本文整理汇总了C++中std::log1p方法的典型用法代码示例。如果您正苦于以下问题：C++ std::log1p方法的具体用法？C++ std::log1p怎么用？C++ std::log1p使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类std的用法示例。
在下文中一共展示了std::log1p方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: logpmf_dlaplace
inline double logpmf_dlaplace(double x, double p, double mu,
bool& throw_warning) {
#ifdef IEEE_754
if (ISNAN(x) || ISNAN(p) || ISNAN(mu))
return x+p+mu;
#endif
if (p <= 0.0 || p >= 1.0) {
throw_warning = true;
return NAN;
}
if (!isInteger(x))
return R_NegInf;
// (1.0-p)/(1.0+p) * pow(p, abs(x-mu));
return log1p(-p) - log1p(p) + log(p) * abs(x-mu);
} 示例2: cdf_dlaplace
inline double cdf_dlaplace(double x, double p, double mu,
bool& throw_warning) {
#ifdef IEEE_754
if (ISNAN(x) || ISNAN(p) || ISNAN(mu))
return x+p+mu;
#endif
if (p <= 0.0 || p >= 1.0) {
throw_warning = true;
return NAN;
}
if (x < 0.0) {
// pow(p, -floor(x-mu))/(1.0+p);
return exp( (log(p) * -floor(x-mu)) - log1p(p) );
} else {
// 1.0 - (pow(p, floor(x-mu)+1.0)/(1.0+p))
return 1.0 - exp( log(p) * (floor(x-mu)+1.0) - log1p(p) );
}
} 示例3: channels
bool
DeepData::split (int pixel, float depth)
{
#if OIIO_CPLUSPLUS_VERSION >= 11
using std::log1p;
using std::expm1;
#endif
bool splits_occurred = false;
int zchan = m_impl->m_z_channel;
int zbackchan = m_impl->m_zback_channel;
if (zchan < 0)
return false; // No channel labeled Z -- we don't know what to do
if (zbackchan < 0)
return false; // The samples are not extended -- nothing to split
int nchans = channels();
for (int s = 0; s < samples(pixel); ++s) {
float zf = deep_value (pixel, zchan, s); // z front
float zb = deep_value (pixel, zbackchan, s); // z back
if (zf < depth && zb > depth) {
// The sample spans depth, so split it.
// See http://www.openexr.com/InterpretingDeepPixels.pdf
splits_occurred = true;
insert_samples (pixel, s+1);
copy_deep_sample (pixel, s+1, *this, pixel, s);
set_deep_value (pixel, zbackchan, s, depth);
set_deep_value (pixel, zchan, s+1, depth);
// We have to proceed in two passes, since we may reuse the
// alpha values, we can't overwrite them yet.
for (int c = 0; c < nchans; ++c) {
int alphachan = m_impl->m_myalphachannel[c];
if (alphachan < 0 // No alpha
|| alphachan == c) // This is an alpha!
continue;
float a = clamp (deep_value (pixel, alphachan, s), 0.0f, 1.0f);
if (a == 1.0f) // Opaque or channels without alpha, we're done.
continue;
float xf = (depth - zf) / (zb - zf);
float xb = (zb - depth) / (zb - zf);
if (a > std::numeric_limits<float>::min()) {
float af = -expm1 (xf * log1p (-a));
float ab = -expm1 (xb * log1p (-a));
float val = deep_value (pixel, c, s);
set_deep_value (pixel, c, s, (af/a) * val);
set_deep_value (pixel, c, s+1, (ab/a) * val);
} else {
float val = deep_value (pixel, c, s);
set_deep_value (pixel, c, s, val * xf);
set_deep_value (pixel, c, s+1, val * xb);
}
}
// Now that we've adjusted the colors, do the alphas
for (int c = 0; c < nchans; ++c) {
int alphachan = m_impl->m_myalphachannel[c];
if (alphachan != c)
continue; // skip if not an alpha
float a = clamp (deep_value (pixel, alphachan, s), 0.0f, 1.0f);
if (a == 1.0f) // Opaque or channels without alpha, we're done.
continue;
float xf = (depth - zf) / (zb - zf);
float xb = (zb - depth) / (zb - zf);
if (a > std::numeric_limits<float>::min()) {
float af = -expm1 (xf * log1p (-a));
float ab = -expm1 (xb * log1p (-a));
set_deep_value (pixel, c, s, af);
set_deep_value (pixel, c, s+1, ab);
} else {
set_deep_value (pixel, c, s, a * xf);
set_deep_value (pixel, c, s+1, a * xb);
}
}
}
}
return splits_occurred;
}示例4: if
void
DeepData::merge_overlaps (int pixel)
{
#if OIIO_CPLUSPLUS_VERSION >= 11
using std::log1p;
#endif
int zchan = m_impl->m_z_channel;
int zbackchan = m_impl->m_zback_channel;
if (zchan < 0)
return; // No channel labeled Z -- we don't know what to do
if (zbackchan < 0)
zbackchan = zchan; // Missing Zback -- use Z
int nchans = channels();
for (int s = 1 /* YES, 1 */; s < samples(pixel); ++s) {
float zf = deep_value (pixel, zchan, s); // z front
float zb = deep_value (pixel, zbackchan, s); // z back
if (zf == deep_value (pixel, zchan, s-1) &&
zb == deep_value (pixel, zbackchan, s-1)) {
// The samples overlap exactly, merge them per
// See http://www.openexr.com/InterpretingDeepPixels.pdf
for (int c = 0; c < nchans; ++c) { // set the colors
int alphachan = m_impl->m_myalphachannel[c];
if (alphachan < 0)
continue; // Not color or alpha
if (alphachan == c)
continue; // Adjust the alphas in a second pass below
float a1 = (alphachan < 0) ? 1.0f :
clamp (deep_value (pixel, alphachan, s-1), 0.0f, 1.0f);
float a2 = (alphachan < 0) ? 1.0f :
clamp (deep_value (pixel, alphachan, s), 0.0f, 1.0f);
float c1 = deep_value (pixel, c, s-1);
float c2 = deep_value (pixel, c, s);
float am = a1 + a2 - a1 * a2;
float cm;
if (a1 == 1.0f && a2 == 1.0f)
cm = (c1 + c2) / 2.0f;
else if (a1 == 1.0f)
cm = c1;
else if (a2 == 1.0f)
cm = c2;
else {
static const float MAX = std::numeric_limits<float>::max();
float u1 = -log1p (-a1);
float v1 = (u1 < a1 * MAX)? u1 / a1: 1.0f;
float u2 = -log1p (-a2);
float v2 = (u2 < a2 * MAX)? u2 / a2: 1.0f;
float u = u1 + u2;
float w = (u > 1.0f || am < u * MAX)? am / u: 1.0f;
cm = (c1 * v1 + c2 * v2) * w;
}
set_deep_value (pixel, c, s-1, cm); // setting color
}
for (int c = 0; c < nchans; ++c) { // set the alphas
int alphachan = m_impl->m_myalphachannel[c];
if (alphachan != c)
continue; // This pass is only for alphas
float a1 = (alphachan < 0) ? 1.0f :
clamp (deep_value (pixel, alphachan, s-1), 0.0f, 1.0f);
float a2 = (alphachan < 0) ? 1.0f :
clamp (deep_value (pixel, alphachan, s), 0.0f, 1.0f);
float am = a1 + a2 - a1 * a2;
set_deep_value (pixel, c, s-1, am); // setting alpha
}
// Now eliminate sample s and revisit again
erase_samples (pixel, s, 1);
--s;
}
}
}