Add PValue op

This op is based on a new statistical framework published in Wang et al
(2017) IEEE Signal Processing "Automated and Robust Quantification of
Colocalization in Dual-Color Fluorescence Microscopy: A Nonparametric
Statistical Approach". This routine repeatedly executes a colocalization
algorithm (coloc op), computing a p-value.

src/main/java/net/imagej/ops/coloc/pValue/PValue.java

@@ -0,0 +1,64 @@
+
+package net.imagej.ops.coloc.pValue;
+
+import net.imagej.ops.Ops;
+import net.imagej.ops.coloc.BlockShuffle;
+import net.imagej.ops.special.function.AbstractBinaryFunctionOp;
+import net.imagej.ops.special.function.BinaryFunctionOp;
+import net.imglib2.img.Img;
+import net.imglib2.type.numeric.RealType;
+
+import org.scijava.plugin.Parameter;
+import org.scijava.plugin.Plugin;
+
+/**
+ * This algorithm repeatedly executes a colocalization algorithm, computing a
+ * p-value. It is based on a new statistical framework published by Wang et al
+ * (2017) IEEE Signal Processing "Automated and Robust Quantification of
+ * Colocalization in Dual-Color Fluorescence Microscopy: A Nonparametric
+ * Statistical Approach".
+ */
+@Plugin(type = Ops.Coloc.PValue.class)
+public class PValue<T extends RealType<T>, U extends RealType<U>> extends
+	AbstractBinaryFunctionOp<Img<T>, Iterable<U>, Double> implements
+	Ops.Coloc.PValue
+{
+
+	@Parameter
+	private BinaryFunctionOp<Iterable<T>, Iterable<U>, Double> op;
+
+	@Parameter(required = false)
+	private final int nrRandomizations = 1000;
+
+	@Parameter(required = false)
+	private final long seed = 0x27372034;
+
+	@Override
+	public Double calculate(final Img<T> image1, final Iterable<U> image2) {
+
+		final BlockShuffle<T> shuffler = new BlockShuffle<>(image1, seed);
+		final double[] sampleDistribution = new double[nrRandomizations];
+
+		final double value = op.calculate(image1, image2);
+
+		for (int i = 0; i < nrRandomizations; i++) {
+			final Img<T> shuffledImage = shuffler.shuffleBlocks(image1.factory());
+			sampleDistribution[i] = op.calculate(shuffledImage, image2);
+		}
+
+		return calculatePvalue(value, sampleDistribution);
+	}
+
+	private double calculatePvalue(final double input,
+		final double[] distribution)
+	{
+		double count = 0;
+		for (int i = 0; i < distribution.length; i++) {
+			if (distribution[i] > input) {
+				count++;
+			}
+		}
+		final double pvalue = count / distribution.length;
+		return pvalue;
+	}
+}

src/main/templates/net/imagej/ops/Ops.list

@@ -30,6 +30,7 @@ namespaces = ```
 		[name: "manders",                     iface: "Manders"],
 		[name: "pearsons",                    iface: "Pearsons"],
 		[name: "pearsonsClassic",             iface: "PearsonsClassic"],
+		[name: "pValue",                      iface: "PValue"],
 		[name: "threshold",     	      iface: "Threshold"],
 		[name: "spearman",                    iface: "Spearman"],
 	]],