Fill set of chaotic Fragment

A feature of generating an image through fragment is: writing an algorithm instead of generating any image, but generating an image or an algorithm. In short, when you write this algorithm or set relevant parameters, you can hardly guess what the image will look like. However, the image generation takes a long time and the parameters cannot be adjusted in real time. So I used the filling set method to calculate a small number of vertices first to display the approximate contour of the image. Confirm the parameters before generating the image. The so-called filling set is to randomly generate vertex positions. When the requirements are met, the vertex is retained; otherwise, the vertex is removed. Here we will fill in the set method to generate the Julia set, the mandeforo set and the Newton Iteration set.

(1) Julia set

// Fill Julia set // http://www.douban.com/note/230496472/class juliaset2: Public fractalequation {public: juliaset2 () {m_startx = 0.0f; m_starty = 0.0f; m_startz = 0.0f; m_parama = 0.11f; m_paramb = 0.615f; m_niteratecount = 80;} void iteratevalue (float X, float y, float Z, float & outx, float & outy, float & outz) const {x = outx = yf_rand_real (-1.0f, 1.0f); y = outy = yf_rand_real (-1.0f, 1.0f); float lengthsqr; float temp; int COUNT = 0; do {temp = x * x-y * Y + m_parama; y = 2 * x * Y + m_paramb; X = temp; lengthsqr = x * x + y * Y; count ++ ;}while (lengthsqr <4.0f) & (count <m_niteratecount); If (lengthsqr> 4.0f) {outx = 0.0f; outy = 0.0f;} outz = z;} bool isvalidparama () const {return true ;} bool isvalidparamb () const {return true;} PRIVATE: int m_niteratecount ;};

(2) Mandalay collection

// Mandalay collection // http://www.cnblogs.com/Ninputer/archive/2009/11/24/1609364.htmlclass mandelbrotset: Public fractalequation {public: sums () {m_startx = 0.0f; m_starty = 0.0f; m_startz = 0.0f; m_parama =-1.5f; m_paramb = 1.0f; m_paramc =-1.0f; m_paramd = 1.0f; m_niteratecount = 100;} void iteratevalue (float X, float y, float Z, float & outx, float & outy, float & outz) const {float Cr = m_parama + (m_paramb-m_parama) * (float) rand ()/rand_max); float CI = m_paramc + (m_paramd-m_paramc) * (float) rand ()/rand_max); outx = 0.0f; outy = 0.0f; float lengthsqr; float temp; int COUNT = 0; do {temp = outx * outx-outy * outy + CR; outy = 2 * outx * outy + ci; outx = temp; lengthsqr = outx * outx + outy * outy; count ++;} while (lengthsqr <4.0f) & (count <m_niteratecount); If (lengthsqr <4.0f) {outx = CR; outy = CI;} else {outx = 0.0f; outy = 0.0f ;} outz = z;} bool isvalidparama () const {return true;} bool isvalidparamb () const {return true;} bool isvalidparamc () const {return true;} bool isvalidparamd () const {return true;} PRIVATE: int m_niteratecount ;};

(3) Newton Iteration set

// Newton Iteration // http://www.douban.com/note/230496472/class newtoniterate: Public fractalequation {public: newtoniterate () {m_startx = 0.0f; m_starty = 0.0f; m_startz = 0.0f; m_parama = 1.0f; bytes = 64 ;} void iteratevalue (float X, float y, float Z, float & outx, float & outy, float & outz) const {x = outx = yf_rand_real (-m_parama, m_parama ); y = outy = yf_rand_real (-m_parama, m_parama); float x X, YY, D, TMP; For (INT I = 0; I <m_niteratecount; I ++) {xx = x * X; YY = y * Y; D = 3.0f * (xx-yy) + 4.0f * XX * YY); If (fabsf (d) <epsilon) {d = D> 0.0f? Epsilon:-Epsilon;} TMP = x; X = 0.666667f * x + (xx-yy)/d; y = 0.666667f * Y-2.0f * TMP * Y/d ;} if (x <0.0f) {outx = 0.0f; outy = 0.0f;} outz = z;} bool isvalidparama () const {return true;} PRIVATE: int m_niteratecount ;};

 

(4)

For the definition of the base class fractalequation, see chaos and fractal.

Several more images:

 

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Fill set of chaotic Fragment