Click Train Detector Help

src/clickTrainDetector/ClickTrainControl.java

@@ -146,6 +146,11 @@ public class ClickTrainControl extends PamControlledUnit implements PamSettings
 	 * Click info manager- handles information from the algorithms. 
 	 */
 	private CTAlgorithmInfoManager clAlgorithmInfoManager;
+	
+	/**
+	 * Help point which can be referenced form dialogs, etc. 
+	 */
+	public static final String helpPoint = "detectors.ClickTrainDetector.docs.ClickTrainDetector";
  
 	/**
 	 * Constructor for the ClickTrainControl. 

src/clickTrainDetector/layout/ClickTrainAlgorithmPaneFX.java

@@ -587,6 +587,11 @@ public class ClickTrainAlgorithmPaneFX extends SettingsPane<ClickTrainParams> {
 	public void paneInitialized() {
 
 	}
+
+	@Override
+	public String getHelpPoint() {
+		return ClickTrainControl.helpPoint;
+	}
 	
 
 }

src/help/JavaHelpSearch/SCHEMA

@@ -1,2 +1,2 @@
 JavaSearch 1.0
-TMAP bs=2048 rt=1 fl=-1 id1=6559 id2=1
+TMAP bs=2048 rt=1 fl=-1 id1=6661 id2=1

src/help/Map.jhm

@@ -442,6 +442,8 @@
 
 <mapID target="localisation.bearingLocaliser.docs.BL_Settings" url="localisation/bearingLocaliser/docs/BL_Settings.html"/>
 
+<mapID target="detectors.ClickTrainDetector.docs.ClickTrainDetector" url="detectors/ClickTrainDetector/docs/ClickTrainDetector.html"/>
+
 <mapID target="sound_processing.FiltersHelp.Docs.Filters_filters" url="sound_processing/FiltersHelp/Docs/Filters_filters.html"/>
 
 <mapID target="localisation.bearingLocaliser.docs.BL_Output" url="localisation/bearingLocaliser/docs/BL_Output.html"/>

src/help/PAMGUARD.hs

@@ -1,7 +1,8 @@
 <?xml version="1.0" encoding="ISO-8859-1" standalone="no"?>
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     <data>
 PAMGUARDTOC.xml
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     <label>
 Index 
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 javax.help.IndexView
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     <data>
 PAMGUARDIndex.xml
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     <label>
 Search 
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src/help/PAMGUARDHelpProject.xml

@@ -6,7 +6,7 @@
   <project>
 PAMGUARD
   </project>
-  <projectdir>C:\PamguardCode2021\PamGuard NOAA2\src\help</projectdir>
+  <projectdir>C:\Users\dg50\source\repos\PAMGuardDG\src\help</projectdir>
   <startpage>
 index.html
   </startpage>

src/help/PAMGUARDTOC.xml

@@ -481,6 +481,10 @@
    <tocitem text="Localisation " target="detectors.gpl.docs.localisation" image="topic"/>
 
   </tocitem>
+  <tocitem text="Click Train Detector " target="detectors.ClickTrainDetector.docs.ClickTrainDetector">
+   <tocitem text="Overview " target="detectors.ClickTrainDetector.docs.ClickTrainDetector" image="topic"/>
+
+  </tocitem>
  </tocitem>
  <tocitem text="Classifiers ">
   <tocitem text="Whistle Classifier ">

src/help/detectors/ClickTrainDetector/docs/ClickTrainDetector.html

@@ -6,7 +6,6 @@
 </head>
 
 <body>
-
 	<h1 id="click-train-detector">Click Train Detector</h1>
 	<h2 id="overview">Overview</h2>
 	<p>When a toothed whale, bat or other echolocator uses echolocation
@@ -33,24 +32,24 @@
 		with multiple types of acoustic data, from CPOD detections to single
 		channel and multi-channel hydrophone recordings.</p>
 	<h2 id="how-it-works">How it works</h2>
-	<p>PAMGuard's click train detector utilises both a detection and
+	<p>PAMGuard’s click train detector utilises both a detection and
 		classification stage to extract click trains from recordings.</p>
 	<p>The detection stage is currently based on a multi hypothesis
 		tracking (MHT) algorithm. This algorithm considers all possible
 		combinations of transient detections creating a large hypothesis
 		matrix which holds potential click trains. As more clicks are added to
 		the hypothesis matrix it grows exponentially and so, to prevent a
-		computer running out memory, it is regularly <em>pruned</em> to keep only
+		computer running out memory, it is regularly “pruned” to keep only the
-		the most likely click trains over time. The assigned likelihood of a
+		most likely click trains over time. The assigned likelihood of a click
-		click train is based on number of properties which can be defined in
+		train is based on number of properties which can be defined in by the
-		by the user. For example, a user might select, ICI, Amplitude and
+		user. For example, a user might select, ICI, Amplitude and Correlation
-		Correlation as variables to score click trains; this would mean that
+		as variables to score click trains; this would mean that combinations
-		combinations of clicks with slowly changing ICI, amplitude and
+		of clicks with slowly changing ICI, amplitude and waveforms would be
-		waveforms would be favoured by the algorithm and stay in the
+		favoured by the algorithm and stay in the hypothesis matrix. Other
-		hypothesis matrix. Other properties such as bearing, click length and
+		properties such as bearing, click length and peak frequency can also
-		peak frequency can also be selected. A graphical explanation of the
+		be selected. A graphical explanation of the click train detection
-		click train detection algorithm is shown in Figure 1 and a more
+		algorithm is shown in Figure 1 and a more detailed explanation of the
-		detailed explanation of the be found in Macaulay (2019).</p>
+		be found in Macaulay (2019).</p>
 	<p align="center">
 		<img width="930" height="900" src="resources/mht_diagram.png">
 	</p>
@@ -67,18 +66,18 @@
 			pruned. After a minimum of Npmin clicks (in this case 4) each track
 			hypothesis (possible click train) is assigned a &Chi;<sup>2</sup> score.
 			The track hypothesis with lowest score (defined by larger coloured
-			circles) has it's branch traced back Np (in this case 3) clicks.
+			circles) has it’s branch traced back Np (in this case 3) clicks. Any
-			Any track hypothesis which do not include the click Np steps back are
+			track hypothesis which do not include the click Np steps back are
 			pruned (defined by the double lines). Clicks which share no click
 			associations with the first track hypothesis are then pruned and the
 			process repeats until all clicks are part of a track or a maximum
 			number of tracks have been considered (in this example there are two
 			tracks). The algorithm then moves to the next click, adds it to the
-			hypothesis matrix, assigns &Chi;<sup>2</sup> scores and traces the
+			hypothesis matrix, assigns &Chi;<sup>2</sup> scores and traces the lowest
-			lowest &Chi;<sup>2</sup> branch Np steps back, pruning the hypothesis
+			&Chi;<sup>2</sup> branch Np steps back, pruning the hypothesis matrix
-			matrix again; the process repeats until the last click. Note that
+			again; the process repeats until the last click. Note that there is
-			there is always a track hypothesis with no associated clicks (i.e.
+			always a track hypothesis with no associated clicks (i.e. the
-			the bottom-most branch where no clicks belong to a click train). If a
+			bottom-most branch where no clicks belong to a click train). If a
 			track hypothesis is confirmed and thus removed from the hypothesis
 			matrix, then this track can be used to start another click train
 		</em>
@@ -98,12 +97,12 @@
 		correlation of the average spectrum of the click train with a
 		predefined spectral template.</p>
 	<p>A click train which has been both detected and classified is
-		saved to PAMGuard's database and can be reclassified in PAMGuard's
+		saved to PAMGuard’s database and can be reclassified in PAMGuard’s
 		viewer mode.</p>
 	<h2 id="configuring-the-click-train-detector">Configuring the
 		click train detector</h2>
 	<p>The primary settings to configure can be split into MHT Kernel
-		and &Chi;<sup>2</sup> settings, these are all set in the primary click train
+		and &Chi;^2 settings – these are all set in the primary click train
 		detector dialog as shown in Figure 2.</p>
 	<p align="center">
 		<img width="850" height="700" src="resources/detection_pane.png">
@@ -119,8 +118,8 @@
 		important because they influence speed (a larger number of possible
 		click trains in memory is more processor intensive) and the quality of
 		the detections (the larger the number of possibilities the more likely
-		that <em>true</em> click trains are contained in the hypothesis matrix).
+		that “true” click trains are contained in the hypothesis matrix). The
-		The specific settings are;</p>
+		specific settings are;</p>
 	<p>
 		<strong><em>Prune-back</em></strong>: The hypothesis matrix needs
 		pruned so that it does not grow exponentially and cause memory issues.
@@ -152,7 +151,7 @@
 	<p>
 		<strong><em>Max no. trains</em></strong>: This is a maximum allowed
 		number of trains in the hypothesis mix. Note this refers to the number
-		of trains which can survive pruning - the actual number of potential
+		of trains which can survive pruning – the actual number of potential
 		click trains in the hypothesis mix will be much larger. Generally,
 		just via pruning, the hypothesis matrix will keep itself below the max
 		no. trains, however, in certain situations it can grow too large and
@@ -165,8 +164,8 @@
 	</h3>
 	<p>
 		&Chi;<sup>2</sup> is a measure of the likelihood that a click train is
-		from a (usually) biological source. The higher the &Chi;<sup>2</sup>
+		from a (usually) biological source. The higher the &Chi;<sup>2</sup> value
-		value the lower the quality of a click train.
+		the lower the quality of a click train.
 	</p>
 	<p>
 		The &Chi;<sup>2</sup> model used in the click train detector considers
@@ -198,8 +197,8 @@
 		influence on the calculation of &Chi;<sup>2</sup> and decreasing means
 		that the descriptor has a larger influence on &Chi;<sup>2</sup>. In some
 		cases, clicks can be so close together that the variance is tiny and
-		thus &Chi;<sup>2</sup> becomes huge e.g. during buzzes. A minimum
+		thus &Chi;<sup>2</sup> becomes huge e.g. during buzzes. A minimum variance
-		variance value (<em>qt<sub>i</sub></em>) prevents the variance <em>(max¡(q<sub>i</sub>
+		value (<em>qt<sub>i</sub></em>) prevents the variance <em>(max(q<sub>i</sub>
 			(t<sub>(k+1)</sub>-t<sub>k</sub> ),qt<sub>i</sub> )<sup>2</sup>)
 		</em> from falling below very low values.
 	</p>
@@ -229,7 +228,7 @@
 		between detections.
 	</p>
 	<p>
-		<strong><em>Amplitude:</em></strong> the amplitude in dB re 1&mu;Pa pp.
+		<strong><em>Amplitude:</em></strong> the amplitude in dB re 1/muPa pp.
 		The algorithm looks for slowly changing amplitude values. Note that
 		the algorithm is comparing the change in change in amplitude so that
 		the click train algorithm is not biased against large but consistent
@@ -312,14 +311,14 @@
 		<strong><em>Long track bonus:</em></strong> add a bonus factor for
 		longer click trains to prevent fragmentation. This is the total length
 		of the click train in seconds divided by the total hypothesis matrix
-		time in seconds L which is then multiplied so that &Chi;<sup>2</sup> =
+		time in seconds L which is then multiplied so that &Chi;<sup>2</sup> = (&Chi;<sup>2</sup>*L)<sup>LT</sup>
-		(&Chi;<sup>2</sup>*L)<sup>LT</sup> where LT is the long track bonus.
+		where LT is the long track bonus.
 	</p>
 	<p>
-		<strong><em>Coast penalty:</em></strong> add a penalty for
+		<strong><em>Coast penalty:</em></strong> add a penalty for “coasting”
-		'coasting' i.e. when an expected click, based on ICI, is not
+		i.e. when an expected click, based on ICI, is not present in the click
-		present in the click train. This penalty is multiplied by the number
+		train. This penalty is multiplied by the number of coasts i.e. the
-		of coasts i.e. the likely number of missed clicks based on ICI
+		likely number of missed clicks based on ICI
 	</p>
 	<p>
 		<strong><em>New Track Penalty:</em></strong> if a track hypothesis is
@@ -361,10 +360,10 @@
 		&Chi;<sup>2</sup> threshold classifier
 	</h3>
 	<p>
-		The click train is classified if it's overall &Chi;<sup>2</sup> value
+		The click train is classified if it’s overall &Chi;<sup>2</sup> value is
-		is lower than the set &Chi;<sup>2</sup> Threshold and it has more than
+		lower than the set &Chi;<sup>2</sup> Threshold and it has more than Min.
-		Min. Clicks and the time between the first and last click is greater
+		Clicks and the time between the first and last click is greater than
-		than Min. Time
+		Min. Time
 	</p>
 	<h3 id="idi-classifier">IDI Classifier</h3>
 	<p>The click train is classified if the median/mean and standard
@@ -374,11 +373,11 @@
 	<p>The click train is classified if the average spectra of the
 		click train has a correlation value above Spectrum Correlation
 		Threshold with a user defined spectral template. The template can be
-		set using the button on the top right of the spectrum plot – a
+		set using the button on the top right of the spectrum plot – a default
-		default spectrum can be loaded or a spectrum can be loaded from a .mat
+		spectrum can be loaded or a spectrum can be loaded from a .mat or .csv
-		or .csv file. A csv file should have the first row as the spectrum and
+		file. A csv file should have the first row as the spectrum and first
-		first column of the second row the sample rate. A .mat file should be
+		column of the second row the sample rate. A .mat file should be a
-		a single saved structure with sR (sample rate) and spectrum (array of
+		single saved structure with sR (sample rate) and spectrum (array of
 		spectrum values) fields.</p>
 	<h3 id="bearing-classifier">Bearing Classifier</h3>
 	<p>The click train is classified if minimum and maximum bearing
@@ -389,7 +388,7 @@
 	<h2 id="parametrising-the-classifier">Parametrising the classifier</h2>
 	<p>Each classifier has a set of metadata that are added to click
 		trains. This can be accessed through the tooltip or right click menus
-		in various displays. For example, in the Time Base Display FX hover
+		in various displays. For example, in the Time Base Display Fx hover
 		the mouse over a click train or bring the pop menu with a right click.
 		Parameters such as the spectral correlation value, IDI and bearing
 		information etc are displayed which allows users to get an idea of
@@ -464,23 +463,23 @@
 			are localised.</em>
 	</p>
 	<p>In viewer mode, add the module and then go to Settings&gt;Click
-		Train Detector &gt; Reanalyse click trains.This will bring up
+		Train Detector &gt; Reanalyse click trains….This will bring up
-		PAMGuard's generic data reprocessing dialog with two settings, Click
+		PAMGuard’s generic data reprocessing dialog with two settings, Click
 		Train Detector or Click Train Classifier. The Click Train Detector
 		option will run the detection and classification algorithm again. The
 		Click Train Classifier will only run the classification algorithm on
 		existing detected click trains (much faster). Note that users can
-		select how much data to reprocess in the Data dropdown menu. All
+		select how much data to reprocess in the Data dropdown menu – All Data
-		Data means the entire dataset will be reprocessed, Loaded Data means
+		means the entire dataset will be reprocessed, Loaded Data means just
-		just the current data loaded in the display (all scrollable data),
+		the current data loaded in the display (all scrollable data), Select
-		Select Data allows the user to define two time limits between which
+		Data allows the user to define two time limits between which all data
-		all data is reprocessed.</p>
+		is reprocessed.</p>
 	<h2 id="visualising-results">Visualising Results</h2>
 	<p>The results from the click train detector can be visualised in a
 		variety of displays in PAMGuard.</p>
 	<h3 id="click-bearing-time-display">Click bearing time display</h3>
 	<p>By default, clicks trains will be shown in the Click Detector
-		Module's in built bearing time display. Different click trains are
+		Module’s in built bearing time display. Different click trains are
 		represented as different colours. Note that you must right click on
 		the display and select Colour by Click Trains</p>
 	<p align="center">
@@ -492,31 +491,22 @@
 			bearing time display. Different colours correspond to different click
 			trains.</em>
 	</p>
-	<h3 id="time-display-fx">Time Display FX</h3>
+	<h3 id="time-display-fx">Time Display Fx</h3>
-	<p>The Time Display FX is a more modern display which allows any
+	<p>The Time Display Fx is a more modern display which allows any
 		time-based data to be plotted together on a large variety of y-axis
 		(e.g., frequency, bearing, amplitude etc.). Click trains will be
 		plotted on the time-based display by adding Click detections to the
 		display and then using the right</p>
 	<p align="center">
-		<img width="940" height="500" src="resources/clicktrain_TDFX.png">
+		<img width="940" height="500" src="resources/clicktrain_TDFx.png">
 	</p>
 
 	<p>
-		<em>Click train data displayed in the time display FX. Users can
+		<em>Click train data displayed in the time display Fx. Users can
 			right click on click trains to view average spectra and waterfall
 			spectrograms (shown here in top right).</em>
 	</p>
 
 
-	<p CLASS="previousLink">
-		<a href=""></a>
-	</p>
-	<p CLASS="nextLink">
-		<a href="ClickDetector_clickDetectorDisplays.html">Next: Click
-			Detector Displays </a>
-	</p>
-	<br>
-	<br>
 </body>
 </html>