Example #1
0
    void SBGaussian::SBGaussianImpl::fillKValue(tmv::MatrixView<std::complex<double> > val,
                                                double kx0, double dkx, int izero,
                                                double ky0, double dky, int jzero) const
    {
        dbg<<"SBGaussian fillKValue\n";
        dbg<<"kx = "<<kx0<<" + i * "<<dkx<<", izero = "<<izero<<std::endl;
        dbg<<"ky = "<<ky0<<" + j * "<<dky<<", jzero = "<<jzero<<std::endl;
        if (izero != 0 || jzero != 0) {
            xdbg<<"Use Quadrant\n";
            fillKValueQuadrant(val,kx0,dkx,izero,ky0,dky,jzero);
        } else {
            xdbg<<"Non-Quadrant\n";
            assert(val.stepi() == 1);
            const int m = val.colsize();
            const int n = val.rowsize();
            typedef tmv::VIt<double,1,tmv::NonConj> It;

            kx0 *= _sigma;
            dkx *= _sigma;
            ky0 *= _sigma;
            dky *= _sigma;

            tmv::Vector<double> gauss_kx(m);
            It kxit = gauss_kx.begin();
            for (int i=0;i<m;++i,kx0+=dkx) *kxit++ = exp(-0.5 * kx0*kx0);
            tmv::Vector<double> gauss_ky(n);
            It kyit = gauss_ky.begin();
            for (int j=0;j<n;++j,ky0+=dky) *kyit++ = exp(-0.5 * ky0*ky0);

            val = _flux * gauss_kx ^ gauss_ky;
        }
    }
Example #2
0
    void SBGaussian::SBGaussianImpl::fillKImage(ImageView<std::complex<T> > im,
                                                double kx0, double dkx, int izero,
                                                double ky0, double dky, int jzero) const
    {
        dbg<<"SBGaussian fillKImage\n";
        dbg<<"kx = "<<kx0<<" + i * "<<dkx<<", izero = "<<izero<<std::endl;
        dbg<<"ky = "<<ky0<<" + j * "<<dky<<", jzero = "<<jzero<<std::endl;
        if (izero != 0 || jzero != 0) {
            xdbg<<"Use Quadrant\n";
            fillKImageQuadrant(im,kx0,dkx,izero,ky0,dky,jzero);
        } else {
            xdbg<<"Non-Quadrant\n";
            const int m = im.getNCol();
            const int n = im.getNRow();
            std::complex<T>* ptr = im.getData();
            int skip = im.getNSkip();
            assert(im.getStep() == 1);

            kx0 *= _sigma;
            dkx *= _sigma;
            ky0 *= _sigma;
            dky *= _sigma;

            // The Gaussian profile is separable:
            //    im(kx,ky) = _flux * exp(-0.5 * (kx*kx + ky*ky)
            //              = _flux * exp(-0.5 * kx*kx) * exp(-0.5 * ky*ky)
            std::vector<double> gauss_kx(m);
            std::vector<double> gauss_ky(n);
            typedef std::vector<double>::iterator It;
            It kxit = gauss_kx.begin();

            for (int i=0; i<m; ++i,kx0+=dkx) *kxit++ = fmath::expd(-0.5 * kx0*kx0);

            if ((kx0 == ky0) && (dkx == dky) && (m==n)) {
                gauss_ky = gauss_kx;
            } else {
                It kyit = gauss_ky.begin();
                for (int j=0; j<n; ++j,ky0+=dky) *kyit++ = fmath::expd(-0.5 * ky0*ky0);
            }

            for (int j=0; j<n; ++j,ptr+=skip) {
                for (int i=0; i<m; ++i)
                    *ptr++ = _flux * gauss_kx[i] * gauss_ky[j];
            }
        }
    }