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/*
* Copyright (c) 2005-2019 Radiance Kirill Grouchnikov. All Rights Reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* o Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* o 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.
*
* o Neither the name of the copyright holder nor the names of
* its contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* 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 OWNER 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.
*/
package org.pushingpixels.substance.internal.utils;
import org.pushingpixels.neon.NeonCortex;
import org.pushingpixels.substance.api.SubstanceSkin;
import org.pushingpixels.substance.api.colorscheme.SubstanceColorScheme;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.awt.image.ConvolveOp;
import java.awt.image.DataBufferInt;
import java.awt.image.Kernel;
/**
* Factory for creating noise images. This class is part of officially supported
* API.
*
* @author Kirill Grouchnikov.
*/
public class NoiseFactory {
/**
* Returns a noise image.
*
* @param skin
* The skin to use for rendering the image.
* @param width
* Image width.
* @param height
* Image height.
* @param xFactor
* X stretch factor.
* @param yFactor
* Y stretch factor.
* @param hasConstantZ
* Indication whether the Z is constant.
* @param toBlur
* Indication whether the resulting image should be blurred.
* @param isPreview
* Indication whether the image is in preview mode.
* @return Noise image.
*/
public static BufferedImage getNoiseImage(SubstanceSkin skin, int width,
int height, double xFactor, double yFactor, boolean hasConstantZ,
boolean toBlur, boolean isPreview) {
SubstanceColorScheme scheme = skin.getWatermarkColorScheme();
Color c1 = scheme.getWatermarkDarkColor();
// c1 = new Color(255, 0, 0, 0);
// System.out.println(c1.getAlpha());
// Color c2 = scheme.getWatermarkStampColor();
Color c3 = scheme.getWatermarkLightColor();
// Note that we are starting with non-hi DPI aware image for creating the
// source for the noise
BufferedImage dst = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
// Borrow from Sebastien Petrucci fast blur code - direct access
// to the raster data
int[] dstBuffer = ((DataBufferInt) dst.getRaster().getDataBuffer())
.getData();
// System.out.println((dstBuffer[0] >>> 24) & 0xFF);
double m2 = xFactor * width * xFactor * width + yFactor * height
* yFactor * height;
int pos = 0;
for (int j = 0; j < height; j++) {
double jj = yFactor * j;
for (int i = 0; i < width; i++) {
double ii = xFactor * i;
double z = hasConstantZ ? 1.0 : Math.sqrt(m2 - ii * ii - jj * jj);
double noise = 0.5 + 0.5 * PerlinNoiseGenerator.noise(ii, jj, z);
double likeness = Math.max(0.0, Math.min(1.0, 2.0 * noise));
// likeness = 0.0;
dstBuffer[pos++] = SubstanceColorUtilities.getInterpolatedRGB(
c3, c1, likeness);
}
}
// System.out.println((dstBuffer[0] >>> 24) & 0xFF);
if (toBlur) {
// and staying here with non-hi DPI aware image for blurred noise
ConvolveOp convolve = new ConvolveOp(new Kernel(3, 3, new float[] {
.08f, .08f, .08f, .08f, .38f, .08f, .08f, .08f, .08f }),
ConvolveOp.EDGE_NO_OP, null);
dst = convolve.filter(dst, null);
}
// and now returning an image that is hi DPI aware if needed
if (NeonCortex.getScaleFactor() > 1.0) {
BufferedImage result = SubstanceCoreUtilities.getBlankImage(width, height);
Graphics2D g2d = result.createGraphics();
g2d.drawImage(dst, 0, 0, null);
g2d.dispose();
return result;
} else {
return dst;
}
}
}
