基于Orange Pi AIpro的OpenGL 3D 性能展示程序

/***************************************************************** Implementation of the fractional Brownian motion algorithm. These functions were originally the work of F. Kenton Musgrave. For documentation of the different functions please refer to the book: "Texturing and modeling: a procedural approach" by David S. Ebert et. al. ******************************************************************/ #if defined (_MSC_VER) #include <qglobal.h> #endif #include <time.h> #include <stdlib.h> #include "fbm.h" #if defined(Q_CC_MSVC) #pragma warning(disable:4244) #endif /* Definitions used by the noise2() functions */ //#define B 0x100 //#define BM 0xff #define B 0x20 #define BM 0x1f #define N 0x1000 #define NP 12 /* 2^N */ #define NM 0xfff static int p[B + B + 2]; static float g3[B + B + 2][3]; static float g2[B + B + 2][2]; static float g1[B + B + 2]; static int start = 1; static void init(void); #define s_curve(t) ( t * t * (3. - 2. * t) ) #define lerp(t, a, b) ( a + t * (b - a) ) #define setup(i,b0,b1,r0,r1)\ t = vec[i] + N;\ b0 = ((int)t) & BM;\ b1 = (b0+1) & BM;\ r0 = t - (int)t;\ r1 = r0 - 1.; #define at3(rx,ry,rz) ( rx * q[0] + ry * q[1] + rz * q[2] ) /* Fractional Brownian Motion function */ double fBm( Vector point, double H, double lacunarity, double octaves, int init ) { double value, frequency, remainder; int i; static double exponent_array[10]; float vec[3]; /* precompute and store spectral weights */ if ( init ) { start = 1; srand( time(0) ); /* seize required memory for exponent_array */ frequency = 1.0; for (i=0; i<=octaves; i++) { /* compute weight for each frequency */ exponent_array[i] = pow( frequency, -H ); frequency *= lacunarity; } } value = 0.0; /* initialize vars to proper values */ frequency = 1.0; vec[0]=point.x; vec[1]=point.y; vec[2]=point.z; /* inner loop of spectral construction */ for (i=0; i<octaves; i++) { /* value += noise3( vec ) * exponent_array[i];*/ value += noise3( vec ) * exponent_array[i]; vec[0] *= lacunarity; vec[1] *= lacunarity; vec[2] *= lacunarity; } /* for */ remainder = octaves - (int)octaves; if ( remainder ) /* add in ``octaves'' remainder */ /* ``i'' and spatial freq. are preset in loop above */ value += remainder * noise3( vec ) * exponent_array[i]; return( value ); } /* fBm() */ float noise3(float vec[3]) { int bx0, bx1, by0, by1, bz0, bz1, b00, b10, b01, b11; float rx0, rx1, ry0, ry1, rz0, rz1, *q, sy, sz, a, b, c, d, t, u, v; int i, j; if (start) { start = 0; init(); } setup(0, bx0,bx1, rx0,rx1); setup(1, by0,by1, ry0,ry1); setup(2, bz0,bz1, rz0,rz1); i = p[ bx0 ]; j = p[ bx1 ]; b00 = p[ i + by0 ]; b10 = p[ j + by0 ]; b01 = p[ i + by1 ]; b11 = p[ j + by1 ]; t = s_curve(rx0); sy = s_curve(ry0); sz = s_curve(rz0); q = g3[ b00 + bz0 ] ; u = at3(rx0,ry0,rz0); q = g3[ b10 + bz0 ] ; v = at3(rx1,ry0,rz0); a = lerp(t, u, v); q = g3[ b01 + bz0 ] ; u = at3(rx0,ry1,rz0); q = g3[ b11 + bz0 ] ; v = at3(rx1,ry1,rz0); b = lerp(t, u, v); c = lerp(sy, a, b); q = g3[ b00 + bz1 ] ; u = at3(rx0,ry0,rz1); q = g3[ b10 + bz1 ] ; v = at3(rx1,ry0,rz1); a = lerp(t, u, v); q = g3[ b01 + bz1 ] ; u = at3(rx0,ry1,rz1); q = g3[ b11 + bz1 ] ; v = at3(rx1,ry1,rz1); b = lerp(t, u, v); d = lerp(sy, a, b); return lerp(sz, c, d); } static void normalize2(float v[2]) { float s; s = sqrt(v[0] * v[0] + v[1] * v[1]); v[0] = v[0] / s; v[1] = v[1] / s; } static void normalize3(float v[3]) { float s; s = sqrt(v[0] * v[0] + v[1] * v[1] + v[2] * v[2]); v[0] = v[0] / s; v[1] = v[1] / s; v[2] = v[2] / s; } static void init(void) { int i, j, k; for (i = 0 ; i < B ; i++) { p[i] = i; g1[i] = (float)((rand() % (B + B)) - B) / B; for (j = 0 ; j < 2 ; j++) g2[i][j] = (float)((rand() % (B + B)) - B) / B; normalize2(g2[i]); for (j = 0 ; j < 3 ; j++) g3[i][j] = (float)((rand() % (B + B)) - B) / B; normalize3(g3[i]); } while (--i) { k = p[i]; p[i] = p[j = rand() % B]; p[j] = k; } for (i = 0 ; i < B + 2 ; i++) { p[B + i] = p[i]; g1[B + i] = g1[i]; for (j = 0 ; j < 2 ; j++) g2[B + i][j] = g2[i][j]; for (j = 0 ; j < 3 ; j++) g3[B + i][j] = g3[i][j]; } }