
org.scijava.ops.image.coloc.saca.SACASigMask Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of scijava-ops-image Show documentation
Show all versions of scijava-ops-image Show documentation
Image processing operations for SciJava Ops.
The newest version!
/*-
* #%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.coloc.saca;
import net.imglib2.RandomAccessibleInterval;
import net.imglib2.type.numeric.real.DoubleType;
import net.imglib2.type.logic.BitType;
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;
/**
* @author Shulei Wang
* @author Curtis Rueden
* @author Ellen TA Dobson
* @author Edward Evans
* @implNote op names='coloc.saca.sigMask', priority='100.'
*/
public class SACASigMask implements
Computers.Arity6, Double, Double, Double, Boolean, Boolean, RandomAccessibleInterval>
{
@OpDependency(name = "threshold.apply")
private Computers.Arity2, DoubleType, RandomAccessibleInterval> thresOp;
@OpDependency(name = "stats.qnorm")
private Functions.Arity5 qnormOp;
/**
* Spatially Adaptive Colocalization Analysis (SACA) significant pixel mask.
* This Op returns a binary mask of the significantly colocalized pixels from
* the input Z-score heatmap produced by the SACA framework. SACA was adapted
* from Shulei's java code for AdaptiveSmoothedKendallTau in his RKColocal
* package
* (https://github.com/lakerwsl/RKColocal/blob/master/RKColocal_0.0.1.0000.tar.gz).
*
* @param heatmap input Z-score heatmap returned from
* 'coloc.saca.heatmapZScore'
* @param alpha significance cuttoff, type 1 error (default=0.05)
* @param mean mean value (default=0)
* @param sd standard div (default=1)
* @param lowerTail lower tail (default=false)
* @param logP log P (default=false)
* @param result BitType significant pixel mask
*/
@Override
public void compute(final RandomAccessibleInterval heatmap,
@Nullable Double alpha, @Nullable Double mean, @Nullable Double sd,
@Nullable Boolean lowerTail, @Nullable Boolean logP,
RandomAccessibleInterval result)
{
// set alpha, mean, sd, lowerTail and logP if null
if (alpha == null) alpha = 0.05;
if (mean == null) mean = 0.0;
if (sd == null) sd = 1.0;
if (lowerTail == null) lowerTail = false;
if (logP == null) logP = false;
// compute QNorm
double thres = qnormOp.apply(alpha / Intervals.numElements(heatmap), mean,
sd, lowerTail, logP);
// apply QNorm thres and create significant pixel mask
thresOp.compute(heatmap, new DoubleType(thres), result);
}
}
© 2015 - 2025 Weber Informatics LLC | Privacy Policy