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Fix javadocs build
1 parent 4c51da8 commit 328bcfe

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‎src/main/java/sc/fiji/snt/tracing/auto/AbstractGWDTTracer.java‎

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@@ -674,11 +674,9 @@ public double getMinSomaDistance() {
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* <li>Neither set: auto-estimation via thickness filtering + gap
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* analysis (best-effort, also experimental)</li>
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* </ul>
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* </p>
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* <p>
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* Set to -1 to trigger auto-estimation (default). Set to 0 to disable
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* the count-based filter entirely.
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* </p>
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*
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* @param nSomas expected number of somas (&gt; 0), -1 for auto, or 0 to disable
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* @see #setMinSomaDistance(double)
@@ -720,7 +718,6 @@ public int getNSomas() {
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* tracer.setNSomas(0); // no count-based cap
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* List<Tree> trees = tracer.traceMultiSoma(somas);
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* }</pre>
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* </p>
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*
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* @param enabled whether to enable automatic soma filtering (default:
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* {@code true})

‎src/main/java/sc/fiji/snt/tracing/auto/ComponentReconnector.java‎

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@@ -63,7 +63,6 @@
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* signal</li>
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* <li><b>Length:</b> the bridge must not exceed the maximum gap distance</li>
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* </ul>
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* </p>
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* <p>
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* Adapted from NeuTube's chain connection logic ({@code Locseg_Chain_Connection_Test}).
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* </p>

‎src/main/java/sc/fiji/snt/tracing/auto/SomaUtils.java‎

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@@ -300,7 +300,6 @@ public static SomaResult detectSomaAt(
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* }</pre>
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* Otherwise, the tracer's heuristic reduction pipeline may discard valid
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* somas. See {@link AbstractGWDTTracer#setAutoFilter(boolean)}.
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* </p>
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*
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* @param source input image (2D)
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* @param seeds list of {@code long[]{x, y}} pixel coordinates
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* tracer.setAutoFilter(false);
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* List<Tree> trees = tracer.traceMultiSoma(somas);
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* }</pre>
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* </p>
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*
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* @param imp the source image (ImagePlus)
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* @param rois ROIs whose centroids serve as soma seeds
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* requiring the user to specify one.</li>
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* </ul>
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* For 2D images, {@code zSlice} is ignored.
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* </p>
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*
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* @param source input image (2D or 3D ImgPlus)
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* @param threshold intensity threshold. Use -1 for Otsu, NaN for mean.
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* clustering on the surviving somas, find the largest ratio gap in
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* merge heights, return the geometric mean of the gap boundaries</li>
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* </ol>
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* </p>
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* <p>
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* <b>Experimental:</b> The quality of the estimate depends heavily on
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* step 1 (thickness filtering), which has known limitations for images
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* with large connected foreground regions, see
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* {@link #filterSomasByThickness} javadoc. The gap analysis in step 2 is
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* well-founded (standard hierarchical clustering), but is only as good as
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* the input somas it receives.
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* </p>
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*
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* @param <T> pixel type
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* @param somas list of detected somas (at least 3 required)

‎src/main/java/sc/fiji/snt/util/ImgUtils.java‎

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@@ -1724,7 +1724,6 @@ public static boolean haveSameSpatialDimensions(final ImagePlus imp,
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* {@code maxClasses}.</li>
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* </ul>
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* The scan terminates early if either condition is violated.
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* </p>
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*
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* @param img the image to check
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* @param maxClasses maximum number of distinct non-zero labels allowed

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