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kernel.cu
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#include "nmmintrin.h"
#include "curand_kernel.h"
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <sstream>
#include <fstream>
#include <thread>
#include <mutex>
#include <random>
#include <iostream>
#include <SFML/Graphics.hpp>
#include <SFML/OpenGL.hpp>
#define NK_IMPLEMENTATION
#define NK_INCLUDE_DEFAULT_ALLOCATOR
#define NK_INCLUDE_DEFAULT_FONT
#include "nuklear.h"
using namespace std;
sf::Sprite screen;
sf::Texture tex;
std::mutex histogramMutex;
float boundedFunctionScale = 1;
std::random_device rd;
std::default_random_engine e(rd());
std::uniform_int_distribution<> d(0, 1);
float width_calculation(nk_handle handle, float height, const char *text, int len)
{
sf::Font *type = (sf::Font*)handle.ptr;
sf::Text temp;
temp.setFont(*type);
temp.setString(text);
temp.setCharacterSize(height);
float text_width = temp.findCharacterPos(len).x - temp.findCharacterPos(0).x;
//float text_width = temp.getLocalBounds().width;
return text_width;
}
void nuklearSfmlDrawRectFilled(const nk_command *cmd, sf::RenderWindow &window) {
nk_command_rect_filled *p = (nk_command_rect_filled *)cmd;
sf::RectangleShape rectangle;
rectangle.setFillColor(sf::Color(p->color.r, p->color.g, p->color.b, p->color.a));
rectangle.setSize(sf::Vector2f(p->w, p->h));
rectangle.setPosition(p->x, p->y);
window.draw(rectangle);
}
void nuklearSfmlDrawText(const nk_command *cmd, sf::RenderWindow &window) {
nk_command_text *p = (nk_command_text *)cmd;
sf::Font* font = (sf::Font*)p->font->userdata.ptr;
sf::Text text;
text.setFont(*font);
text.setString(p->string);
text.setCharacterSize(p->height);
text.setFillColor(sf::Color(p->foreground.r, p->foreground.g, p->foreground.b, p->foreground.a));
text.setPosition(sf::Vector2f(p->x, p->y));
window.draw(text);
}
void nuklearSfmlDrawScissor(const nk_command *cmd, sf::RenderWindow &window) {
nk_command_scissor *p = (nk_command_scissor *)cmd;
glEnable(GL_SCISSOR_TEST);
glScissor(
(GLint)(p->x),
(GLint)((window.getSize().y - (GLint)(p->y + p->h))),//bottom left corner
(GLint)(p->w),
(GLint)(p->h));
}
void nuklearSfmlDrawRectOutline(const nk_command *cmd, sf::RenderWindow &window) {
nk_command_rect *p = (nk_command_rect *)cmd;
sf::RectangleShape rect;
rect.setSize(sf::Vector2f(p->w, p->h));
rect.setPosition(sf::Vector2f(p->x, p->y));
rect.setOutlineThickness(p->line_thickness);
rect.setFillColor(sf::Color(0, 0, 0, 0));
rect.setOutlineColor(sf::Color(p->color.r, p->color.g, p->color.b, p->color.a));
window.draw(rect);
}
void nuklearSfmlDrawCircleFilled(const nk_command *cmd, sf::RenderWindow &window) {
nk_command_circle_filled *p = (nk_command_circle_filled *)cmd;
sf::CircleShape circle;
circle.setRadius(p->h / 2);
circle.setPosition(sf::Vector2f(p->x, p->y));
circle.setFillColor(sf::Color(p->color.r, p->color.g, p->color.b, p->color.a));
window.draw(circle);
}
void nuklearSfmlDrawTriangleFilled(const nk_command *cmd, sf::RenderWindow &window) {
nk_command_triangle_filled *p = (nk_command_triangle_filled *)cmd;
sf::ConvexShape convex;
convex.setPointCount(3);
convex.setPoint(0, sf::Vector2f(p->a.x, p->a.y));
convex.setPoint(1, sf::Vector2f(p->b.x, p->b.y));
convex.setPoint(2, sf::Vector2f(p->c.x, p->c.y));
convex.setFillColor(sf::Color(p->color.r, p->color.g, p->color.b, p->color.a));
window.draw(convex);
}
void eventsToGui(sf::Event *evt, nk_context* ctx) {
if (evt->type == sf::Event::MouseButtonPressed || evt->type == sf::Event::MouseButtonReleased) {
int down = evt->type == sf::Event::MouseButtonPressed;
const int x = evt->mouseButton.x, y = evt->mouseButton.y;
if (evt->mouseButton.button == sf::Mouse::Left)
nk_input_button(ctx, NK_BUTTON_LEFT, x, y, down);
if (evt->mouseButton.button == sf::Mouse::Middle)
nk_input_button(ctx, NK_BUTTON_MIDDLE, x, y, down);
if (evt->mouseButton.button == sf::Mouse::Right)
nk_input_button(ctx, NK_BUTTON_RIGHT, x, y, down);
}
else if (evt->type == sf::Event::MouseMoved) {
nk_input_motion(ctx, evt->mouseMove.x, evt->mouseMove.y);
}
else if (evt->type == sf::Event::KeyPressed || evt->type == sf::Event::KeyReleased) {
int down = evt->type == sf::Event::KeyPressed;
if (evt->key.code == sf::Keyboard::Backspace) {
nk_input_key(ctx, NK_KEY_BACKSPACE, down);
nk_input_key(ctx, NK_KEY_BACKSPACE, 0);
}
else if (evt->key.code == sf::Keyboard::Enter)
nk_input_key(ctx, NK_KEY_ENTER, down);
if (down == 1)
if (evt->key.code >= sf::Keyboard::Num0&&evt->key.code <= sf::Keyboard::Num9)
nk_input_char(ctx, evt->key.code + 22);
else if (evt->key.code == sf::Keyboard::Period)
nk_input_char(ctx, 46);
else if (evt->key.code == sf::Keyboard::Dash)
nk_input_char(ctx, 45);
else if (evt->key.code == sf::Keyboard::Space)
nk_input_char(ctx, 32);
else if (evt->key.code >= sf::Keyboard::A&&evt->key.code <= sf::Keyboard::Z) {
if (sf::Keyboard::isKeyPressed(sf::Keyboard::LShift))
nk_input_char(ctx, evt->key.code + 65);
else
nk_input_char(ctx, evt->key.code + 97);
}
}
}
template <typename T>
T mix(T x, T y, T a) {
return x*(1 - a) + y*a;
}
template <typename T>
T clamp(T x, T minVal, T maxVal) {
return min(max(x, minVal), maxVal);
}
double determinant(sf::Transform mat) {
const float* matPointer = mat.getMatrix();
return abs(matPointer[0] * matPointer[5] * matPointer[10] - matPointer[4] * matPointer[1] * matPointer[10]);
}
void operator /=(sf::Transform &mat, double x)
{
mat = sf::Transform(mat.getMatrix()[0] / x, mat.getMatrix()[4] / x, mat.getMatrix()[12], mat.getMatrix()[1] / x, mat.getMatrix()[5] / x, mat.getMatrix()[13], mat.getMatrix()[2], mat.getMatrix()[6], mat.getMatrix()[10]);
}
//gaussian
float calculateKernel(float x, float sigma)
{
return 0.39894*exp(-0.5*x*x / (sigma*sigma)) / sigma;
}
//Unlinear functions
void spherical(sf::Vector2f &point) {
point = 1 / (pow(point.x, 2) + pow(point.y, 2))*point;
}
void swirl(sf::Vector2f &point) {
float r2 = pow(point.x, 2) + pow(point.y, 2);
point = sf::Vector2f(point.x*sin(r2) - point.y*cos(r2), point.x*cos(r2) + point.y*sin(r2));
}
void handkerchief(sf::Vector2f &point) {
float r = sqrt(pow(point.x, 2) + pow(point.y, 2));
float theta = atan2(point.x, point.y);
point = sf::Vector2f(r*sin(theta + r), r*cos(theta - r));
}
void sinusoidal(sf::Vector2f &point) {
point = sf::Vector2f(sin(point.x)*boundedFunctionScale, sin(point.y)*boundedFunctionScale);
}
void linear(sf::Vector2f &point) {
}
void horseshoe(sf::Vector2f &point) {
float r = sqrt(pow(point.x, 2) + pow(point.y, 2));
point = sf::Vector2f(1 / r*(point.x - point.y)*(point.x + point.y), 1 / r * 2 * point.x*point.y);
}
void polar(sf::Vector2f &point) {
float r = sqrt(pow(point.x, 2) + pow(point.y, 2));
float theta = atan2(point.x, point.y);
point = sf::Vector2f(theta / 3.1415*boundedFunctionScale, (r - 1)*boundedFunctionScale);
}
void disc(sf::Vector2f &point) {
float r = sqrt(pow(point.x, 2) + pow(point.y, 2));
float theta = atan2(point.x, point.y);
point = sf::Vector2f(theta / 3.1415*sin(3.1415*r)*boundedFunctionScale, theta / 3.1415*cos(3.1415*r)*boundedFunctionScale);
}
void heart(sf::Vector2f &point) {
float r = sqrt(pow(point.x, 2) + pow(point.y, 2));
float theta = atan2(point.x, point.y);
point = sf::Vector2f(r*sin(theta*r), r*(-cos(theta*r)));
}
void spiral(sf::Vector2f &point) {
float r = sqrt(pow(point.x, 2) + pow(point.y, 2));
float theta = atan2(point.x, point.y);
point = sf::Vector2f(1 / r*(cos(theta) + sin(r)), 1 / r*(sin(theta) - cos(r)));
}
void hyperbolic(sf::Vector2f &point) {
float r = sqrt(pow(point.x, 2) + pow(point.y, 2));
float theta = atan2(point.x, point.y);
point = sf::Vector2f(sin(theta) / r, r*cos(theta));
}
void diamond(sf::Vector2f &point) {
float r = sqrt(pow(point.x, 2) + pow(point.y, 2));
float theta = atan2(point.x, point.y);
point = sf::Vector2f(sin(theta)*cos(r)*boundedFunctionScale, cos(theta)*sin(r)*boundedFunctionScale);
}
void ex(sf::Vector2f &point) {
float r = sqrt(pow(point.x, 2) + pow(point.y, 2));
float theta = atan2(point.x, point.y);
float p0 = sin(theta + r);
float p1 = cos(theta - r);
point = sf::Vector2f(r*(pow(p0, 3) + pow(p1, 3)), r*(pow(p0, 3) - pow(p1, 3)));
}
void julia(sf::Vector2f &point) {
float omega = d(e)* 3.1415;
float sqrtr = sqrt(sqrt(pow(point.x, 2) + pow(point.y, 2)));
float theta = atan2(point.x, point.y);
point = sf::Vector2f(sqrtr*cos(theta / 2 + omega)*boundedFunctionScale, sqrtr*sin(theta / 2 + omega)*boundedFunctionScale);
}
//SIMD functions
inline void SIMDMatrix32Mul(float *mat, sf::Vector2f *point) {//After performance tests it seems that SFML or compiler vectorize matrix-vector multiplication itself
float temp,temp2;
__m128 p = _mm_set_ps(point->x, point->y, 1, 0);
_mm_store_ss(&temp, _mm_dp_ps(_mm_set_ps(mat[0],mat[1],mat[2],0), p , 0xFF));
_mm_store_ss(&temp2, _mm_dp_ps(_mm_set_ps(mat[3], mat[4], mat[5], 0), p, 0xFF));
point->x = temp;
point->y = temp2;
}
//CUDA
//CUDA math functions
inline __host__ __device__ float2 operator*(float2 a, float2 b)
{
return make_float2(a.x * b.x, a.y * b.y);
}
inline __host__ __device__ void operator*=(float2 &a, float2 b)
{
a.x *= b.x;
a.y *= b.y;
}
inline __host__ __device__ float2 operator*(float2 a, float b)
{
return make_float2(a.x * b, a.y * b);
}
inline __host__ __device__ float2 operator*(float b, float2 a)
{
return make_float2(b * a.x, b * a.y);
}
inline __host__ __device__ void operator*=(float2 &a, float b)
{
a.x *= b;
a.y *= b;
}
inline __host__ __device__ void mulMatVec(float *data,int index,float2* point)//multiply 3x2 matrix by vector
{
float temp;
temp = data[index] * point->x + data[index + 1] * point->y + data[index + 2];
point->y= data[index+3] * point->x + data[index + 4] * point->y + data[index + 5];
point->x = temp;
}
inline __device__ float calculateKernel_d(float x, float sigma)
{
return 0.39894*expf(-0.5*x*x / (sigma*sigma)) / sigma;
}
//CUDA variations functions
__device__ float boundedFunctionScale_d = 1;
inline __device__ void spherical(float2 &point, curandState& s) {
point = 1 / (powf(point.x, 2) + powf(point.y, 2))*(point);
}
inline __device__ void swirl(float2 &point, curandState& s) {
float r2 = powf(point.x, 2) + powf(point.y, 2);
point = make_float2(point.x*sinf(r2) - point.y*cosf(r2), point.x*cosf(r2) + point.y*sinf(r2));
}
inline __device__ void handkerchief(float2 &point, curandState& s) {
float r = sqrtf(powf(point.x, 2) + powf(point.y, 2));
float theta = atan2f(point.x, point.y);
point = make_float2(r*sinf(theta + r), r*cosf(theta - r));
}
inline __device__ void sinusoidal(float2 &point, curandState& s) {
point = make_float2(sinf(point.x)*boundedFunctionScale_d, sinf(point.y)*boundedFunctionScale_d);
}
inline __device__ void linear(float2 &point, curandState& s) {
}
inline __device__ void horseshoe(float2 &point, curandState& s) {
float r = sqrtf(pow(point.x, 2) + powf(point.y, 2));
point = make_float2(1 / r*(point.x - point.y)*(point.x + point.y), 1 / r * 2 * point.x*point.y);
}
inline __device__ void polar(float2 &point, curandState& s) {
float r = sqrtf(pow(point.x, 2) + powf(point.y, 2));
float theta = atan2f(point.x, point.y);
point = make_float2(theta / 3.1415*boundedFunctionScale_d, (r - 1)*boundedFunctionScale_d);
}
inline __device__ void disc(float2 &point, curandState& s) {
float r = sqrtf(powf(point.x, 2) + powf(point.y, 2));
float theta = atan2f(point.x, point.y);
point = make_float2(theta / 3.1415*sinf(3.1415*r)*boundedFunctionScale_d, theta / 3.1415*cosf(3.1415*r)*boundedFunctionScale_d);
}
inline __device__ void heart(float2 &point, curandState& s) {
float r = sqrtf(powf(point.x, 2) + powf(point.y, 2));
float theta = atan2f(point.x, point.y);
point = make_float2(r*sinf(theta*r), r*(-cosf(theta*r)));
}
inline __device__ void spiral(float2 &point, curandState& s) {
float r = sqrtf(powf(point.x, 2) + powf(point.y, 2));
float theta = atan2f(point.x, point.y);
point = make_float2(1 / r*(cosf(theta) + sinf(r)), 1 / r*(sinf(theta) - cosf(r)));
}
inline __device__ void hyperbolic(float2 &point, curandState& s) {
float r = sqrtf(powf(point.x, 2) + powf(point.y, 2));
float theta = atan2f(point.x, point.y);
point = make_float2(sinf(theta) / r, r*cosf(theta));
}
inline __device__ void diamond(float2 &point, curandState& s) {
float r = sqrtf(powf(point.x, 2) + powf(point.y, 2));
float theta = atan2f(point.x, point.y);
point = make_float2(sinf(theta)*cosf(r)*boundedFunctionScale_d, cosf(theta)*sinf(r)*boundedFunctionScale_d);
}
__device__ void ex(float2 &point, curandState& s) {
float r = sqrtf(powf(point.x, 2) + powf(point.y, 2));
float theta = atan2f(point.x, point.y);
float p0 = sinf(theta + r);
float p1 = cosf(theta - r);
point = make_float2(r*(powf(p0, 3) + powf(p1, 3)), r*(powf(p0, 3) - powf(p1, 3)));
}
__device__ void julia(float2 &point, curandState& s) {
float omega = (int)(curand_uniform(&s)+0.5)* 3.1415;
float sqrtr = sqrtf(sqrtf(powf(point.x, 2) + powf(point.y, 2)));
float theta = atan2f(point.x, point.y);
point = make_float2(sqrtr*cosf(theta / 2 + omega)*boundedFunctionScale_d, sqrtr*sinf(theta / 2 + omega)*boundedFunctionScale_d);
}
__device__ void(*deviceFunctionArray[14])(float2&, curandState&) = { spherical,swirl,handkerchief,sinusoidal,linear,horseshoe,polar,disc,heart,spiral,hyperbolic,diamond,ex,julia };//function pointers for device
//CUDA main algorithm
//pass1 0-5 current
//pass1 6 offset for random generator
//pass1 7 max
//pass2 0-5 probability
//pass2 6-11 mat1
//pass2 12-17 mat2
//pass2 18-23 mat3
//pass2 24-29 mat4
//pass2 30-35 mat5
//pass2 36-41 mat6
//pass2 42-47 color
//pass2 48 zoom
//pass2 49 boundedFunctionScale
//pass2 50+ postTransforms
//pass3 0-104 857 599 histogram count
//pass3 104 857 600-209 715 199 histogram color
__global__ void cudaAcceleratedHistogram(int* pass1,float* pass2,float* pass3) {
boundedFunctionScale_d = pass2[49];
curandState s;
curand_init(blockIdx.x * 1024 + threadIdx.x+pass1[6], 0, 0, &s);
float2 point = make_float2(0, 0);
int temp, temp2;
float cad = 0;
for (int i = 0; i <1000; i++)
{
float r = curand_uniform(&s);
if (r <= pass2[0]) { mulMatVec(pass2,6,&point); cad = (cad + pass2[42]) / 2; deviceFunctionArray[pass1[0]](point,s); mulMatVec(pass2, 50, &point);}
else if (r <= pass2[1]) { mulMatVec(pass2, 12, &point); cad = (cad + pass2[43]) / 2; deviceFunctionArray[pass1[1]](point,s); mulMatVec(pass2, 56, &point);}
else if (r <=pass2[2]) { mulMatVec(pass2, 18, &point); cad = (cad + pass2[44]) / 2; deviceFunctionArray[pass1[2]](point,s); mulMatVec(pass2, 62, &point);}
else if (r <=pass2[3]) { mulMatVec(pass2, 24, &point) ; cad = (cad + pass2[45]) / 2; deviceFunctionArray[pass1[3]](point,s); mulMatVec(pass2, 68, &point);}
else if (r <=pass2[4]) { mulMatVec(pass2, 30, &point); cad = (cad + pass2[46]) / 2; deviceFunctionArray[pass1[4]](point,s); mulMatVec(pass2, 74, &point);}
else { mulMatVec(pass2, 36, &point); cad = (cad + pass2[47]) / 2; deviceFunctionArray[pass1[5]](point,s); mulMatVec(pass2, 80, &point);}
if (i > 20) {
if (abs(point.x) >= (5 * pass2[48])-0.001 || abs(point.y) >= (5 * pass2[48])-0.001)//GPU rounding makes exacly comp useless, need some space
continue;
temp = (int)((point.x + 5 * pass2[48]) * (1024 / pass2[48]));
temp2 = (int)((point.y + 5 * pass2[48]) * (1024 / pass2[48]));
temp2 = temp * 10240 + temp2;
pass3[temp2]= (int)(pass3[temp2]+1);
if (pass3[temp2] > pass1[7])
atomicExch(&pass1[7],pass3[temp2]);
pass3[104857600 + temp2] = (pass3[104857600 + temp2] + cad) / 2;
}
}
}
__global__ void cudaAcceleratedSupersampling(float* histogram, float* image,int* max) {
float freq = 0;
float color = 0;
float alpha = 0;
int y = blockIdx.x % 2*1024 + threadIdx.x;
int i = blockIdx.x / 2;
for (int a = 0; a < 5; a++) {
for (int b = 0; b < 5; b++) {
freq = histogram[5 * y * 10240 + b * 10240 + (5 * i + a)];
color = histogram[5 * y * 10240 + b * 10240 + (5 * i + a) + 104857600];
if (freq != 0)
alpha += color*powf((log10f(freq) / log10f(*max)), 1 / 2.2);
image[y * 2048 + i+ 4194304] += histogram[5 * y * 10240 + b * 10240 + (5 * i + a)];
}
}
alpha /= 25;
image[y * 2048 + i] = alpha;
}
__global__ void cudaAcceleratedGaussianBlur(float *image,int *gauss) {
int x = blockIdx.x % 2 * 1024 + threadIdx.x;
int y = blockIdx.x / 2;
float kernel[20];
int kernelWidth = *gauss / powf(image[x*2048+y+ 4194304], 0.4);
if (kernelWidth >9|| kernelWidth <0)
kernelWidth = *gauss;
if (kernelWidth == 0)
return;
int kernelSize = kernelWidth * 2 + 1;
float sigma = 6.;
float Z = 0.0;
float final_colour = 0;
for (int j = 0; j <= kernelWidth; ++j)
{
kernel[kernelWidth + j] = kernel[kernelWidth - j] = calculateKernel_d(float(j), sigma);
}
for (int j = 0; j < kernelSize; ++j)
{
Z += kernel[j];
}
for (int i = -kernelWidth; i <= kernelWidth; ++i)
{
for (int j = -kernelWidth; j <= kernelWidth; ++j)
{
if (x + i < 0 || y + j < 0 || x + 1>2047 || y + j>2047)
continue;
final_colour += kernel[kernelWidth + j] * kernel[kernelWidth + i] * image[x*2048 + i*2048+y + j];
}
}
final_colour /= (Z*Z);
image[x * 2048 + y] = final_colour;
}
void calculateHistogramPart(float(*affineTransforms)[8], int current[], int affineNum, long long iterations, float(*histogram)[10241][2], float zoom, float(*postTransforms)[6]) {
sf::Transform *affineMatrix = new sf::Transform[6];
sf::Transform *postMatrix = new sf::Transform[6];
for (int i = 0; i < affineNum; i++) {
affineMatrix[i] = sf::Transform(affineTransforms[i][0], affineTransforms[i][1], affineTransforms[i][2], affineTransforms[i][3], affineTransforms[i][4], affineTransforms[i][5], 0, 0, 1);
postMatrix[i] = sf::Transform(postTransforms[i][0], postTransforms[i][1], postTransforms[i][2], postTransforms[i][3], postTransforms[i][4], postTransforms[i][5], 0, 0, 1);
}
void(*unlinearPointer[14])(sf::Vector2f &point) = { spherical,swirl,handkerchief,sinusoidal,linear,horseshoe,polar,disc,heart,spiral,hyperbolic,diamond,ex,julia };//array of pointers to functions
int max = 0;
sf::Vector2f point = sf::Vector2f(0, 0);//be aware with translation 0 in matrix can cause division by 0
float cad = 0;
std::random_device rd;
std::default_random_engine e(rd());
std::uniform_real_distribution<> d(0.0, 1.0);
float probability0 = affineTransforms[0][7];
float probability1 = probability0 + affineTransforms[1][7];
float probability2 = probability1 + affineTransforms[2][7];
float probability3 = probability2 + affineTransforms[3][7];
float probability4 = probability3 + affineTransforms[4][7];
float probability5 = probability4 + affineTransforms[5][7];
int temp, temp2;
for (long long i = 0; i < iterations; i++)
{
float result = d(e);
if (result < probability0) { point = affineMatrix[0] * point; cad = (cad + affineTransforms[0][6]) / 2; unlinearPointer[current[0]](point); point = postMatrix[0] * point;}
else if (result < probability1) { point = affineMatrix[1] * point; cad = (cad + affineTransforms[1][6]) / 2; unlinearPointer[current[1]](point); point = postMatrix[1] * point;}
else if (result <probability2) { point = affineMatrix[2] * point; cad = (cad + affineTransforms[2][6]) / 2; unlinearPointer[current[2]](point); point = postMatrix[2] * point;}
else if (result <probability3) {point = affineMatrix[3] * point; cad = (cad + affineTransforms[3][6]) / 2; unlinearPointer[current[3]](point); point = postMatrix[3] * point;}
else if (result <probability4) { point = affineMatrix[4] * point; cad = (cad + affineTransforms[4][6]) / 2; unlinearPointer[current[4]](point); point = postMatrix[4] * point;}
else { point = affineMatrix[5] * point; cad = (cad + affineTransforms[5][6]) / 2; unlinearPointer[current[5]](point); point = postMatrix[5] * point;}
if (i > 20) {
if (abs(point.x) > 5 * zoom || abs(point.y) > 5 * zoom)
continue;
temp = (unsigned int)((point.x + 5 * zoom) * (1024 / zoom));
temp2 = (unsigned int)((point.y + 5 * zoom) * (1024 / zoom));
histogram[temp][temp2][0] += 1;
//if (histogram[(int)((point.x + 5) * 1024)][(int)((point.y + 5) * 1024)][0] > max)
//max = histogram[(int)((point.x + 5) * 1024)][(int)((point.y + 5) * 1024)][0];
histogram[temp][temp2][1] = (histogram[temp][temp2][1] + cad) / 2;
}
}
}
void renderToFile(int renderType, float(*affineTransforms)[8], int current[], bool unlinearNum, int affineNum, float zoom, int gauss, int iterationsInMld, float(*postTransforms)[6]) {
long long iterations = iterationsInMld * (long long)1000000000;
if (renderType == 0) {
if (unlinearNum == 0) {
for (int i = 1; i<6; i++)
current[i] = current[0];
}
sf::Transform *affineMatrix = new sf::Transform[6];
sf::Transform *postMatrix = new sf::Transform[6];
for (int i = 0; i < affineNum; i++) {
affineMatrix[i] = sf::Transform(affineTransforms[i][0], affineTransforms[i][1], affineTransforms[i][2], affineTransforms[i][3], affineTransforms[i][4], affineTransforms[i][5], 0, 0, 1);
postMatrix[i] = sf::Transform(postTransforms[i][0], postTransforms[i][1], postTransforms[i][2], postTransforms[i][3], postTransforms[i][4], postTransforms[i][5], 0, 0, 1);
//affineMatrix[i] /= mix(1.0, determinant(affineMatrix[i]), clamp(determinant(affineMatrix[i])*3.0 - 2.0, 0.0, 1.0));
//affineTransforms[i][0] = affineMatrix[i].getMatrix()[0];
//affineTransforms[i][1] = affineMatrix[i].getMatrix()[4];
//affineTransforms[i][2] = affineMatrix[i].getMatrix()[12];
//affineTransforms[i][3] = affineMatrix[i].getMatrix()[1];
//affineTransforms[i][4] = affineMatrix[i].getMatrix()[5];
//affineTransforms[i][5] = affineMatrix[i].getMatrix()[13];
}
void(*unlinearPointer[14])(sf::Vector2f &point) = { spherical,swirl,handkerchief,sinusoidal,linear,horseshoe,polar,disc,heart,spiral,hyperbolic,diamond,ex,julia };//array of pointers to functions
int max = 0;
sf::Vector2f point = sf::Vector2f(0, 0);//be aware with translation 0 in matrix can cause division by 0
float cad = 0;
auto histogram = new float[10241][10241][2]();
std::random_device rd;
std::default_random_engine e(rd());
std::uniform_real_distribution<> d(0.0, 1.0);
float probability0 = affineTransforms[0][7];
float probability1 = probability0 + affineTransforms[1][7];
float probability2 = probability1 + affineTransforms[2][7];
float probability3 = probability2 + affineTransforms[3][7];
float probability4 = probability3 + affineTransforms[4][7];
float probability5 = probability4 + affineTransforms[5][7];
int temp, temp2;
for (long long i = 0; i < iterations; i++)
{
float result = d(e);
if (result < probability0) { point = affineMatrix[0] * point; cad = (cad + affineTransforms[0][6]) / 2; unlinearPointer[current[0]](point); point = postMatrix[0] * point;}
else if (result < probability1) { point = affineMatrix[1] * point; cad = (cad + affineTransforms[1][6]) / 2; unlinearPointer[current[1]](point); point = postMatrix[1] * point;}
else if (result <probability2) { point = affineMatrix[2] * point; cad = (cad + affineTransforms[2][6]) / 2; unlinearPointer[current[2]](point); point = postMatrix[2] * point;}
else if (result <probability3) { point = affineMatrix[3] * point; cad = (cad + affineTransforms[3][6]) / 2; unlinearPointer[current[3]](point); point = postMatrix[3] * point;}
else if (result <probability4) { point = affineMatrix[4] * point; cad = (cad + affineTransforms[4][6]) / 2; unlinearPointer[current[4]](point); point = postMatrix[4] * point;}
else { point = affineMatrix[5] * point; cad = (cad + affineTransforms[5][6]) / 2; unlinearPointer[current[5]](point); point = postMatrix[5] * point;}
if (i > 20) {
if (abs(point.x) > 5 * zoom || abs(point.y) > 5 * zoom)
continue;
temp = (unsigned int)((point.x + 5 * zoom) * (1024 / zoom));
temp2 = (unsigned int)((point.y + 5 * zoom) * (1024 / zoom));
histogram[temp][temp2][0] += 1;
if (histogram[temp][temp2][0] > max)
max = histogram[temp][temp2][0];
histogram[temp][temp2][1] = (histogram[temp][temp2][1] + cad) / 2;
}
}
sf::Image img;
img.create(2048, 2048);
float freq = 0;
float color = 0;
float alpha = 0;
auto freqArchive = new float[2048][2048];
for (int i = 0; i < 2048; i++)
for (int y = 0; y < 2048; y++) {
for (int a = 0; a < 5; a++) {
for (int b = 0; b < 5; b++) {
freq = histogram[5 * y + b][5 * i + a][0];
color = histogram[5 * y + b][5 * i + a][1];
if (freq != 0)
alpha += color*pow((log10(freq) / log10(max)), 1 / 2.2);
freqArchive[y][i] += histogram[5 * y + b][5 * i + a][0];
}
}
alpha /= 25;
sf::Color col(alpha * 255, alpha * 255, alpha * 255, 255);
img.setPixel(y, i, col);
}
//gaussian blur with density estimation
float kernel[20];
for (int y = 0; y<2048; y++)
for (int x = 0; x < 2048; x++) {
int kernelWidth = gauss / pow(freqArchive[x][y], 0.4);
if (kernelWidth < 0)
kernelWidth = gauss;
if (kernelWidth == 0)
continue;
int kernelSize = kernelWidth * 2 + 1;
//float* kernel = new float[kernelSize + 1];
float sigma = 6.;
float Z = 0.0;
float final_colour = 0;
for (int j = 0; j <= kernelWidth; ++j)
{
kernel[kernelWidth + j] = kernel[kernelWidth - j] = calculateKernel(float(j), sigma);
}
for (int j = 0; j < kernelSize; ++j)
{
Z += kernel[j];
}
for (int i = -kernelWidth; i <= kernelWidth; ++i)
{
for (int j = -kernelWidth; j <= kernelWidth; ++j)
{
if (x + i < 0 || y + j < 0 || x + 1>2047 || y + j>2047)
continue;
final_colour += kernel[kernelWidth + j] * kernel[kernelWidth + i] * img.getPixel(x + i, y + j).r;
}
}
final_colour /= (Z*Z);
sf::Color f(final_colour, final_colour, final_colour, 255);
img.setPixel(x, y, f);
}
img.saveToFile("ifs.png");
delete[] histogram;
delete[] freqArchive;
}
else if (renderType == 1) {
if (unlinearNum == 0) {
for (int i = 1; i<6; i++)
current[i] = current[0];
}
sf::Transform *affineMatrix = new sf::Transform[6];
sf::Transform *postMatrix = new sf::Transform[6];
for (int i = 0; i < affineNum; i++) {
affineMatrix[i] = sf::Transform(affineTransforms[i][0], affineTransforms[i][1], affineTransforms[i][2], affineTransforms[i][3], affineTransforms[i][4], affineTransforms[i][5], 0, 0, 1);
//affineMatrix[i] /= mix(1.0, determinant(affineMatrix[i]), clamp(determinant(affineMatrix[i])*3.0 - 2.0, 0.0, 1.0));
//affineTransforms[i][0] = affineMatrix[i].getMatrix()[0];
//affineTransforms[i][1] = affineMatrix[i].getMatrix()[4];
//affineTransforms[i][2] = affineMatrix[i].getMatrix()[12];
//affineTransforms[i][3] = affineMatrix[i].getMatrix()[1];
//affineTransforms[i][4] = affineMatrix[i].getMatrix()[5];
//affineTransforms[i][5] = affineMatrix[i].getMatrix()[13];
}
auto histogram = new float[10241][10241][2]();
std::thread t1(calculateHistogramPart, affineTransforms, current, affineNum, iterations / 3, histogram, zoom,postTransforms);
std::thread t2(calculateHistogramPart, affineTransforms, current, affineNum, iterations / 3, histogram, zoom, postTransforms);
std::thread t3(calculateHistogramPart, affineTransforms, current, affineNum, iterations / 3, histogram, zoom, postTransforms);
t1.join();
t2.join();
t3.join();
int max = 0;
for (int i = 0; i<10240; i++)
for (int y = 0; y < 10240; y++) {
if (histogram[y][i][0] > max)
max = histogram[y][i][0];
}
sf::Image img;
img.create(2048, 2048);
float freq = 0;
float color = 0;
float alpha = 0;
auto freqArchive = new float[2048][2048];
for (int i = 0; i < 2048; i++)
for (int y = 0; y < 2048; y++) {
for (int a = 0; a < 5; a++) {
for (int b = 0; b < 5; b++) {
freq = histogram[5 * y + b][5 * i + a][0];
color = histogram[5 * y + b][5 * i + a][1];
if (freq != 0)
alpha += color*pow((log10(freq) / log10(max)), 1 / 2.2);
freqArchive[y][i] += histogram[5 * y + b][5 * i + a][0];
}
}
alpha /= 25;
sf::Color col(alpha * 255, alpha * 255, alpha * 255, 255);
img.setPixel(y, i, col);
}
//gaussian blur with density estimation
float kernel[20];
for (int y = 0; y<2048; y++)
for (int x = 0; x < 2048; x++) {
int kernelWidth = gauss / pow(freqArchive[x][y], 0.4);
if (kernelWidth < 0)
kernelWidth = gauss;
if (kernelWidth == 0)
continue;
int kernelSize = kernelWidth * 2 + 1;
//float* kernel = new float[kernelSize + 1];
float sigma = 6.;
float Z = 0.0;
float final_colour = 0;
for (int j = 0; j <= kernelWidth; ++j)
{
kernel[kernelWidth + j] = kernel[kernelWidth - j] = calculateKernel(float(j), sigma);
}
for (int j = 0; j < kernelSize; ++j)
{
Z += kernel[j];
}
for (int i = -kernelWidth; i <= kernelWidth; ++i)
{
for (int j = -kernelWidth; j <= kernelWidth; ++j)
{
if (x + i < 0 || y + j < 0 || x + 1>2047 || y + j>2047)
continue;
final_colour += kernel[kernelWidth + j] * kernel[kernelWidth + i] * img.getPixel(x + i, y + j).r;
}
}
final_colour /= (Z*Z);
sf::Color f(final_colour, final_colour, final_colour, 255);
img.setPixel(x, y, f);
}
img.saveToFile("ifs.png");
delete[] histogram;
}
else if (renderType == 2) {//CUDA acceleration
std::random_device rd;
std::default_random_engine e(rd());
std::uniform_real_distribution<> d(0.0, 1.0);
//memory allocation
int *pass1_d;
float *pass2_d;
float *pass3_d;
int *pass1_h;
float *pass2_h;
//device allocation
cudaMalloc(&pass1_d, 8 * sizeof(int));
cudaMalloc(&pass2_d, 87 * sizeof(float));
cudaMalloc(&pass3_d, 209715200 * sizeof(float));
cudaMemset(&pass3_d, 0, 209715200 * sizeof(float));
//host allocation
pass1_h = (int*)malloc(8 * sizeof(int));
pass2_h = (float*)malloc(86 * sizeof(float));
//pre-calculations
if (unlinearNum == 0) {
for (int i = 1; i<6; i++)
current[i] = current[0];
}
sf::Transform *affineMatrix = new sf::Transform[6];
sf::Transform *postMatrix = new sf::Transform[6];
for (int i = 0; i < affineNum; i++) {
affineMatrix[i] = sf::Transform(affineTransforms[i][0], affineTransforms[i][1], affineTransforms[i][2], affineTransforms[i][3], affineTransforms[i][4], affineTransforms[i][5], 0, 0, 1);
postMatrix[i] = sf::Transform(postTransforms[i][0], postTransforms[i][1], postTransforms[i][2], postTransforms[i][3], postTransforms[i][4], postTransforms[i][5], 0, 0, 1);
//affineMatrix[i] /= mix(1.0, determinant(affineMatrix[i]), clamp(determinant(affineMatrix[i])*3.0 - 2.0, 0.0, 1.0));
//affineTransforms[i][0] = affineMatrix[i].getMatrix()[0];
//affineTransforms[i][1] = affineMatrix[i].getMatrix()[4];
//affineTransforms[i][2] = affineMatrix[i].getMatrix()[12];
//affineTransforms[i][3] = affineMatrix[i].getMatrix()[1];
//affineTransforms[i][4] = affineMatrix[i].getMatrix()[5];
//affineTransforms[i][5] = affineMatrix[i].getMatrix()[13];
//data feed
pass2_h[6*i+6] = affineMatrix[i].getMatrix()[0];
pass2_h[6*i+1+6] = affineMatrix[i].getMatrix()[4];
pass2_h[6*i+2+6] = affineMatrix[i].getMatrix()[12];
pass2_h[6*i+3+6] = affineMatrix[i].getMatrix()[1];
pass2_h[6*i+4+6] = affineMatrix[i].getMatrix()[5];
pass2_h[6*i+5+6] = affineMatrix[i].getMatrix()[13];
pass2_h[42+i] = affineTransforms[i][6];
//post transform feed
pass2_h[6 * i + 50] = affineMatrix[i].getMatrix()[0];
pass2_h[6 * i + 1 + 50] = affineMatrix[i].getMatrix()[4];
pass2_h[6 * i + 2 + 50] = affineMatrix[i].getMatrix()[12];
pass2_h[6 * i + 3 + 50] = affineMatrix[i].getMatrix()[1];
pass2_h[6 * i + 4 + 50] = affineMatrix[i].getMatrix()[5];
pass2_h[6 * i + 5 + 50] = affineMatrix[i].getMatrix()[13];
}
//data feed
pass2_h[0] = affineTransforms[0][7];
pass2_h[1] = pass2_h[0] + affineTransforms[1][7];
pass2_h[2] = pass2_h[1] + affineTransforms[2][7];
pass2_h[3] = pass2_h[2] + affineTransforms[3][7];
pass2_h[4] = pass2_h[3] + affineTransforms[4][7];
pass2_h[5] = pass2_h[4] + affineTransforms[5][7];
for (int i = 0; i < 6; i++)
pass1_h[i] = current[i];
pass2_h[48] = zoom;
pass2_h[49] = boundedFunctionScale;
cudaMemcpy(pass2_d, pass2_h, 86 * sizeof(float), cudaMemcpyHostToDevice);
cudaMemcpy(pass1_d, pass1_h, 7 * sizeof(int), cudaMemcpyHostToDevice);
int blocks;
int loops;
if (iterationsInMld < 10) {
blocks = iterations / 1024000;
loops = 1;
}
else {
blocks = 2500;
loops = (double)iterations / 2560000000+0.7;
}
for (int i = 0; i < loops; i++) {
pass1_h[6] = d(e)*1000;
cudaMemcpy(&pass1_d[6], &pass1_h[6], sizeof(int), cudaMemcpyHostToDevice);
cudaAcceleratedHistogram << <blocks, 1024 >> > (pass1_d, pass2_d, pass3_d);
cudaDeviceSynchronize();
}
float *image_d;
cudaMalloc(&image_d, 8388608 * sizeof(float));
cudaAcceleratedSupersampling << <4096, 1024 >> > (pass3_d, image_d,&pass1_d[7]);
cudaFree(pass3_d);
int *gauss_d;
cudaMalloc(&gauss_d, sizeof(int));
cudaMemcpy(gauss_d, &gauss, sizeof(int), cudaMemcpyHostToDevice);
cudaAcceleratedGaussianBlur << <4096, 1024 >> > (image_d, gauss_d);
float* image_h = (float*)malloc(8388608 * sizeof(float));
cudaMemcpy(image_h, image_d, 8388608 * sizeof(float), cudaMemcpyDeviceToHost);
sf::Image img;
float alpha;
img.create(2048, 2048);
for (int i = 0; i < 2048; i++)
for (int y = 0; y < 2048; y++) {
alpha = image_h[y * 2048 + i];
sf::Color col(alpha * 255, alpha * 255, alpha * 255, 255);
img.setPixel(y, i, col);
}
img.saveToFile("ifs.png");
//memory deallocation
cudaFree(pass2_d);
cudaFree(pass1_d);
cudaFree(image_d);
free(pass1_h);
free(pass2_h);
free(image_h);
}
}
void renderToOverview(int renderType, float(*affineTransforms)[8], int current[], bool unlinearNum, int affineNum, sf::RenderWindow& window, float zoom, float(*postTransforms)[6]) {
//if (renderType == 0) {
if (unlinearNum == 0) {
for (int i = 1; i<6; i++)
current[i] = current[0];
}
sf::Transform *affineMatrix = new sf::Transform[6];
sf::Transform *postMatrix = new sf::Transform[6];
for (int i = 0; i < affineNum; i++) {
affineMatrix[i] = sf::Transform(affineTransforms[i][0], affineTransforms[i][1], affineTransforms[i][2], affineTransforms[i][3], affineTransforms[i][4], affineTransforms[i][5], 0, 0, 1);
postMatrix[i] = sf::Transform(postTransforms[i][0], postTransforms[i][1], postTransforms[i][2], postTransforms[i][3], postTransforms[i][4], postTransforms[i][5],0,0,1);
//affineMatrix[i] /= mix(1.0, determinant(affineMatrix[i]), clamp(determinant(affineMatrix[i])*3.0 - 2.0, 0.0, 1.0));
//affineTransforms[i][0] = affineMatrix[i].getMatrix()[0];
//affineTransforms[i][1] = affineMatrix[i].getMatrix()[4];
//affineTransforms[i][2] = affineMatrix[i].getMatrix()[12];
//affineTransforms[i][3] = affineMatrix[i].getMatrix()[1];
//affineTransforms[i][4] = affineMatrix[i].getMatrix()[5];
//affineTransforms[i][5] = affineMatrix[i].getMatrix()[13];
}
void(*unlinearPointer[14])(sf::Vector2f &point) = { spherical,swirl,handkerchief,sinusoidal,linear,horseshoe,polar,disc,heart,spiral,hyperbolic,diamond,ex,julia };//array of pointers to functions
int max = 0;
sf::Vector2f point = sf::Vector2f(0, 0);//be aware with translation 0 in matrix can cause division by 0
float cad = 0;
auto histogram = new float[501][501][2]();
std::random_device rd;
std::default_random_engine e(rd());
std::uniform_real_distribution<> d(0.0, 1.0);
float probability0 = affineTransforms[0][7];
float probability1 = probability0 + affineTransforms[1][7];
float probability2 = probability1 + affineTransforms[2][7];
float probability3 = probability2 + affineTransforms[3][7];
float probability4 = probability3 + affineTransforms[4][7];
float probability5 = probability4 + affineTransforms[5][7];
int temp, temp2;
for (int i = 0; i < 5000000; i++)
{
float result = d(e);
if (result < probability0) { point = affineMatrix[0] * point; cad = (cad + affineTransforms[0][6]) / 2; unlinearPointer[current[0]](point); point = postMatrix[0] * point; }
else if (result < probability1) { point = affineMatrix[1] * point; cad = (cad + affineTransforms[1][6]) / 2; unlinearPointer[current[1]](point); point = postMatrix[1] * point;}
else if (result <probability2) { point = affineMatrix[2] * point; cad = (cad + affineTransforms[2][6]) / 2; unlinearPointer[current[2]](point); point = postMatrix[2] * point;}
else if (result <probability3) { point = affineMatrix[3] * point; cad = (cad + affineTransforms[3][6]) / 2; unlinearPointer[current[3]](point); point = postMatrix[3] * point;}
else if (result <probability4) { point = affineMatrix[4] * point; cad = (cad + affineTransforms[4][6]) / 2; unlinearPointer[current[4]](point); point = postMatrix[4] * point;}
else { point = affineMatrix[5] * point ; cad = (cad + affineTransforms[5][6]) / 2; unlinearPointer[current[5]](point); point = postMatrix[5] * point;}
if (i > 20) {
if (abs(point.x) > 5 * zoom || abs(point.y) > 5 * zoom)
continue;
temp = (unsigned int)((point.x + 5 * zoom) * (50 / zoom));
temp2 = (unsigned int)((point.y + 5 * zoom) * (50 / zoom));
histogram[temp][temp2][0] += 1;
if (histogram[temp][temp2][0] > max)
max = histogram[temp][temp2][0];
histogram[temp][temp2][1] = (histogram[temp][temp2][1] + cad) / 2;
}
}
sf::Image img;