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elevanselevans
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Convert SACA PNorm helper class into an Op
This commit converts the PNorm.java helper class into an Op in the `stats` namespace. This commit also adds a test for this new Op.
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‎scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/SACAHeatmapPValue.java‎

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This file was deleted.

scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/PNorm.java renamed to scijava-ops-image/src/main/java/org/scijava/ops/image/stats/DefaultPNorm.java

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* #L%
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*/
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package org.scijava.ops.image.coloc.saca;
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package org.scijava.ops.image.stats;
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import org.apache.commons.math3.distribution.NormalDistribution;
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import net.imglib2.loops.LoopBuilder;
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import net.imglib2.RandomAccessibleInterval;
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import net.imglib2.type.numeric.real.DoubleType;
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import org.apache.commons.math3.distribution.NormalDistribution;
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import org.scijava.function.Computers;
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import org.scijava.ops.spi.Nullable;
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/**
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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
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* of 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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* @implNote op names='stats.pnorm', priority='100.'
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*/
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public final class PNorm {
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private PNorm() {}
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public final class DefaultPNorm implements
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Computers.Arity2<RandomAccessibleInterval<DoubleType>, Boolean, RandomAccessibleInterval<DoubleType>>
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{
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public static void compute(RandomAccessibleInterval<DoubleType> input,
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boolean lowerTail, RandomAccessibleInterval<DoubleType> output)
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/**
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* Op to calculate the pixel-wise cumulative probability of a normal
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* distribution over an image.
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*
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* @param input input image
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* @param lowerTail indicates whether to compute the lower tail cumulative
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* probability
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* @param result the pixel-wise normal distribution over the image
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*/
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@Override
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public void compute(final RandomAccessibleInterval<DoubleType> input,
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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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final boolean finalLowerTail = lowerTail;
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// compute normal distribution over the image
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NormalDistribution normalDistribution = new NormalDistribution();
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LoopBuilder.setImages(input, output).multiThreaded().forEachPixel((i,
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o) -> {
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LoopBuilder.setImages(input, result).multiThreaded().forEachPixel((i,
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r) -> {
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double normDistValue = normalDistribution.cumulativeProbability(i.get());
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if (!lowerTail) {
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if (!finalLowerTail) {
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normDistValue = 1 - normDistValue;
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}
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o.set(normDistValue);
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r.set(normDistValue);
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});
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}
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}

‎scijava-ops-image/src/test/java/org/scijava/ops/image/coloc/saca/SACATest.java‎

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@@ -81,8 +81,8 @@ public void testSACAFramework() {
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// run SACA heatmap Z score op
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ops.op("coloc.saca.heatmapZScore").input(gs, rs).output(zscore).compute();
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// run SACA heatmap p value op
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ops.op("coloc.saca.heatmapPValue").input(zscore).output(pvalue).compute();
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// run stats.pnorm op
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ops.op("stats.pnorm").input(zscore).output(pvalue).compute();
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// run SACA significant pixel mask op
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ops.op("coloc.saca.sigMask").input(zscore).output(sigMask).compute();

‎scijava-ops-image/src/test/java/org/scijava/ops/image/stats/DefaultPNormTest.java‎

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/*-
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* #%L
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* Image processing operations for SciJava Ops.
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* %%
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* Copyright (C) 2014 - 2024 SciJava 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:
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*
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* 1. Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
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* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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* #L%
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*/
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package org.scijava.ops.image.stats;
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import net.imglib2.RandomAccess;
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import net.imglib2.img.Img;
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import net.imglib2.type.numeric.real.DoubleType;
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import net.imglib2.type.numeric.real.FloatType;
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import org.scijava.ops.image.AbstractOpTest;
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import org.scijava.types.Nil;
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import org.junit.jupiter.api.Test;
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import static org.junit.jupiter.api.Assertions.assertEquals;
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/**
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* Test {@code stats.pnorm} op.
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*
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* @author Edward Evans
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*/
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public class DefaultPNormTest extends AbstractOpTest {
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@Test
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public void testImg() {
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final int[] xPositions = { 30, 79, 77, 104, 7, 52, 164, 88, 119, 65 };
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final int[] yPositions = { 30, 36, 80, 79, 139, 102, 77, 41, 142, 118 };
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final double[] pvalueExpected = { 0.5, 0.9999998132675161, 0.5,
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0.8861427670894226, 0.5, 0.9999999999828452, 0.5, 0.9960363221624154, 0.5,
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0.999998128463855 };
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// load Z-score heatmap slice
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Img<FloatType> zscore = openFloatImg("zscore_test_data.tif");
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// create p-value image container
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Img<DoubleType> pvalue = ops.op("create.img").input(zscore,
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new DoubleType()).outType(new Nil<Img<DoubleType>>()
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{}).apply();
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// run stats.pnorm op on Z-score data
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ops.op("stats.pnorm").input(zscore).output(pvalue).compute();
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// get random access and compare pixels
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final RandomAccess<DoubleType> pRA = pvalue.randomAccess();
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// assert results are equal
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for (int i = 0; i < xPositions.length; i++) {
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pRA.setPosition(xPositions[i], 0);
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pRA.setPosition(yPositions[i], 1);
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assertEquals(pvalueExpected[i], pRA.get().getRealDouble());
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}
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}
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}

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