SINF SINF文件是一个LTV+KV结构的文件，它的字段如下所示： sinf.frma: game sinf.schm: itun sinf.schi.user: 0xdeadbeef sinf.schi.key...: 0x00000005 sinf.schi.iviv: 0x12345678901234567890123456789012 sinf.schi.righ.veID: 0x000007d3 sinf.schi.righ.plat...: 0x00000000 sinf.schi.righ.aver: 0x01010100 sinf.schi.righ.tran: 0xdc64f80c sinf.schi.righ.sing: 0x00000000...sinf.schi.righ.song: 0x59a73c58 sinf.schi.righ.tool: P550 sinf.schi.righ.medi: 0x00000080 sinf.schi.righ.mode...: 0x00002000 sinf.schi.righ.hi32: 0x00000004 sinf.schi.name: User Name sinf.schi.priv: (432 Bytes Private
* (numSlices + 1) + j) * 3; if (vertices) { (*vertices)[vertex + 0] = radius * sinf...(angleStep * (float)i) * sinf(angleStep * (float)j); (*vertices)[vertex + 1]...= radius * cosf(angleStep * (float)i); (*vertices)[vertex + 2] = radius * sinf(angleStep
tmp; tmp = tp; float factor_w = -flag * M_PI / l; cmplx w = {cosf(factor_w), sinf...np, flag); float wexp0 = -2 * (float) M_PI * (flag) / (float) (n); cmplx wt = {cosf(wexp0), sinf...np, flag); float wexp0 = -2 * (float) M_PI * (flag) / (float) (n); cmplx wt = {cosf(wexp0), sinf...np, flag); float wexp0 = -2 * (float) M_PI * (flag) / (float) (n); cmplx wt = {cosf(wexp0), sinf...np, flag); float wexp0 = -2 * (float) M_PI * (flag) / (float) (n); cmplx wt = {cosf(wexp0), sinf
lines; int a = 10; for (float t = 0; t < 2 * M_PI; t += 0.001) { float x = 16 * pow(sinf
另一种则是使用这些函数代替： __expf(x) 代替 expf(x)； __logf(x) 代替 logf(x); __sinf(x) 代替 sinf(x); 以此类推，在函数名前面加两个下划线，可以将原数学函数替换为允许在精度上妥协而提升计算性能的数学函数
QVector lines; for (float t = 0; t < 2 * M_PI; t += 0.001) { float x = 16 * pow(sinf
（2）单精度测试 使用函数sinf 测试100次求平均是69.8个时钟周期一次： ?
.:-=+*#%@"); for (float t = 0.0f;; t += 0.1f) { int sy = 0; float s = sinf(t); float a = s
.:-=+*#%@"); for (float t = 0.0f;; t += 0.1f) { int sy = 0; float s = sinf(t);
分解成尾数和阶 using ::pow; //计算幂 using ::powf; //计算幂 using ::powl; //计算幂 using ::sin; //正弦 using ::sinf
不难看出，这里使用了C++中的cmath库，因此其中的sinf、cosf和sqrtf都来自这个库。 ? ?
time) { return std::powf(number::e, r_ * time) * (c1_ * std::cosf(w_ * time) + c2_ * std::sinf...power = std::powf(number::e, r_ * time); float cosine = std::cosf(w_ * time); float sine = std::sinf
if(is%2==0)system("color d"); else system("color c"); int sy = 0; float s = sinf
static float transY = 0.0; glMatrixMode(GL_MODELVIEW); glLoadIdentity(); glTranslatef(0.0, (GLfloat)(sinf
自身的半径大小 float x = center.x+cosf(2*M_PI/_itemCount*i)*(radius-25); float y = center.y+sinf
acosf() asinf() atanf() atan2f() ceilf() cosf() expf() fabsf() floorf() fmodf() logf() log10f() powf() sinf
static GLfloat z=-2.0; //1 static GLfloat spinX=0; static GLfloat spinY=0; glTranslatef(0.0, (GLfloat)(sinf
生成正弦波数据 for (int i = 0; i < numFrames; ++i) { float sampleValue = kAmplitude * sinf
当然，也可以通过如下代码来动态获取当前操作系统的分配粒度： SYSTEM_INFO sinf; GetSystemInfo(&sinf); DWORD dwAllocationGranularity...= sinf.dwAllocationGranularity; 参数dwNumberOfBytesToMap指定了数据文件的映射长度，这里需要特别指出的是，对于Windows
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