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elevanselevans
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Clean up imports and improve SACA Op descriptions
1 parent dbd0628 commit 658fd2d

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-34
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‎scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/AdaptiveSmoothedKendallTau.java‎

Lines changed: 4 additions & 2 deletions
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@@ -2,7 +2,7 @@
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* #%L
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* ImageJ2 software for multidimensional image processing and analysis.
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* %%
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* Copyright (C) 2014 - 2023 ImageJ2 developers.
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* Copyright (C) 2014 - 2024 ImageJ2 developers.
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* %%
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
@@ -49,7 +49,9 @@
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import net.imglib2.type.numeric.real.DoubleType;
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/**
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* Helper class for Spatially Adaptive Colocalization Analysis (SACA) op.
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* Helper class for Spatially Adaptive Colocalization Analysis (SACA) framework.
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* This class is used by the "coloc.saca.heatmapZScore" Op to produce the Z-score
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* heatmap of pixel colocalization strength.
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*
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* @author Shulei Wang
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* @author Ellen TA Dobson

‎scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/PNorm.java‎

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@@ -36,7 +36,9 @@
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import org.apache.commons.math3.distribution.NormalDistribution;
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/**
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* Helper class for Spatially Adaptive Colocalization Analysis (SACA) op.
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* Helper class for Spatially Adaptive Colocalization Analysis (SACA) framework.
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* This class is used by the "coloc.saca.heatmapPValue" Op to produce a heatmap of
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* pixelwise p-values. This class replicates R's pnorm function.
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*
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* @author Edward Evans
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*/
@@ -51,7 +53,8 @@ public static void compute(RandomAccessibleInterval<DoubleType> input,
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// compute normal distribution over the image
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NormalDistribution normalDistribution = new NormalDistribution();
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54-
LoopBuilder.setImages(input, output).multiThreaded().forEachPixel((i, o) -> {
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LoopBuilder.setImages(input, output).multiThreaded().forEachPixel((i,
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o) -> {
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double normDistValue = normalDistribution.cumulativeProbability(i.get());
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if (!lowerTail) {
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normDistValue = 1 - normDistValue;

‎scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/QNorm.java‎

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@@ -32,7 +32,9 @@
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import org.apache.commons.math3.distribution.NormalDistribution;
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/**
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* Helper class for Spatially Adaptive Colocalization Analysis (SACA) op.
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* Helper class for Spatially Adaptive Colocalization Analysis (SACA) framework.
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* This class is used by the "coloc.saca.sigMask" Op to produce a binary mask of
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* significantly colocalized pixels. This class replicates R's qnorm function.
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*
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* @author Shulei Wang
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* @author Ellen TA Dobson

‎scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/SACAHeatmapPValue.java‎

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Original file line numberDiff line numberDiff line change
@@ -36,11 +36,6 @@
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import org.scijava.ops.spi.Nullable;
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/**
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* Spatially Adaptive Colocalization Analysis (SACA) Adapted from Shulei's
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* original Java code for AdaptiveSmoothedKendallTau from his RKColocal R
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* package.
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* (https://github.com/lakerwsl/RKColocal/blob/master/RKColocal_0.0.1.0000.tar.gz)
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*
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* @author Shulei Wang
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* @author Curtis Rueden
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* @author Ellen TA Dobson
@@ -53,21 +48,25 @@ public class SACAHeatmapPValue implements
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{
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/**
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* Spatially Adaptive Colocalization Analysis (SACA) P Value heatmap
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* Spatially Adaptive Colocalization Analysis (SACA) p-value heatmap. This Op
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* returns the pixelwise p-value of the input Z-score heatmap produced by the
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* SACA framework. SACA was adapted from Shulei's java code for
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* AdaptiveSmoothedKendallTau in his RKColocal package
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* (https://github.com/lakerwsl/RKColocal/blob/master/RKColocal_0.0.1.0000.tar.gz).
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*
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* @param heatmap input heatmap returned from 'coloc.saca.heatmapZScore'
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* @param heatmap input Z-score heatmap returned from 'coloc.saca.heatmapZScore'
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* @param lowerTail lower tail (default=false)
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* @param result P value heatmap output
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* @param result p value heatmap output
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*/
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@Override
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public void compute(final RandomAccessibleInterval<DoubleType> heatmap,
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@Nullable Boolean lowerTail, RandomAccessibleInterval<DoubleType> result)
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{
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// set lowerTail if necessary
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if (lowerTail == null) lowerTail = true;
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// set lowerTail if necessary
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if (lowerTail == null) lowerTail = true;
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// compute the normal distribution
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// compute the normal distribution
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PNorm.compute(heatmap, lowerTail, result);
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}
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}

‎scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/SACAHeatmapZScore.java‎

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Original file line numberDiff line numberDiff line change
@@ -44,11 +44,6 @@
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import org.scijava.ops.spi.OpDependency;
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/**
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* Spatially Adaptive Colocalization Analysis (SACA) Adapted from Shulei's
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* original Java code for AdaptiveSmoothedKendallTau from his RKColocal R
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* package.
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* (https://github.com/lakerwsl/RKColocal/blob/master/RKColocal_0.0.1.0000.tar.gz)
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*
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* @author Shulei Wang
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* @author Curtis Rueden
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* @author Ellen TA Dobson
@@ -68,14 +63,20 @@ public class SACAHeatmapZScore<I extends RealType<I>> implements
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private Function<Histogram1d<I>, I> otsuOp;
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/**
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* Spatially Adaptive Colocalization Analysis (SACA)
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* Spatially Adaptive Colocalization Analysis (SACA) Z-score heatmap. This Op
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* utilizes the SACA framework to identify colocalized pixels and their
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* strength as a Z-score heatmap. The Z-score heatmap is a produced by
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* Shulei's adaptive smoothed kendall tau algorithim. SACA was adapted from
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* Shulei's java code for AdaptiveSmoothedKendallTau in his RKColocal package
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* (https://github.com/lakerwsl/RKColocal/blob/master/RKColocal_0.0.1.0000.tar.gz).
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*
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* @param image1 input image 1
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* @param image2 input image 2
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* @param thres1 threshold 1 value; otsu threshold applied if null
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* @param thres2 threshold 2 value; otsu threshold applied if null
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* @param seed seed to use; default 0xdeadbeefL
78-
* @param result result image
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* @param seed seed value to use; default 0xdeadbeefL
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* @param result Adaptive smoothed kendall tau Z-score heatmap (i.e.
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* colocalization strength)
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*/
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@Override

‎scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/SACASigMask.java‎

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Original file line numberDiff line numberDiff line change
@@ -29,23 +29,16 @@
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package org.scijava.ops.image.coloc.saca;
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import net.imglib2.img.Img;
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import net.imglib2.RandomAccessibleInterval;
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import net.imglib2.type.numeric.real.DoubleType;
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import net.imglib2.type.logic.BitType;
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import net.imglib2.util.Intervals;
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import net.imglib2.util.Util;
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import org.scijava.function.Computers;
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import org.scijava.ops.spi.Nullable;
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import org.scijava.ops.spi.OpDependency;
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/**
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* Spatially Adaptive Colocalization Analysis (SACA) Adapted from Shulei's
45-
* original Java code for AdaptiveSmoothedKendallTau from his RKColocal R
46-
* package.
47-
* (https://github.com/lakerwsl/RKColocal/blob/master/RKColocal_0.0.1.0000.tar.gz)
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*
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* @author Shulei Wang
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* @author Curtis Rueden
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* @author Ellen TA Dobson
@@ -61,9 +54,14 @@ public class SACASigMask implements
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private Computers.Arity2<RandomAccessibleInterval<DoubleType>, DoubleType, RandomAccessibleInterval<BitType>> thresOp;
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/**
64-
* Spatially Adaptive Colocalization Analysis (SACA) Significant pixel mask.
57+
* Spatially Adaptive Colocalization Analysis (SACA) significant pixel mask.
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* This Op returns a binary mask of the significantly colocalized pixels from
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* the input Z-score heatmap produced by the SACA framework. SACA was adapted
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* from Shulei's java code for AdaptiveSmoothedKendallTau in his RKColocal
61+
* package
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* (https://github.com/lakerwsl/RKColocal/blob/master/RKColocal_0.0.1.0000.tar.gz).
6563
*
66-
* @param heatmap input heatmap returned from 'coloc.saca.heatmapZScore'
64+
* @param heatmap input Z-score heatmap returned from 'coloc.saca.heatmapZScore'
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* @param alpha significance cuttoff, type 1 error (default=0.05)
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* @param mean mean value (default=0)
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* @param sd standard div (default=1)

‎scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/WtKendallTau.java‎

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@@ -37,7 +37,8 @@
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import org.scijava.ops.image.coloc.IntComparator;
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/**
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* Helper class for Spatially Adaptive Colocalization Analysis (SACA) op.
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* Helper class for Spatially Adaptive Colocalization Analysis (SACA) framework.
41+
* This class is used by the AdaptiveSmoothedKendallTau class.
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*
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* @author Shulei Wang
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* @author Ellen TA Dobson

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