Convert SACA QNorm helper class into an Op

elevans · elevans · commit 770d565e1428 · 2024-05-02T11:10:13.000-05:00
This commit converts the QNorm.java helper class
for SACA into an Op. This commit also includes a test
for this new Op.
diff --git a/scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/SACASigMask.java b/scijava-ops-image/src/main/java/org/scijava/ops/image/coloc/saca/SACASigMask.java
@@ -35,6 +35,7 @@
 import net.imglib2.util.Intervals;
 
 import org.scijava.function.Computers;
+import org.scijava.function.Functions;
 import org.scijava.ops.spi.Nullable;
 import org.scijava.ops.spi.OpDependency;
 
@@ -53,6 +54,9 @@ public class SACASigMask implements
 	@OpDependency(name = "threshold.apply")
 	private Computers.Arity2<RandomAccessibleInterval<DoubleType>, DoubleType, RandomAccessibleInterval<BitType>> thresOp;
 
+	@OpDependency(name = "stats.qnorm")
+	private Functions.Arity5<Double, Double, Double, Boolean, Boolean, Double> qnormOp;
+
 	/**
 	 * Spatially Adaptive Colocalization Analysis (SACA) significant pixel mask.
 	 * This Op returns a binary mask of the significantly colocalized pixels from
@@ -85,7 +89,7 @@ public void compute(final RandomAccessibleInterval<DoubleType> heatmap,
 		if (logP == null) logP = false;
 
 		// compute QNorm
-		double thres = QNorm.compute(alpha / Intervals.numElements(heatmap), mean,
+		double thres = qnormOp.apply(alpha / Intervals.numElements(heatmap), mean,
 			sd, lowerTail, logP);
 
 		// apply QNorm thres and create significant pixel mask
diff --git a/scijava-ops-image/src/main/java/org/scijava/ops/image/stats/DefaultQNorm.java b/scijava-ops-image/src/main/java/org/scijava/ops/image/stats/DefaultQNorm.java
@@ -27,41 +27,65 @@
  * #L%
  */
 
-package org.scijava.ops.image.coloc.saca;
+package org.scijava.ops.image.stats;
+
+import org.scijava.function.Computers;
+import org.scijava.function.Functions;
+import org.scijava.ops.spi.Nullable;
 
 import org.apache.commons.math3.distribution.NormalDistribution;
 
 /**
- * Helper class for Spatially Adaptive Colocalization Analysis (SACA) framework.
- * This class is used by the "coloc.saca.sigMask" Op to produce a binary mask of
- * significantly colocalized pixels. This class replicates R's qnorm function.
- *
  * @author Shulei Wang
  * @author Ellen TA Dobson
  * @author Curtis Rueden
+ * @author Edward Evans
+ * @implNote op names='stats.qnorm', priority='100.'
  */
 
-public final class QNorm {
+public final class DefaultQNorm implements
+	Functions.Arity5<Double, Double, Double, Boolean, Boolean, Double>
+{
+
+	/**
+	 * Op to calculate the quantile function for a normal distribution.
+	 *
+	 * @param p
+	 * @param mean
+	 * @param sd
+	 * @param lowerTail
+	 * @param logP
+	 * @return quantiles for input probaility
+	 */
+	@Override
+	public Double apply(Double p, @Nullable Double mean, @Nullable Double sd,
+		@Nullable Boolean lowerTail, @Nullable Boolean logP)
+	{
+		// set mean if necessary
+		if (mean == null) mean = 0.0;
+
+		// set sd if necessary
+		if (sd == null) sd = 1.0;
 
-	private QNorm() {}
+		// set lowerTail if necessary
+		if (lowerTail == null) lowerTail = true;
 
-	public static double compute(final double p) {
+		// set logP if necessary
+		if (logP == null) logP = false;
+
+		// check the bounds of p
 		if (p < 0 || p > 1) {
 			return Double.NaN;
 		}
 		if (p == 0 || p == 1) {
 			return Double.POSITIVE_INFINITY;
 		}
 
-		return compute(p, 0, 1, true, false);
-	}
-
-	public static double compute(double p, final double mean, final double sd,
-		final boolean lowerTail, final boolean logP)
-	{
+		// compute QNorm
 		final NormalDistribution dist = new NormalDistribution(mean, sd);
 		if (logP) p = Math.exp(p);
 		final double q = dist.inverseCumulativeProbability(p);
 		return lowerTail ? q : -q;
+
 	}
 }
diff --git a/scijava-ops-image/src/test/java/org/scijava/ops/image/OpRegressionTest.java b/scijava-ops-image/src/test/java/org/scijava/ops/image/OpRegressionTest.java
@@ -42,7 +42,7 @@ public class OpRegressionTest {
 
 	@Test
 	public void opDiscoveryRegressionIT() {
-		long expected = 1937;
+		long expected = 1942;
 		long actual = ops.infos().size();
 		assertEquals(expected, actual);
 	}
diff --git a/scijava-ops-image/src/test/java/org/scijava/ops/image/stats/DefaultQNormTest.java b/scijava-ops-image/src/test/java/org/scijava/ops/image/stats/DefaultQNormTest.java
@@ -0,0 +1,57 @@
+/*-
+ * #%L
+ * Image processing operations for SciJava Ops.
+ * %%
+ * Copyright (C) 2014 - 2024 SciJava developers.
+ * %%
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are met:
+ *
+ * 1. Redistributions of source code must retain the above copyright notice,
+ *    this list of conditions and the following disclaimer.
+ * 2. Redistributions in binary form must reproduce the above copyright notice,
+ *    this list of conditions and the following disclaimer in the documentation
+ *    and/or other materials provided with the distribution.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+ * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
+ * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+ * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+ * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+ * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+ * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+ * POSSIBILITY OF SUCH DAMAGE.
+ * #L%
+ */
+
+package org.scijava.ops.image.stats;
+
+import org.scijava.ops.image.AbstractOpTest;
+
+import org.junit.jupiter.api.Test;
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+/**
+ * Test {@code stats.qnorm} op.
+ *
+ * @author Edward Evans
+ */
+
+public class DefaultQNormTest extends AbstractOpTest {
+
+	@Test
+	public void testCalculation() {
+		final double[] input = { 0.05, 0.001, 1e-7, 1, 0, 0.99, -0.99, 1.1 };
+		final double[] expected = { -1.644853626951473, -3.0902323061678136,
+			-5.199337582187473, Double.POSITIVE_INFINITY, Double.POSITIVE_INFINITY,
+			2.326347874040841, Double.NaN, Double.NaN };
+
+		// assert calculations are equal
+		for (int i = 0; i < input.length; i++) {
+			assertEquals(expected[i], ops.op("stats.qnorm").input(input[i]).apply());
+		}
+	}
+}

Original file line number	Diff line number	Diff line change
`@@ -42,7 +42,7 @@ public class OpRegressionTest {`
`42`	`42`
`43`	`43`	`@Test`
`44`	`44`	`public void opDiscoveryRegressionIT() {`
`45`		`- long expected = 1937;`
	`45`	`+ long expected = 1942;`
`46`	`46`	`long actual = ops.infos().size();`
`47`	`47`	`assertEquals(expected, actual);`
`48`	`48`	`}`