||||
|
||||
@ -88,6 +97,7 @@ public class DataModelConnectPane extends ConnectionPane {
|
||||
if (dragboard.hasString()
|
||||
&& dataModelPaneFX.getModuleDragKey().equals(dragboard.getString())
|
||||
&& dataModelPaneFX.getDraggingStructure().get() != null){
|
||||
// System.out.println("Add Structure Node drag dropped");
|
||||
|
||||
dataModelPaneFX.getConnectionNodeFactory().addNewStructure(dataModelPaneFX.getDraggingStructure().get(), event.getX(), event.getY());
|
||||
dataModelPaneFX.getDraggingStructure().set(null);
|
||||
|
||||
@ -121,8 +121,7 @@ public class ConnectionNodeFactory {
|
||||
* @param y - the pixel y co-ordinate
|
||||
*/
|
||||
public StandardConnectionNode addNewStructure(StructureRectangle structureRectangle, double x, double y) {
|
||||
// System.out.println("DataModelConnectPane: add new structure " + structureRectangle.getStructureType()
|
||||
// + " no. nodes: " + this.getConnectionNodes().size());
|
||||
System.out.println("DataModelConnectPane: add new structure " + structureRectangle.getStructureType() );
|
||||
StandardConnectionNode connectionNode = createConnectionNode(structureRectangle.getStructureType(), null);
|
||||
|
||||
if (connectionNode!=null) {
|
||||
|
||||
@ -136,6 +136,8 @@ public class GenericDataPlotInfo extends TDDataInfoFX {
|
||||
System.out.println("GenericDataPlotInfo: Single frequency measure in data unit " + pamDataUnit.toString());
|
||||
}
|
||||
|
||||
//System.out.println("Frequency: " + f[0] + " " + f[1] + " " + pamDataUnit);
|
||||
|
||||
// draw a frequency box.
|
||||
double y0 = tdProjector.getYPix(f[0]);
|
||||
double y1 = tdProjector.getYPix(f[1]);
|
||||
|
||||
@ -153,6 +153,9 @@ public class MLDetectionsManager implements PamDataUnitExporter {
|
||||
public boolean hasCompatibleUnits(List<PamDataUnit> dataUnits) {
|
||||
//first need to figure out how many data units there are.
|
||||
for (int j=0; j<dataUnits.size(); j++){
|
||||
|
||||
|
||||
|
||||
if (hasCompatibleUnits(dataUnits.get(j).getClass())) return true;
|
||||
}
|
||||
return false;
|
||||
|
||||
@ -232,7 +232,7 @@ public class Group3DProcess extends PamProcess implements DetectionGroupMonitor
|
||||
}
|
||||
}
|
||||
|
||||
// System.out.println("Ran localisation " + i + " " + localiserAlgorithm3D.getName() + " got: " + abstractLocalisation.getLatLong(0) + " " + abstractLocalisation.getHeight(0) + " Error: " + abstractLocalisation.getLocError(0));
|
||||
System.out.println("Ran localisation " + i + " " + localiserAlgorithm3D.getName() + " got: " + abstractLocalisation.getLatLong(0) + " " + abstractLocalisation.getHeight(0) + " Error: " + abstractLocalisation.getLocError(0));
|
||||
|
||||
if (abstractLocalisation instanceof GroupLocalisation) {
|
||||
groupLocalisation = (GroupLocalisation) abstractLocalisation;
|
||||
|
||||
@ -388,7 +388,8 @@ public class HyperbolicLocaliser extends TOADBaseAlgorithm {
|
||||
PamVector centre = geometry.getGeometricCentre();
|
||||
int[] hydrophones = toadInformation.getHydrophoneList();
|
||||
double xArray[] = new double[geom.length];
|
||||
for (int i = 0; i < geom.length; i++) {
|
||||
//System.out.println("Hyperbolic loc: Geom length: " + hydrophones.length + " " + geom.length);
|
||||
for (int i = 0; i < hydrophones.length; i++) {
|
||||
xArray[i] = geom[hydrophones[i]].sub(centre).dotProd(arrayAxes);
|
||||
}
|
||||
|
||||
@ -581,6 +582,8 @@ public class HyperbolicLocaliser extends TOADBaseAlgorithm {
|
||||
//// glr.setModel(model);
|
||||
// return groupLocalisation;
|
||||
LinearLocalisation linLoc = new LinearLocalisation(groupDataUnit, toadInformation.getHydrophoneMap(), geometry.getArrayAxes(), angle, r);
|
||||
linLoc.setChi2(chiData);
|
||||
|
||||
GpsData refPos = new GpsData(geometry.getReferenceGPS().addDistanceMeters(geometry.getGeometricCentre()));
|
||||
linLoc.setReferencePosition(refPos);
|
||||
return linLoc;
|
||||
|
||||
@ -132,11 +132,14 @@ abstract public class TOADBaseAlgorithm extends LocaliserAlgorithm3D {
|
||||
// if (superDetection.getSubDetection(0).getUID() == 9035004477L) {
|
||||
// System.out.println("Found it");
|
||||
// }
|
||||
|
||||
|
||||
TOADInformation toadInformation = toadCalculator.getTOADInformation(superDetection.getSubDetections(), sampleRate, allChannels, geometry);
|
||||
|
||||
|
||||
boolean toadOK = checkTOADInformation(toadInformation);
|
||||
|
||||
// System.out.println("ToadOK: " + toadOK + " toadInformation: " + toadInformation + " allChannels: " + allChannels + " geometry: " + geometry);
|
||||
//System.out.println("ToadOK: " + toadOK + " toadInformation: " + toadInformation + " allChannels: " + allChannels + " geometry: " + geometry.getGeometry() + "n sub: " + superDetection.getSubDetectionsCount() );
|
||||
|
||||
if (!toadOK) {
|
||||
return null;
|
||||
|
||||
@ -0,0 +1,17 @@
|
||||
package group3dlocaliser.algorithm.toadmimplex;
|
||||
|
||||
import Localiser.detectionGroupLocaliser.GroupLocResult;
|
||||
import group3dlocaliser.localisation.LinearLocalisation;
|
||||
|
||||
|
||||
/**
|
||||
* Wrapper to make a linear localisation into a group localisation
|
||||
*/
|
||||
public class LinearGroupLocResult extends GroupLocResult {
|
||||
|
||||
public LinearGroupLocResult(LinearLocalisation linearLocalisation) {
|
||||
super(linearLocalisation.getReferencePosition(), 0, linearLocalisation.getChi2());
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
@ -17,6 +17,7 @@ import group3dlocaliser.algorithm.toadmcmc.MCMCLocaliserPane;
|
||||
import group3dlocaliser.algorithm.toadmcmc.ToadMCMCLocaliser;
|
||||
import group3dlocaliser.algorithm.toadsimplex.ToadSimplexLocaliser;
|
||||
import group3dlocaliser.grouper.DetectionGroupedSet;
|
||||
import group3dlocaliser.localisation.LinearLocalisation;
|
||||
|
||||
|
||||
/**
|
||||
@ -94,7 +95,7 @@ public class ToadMimplexLocaliser extends ToadMCMCLocaliser {
|
||||
*/
|
||||
public DetectionGroupedSet preFilterLoc(DetectionGroupedSet preGroups) {
|
||||
|
||||
System.out.println("Pre filter groups: " + preGroups.getNumGroups());
|
||||
//System.out.println("Pre filter groups: " + preGroups.getNumGroups());
|
||||
|
||||
MimplexParams params = (MimplexParams) group3dLocaliser.getLocaliserAlgorithmParams(this).getAlgorithmParameters();
|
||||
|
||||
@ -105,12 +106,12 @@ public class ToadMimplexLocaliser extends ToadMCMCLocaliser {
|
||||
return preGroups;
|
||||
}
|
||||
|
||||
//no need to do a y more processing.
|
||||
//no need to do a any more processing.
|
||||
if (preGroups.getNumGroups()<=2 && params.useFirstCombination) {
|
||||
return preGroups;
|
||||
}
|
||||
|
||||
//localiser using both hyperbolic and the
|
||||
//localiser using both hyperbolic and simplex the
|
||||
// will have to make a data unit for each group now...
|
||||
Group3DDataUnit[] group3dDataUnits = new Group3DDataUnit[preGroups.getNumGroups()];
|
||||
|
||||
@ -121,18 +122,22 @@ public class ToadMimplexLocaliser extends ToadMCMCLocaliser {
|
||||
|
||||
group3dDataUnits[i] = new Group3DDataUnit(preGroups.getGroup(i));
|
||||
|
||||
//System.out.println("ToadMImplex. group3dDataUnits[i]: " + group3dDataUnits[i] );
|
||||
|
||||
GroupLocalisation preAbstractLocalisation = null;
|
||||
AbstractLocalisation preAbstractLocalisation = null;
|
||||
double minChi2 = Double.MAX_VALUE;
|
||||
|
||||
GroupLocResult locResult = null;
|
||||
for (LocaliserModel model: preLocaliserModels) {
|
||||
|
||||
//System.out.println("ToadMImplex. model: " + model );
|
||||
|
||||
|
||||
locResult = null;
|
||||
minChi2=Double.MAX_VALUE;
|
||||
preAbstractLocalisation = null; //must reset this.
|
||||
try {
|
||||
preAbstractLocalisation = (GroupLocalisation) model.runModel(group3dDataUnits[i], null, false);
|
||||
preAbstractLocalisation = model.runModel(group3dDataUnits[i], null, false);
|
||||
}
|
||||
catch (Exception e) {
|
||||
System.out.println("Mimplex pre filter loclaisation failed");
|
||||
@ -142,12 +147,23 @@ public class ToadMimplexLocaliser extends ToadMCMCLocaliser {
|
||||
// System.out.println("Pre-localisation result: " + locResult + " " + model.getName() + "N units: " + preGroups.getGroup(i).size());
|
||||
|
||||
if (preAbstractLocalisation!=null) {
|
||||
|
||||
if (preAbstractLocalisation instanceof GroupLocalisation) {
|
||||
//now iterate through the potential ambiguities (this is a bit redunadant with Simplex and Hyperbolic)
|
||||
for (GroupLocResult groupLocResult: preAbstractLocalisation.getGroupLocResults()) {
|
||||
for (GroupLocResult groupLocResult: ((GroupLocalisation) preAbstractLocalisation).getGroupLocResults()) {
|
||||
if (groupLocResult.getChi2()<minChi2) {
|
||||
locResult = groupLocResult;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (preAbstractLocalisation instanceof LinearLocalisation) {
|
||||
//if a linear vertical array (exactly) then will return a linear localisation. Need to make this into
|
||||
//a group localisation to satisfy the mimplex localiser.
|
||||
if (((LinearLocalisation) preAbstractLocalisation).getChi2()<minChi2) {
|
||||
locResult = new LinearGroupLocResult(((LinearLocalisation) preAbstractLocalisation));
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@ -244,6 +244,7 @@ public class DetectionGrouper {
|
||||
*/
|
||||
public synchronized void closeMotherGroup() {
|
||||
processFirstGroup(motherGroup);
|
||||
if (maxInterGroupSamples==null) return;
|
||||
motherGroup = new FirstGrouping(maxInterGroupSamples.length, 0, null);
|
||||
|
||||
}
|
||||
|
||||
@ -5,6 +5,7 @@ import Localiser.detectionGroupLocaliser.LocalisationChi2;
|
||||
import PamDetection.AbstractLocalisation;
|
||||
import PamDetection.LocContents;
|
||||
import PamguardMVC.PamDataUnit;
|
||||
import group3dlocaliser.algorithm.Chi2Data;
|
||||
import pamMaths.PamVector;
|
||||
|
||||
public class LinearLocalisation extends AbstractLocalisation implements LocalisationChi2{
|
||||
@ -12,6 +13,7 @@ public class LinearLocalisation extends AbstractLocalisation implements Localisa
|
||||
private double[] angles;
|
||||
private Double range;
|
||||
private GpsData referencePosition;
|
||||
private Chi2Data chi2Dat;
|
||||
|
||||
public LinearLocalisation(PamDataUnit pamDataUnit, int referenceHydrophones, PamVector[] arrayAxes, double bearing, Double range) {
|
||||
super(pamDataUnit, LocContents.HAS_BEARING | LocContents.HAS_AMBIGUITY, referenceHydrophones);
|
||||
@ -42,8 +44,7 @@ public class LinearLocalisation extends AbstractLocalisation implements Localisa
|
||||
|
||||
@Override
|
||||
public Double getChi2() {
|
||||
// TODO Auto-generated method stub
|
||||
return null;
|
||||
return chi2Dat.getChi2();
|
||||
}
|
||||
|
||||
@Override
|
||||
@ -84,6 +85,14 @@ public class LinearLocalisation extends AbstractLocalisation implements Localisa
|
||||
public void setReferencePosition(GpsData referencePosition) {
|
||||
this.referencePosition = referencePosition;
|
||||
}
|
||||
|
||||
/**
|
||||
* Set Chi2 data
|
||||
* @param chi2dat
|
||||
*/
|
||||
public void setChi2(Chi2Data chi2dat) {
|
||||
this.chi2Dat = chi2dat;
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
@ -58,7 +58,13 @@ public class Group3DOfflineTask extends OfflineTask<PamDataUnit>{
|
||||
|
||||
@Override
|
||||
public boolean processDataUnit(PamDataUnit dataUnit) {
|
||||
try {
|
||||
group3DProcess.newData(null, dataUnit);
|
||||
}
|
||||
catch (Exception e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
//System.out.println("New data unit added: " +dataUnit);
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
@ -210,7 +210,7 @@ public class DLClassifyProcess extends PamProcess {
|
||||
*/
|
||||
@Override
|
||||
public void newData(PamObservable obs, PamDataUnit pamRawData) {
|
||||
//System.out.println("NEW SEGMENTER DATA: " + PamCalendar.formatDateTime2(pamRawData.getTimeMilliseconds(), "dd MMM yyyy HH:mm:ss.SSS", false) + " " + pamRawData.getUID() + " " + pamRawData.getChannelBitmap() + " " + pamRawData);
|
||||
//System.out.println("NEW SEGMENTER DATA: " + PamCalendar.formatDateTime2(pamRawData.getTimeMilliseconds(), "dd MMM yyyy HH:mm:ss.SSS", false) + " " + pamRawData.getUID() + " " + pamRawData.getChannelBitmap() + " " + pamRawData);
|
||||
|
||||
//if grouped data then just run the classifier on the group - do not try and create a buffer.
|
||||
if (pamRawData instanceof SegmenterDetectionGroup) {
|
||||
@ -618,10 +618,11 @@ public class DLClassifyProcess extends PamProcess {
|
||||
*/
|
||||
public void forceRunClassifier(PamDataUnit dataUnit) {
|
||||
|
||||
// System.out.println("CLASSIFICATION BUFFER: " + classificationBuffer.size());
|
||||
//System.out.println("CLASSIFICATION BUFFER: " + classificationBuffer.size());
|
||||
|
||||
if (this.classificationBuffer.size()>0) {
|
||||
if (classificationBuffer.get(0) instanceof GroupedRawData) {
|
||||
//System.out.println("Run raw model on: " + classificationBuffer.get(0) + " " + classificationBuffer.get(1));
|
||||
runRawModel(); //raw data or raw data units
|
||||
}
|
||||
if (classificationBuffer.get(0) instanceof SegmenterDetectionGroup) {
|
||||
@ -689,10 +690,12 @@ public class DLClassifyProcess extends PamProcess {
|
||||
DataUnitBaseData basicData = groupDataBuffer.get(0).getBasicData().clone();
|
||||
basicData.setMillisecondDuration(1000.*rawdata[0].length/this.sampleRate);
|
||||
basicData.setSampleDuration((long) (groupDataBuffer.size()*dlControl.getDLParams().rawSampleSize));
|
||||
|
||||
|
||||
// System.out.println("Model result: " + modelResult.size());
|
||||
DLDetection dlDetection = new DLDetection(basicData, rawdata, getSampleRate());
|
||||
addDLAnnotation(dlDetection,modelResult);
|
||||
dlDetection.setFrequency(new double[] {0, this.getSampleRate()/2});
|
||||
|
||||
//create the data unit
|
||||
return dlDetection;
|
||||
|
||||
@ -139,9 +139,8 @@ public class ArchiveModelWorker extends GenericModelWorker {
|
||||
System.out.println(modelParams.dlTransforms);
|
||||
ArrayList<DLTransform> transforms = DLTransformsFactory.makeDLTransforms(modelParams.dlTransforms);
|
||||
|
||||
// ///HACK here for now to fix an issue with dB and Ketos transforms having zero length somehow...
|
||||
// for (int i=0; i<modelParams.dlTransforms.size(); i++) {
|
||||
// System.out.println(modelParams.dlTransforms.get(i));
|
||||
// System.out.println(modelParams.dlTransforms.get(i).toString());
|
||||
// }
|
||||
|
||||
//only load new transforms if defaults are selected
|
||||
|
||||
@ -11,6 +11,7 @@ import org.jamdev.jdl4pam.transforms.DLTransformsFactory;
|
||||
import org.jamdev.jdl4pam.utils.DLUtils;
|
||||
import org.jamdev.jpamutils.wavFiles.AudioData;
|
||||
|
||||
import PamUtils.PamArrayUtils;
|
||||
import PamguardMVC.PamDataUnit;
|
||||
import rawDeepLearningClassifier.DLControl;
|
||||
import rawDeepLearningClassifier.DLStatus;
|
||||
@ -82,10 +83,17 @@ public abstract class DLModelWorker<T> {
|
||||
DLTransform transform = modelTransforms.get(0);
|
||||
for (int i =0; i<modelTransforms.size(); i++) {
|
||||
transform = modelTransforms.get(i).transformData(transform);
|
||||
|
||||
// //TEMP
|
||||
// if (transform instanceof FreqTransform) {
|
||||
// transformedData = ((FreqTransform) transform).getSpecTransfrom().getTransformedData();
|
||||
// System.out.println("DLModelWorker: transform : " + modelTransforms.get(i).getDLTransformType() + " "+ i + transformedData.length + " " + transformedData[0].length + " minmax: " + PamArrayUtils.minmax(transformedData)[0] + " " + PamArrayUtils.minmax(transformedData)[1]);
|
||||
// }
|
||||
|
||||
// //TEMP
|
||||
// if (transform instanceof WaveTransform) {
|
||||
// transformedData1 = ((WaveTransform) transform).getWaveData().getScaledSampleAmplitudes();
|
||||
// System.out.println("DLModelWorker: transform : " + modelTransforms.get(i).getDLTransformType() + " "+ i + " " + transformedData1.length + " " + PamArrayUtils.minmax(transformedData1)[0] + " " + PamArrayUtils.minmax(transformedData1)[1]);
|
||||
// }
|
||||
}
|
||||
|
||||
|
||||
@ -104,6 +104,7 @@ public class GenericModelWorker extends DLModelWorker<StandardPrediction> {
|
||||
}
|
||||
|
||||
setModelTransforms(genericParams.dlTransfroms);
|
||||
|
||||
|
||||
//is this a waveform or a spectrogram model?
|
||||
setWaveFreqModel(genericParams);
|
||||
|
||||
@ -583,10 +583,11 @@ public class DLSettingsPane extends SettingsPane<RawDLParams>{
|
||||
|
||||
@Override
|
||||
public void setParams(RawDLParams currParams) {
|
||||
|
||||
sourcePane.setParams(currParams.groupedSourceParams);
|
||||
|
||||
|
||||
sourcePane.sourceChanged();
|
||||
sourcePane.setSourceList();
|
||||
sourcePane.setParams(currParams.groupedSourceParams);
|
||||
|
||||
dlControl.createDataSelector(sourcePane.getSource());
|
||||
|
||||
|
||||
@ -59,7 +59,7 @@ public class PeakTrimTransformPane extends DLTransformPane {
|
||||
});
|
||||
|
||||
//spinner for changing filter order.
|
||||
targetLenSpinner = new Spinner<Integer>(1,50,4,1);
|
||||
targetLenSpinner = new Spinner<Integer>(1,Integer.MAX_VALUE,4,1);
|
||||
targetLenSpinner.valueProperty().addListener((obsVal, oldVal, newVal)->{
|
||||
this.notifySettingsListeners();
|
||||
});
|
||||
|
||||
@ -1,5 +1,7 @@
|
||||
package rawDeepLearningClassifier.offline;
|
||||
|
||||
import java.util.ListIterator;
|
||||
|
||||
import PamController.PamController;
|
||||
import PamguardMVC.PamDataUnit;
|
||||
import PamguardMVC.PamObservable;
|
||||
@ -8,6 +10,7 @@ import dataMap.OfflineDataMapPoint;
|
||||
import matchedTemplateClassifer.MTClassifierControl;
|
||||
import offlineProcessing.OfflineTask;
|
||||
import rawDeepLearningClassifier.DLControl;
|
||||
import rawDeepLearningClassifier.segmenter.GroupedRawData;
|
||||
import rawDeepLearningClassifier.segmenter.SegmenterDetectionGroup;
|
||||
import rawDeepLearningClassifier.segmenter.SegmenterProcess;
|
||||
|
||||
@ -48,7 +51,7 @@ public class DLOfflineTask extends OfflineTask<PamDataUnit<?,?>>{
|
||||
@Override
|
||||
public boolean processDataUnit(PamDataUnit<?, ?> dataUnit) {
|
||||
// System.out.println("--------------");
|
||||
// System.out.println("Offline task start: " + dataUnit.getUpdateCount() + " UID " + dataUnit.getUID());
|
||||
//System.out.println("Offline task start: " + dataUnit.getUpdateCount() + " UID " + dataUnit.getUID() + " " + dlControl.getDLParams().enableSegmentation);
|
||||
boolean saveBinary = false;
|
||||
try {
|
||||
|
||||
@ -79,9 +82,16 @@ public class DLOfflineTask extends OfflineTask<PamDataUnit<?,?>>{
|
||||
//detection has been added we force the classifier to run on all the segments generated from
|
||||
//the raw data.
|
||||
|
||||
//Process a data unit
|
||||
//Process a data unit within the segmenter
|
||||
dlControl.getSegmenter().newData(dataUnit);
|
||||
|
||||
|
||||
//System.out.println("Segments: " + dlControl.getSegmenter().getSegmenterDataBlock().getUnitsCount());
|
||||
//need to add the segmenter data units into the classification buffer
|
||||
ListIterator<GroupedRawData> iterator = dlControl.getSegmenter().getSegmenterDataBlock().getListIterator(0);
|
||||
while (iterator.hasNext()) {
|
||||
dlControl.getDLClassifyProcess().newData(dlControl.getSegmenter().getSegmenteGroupDataBlock(), iterator.next());
|
||||
}
|
||||
|
||||
//force click data save
|
||||
dlControl.getDLClassifyProcess().forceRunClassifier(dataUnit);
|
||||
|
||||
|
||||
@ -96,7 +96,7 @@ public class SegmenterProcess extends PamProcess {
|
||||
segmenterDataBlock = new SegmenterDataBlock("Segmented Raw Data", this,
|
||||
dlControl.getDLParams().groupedSourceParams.getChanOrSeqBitmap());
|
||||
|
||||
segmenterGroupDataBlock = new SegmenterGroupDataBlock("Segmented data units", this,
|
||||
segmenterGroupDataBlock = new SegmenterGroupDataBlock("Segmented Group Data", this,
|
||||
dlControl.getDLParams().groupedSourceParams.getChanOrSeqBitmap());
|
||||
|
||||
addOutputDataBlock(segmenterDataBlock);
|
||||
@ -241,7 +241,7 @@ public class SegmenterProcess extends PamProcess {
|
||||
newRawDataUnit(pamRawData);
|
||||
}
|
||||
else if (pamRawData instanceof ClickDetection) {
|
||||
newClickData( pamRawData);
|
||||
newClickData(pamRawData);
|
||||
}
|
||||
else if (pamRawData instanceof ClipDataUnit) {
|
||||
newClipData(pamRawData);
|
||||
@ -491,7 +491,7 @@ public class SegmenterProcess extends PamProcess {
|
||||
public void newClickData(PamDataUnit pamRawData) {
|
||||
|
||||
//the raw data units should appear in sequential channel order
|
||||
// System.out.println("New raw data in: chan: " + PamUtils.getSingleChannel(pamRawData.getChannelBitmap()) + " Size: " + pamRawData.getSampleDuration());
|
||||
//System.out.println("New raw data in: chan: " + PamUtils.getSingleChannel(pamRawData.getChannelBitmap()) + " Size: " + pamRawData.getSampleDuration());
|
||||
|
||||
ClickDetection clickDataUnit = (ClickDetection) pamRawData;
|
||||
|
||||
@ -542,6 +542,12 @@ public class SegmenterProcess extends PamProcess {
|
||||
//segment the data unit into different chunks.
|
||||
newRawData(pamDataUnit,
|
||||
rawDataChunk[i], chans[i], dlControl.getDLParams().rawSampleSize, dlControl.getDLParams().sampleHop, true);
|
||||
//the way that the newRawdata works is it waits for the next chunk and copies all relevant bits
|
||||
//from previous chunks into segments. This is fine for continuous data but means that chunks of data
|
||||
//don't get their last hop...
|
||||
|
||||
//got to save the last chunk of raw data -even if the segment has not been filled.
|
||||
saveRawGroupData(true);
|
||||
}
|
||||
else {
|
||||
// //send the whole data chunk to the deep learning unit
|
||||
@ -551,13 +557,8 @@ public class SegmenterProcess extends PamProcess {
|
||||
// pamDataUnit.getStartSample(), rawDataChunk[i].length, rawDataChunk[i].length);
|
||||
}
|
||||
|
||||
//the way that the newRawdata works is it waits for the next chunk and copies all relevant bits
|
||||
//from previous chunks into segments. This is fine for continuous data but means that chunks of data
|
||||
//don't get their last hop...
|
||||
}
|
||||
|
||||
//got to save the last chunk of raw data -even if the segment has not been filled.
|
||||
saveRawGroupData(true);
|
||||
}
|
||||
|
||||
|
||||
@ -600,7 +601,7 @@ public class SegmenterProcess extends PamProcess {
|
||||
long timeMilliseconds = unit.getTimeMilliseconds();
|
||||
long startSampleTime = unit.getStartSample();
|
||||
|
||||
//System.out.println("Segmenter: RawDataIn: chan: 1 " + getSourceParams().countChannelGroups() + currentRawChunks);
|
||||
//System.out.println("Segmenter: RawDataIn: chan: 1 " + getSourceParams().countChannelGroups() + currentRawChunks + " rawSampleSize " + rawSampleSize + " rawSampleHop: " +rawSampleHop);
|
||||
|
||||
if (currentRawChunks==null) {
|
||||
System.err.println("Current raw chunk arrays are null");
|
||||
@ -753,6 +754,7 @@ public class SegmenterProcess extends PamProcess {
|
||||
* @param forceSave - true to also save the remaining unfilled segment.
|
||||
*/
|
||||
private void saveRawGroupData(boolean forceSave) {
|
||||
//System.out.println("Segmenter process: saveRawGroupData(boolean forceSave)");
|
||||
for (int i=0; i<getSourceParams().countChannelGroups(); i++) {
|
||||
saveRawGroupData(i, forceSave);
|
||||
}
|
||||
@ -771,6 +773,7 @@ public class SegmenterProcess extends PamProcess {
|
||||
* @param i - the group index.
|
||||
*/
|
||||
private void saveRawGroupData(int i) {
|
||||
//System.out.println("Segmenter process: saveRawGroupData(int i)");
|
||||
saveRawGroupData(i, false);
|
||||
}
|
||||
|
||||
|
||||
@ -1,23 +1,33 @@
|
||||
package test.rawDeepLearningClassifier;
|
||||
|
||||
import static org.junit.Assert.assertTrue;
|
||||
import static org.junit.jupiter.api.Assertions.assertEquals;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.nio.file.Path;
|
||||
import java.nio.file.Paths;
|
||||
import java.util.ArrayList;
|
||||
|
||||
import org.jamdev.jdl4pam.transforms.DLTransform;
|
||||
import org.jamdev.jdl4pam.transforms.DLTransformsFactory;
|
||||
import org.jamdev.jdl4pam.transforms.DLTransfromParams;
|
||||
import org.jamdev.jdl4pam.transforms.SimpleTransformParams;
|
||||
import org.jamdev.jdl4pam.transforms.WaveTransform;
|
||||
import org.jamdev.jdl4pam.utils.DLMatFile;
|
||||
import org.jamdev.jpamutils.wavFiles.AudioData;
|
||||
import org.jamdev.jdl4pam.transforms.DLTransform.DLTransformType;
|
||||
import org.junit.jupiter.api.Test;
|
||||
|
||||
import PamUtils.PamArrayUtils;
|
||||
import rawDeepLearningClassifier.dlClassification.animalSpot.StandardModelParams;
|
||||
import rawDeepLearningClassifier.dlClassification.archiveModel.ArchiveModelWorker;
|
||||
import rawDeepLearningClassifier.dlClassification.genericModel.GenericModelParams;
|
||||
import rawDeepLearningClassifier.dlClassification.genericModel.GenericModelWorker;
|
||||
import rawDeepLearningClassifier.dlClassification.genericModel.StandardPrediction;
|
||||
import rawDeepLearningClassifier.segmenter.GroupedRawData;
|
||||
import us.hebi.matlab.mat.format.Mat5;
|
||||
import us.hebi.matlab.mat.format.Mat5File;
|
||||
import us.hebi.matlab.mat.types.MatFile;
|
||||
import us.hebi.matlab.mat.types.Matrix;
|
||||
import us.hebi.matlab.mat.types.Struct;
|
||||
|
||||
@ -26,18 +36,231 @@ import us.hebi.matlab.mat.types.Struct;
|
||||
* Model from Thomas webber which is a good way to test the click based stuff is working in PAMGUard.
|
||||
*/
|
||||
public class ClickDLTest {
|
||||
|
||||
|
||||
|
||||
/**
|
||||
* Test just one click using the zipped classifier
|
||||
* @throws
|
||||
*/
|
||||
@Test
|
||||
public void clickDLTest() {
|
||||
public void aclickDLTestZip() {
|
||||
|
||||
System.out.println("*****CLickDLTest: Single click test zip*****");
|
||||
|
||||
float SAMPLE_RATE = 500000;
|
||||
//relative paths to the resource folders.
|
||||
String relModelPath = "/home/jamiemac/Dropbox/PAMGuard_dev/Deep_Learning/click_classifier_Thomas/model_v2/model_pb.zip";
|
||||
String clicksPath = "/home/jamiemac/Dropbox/PAMGuard_dev/Deep_Learning/click_classifier_Thomas/model_v2/example_2000021.mat";
|
||||
|
||||
// String matout = "/home/jamiemac/MATLAB-Drive/MATLAB/PAMGUARD/deep_learning/generic_classifier/example_2000021_transforms.mat";
|
||||
String matout=null;
|
||||
// load the click data up.
|
||||
Path clkPath = Paths.get(clicksPath);
|
||||
PredGroupedRawData clickData = null;
|
||||
|
||||
Struct matclkStruct = Mat5.newStruct();
|
||||
try {
|
||||
Mat5File mfr = Mat5.readFromFile(clkPath.toAbsolutePath().normalize().toString());
|
||||
|
||||
// //get array of a name "my_array" from file
|
||||
Struct mlArrayRetrived = mfr.getStruct( "newStruct" );
|
||||
|
||||
Matrix clickWavM = mlArrayRetrived.get("wave", 0);
|
||||
|
||||
double[][] clickWaveform= PamArrayUtils.matrix2array(clickWavM);
|
||||
clickWaveform=PamArrayUtils.transposeMatrix(clickWaveform);
|
||||
|
||||
Matrix clickUID= mlArrayRetrived.get("UID", 0);
|
||||
Matrix pred= mlArrayRetrived.get("pred", 0);
|
||||
|
||||
//create a click object whihc we can pass through transforms etc.
|
||||
clickData = new PredGroupedRawData(0L, 1, 0, clickWaveform[0].length, clickWaveform[0].length);
|
||||
clickData.setUID(clickUID.getLong(0));
|
||||
clickData.setRawData(clickWaveform);
|
||||
clickData.setPrediction(new double[] {pred.getDouble(0)});
|
||||
|
||||
// load the model up
|
||||
Path path = Paths.get(relModelPath);
|
||||
|
||||
ArchiveModelWorker genericModelWorker = new ArchiveModelWorker();
|
||||
|
||||
StandardModelParams genericModelParams = new StandardModelParams();
|
||||
genericModelParams.modelPath = path.toAbsolutePath().normalize().toString();
|
||||
|
||||
//prep the model - all setting are included within the model
|
||||
genericModelWorker.prepModel(genericModelParams, null);
|
||||
System.out.println("seglen: " + genericModelParams.defaultSegmentLen);
|
||||
|
||||
ArrayList<GroupedRawData> groupedData = new ArrayList<GroupedRawData>();
|
||||
groupedData.add(clickData);
|
||||
|
||||
System.out.println("Waveform input: " + groupedData.get(0).getRawData().length + " " + groupedData.get(0).getRawData()[0].length);
|
||||
|
||||
ArrayList<StandardPrediction> genericPrediction = genericModelWorker.runModel(groupedData,96000, 0);
|
||||
|
||||
float[] outputPAMGuard = genericPrediction.get(0).getPrediction();
|
||||
|
||||
System.out.println("Model output PAMGuard: " + outputPAMGuard[0]);
|
||||
assertEquals(outputPAMGuard[0], 0.99, 0.05);
|
||||
|
||||
}
|
||||
catch (Exception e) {
|
||||
// TODO Auto-generated catch block
|
||||
e.printStackTrace();
|
||||
assertTrue(false); //make sure the unit test fails
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Test just one click
|
||||
* @throws
|
||||
*/
|
||||
@Test
|
||||
public void aclickDLTest() {
|
||||
|
||||
System.out.println("*****CLickDLTest: Single click test*****");
|
||||
|
||||
//relative paths to the resource folders.
|
||||
System.out.println("*****Click classification Deep Learning C*****");
|
||||
|
||||
// //relative paths to the resource folders.
|
||||
// String relModelPath = "/Users/jdjm/Library/CloudStorage/Dropbox/PAMGuard_dev/Deep_Learning/click_classifier_Thomas/model_v2/model_pb/saved_model.pb";
|
||||
// String clicksPath = "/Users/jdjm/Library/CloudStorage/Dropbox/PAMGuard_dev/Deep_Learning/click_classifier_Thomas/model_v2/example_2000021.mat";
|
||||
|
||||
//relative paths to the resource folders.
|
||||
String relModelPath = "./src/test/resources/rawDeepLearningClassifier/Generic/risso_click/uniform_model/saved_model.pb";
|
||||
String clicksPath = "./src/test/resources/rawDeepLearningClassifier/Generic/risso_click/clicks.mat";
|
||||
String relModelPath = "/home/jamiemac/Dropbox/PAMGuard_dev/Deep_Learning/click_classifier_Thomas/model_v2/model_pb/saved_model.pb";
|
||||
String clicksPath = "/home/jamiemac/Dropbox/PAMGuard_dev/Deep_Learning/click_classifier_Thomas/model_v2/example_2000021.mat";
|
||||
//load the click up
|
||||
|
||||
// String matout = "/home/jamiemac/MATLAB-Drive/MATLAB/PAMGUARD/deep_learning/generic_classifier/example_2000021_transforms.mat";
|
||||
String matout=null;
|
||||
// load the click data up.
|
||||
Path clkPath = Paths.get(clicksPath);
|
||||
PredGroupedRawData clickData = null;
|
||||
|
||||
Struct matclkStruct = Mat5.newStruct();
|
||||
try {
|
||||
Mat5File mfr = Mat5.readFromFile(clkPath.toAbsolutePath().normalize().toString());
|
||||
|
||||
// //get array of a name "my_array" from file
|
||||
Struct mlArrayRetrived = mfr.getStruct( "newStruct" );
|
||||
|
||||
|
||||
Matrix clickWavM = mlArrayRetrived.get("wave", 0);
|
||||
Matrix modelInputM= mlArrayRetrived.get("wave_pad", 0);
|
||||
|
||||
double[][] clickWaveform= PamArrayUtils.matrix2array(clickWavM);
|
||||
clickWaveform=PamArrayUtils.transposeMatrix(clickWaveform);
|
||||
|
||||
//get the raw model input so we can test the model directly.
|
||||
double[][] pythonModelInput= PamArrayUtils.matrix2array(modelInputM);
|
||||
pythonModelInput = PamArrayUtils.transposeMatrix(pythonModelInput);
|
||||
float[] pythonModelInputF = PamArrayUtils.double2Float(pythonModelInput[0]);
|
||||
|
||||
Matrix clickUID= mlArrayRetrived.get("UID", 0);
|
||||
Matrix pred= mlArrayRetrived.get("pred", 0);
|
||||
|
||||
//create a click object whihc we can pass through transforms etc.
|
||||
clickData = new PredGroupedRawData(0L, 1, 0, clickWaveform[0].length, clickWaveform[0].length);
|
||||
clickData.setUID(clickUID.getLong(0));
|
||||
clickData.setRawData(clickWaveform);
|
||||
clickData.setPrediction(new double[] {pred.getDouble(0)});
|
||||
|
||||
|
||||
// load the model up
|
||||
Path path = Paths.get(relModelPath);
|
||||
|
||||
GenericModelWorker genericModelWorker = new GenericModelWorker();
|
||||
|
||||
GenericModelParams genericModelParams = new GenericModelParams();
|
||||
genericModelParams.modelPath = path.toAbsolutePath().normalize().toString();
|
||||
|
||||
|
||||
//create the transforms.
|
||||
ArrayList<DLTransfromParams> dlTransformParamsArr = new ArrayList<DLTransfromParams>();
|
||||
|
||||
//waveform transforms.
|
||||
dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.DECIMATE_SCIPY, 96000.));
|
||||
dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.NORMALISE_WAV, 0., 1, AudioData.ZSCORE)); //needs to be here
|
||||
dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.PEAK_TRIM, 64, 1));
|
||||
|
||||
genericModelParams.dlTransfromParams = dlTransformParamsArr;
|
||||
genericModelParams.dlTransfroms = DLTransformsFactory.makeDLTransforms((ArrayList<DLTransfromParams>)genericModelParams.dlTransfromParams);
|
||||
|
||||
//create the clicks.
|
||||
path = Paths.get(clicksPath);
|
||||
|
||||
//prep the model
|
||||
genericModelWorker.prepModel(genericModelParams, null);
|
||||
|
||||
ArrayList<GroupedRawData> groupedData = new ArrayList<GroupedRawData>();
|
||||
groupedData.add(clickData);
|
||||
|
||||
System.out.println("Waveform input: " + groupedData.get(0).getRawData().length + " " + groupedData.get(0).getRawData()[0].length);
|
||||
|
||||
ArrayList<StandardPrediction> genericPrediction = genericModelWorker.runModel(groupedData,96000, 0);
|
||||
|
||||
// System.out.println("PAMGuard input len: " + pythonModelInputF.length);
|
||||
|
||||
float[] outputPAMGuard = genericPrediction.get(0).getPrediction();
|
||||
|
||||
System.out.println("Model output PAMGuard: " + outputPAMGuard[0]);
|
||||
|
||||
//run the transforms so we can take a look at the inpout
|
||||
((WaveTransform) genericModelParams.dlTransfroms.get(0)).setWaveData(new AudioData(groupedData.get(0).getRawData()[0], 248000));;
|
||||
//create the transformed wave
|
||||
DLTransform transform = genericModelParams.dlTransfroms.get(0);
|
||||
double[] audioOut = null;
|
||||
for (int i=0; i<genericModelParams.dlTransfroms .size(); i++) {
|
||||
transform = genericModelParams.dlTransfroms.get(i).transformData(transform);
|
||||
audioOut = ((WaveTransform) transform).getWaveData().getScaledSampleAmplitudes();
|
||||
matclkStruct.set(transform.getDLTransformType().getJSONString(), DLMatFile.array2Matrix(audioOut));
|
||||
}
|
||||
|
||||
//RUN THE RAW MODEL with Python transformed input
|
||||
|
||||
// System.out.println("Python input len: " + pythonModelInputF.length);
|
||||
// float[] outPutPython = genericModelWorker.getModel().runModel(new float[][] {PamArrayUtils.double2Float(audioOut)});
|
||||
|
||||
float[] outPutPython = genericModelWorker.getModel().runModel(new float[][] {pythonModelInputF});
|
||||
|
||||
System.out.println("Model output Python: " + outPutPython[0]);
|
||||
|
||||
assertEquals(outputPAMGuard[0], outPutPython[0], 0.05);
|
||||
|
||||
}
|
||||
catch (Exception e) {
|
||||
// TODO Auto-generated catch block
|
||||
e.printStackTrace();
|
||||
assertTrue(false); //make sure the unit test fails
|
||||
return;
|
||||
}
|
||||
|
||||
if (matout!=null) {
|
||||
// Create MAT file with a scalar in a nested struct
|
||||
MatFile matFile = Mat5.newMatFile()
|
||||
.addArray("click_transforms", matclkStruct);
|
||||
// Serialize to disk using default configurations
|
||||
try {
|
||||
Mat5.writeToFile(matFile, matout);
|
||||
} catch (IOException e) {
|
||||
// TODO Auto-generated catch block
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
@Test
|
||||
public void clicksDLTest() {
|
||||
|
||||
float SAMPLE_RATE = 96000;
|
||||
//relative paths to the resource folders.
|
||||
System.out.println("*****CLickDLTest: Clicks test*****");
|
||||
|
||||
//relative paths to the resource folders.
|
||||
String relModelPath = "/home/jamiemac/Dropbox/PAMGuard_dev/Deep_Learning/click_classifier_Thomas/model_v2/model_pb/saved_model.pb";
|
||||
String clicksPath = "/home/jamiemac/Dropbox/PAMGuard_dev/Deep_Learning/click_classifier_Thomas/model_v2/Click_Detector_Click_Detector_Clicks_20220603_111000_classified.mat";
|
||||
|
||||
Path path = Paths.get(relModelPath);
|
||||
|
||||
@ -46,59 +269,67 @@ public class ClickDLTest {
|
||||
GenericModelParams genericModelParams = new GenericModelParams();
|
||||
genericModelParams.modelPath = path.toAbsolutePath().normalize().toString();
|
||||
|
||||
|
||||
|
||||
//create the transforms.
|
||||
ArrayList<DLTransfromParams> dlTransformParamsArr = new ArrayList<DLTransfromParams>();
|
||||
|
||||
//waveform transforms.
|
||||
dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.DECIMATE_SCIPY, 248000.));
|
||||
dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.PEAK_TRIM, 128, 1));
|
||||
dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.DECIMATE_SCIPY, 96000.));
|
||||
dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.NORMALISE_WAV, 0., 1, AudioData.ZSCORE));
|
||||
|
||||
dlTransformParamsArr.add(new SimpleTransformParams(DLTransformType.PEAK_TRIM, 64, 1));
|
||||
|
||||
genericModelParams.dlTransfromParams = dlTransformParamsArr;
|
||||
genericModelParams.dlTransfroms = DLTransformsFactory.makeDLTransforms((ArrayList<DLTransfromParams>)genericModelParams.dlTransfromParams);
|
||||
|
||||
|
||||
//create the clicks.
|
||||
path = Paths.get(clicksPath);
|
||||
ArrayList<PredGroupedRawData> clicks = importClicks(path.toAbsolutePath().normalize().toString(), SAMPLE_RATE);
|
||||
|
||||
ArrayList<PredGroupedRawData> clicks = importClicks(path.toAbsolutePath().normalize().toString(), SAMPLE_RATE);
|
||||
|
||||
//prep the model
|
||||
genericModelWorker.prepModel(genericModelParams, null);
|
||||
|
||||
System.out.println("Model has loaded");
|
||||
|
||||
ArrayList<GroupedRawData> groupedData = new ArrayList<GroupedRawData>();
|
||||
|
||||
for (int i=0; i<1; i++) {
|
||||
|
||||
System.out.println("Model has loaded: n clicks " + clicks.size());
|
||||
|
||||
float count = 0;
|
||||
long timeStart = System.currentTimeMillis();
|
||||
for (int i=0; i<clicks.size(); i++) {
|
||||
|
||||
float prediction = (float) clicks.get(i).getPrediction()[0];
|
||||
|
||||
|
||||
ArrayList<GroupedRawData> groupedData = new ArrayList<GroupedRawData>();
|
||||
groupedData.add(clicks.get(i)); //TODO for loop
|
||||
|
||||
//System.out.println("Waveform input: " + groupedData.get(i).getRawData().length + " " + groupedData.get(i).getRawData()[0].length);
|
||||
|
||||
ArrayList<StandardPrediction> genericPrediction = genericModelWorker.runModel(groupedData,SAMPLE_RATE, 0);
|
||||
|
||||
float[] output = genericPrediction.get(i).getPrediction();
|
||||
|
||||
System.out.println(String.format("Click %d Predicted output: %.2f true output: %.2f passed: %b", clicks.get(i).getUID(),
|
||||
output[0], prediction, output[0]>prediction*0.9 && output[0]<prediction*1.1));
|
||||
|
||||
}
|
||||
|
||||
|
||||
//System.out.println("Waveform input: " + groupedData.get(i).getRawData().length + " " + groupedData.get(i).getRawData()[0].length);
|
||||
|
||||
ArrayList<StandardPrediction> genericPrediction = genericModelWorker.runModel(groupedData,SAMPLE_RATE, 0);
|
||||
|
||||
float[] output = genericPrediction.get(0).getPrediction();
|
||||
|
||||
System.out.println(String.format("Click %d Predicted output: %.4f true output: %.4f passed: %b delta %.2f", clicks.get(i).getUID(),
|
||||
output[0], prediction, output[0]>prediction*0.9 && output[0]<prediction*1.1, (Math.abs(output[0] -prediction))));
|
||||
|
||||
if (output[0]>prediction*0.9 && output[0]<prediction*1.1) {
|
||||
count++;
|
||||
}
|
||||
|
||||
}
|
||||
long timeEnd = System.currentTimeMillis();
|
||||
|
||||
double perctrue = count/clicks.size();
|
||||
|
||||
System.out.println(String.format("Percentage clicks passed: %.2f TIme to process %d clicks - %2f seconds", perctrue, clicks.size(), ((double) (timeEnd-timeStart))/1000.));
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Import a bunch of clicks from a .mat file
|
||||
*/
|
||||
public static ArrayList<PredGroupedRawData> importClicks(String filePath, float sR) {
|
||||
|
||||
try {
|
||||
Mat5File mfr = Mat5.readFromFile(filePath);
|
||||
Mat5File mfr = Mat5.readFromFile(filePath);
|
||||
|
||||
// //get array of a name "my_array" from file
|
||||
Struct mlArrayRetrived = mfr.getStruct( "clickpreds" );
|
||||
Struct mlArrayRetrived = mfr.getStruct( "binarydata" );
|
||||
|
||||
int numClicks= mlArrayRetrived.getNumCols();
|
||||
ArrayList<PredGroupedRawData> clicks = new ArrayList<PredGroupedRawData>(numClicks);
|
||||
@ -106,12 +337,12 @@ public class ClickDLTest {
|
||||
PredGroupedRawData clickData;
|
||||
for (int i=0; i<numClicks; i++) {
|
||||
Matrix clickWav= mlArrayRetrived.get("wave", i);
|
||||
|
||||
|
||||
double[][] clickwaveform= PamArrayUtils.matrix2array(clickWav);
|
||||
|
||||
|
||||
clickwaveform = PamArrayUtils.transposeMatrix(clickwaveform);
|
||||
//System.out.println("click: " + click[0].length + " num: " + numClicks);
|
||||
|
||||
|
||||
Matrix clickUID= mlArrayRetrived.get("UID", i);
|
||||
Matrix clickmillis= mlArrayRetrived.get("millis", i);
|
||||
Matrix channelMap= mlArrayRetrived.get("channelMap", i);
|
||||
@ -122,11 +353,11 @@ public class ClickDLTest {
|
||||
clickData = new PredGroupedRawData(clickmillis.getLong(0), channelMap.getInt(0), startSample.getLong(0), sampleDuration.getLong(0), sampleDuration.getInt(0));
|
||||
clickData.setUID(clickUID.getLong(0));
|
||||
clickData.setRawData(clickwaveform);
|
||||
clickData.setPrediction(new double[] {pred.getDouble(0), pred.getDouble(1)});
|
||||
|
||||
clickData.setPrediction(new double[] {pred.getDouble(0)});
|
||||
|
||||
clicks.add(clickData);
|
||||
}
|
||||
|
||||
|
||||
return clicks;
|
||||
}
|
||||
catch (Exception e) {
|
||||
@ -135,11 +366,11 @@ public class ClickDLTest {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
public static class PredGroupedRawData extends GroupedRawData {
|
||||
|
||||
|
||||
private double[] prediction;
|
||||
|
||||
|
||||
public double[] getPrediction() {
|
||||
return prediction;
|
||||
}
|
||||
@ -151,10 +382,10 @@ public class ClickDLTest {
|
||||
public PredGroupedRawData(long timeMilliseconds, int channelBitmap, long startSample, long duration, int samplesize) {
|
||||
super(timeMilliseconds, channelBitmap, startSample, duration, samplesize);
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user