[ImageJ-devel] Help with Java Code?

[Mark Hiner]

For the archives, this is answered here:
http://imagej.net/pipermail/imagej-devel/2015-January/002439.html

On Wed, Jan 28, 2015 at 7:36 PM, Francis OBrien <francisobrien2007 at gmail.com
> wrote:

> Hello,
>
> How do I run the following code in ImageJ?
>
> /*
>  * #%L
>  * ImageJ software for multidimensional image processing and analysis.
>  * %%
>  * Copyright (C) 2009 - 2015 Board of Regents of the University of
>  * Wisconsin-Madison, Broad Institute of MIT and Harvard, and Max Planck
>  * Institute of Molecular Cell Biology and Genetics.
>  * %%
>  * 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 net.imagej.autoscale;
>
> import net.imglib2.IterableInterval;
> import net.imglib2.histogram.Histogram1d;
> import net.imglib2.histogram.Real1dBinMapper;
> import net.imglib2.type.numeric.RealType;
>
> import org.scijava.plugin.Parameter;
> import org.scijava.plugin.Plugin;
>
> /**
>  * Computes a confidence interval containing percentages of the an entire set of
>  * values in an {@link IterableInterval}.
>  *
>  * @author Barry DeZonia
>  */
> @Plugin(type = AutoscaleMethod.class, name = "Confidence Interval")
> public class ConfidenceIntervalAutoscaleMethod<T extends RealType<T>> extends
> 	AbstractAutoscaleMethod<T>
> {
>
> 	// -- instance variables --
>
> 	private double lowerTail, upperTail;
>
> 	@Parameter
> 	private AutoscaleService autoscaleService;
>
> 	// -- ConfidenceIntervalAutoscaleMethod methods --
>
> 	/**
> 	 * Construct a confidence interval that contains 95% of the data range.
> 	 */
> 	public ConfidenceIntervalAutoscaleMethod() {
> 		this(0.025, 0.025); // fit 95% of the data range
> 	}
>
> 	/**
> 	 * Construct a confidence interval with user specified percentages of the data
> 	 * range. Ranges are specified as fractions of 1. They must sum to less than
> 	 * 1.
> 	 *
> 	 * @param lowerTailProportion The proportion of the distribution to be treated
> 	 *          as lower tail values
> 	 * @param upperTailProportion The proportion of the distribution to be treated
> 	 *          as upper tail values
> 	 */
> 	public ConfidenceIntervalAutoscaleMethod(double lowerTailProportion,
> 		double upperTailProportion)
> 	{
> 		setTailProportions(lowerTailProportion, upperTailProportion);
> 	}
>
> 	/**
> 	 * Returns the fractional proportion of the distribution to count as in lower
> 	 * tail.
> 	 */
> 	public double getLowerTailProportion() {
> 		return lowerTail;
> 	}
>
> 	/**
> 	 * Returns the fractional proportion of the distribution to count as in upper
> 	 * tail.
> 	 */
> 	public double getUpperTailProportion() {
> 		return upperTail;
> 	}
>
> 	/**
> 	 * Sets the fractional proportions of the distribution.
> 	 *
> 	 * @param lower A fraction of 1 specifying the size of the lower tail
> 	 * @param upper A fraction of 1 specifying the size of the upper tail
> 	 */
> 	public void setTailProportions(double lower, double upper) {
> 		if (lower < 0 || lower > 1) {
> 			throw new IllegalArgumentException(
> 				"lower tail fraction must be between 0 and 1");
> 		}
> 		if (upper < 0 || upper > 1) {
> 			throw new IllegalArgumentException(
> 				"upper tail fraction must be between 0 and 1");
> 		}
> 		if (lower + upper >= 1) {
> 			throw new IllegalArgumentException("tails must not span whole data range");
> 		}
> 		lowerTail = lower;
> 		upperTail = upper;
> 	}
>
> 	// -- AutoscaleMethod methods --
>
> 	@Override
> 	public DataRange getRange(IterableInterval<T> interval) {
> 		// pass one through data
> 		DataRange range = autoscaleService.getDefaultIntervalRange(interval);
> 		// pass two through data
> 		Real1dBinMapper<T> mapper =
> 			new Real1dBinMapper<T>(range.getMin(), range.getMax(), 1000, false);
> 		Histogram1d<T> histogram = new Histogram1d<T>(mapper);
> 		histogram.countData(interval);
> 		// calc some sizes
> 		long totValues = histogram.distributionCount();
> 		long lowerSize = (long) Math.floor(lowerTail * totValues);
> 		long upperSize = (long) Math.floor(upperTail * totValues);
> 		// determine bin number containing > than lower tail size
> 		long soFar = 0;
> 		int bottom = 0;
> 		while (soFar < lowerSize) {
> 			soFar += histogram.frequency(bottom++);
> 		}
> 		while (histogram.frequency(bottom) == 0) {
> 			bottom++;
> 		}
> 		// determine bin number containing < upper tail size
> 		soFar = 0;
> 		int top = 999;
> 		while (soFar < upperSize) {
> 			soFar += histogram.frequency(top--);
> 		}
> 		while (histogram.frequency(top) == 0) {
> 			top--;
> 		}
> 		// determine approx boundaries
> 		T approxMin = interval.firstElement().createVariable();
> 		T approxMax = approxMin.createVariable();
> 		histogram.getLowerBound(bottom, approxMin);
> 		histogram.getUpperBound(top, approxMax);
> 		double min = approxMin.getRealDouble();
> 		double max = approxMax.getRealDouble();
> 		// return them
> 		return new DataRange(min, max);
> 	}
>
> }
>
>
>
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