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 * ImageJ software for multidimensional image processing and analysis.
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package net.imagej.ops.arithmetic.real;

import static org.junit.Assert.assertEquals;
import net.imagej.ops.AbstractOpTest;
import net.imglib2.type.numeric.real.DoubleType;

import org.junit.Test;

/**
 * Tests {@link RealGaussianRandom}.
 *
 * @author Alison Walter
 * @author Curtis Rueden
 */
public class RealGaussianRandomTest extends AbstractOpTest {

	@Test
	public void testGaussianRandom() {
		assertGaussianRandom(23, 16.53373419964066);
		assertGaussianRandom(27, -15.542815799078497, 0xfeeddeadbeefbeefL);
		assertGaussianRandom(123, -49.838353142718006, 124, 181.75101003563117);
	}

	private void assertGaussianRandom(final double i, final double o) {
		final DoubleType in = new DoubleType(i);
		final DoubleType out = ops.math().gaussianrandom(in.createVariable(), in);
		assertEquals(o, out.get(), 0);
	}

	private void assertGaussianRandom(final double i, final double o,
		final long seed)
	{
		final DoubleType in = new DoubleType(i);
		final DoubleType out =
			ops.math().gaussianrandom(in.createVariable(), in, seed);
		assertEquals(o, out.get(), 0);
	}

	private void assertGaussianRandom(final double i, final double o,
		final double i2, final double o2)
	{
		final DoubleType in = new DoubleType(i);
		final DoubleType out = new DoubleType();
		final long seed = 0xcafebabe12345678L;
		@SuppressWarnings("unchecked")
		final RealGaussianRandom<DoubleType, DoubleType> op =
			ops.op(RealGaussianRandom.class, in.createVariable(), in, seed);
		op.compute(in, out);
		assertEquals(o, out.get(), 0);
		in.set(i2);
		op.compute(in, out);
		assertEquals(o2, out.get(), 0);
	}
}

Add test for RealGaussianRandom functionality