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3D rendering engine. Plus modeling. Expected glsl textures 3d and 2d rendering
/*
* Copyright (c) 2023. Manuel Daniel Dahmen
*
*
* Copyright 2012-2023 Manuel Daniel Dahmen
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package one.empty3.feature;// Java program to perform a 2D FFT Inplace Given a Complex
// 2D Array
// Declare the needed libraries
import one.empty3.feature.app.replace.javax.imageio.ImageIO;
import one.empty3.io.ProcessFile;
import one.empty3.library.*;
import one.empty3.library.core.math.Matrix;
import one.empty3.library.core.nurbs.Fct1D_1D;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
public class GFG extends ProcessFile {
Fct1D_1D fct1D1D;
// Now by taking the discrete function
// This is the declaration of the function
// This function includes 4 parameters
// The parameters are the 4 matrices.
static void discrete(double[][] input,
double[][] realOut,
double[][] imagOut) {
// Height is the variable of data type int
// the length of the input variable is stored in
// variable height
int height = input.length;
// The input of the first index length is stored in
// variable width
int width = input[0].length;
// Iterating the input till height stored in
// variable y
for (int y = 0; y < height; y++) {
// Taking the input iterating till width in
// variable x
for (int x = 0; x < width; x++) {
// Taking another variable y1 which will be
// the continuation of
// the variable y
// This y1 will be iterating till height
// This index of the variable starts at 0
for (int y1 = 0; y1 < height; y1++) {
// This index x1 iterates till width
// This x1 is continuation of x
// The variables y1 and x1 are the
// continuation of summable of x and y
for (int x1 = 0; x1 < width; x1++) {
// realOut is the variable which
// lets us know the real output as
// we do the summation of exponential
// signal
// we get cos as real term and sin
// as imaginary term
// so taking the consideration of
// above properties we write the
// formula of real as
// summing till x and y and
// multiplying it with cos2pie
// and then dividing it with width
// *height gives us the real term
realOut[y][x]
+= (input[y1][x1]
* Math.cos(
2 * Math.PI
* ((1.0 * x * x1
/ width)
+ (1.0 * y * y1
/ height))))
/ Math.sqrt(width * height);
// Now imagOut is the imaginary term
// That is the sine term
// This sine term can be obtained
// using sin2pie and then we divide
// it using width*height The
// formulae is same as real
imagOut[y][x]
-= (input[y1][x1]
* Math.sin(
2 * Math.PI
* ((1.0 * x * x1
/ width)
+ (1.0 * y * y1
/ height))))
/ Math.sqrt(width * height);
}
// Now we will print the value of
// realOut and imaginary outputn The
// ppoutput of imaginary output will end
// with value 'i'.
//System.out.println(realOut[y][x] + " +" + imagOut[y][x] + "i");
}
}
}
}
/**
* "Calculate the Fourier series coefficients up to the Nth harmonic"
*
* @param N
* @return
*/
public double[][] fourierSeries(double [] Ft, double[] period, int N) {
double[][] result = new double[N][2];
int T = period.length;
double[] t = new double[T];
for (int i = 0; i < T; i++)
t[i] = i;
for (int n = 0; n < N; n++) {
double an = 0, bn = 0;
for (int tt = 0; tt < T; tt++) {
double v = 2. * Math.PI * n * Ft[tt] / T;
an += 2.0 / T * (period[tt] * Math.cos(v));
bn += 2.0 / T * (period[tt] * Math.sin(v));
}
result[n][0] = an;
result[n][1] = bn;
}
return result;
}
public double reconstruct(double T, double t, double[][] anbn, int N) {
double result = 0.0;
double a = 0, b;
for (int n = 0; n < N; n++) {
a = anbn[n][0];
b = anbn[n][1];
if (n == 0) {
a = a / 2;
}
double f = 2 * Math.PI * n * t / T;
result = result + a * Math.cos(f) + b * Math.sin(f);
}
return result;
}
@Override
public boolean process(File in, File out) {
BufferedImage read = ImageIO.read(in);
if (read == null)
return false;
PixM pix = new PixM(read);
PixM pixOut = new PixM(pix.columns, pix.lines);
pixOut = pix;
int sizeT = Math.max(pix.getColumns(), pix.getLines());
int n = 30;
final double[] points = new double[sizeT];
final double[] t_period = new double[sizeT];
for (int x = 0; x < pix.getColumns(); x++) {
for (int y = 0; y < pix.getLines(); y++) {
if (pix.luminance(x, y) >= 0.2) {
t_period[x] = x;
points[x] = y;
}
}
}
double[] F = new double[sizeT];
System.arraycopy(points, 0, F, 0, t_period.length);
double[] F2 = new double[sizeT];
System.arraycopy(points, 0, F2, 0, t_period.length);
double[][] anbn = fourierSeries(t_period, F, n);
for (int i = 0; i < t_period.length; i++) {
double reconstruct = reconstruct(t_period[i], F[i], anbn, n);
F2[i] = reconstruct;
}
double F2min = Double.POSITIVE_INFINITY;
double F2max = Double.NEGATIVE_INFINITY;
for (int i = 0; i < sizeT; i++) {
if (F2[i] < F2min)
F2min = F2[i];
if (F2[i] > F2max)
F2max = F2[i];
}
for (int i = 0; i < sizeT; i++) {
F2[i] = (F2[i] - F2min) / (F2max - F2min) * pixOut.getLines();
//pixOut.setValues(i, (int) (F2[i]), 0, 0, 1);
}
ITexture blue = new ColorTexture(Color.BLUE);
for (int i = 0; i < sizeT-1; i++) {
pixOut.plotCurve(new LineSegment(new Point3D((double)i,
(double)(int) (F2[i]), 0d),
new Point3D((double)i, (double)(int) (F2[i+1]), 0d)), blue);
}
try {
ImageIO.write(pixOut.normalize(0, 1).getImage(), "jpg", out);
return true;
} catch (IOException e) {
throw new RuntimeException(e);
}
}
public boolean process2(File in, File out) {
PixM inPix = PixM.getPixM(ImageIO.read(in), maxRes);
int n = Math.max(inPix.getColumns(), inPix.getLines());
double[][] inPix2 = new double[n][n];
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++) {
inPix2[i][j] = inPix.luminance(i, j);
}
// Declaring the matrices in double datatype
// Declaring the input variable where we take in the
// input
double[][] input = new double[n][n];
input = inPix2;
// Taking the matrices for real value
double[][] realOut = new double[n][n];
// Taking the matrices for imaginary output
double[][] imagOut = new double[n][n];
// Calling the function discrete
discrete(input, realOut, imagOut);
Matrix pixM1 = new Matrix(n, n, 1);
Matrix pixM2 = new Matrix(n, n, 1);
pixM1.forEach((row, col, index, value) -> pixM1.set(row, col, realOut[row][col]));
pixM2.forEach((row, col, index, value) -> pixM2.set(row, col, imagOut[row][col]));
Matrix multiply = pixM1.multiply(pixM2);
try {
ImageIO.write(multiply.normalize(0, 1).getImage(), "jpg", out);
return true;
} catch (IOException e) {
throw new RuntimeException(e);
}
}
}