All Downloads are FREE. Search and download functionalities are using the official Maven repository.

uk.ac.sussex.gdsc.smlm.function.gaussian.SingleNbCircularGaussian2DFunction Maven / Gradle / Ivy

Go to download

Genome Damage and Stability Centre SMLM Package Software for single molecule localisation microscopy (SMLM)

The newest version!
/*-
 * #%L
 * Genome Damage and Stability Centre SMLM Package
 *
 * Software for single molecule localisation microscopy (SMLM)
 * %%
 * Copyright (C) 2011 - 2023 Alex Herbert
 * %%
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as
 * published by the Free Software Foundation, either version 3 of the
 * License, or (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public
 * License along with this program.  If not, see
 * .
 * #L%
 */

package uk.ac.sussex.gdsc.smlm.function.gaussian;

import uk.ac.sussex.gdsc.smlm.utils.StdMath;

/**
 * Evaluates a 2-dimensional Gaussian function for a single peak.
 *
 * 

The single parameter x in the {@link #eval(int, double[])} function is assumed to be a linear * index into 2-dimensional data. The dimensions of the data must be specified to allow unpacking to * coordinates. * *

Data should be packed in descending dimension order, e.g. Y,X : Index for [x,y] = MaxX*y + x. */ public class SingleNbCircularGaussian2DFunction extends SingleCircularGaussian2DFunction { private static final int[] gradientIndices; static { gradientIndices = createGradientIndices(1, new SingleNbCircularGaussian2DFunction(1, 1)); } /** * Constructor. * * @param maxx The maximum x value of the 2-dimensional data (used to unpack a linear index into * coordinates) * @param maxy The maximum y value of the 2-dimensional data (used to unpack a linear index into * coordinates) */ public SingleNbCircularGaussian2DFunction(int maxx, int maxy) { super(maxx, maxy); } @Override public Gaussian2DFunction copy() { return new SingleNbCircularGaussian2DFunction(maxx, maxy); } /** * Evaluates a 2-dimensional circular Gaussian function for a single peak. * *

{@inheritDoc} */ @Override public double eval(final int x, final double[] dyda) { // Unpack the predictor into the dimensions final int x1 = x / maxx; final int x0 = x % maxx; return background + gaussian(x0, x1, dyda); } private double gaussian(final int x0, final int x1, final double[] dyDa) { final double dx = x0 - x0pos; final double dy = x1 - x1pos; // Calculate gradients final double aadx2dy2 = aa * (dx * dx + dy * dy); final double exp = StdMath.exp(aadx2dy2); dyDa[0] = norm * exp; final double y = height * exp; final double yaa2 = y * aa2; dyDa[1] = yaa2 * dx; dyDa[2] = yaa2 * dy; dyDa[3] = ax * y * (1 + aadx2dy2); return y; } @Override public boolean evaluatesBackground() { return false; } @Override public int[] gradientIndices() { return gradientIndices; } }





© 2015 - 2024 Weber Informatics LLC | Privacy Policy