本文整理汇总了C++中Image2D::SetValue方法的典型用法代码示例。如果您正苦于以下问题：C++ Image2D::SetValue方法的具体用法？C++ Image2D::SetValue怎么用？C++ Image2D::SetValue使用的例子？那么, 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Image2D的用法示例。
在下文中一共展示了Image2D::SetValue方法的5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: MakeGaussianData
Image2D TestSetGenerator::MakeGaussianData(unsigned width, unsigned height)
{
Image2D image = Image2D::MakeUnsetImage(width, height);
for(unsigned y=0;y<height;++y) {
for(unsigned x=0;x<width;++x) {
image.SetValue(x, y, RNG::Gaussian());
}
}
return image;
}示例2: sampleRFIDistribution
Image2D TestSetGenerator::sampleRFIDistribution(unsigned width, unsigned height, double ig_over_rsq)
{
Image2D image = Image2D::MakeUnsetImage(width, height);
const double sigma = 1.0;
for(size_t f=0; f<height;++f) {
for(size_t t=0; t<width;++t) {
image.SetValue(t, f, Rand(Gaussian)*sigma + ig_over_rsq / RNG::Uniform());
}
}
return image;
}示例3: SetValueAt
void ImageTile::SetValueAt(Image2D &dest, unsigned frequencyIndex, unsigned scanIndex, long double newValue) {
return dest.SetValue(_scanOffset + scanIndex, _channelOffset + frequencyIndex, newValue);
}示例4: MakeTestSet
Image2D TestSetGenerator::MakeTestSet(int number, Mask2D& rfi, unsigned width, unsigned height, int gaussianNoise)
{
Image2D image;
switch(number)
{
case 0: // Image of all zero's
return Image2D::MakeZeroImage(width, height);
case 1: // Image of all ones
image = Image2D::MakeUnsetImage(width, height);
image.SetAll(1.0);
break;
case 2: // Noise
return MakeNoise(width, height, gaussianNoise);
case 3: { // Several broadband lines
image = MakeNoise(width, height, gaussianNoise);
AddBroadbandToTestSet(image, rfi, 1.0);
} break;
case 4: { // Several broadband lines
image = MakeNoise(width, height, gaussianNoise);
AddBroadbandToTestSet(image, rfi, 0.5);
} break;
case 5: { // Several broadband lines of random length
image = MakeNoise(width, height, gaussianNoise);
AddVarBroadbandToTestSet(image, rfi);
} break;
case 6: { // Different broadband lines + low freq background
image = MakeNoise(width, height, gaussianNoise);
AddVarBroadbandToTestSet(image, rfi);
for(unsigned y=0;y<image.Height();++y) {
for(unsigned x=0;x<image.Width();++x) {
image.AddValue(x, y, sinn(num_t(x)*M_PIn*5.0 / image.Width()) + 0.1);
}
}
} break;
case 7: { // Different broadband lines + high freq background
image = MakeNoise(width, height, gaussianNoise);
for(unsigned y=0;y<image.Height();++y) {
for(unsigned x=0;x<image.Width();++x) {
image.AddValue(x, y, sinn((long double) (x+y*0.1)*M_PIn*5.0L / image.Width() + 0.1));
image.AddValue(x, y, sinn((long double) (x+pown(y, 1.1))*M_PIn*50.0L / image.Width() + 0.1));
}
}
AddVarBroadbandToTestSet(image, rfi);
for(unsigned y=0;y<image.Height();++y) {
for(unsigned x=0;x<image.Width();++x) {
image.AddValue(x, y, 1.0);
}
}
} break;
case 8: { // Different droadband lines + smoothed&subtracted high freq background
image = MakeNoise(width, height, gaussianNoise);
for(unsigned y=0;y<image.Height();++y) {
for(unsigned x=0;x<image.Width();++x) {
image.AddValue(x, y, sinn((num_t) (x+y*0.1)*M_PIn*5.0 / image.Width() + 0.1));
image.AddValue(x, y, sinn((num_t) (x+pown(y, 1.1))*M_PIn*50.0 / image.Width() + 0.1));
}
}
SubtractBackground(image);
AddVarBroadbandToTestSet(image, rfi);
} break;
case 9: { //FFT of 7
image = MakeTestSet(7, rfi, width, height);
Image2D copy(image);
FFTTools::CreateHorizontalFFTImage(image, copy, false);
for(unsigned y=0;y<rfi.Height();++y) {
for(unsigned x=0;x<rfi.Width();++x) {
image.SetValue(x, y, image.Value(x, y) / sqrtn(image.Width()));
}
}
} break;
case 10: { // Identity matrix
image = Image2D::MakeZeroImage(width, height);
unsigned min = width < height ? width : height;
for(unsigned i=0;i<min;++i) {
image.SetValue(i, i, 1.0);
rfi.SetValue(i, i, true);
}
} break;
case 11: { // FFT of identity matrix
image = MakeTestSet(10, rfi, width, height);
Image2D copy(image);
FFTTools::CreateHorizontalFFTImage(image, copy, false);
for(unsigned y=0;y<rfi.Height();++y) {
for(unsigned x=0;x<rfi.Width();++x) {
image.SetValue(x, y, image.Value(x, y) / sqrtn(width));
}
}
} break;
case 12: { // Broadband contaminating all channels
image = MakeNoise(width, height, gaussianNoise);
for(unsigned y=0;y<image.Height();++y) {
for(unsigned x=0;x<image.Width();++x) {
image.AddValue(x, y, sinn((num_t) (x+y*0.1)*M_PIn*5.0 / image.Width() + 0.1));
image.AddValue(x, y, sinn((num_t) (x+powl(y, 1.1))*M_PIn*50.0 / image.Width() + 0.1));
}
}
AddBroadbandToTestSet(image, rfi, 1.0);
} break;
case 13: { // Model of three point sources with broadband RFI
SetModelData(image, rfi, 3);
//.........这里部分代码省略.........
示例5: main
//.........这里部分代码省略.........
unsigned upper = i+9;
if(upper > images) upper = images;
cout << "Adding image " << (i+1) << " - " << upper << "..." << endl;
}
bool skip = false;
if(removeNoiseImages > 0) {
for(std::vector<ImageInfo>::const_iterator j=variances.begin();j<variances.begin()+removeNoiseImages;++j)
{
if(j->index == i) { skip = true; break; }
}
}
if(!skip) {
long double wavelengthRatio;
if(images*inputCount > 1)
wavelengthRatio = (1.0 - (long double) (i+((int) inputIndex-(int) pindex)*images) / (images*inputCount-1.0));
else
wavelengthRatio = 0.5;
std::cout << "ratio=" << wavelengthRatio << '\n';
Image2D *image = Image2D::CreateFromFits(fitsfile, i);
if(subtract)
{
Image2D *imageB = Image2D::CreateFromFits(*subtractFits, i);
Image2D *AminB = Image2D::CreateFromDiff(*image, *imageB);
delete image;
image = AminB;
delete imageB;
}
if(window)
{
Image2D *empty = Image2D::CreateZeroImage(image->Width(), image->Height());
for(unsigned y=image->Height()-windowY-windowHeight;y<image->Height()-windowY;++y)
{
for(unsigned x=windowX;x<windowX+windowWidth;++x)
empty->SetValue(x, y, image->Value(x, y));
}
delete image;
image = empty;
}
if(cutWindow)
{
for(unsigned y=image->Height()-cutWindowY-cutWindowHeight;y<image->Height()-cutWindowY;++y)
{
for(unsigned x=cutWindowX;x<cutWindowX+cutWindowWidth;++x)
image->SetValue(x, y, 0.0);
}
}
if(fft) {
Image2D *fft = FFTTools::CreateFFTImage(*image, FFTTools::Absolute);
Image2D *fullfft = FFTTools::CreateFullImageFromFFT(*fft);
delete image;
delete fft;
image = fullfft;
}
long double max;
if(individualMaximization) {
max = image->GetMaximum();
if(max <= 0.0) max = 1.0;
} else {
max = 1.0;
}
if(displayMax)
cout << "max=" << image->GetMinimum() << ":" << image->GetMaximum() << endl;
if(rms)
ReportRMS(image);
long double r=0.0,g=0.0,b=0.0;
if(redblue) {