[301] | 1 | // ----------------------------------------------------------------------- |
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[684] | 2 | // GaussSmooth2D.tcc: Member functions for the GaussSmooth2D class. |
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[301] | 3 | // ----------------------------------------------------------------------- |
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| 4 | // Copyright (C) 2006, Matthew Whiting, ATNF |
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| 5 | // |
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| 6 | // This program is free software; you can redistribute it and/or modify it |
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| 7 | // under the terms of the GNU General Public License as published by the |
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| 8 | // Free Software Foundation; either version 2 of the License, or (at your |
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| 9 | // option) any later version. |
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| 10 | // |
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| 11 | // Duchamp is distributed in the hope that it will be useful, but WITHOUT |
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| 12 | // ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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| 13 | // FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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| 14 | // for more details. |
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| 15 | // |
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| 16 | // You should have received a copy of the GNU General Public License |
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| 17 | // along with Duchamp; if not, write to the Free Software Foundation, |
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| 18 | // Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA |
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| 19 | // |
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| 20 | // Correspondence concerning Duchamp may be directed to: |
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| 21 | // Internet email: Matthew.Whiting [at] atnf.csiro.au |
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| 22 | // Postal address: Dr. Matthew Whiting |
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| 23 | // Australia Telescope National Facility, CSIRO |
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| 24 | // PO Box 76 |
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| 25 | // Epping NSW 1710 |
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| 26 | // AUSTRALIA |
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| 27 | // ----------------------------------------------------------------------- |
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[275] | 28 | #include <iostream> |
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[683] | 29 | #include <sstream> |
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| 30 | #include <duchamp/duchamp.hh> |
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[636] | 31 | #include <duchamp/config.h> |
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[275] | 32 | #include <math.h> |
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[635] | 33 | #ifdef HAVE_VALUES_H |
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| 34 | #include <values.h> |
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| 35 | #endif |
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[636] | 36 | #ifdef MAXFLOAT |
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| 37 | #define MAXVAL MAXFLOAT |
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| 38 | #else |
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| 39 | #define MAXVAL 1.e38F |
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| 40 | #endif |
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[638] | 41 | #include <duchamp/Utils/GaussSmooth2D.hh> |
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[275] | 42 | |
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[913] | 43 | using namespace duchamp; |
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| 44 | |
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[516] | 45 | template <class Type> |
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[682] | 46 | void GaussSmooth2D<Type>::defaults() |
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| 47 | { |
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| 48 | this->allocated=false; |
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| 49 | this->blankVal = Type(-99); |
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[1187] | 50 | this->kernWidth = 0; |
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[682] | 51 | } |
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| 52 | |
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| 53 | template <class Type> |
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[638] | 54 | GaussSmooth2D<Type>::GaussSmooth2D() |
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[275] | 55 | { |
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[682] | 56 | this->defaults(); |
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[419] | 57 | } |
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| 58 | |
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[516] | 59 | template <class Type> |
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[638] | 60 | GaussSmooth2D<Type>::~GaussSmooth2D() |
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[275] | 61 | { |
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[682] | 62 | if(this->allocated) delete [] kernel; |
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[419] | 63 | } |
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[275] | 64 | |
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[516] | 65 | template <class Type> |
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[638] | 66 | GaussSmooth2D<Type>::GaussSmooth2D(const GaussSmooth2D& g) |
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[365] | 67 | { |
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| 68 | operator=(g); |
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| 69 | } |
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| 70 | |
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[516] | 71 | template <class Type> |
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[638] | 72 | GaussSmooth2D<Type>& GaussSmooth2D<Type>::operator=(const GaussSmooth2D& g) |
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[365] | 73 | { |
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| 74 | if(this==&g) return *this; |
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| 75 | this->kernMaj = g.kernMaj; |
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| 76 | this->kernMin = g.kernMin; |
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| 77 | this->kernPA = g.kernPA; |
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| 78 | this->kernWidth = g.kernWidth; |
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| 79 | this->stddevScale = g.stddevScale; |
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[682] | 80 | this->blankVal = g.blankVal; |
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[526] | 81 | if(this->allocated) delete [] this->kernel; |
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[365] | 82 | this->allocated = g.allocated; |
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| 83 | if(this->allocated){ |
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[516] | 84 | this->kernel = new Type[this->kernWidth*this->kernWidth]; |
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[365] | 85 | for(int i=0;i<this->kernWidth*this->kernWidth;i++) |
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| 86 | this->kernel[i] = g.kernel[i]; |
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| 87 | } |
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| 88 | return *this; |
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| 89 | } |
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| 90 | |
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[516] | 91 | template <class Type> |
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[1279] | 92 | GaussSmooth2D<Type>::GaussSmooth2D(float maj, float min, float pa, float cutoff) |
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| 93 | { |
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| 94 | this->defaults(); |
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| 95 | this->define(maj, min, pa, cutoff); |
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| 96 | } |
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| 97 | |
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| 98 | template <class Type> |
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[638] | 99 | GaussSmooth2D<Type>::GaussSmooth2D(float maj, float min, float pa) |
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[275] | 100 | { |
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[682] | 101 | this->defaults(); |
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[1279] | 102 | this->define(maj, min, pa, 1./MAXVAL); |
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[419] | 103 | } |
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[275] | 104 | |
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[516] | 105 | template <class Type> |
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[638] | 106 | GaussSmooth2D<Type>::GaussSmooth2D(float maj) |
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[275] | 107 | { |
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[682] | 108 | this->defaults(); |
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[1279] | 109 | this->define(maj, maj, 0, 1./MAXVAL); |
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[419] | 110 | } |
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[275] | 111 | |
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[516] | 112 | template <class Type> |
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[1279] | 113 | void GaussSmooth2D<Type>::define(float maj, float min, float pa, float cutoff) |
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[275] | 114 | { |
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| 115 | |
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| 116 | this->kernMaj = maj; |
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| 117 | this->kernMin = min; |
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| 118 | this->kernPA = pa; |
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| 119 | |
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| 120 | // The parameters kernMaj & kernMin are the FWHM in the major and |
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| 121 | // minor axis directions. We correct these to the sigma_x and |
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| 122 | // sigma_y parameters for the 2D gaussian by halving and dividing by |
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| 123 | // sqrt(2 ln(2)). Actually work with sigma_x^2 to make things |
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| 124 | // easier. |
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| 125 | float sigmaX2 = (this->kernMaj*this->kernMaj/4.) / (2.*M_LN2); |
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| 126 | float sigmaY2 = (this->kernMin*this->kernMin/4.) / (2.*M_LN2); |
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| 127 | |
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[618] | 128 | // First determine the size of the kernel. Calculate the size based |
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| 129 | // on the number of pixels needed to make the exponential drop to |
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| 130 | // less than the minimum floating-point value. Use the major axis to |
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| 131 | // get the largest square that includes the ellipse. |
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[1187] | 132 | // float majorSigma = this->kernMaj / (4.*M_LN2); |
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| 133 | float majorSigma = this->kernMaj / (2*sqrt(2.*M_LN2)); |
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[1279] | 134 | // unsigned int kernelHW = (unsigned int)(ceil(majorSigma * sqrt(-2.*log(1. / MAXVAL)))); |
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| 135 | unsigned int kernelHW = (unsigned int)(ceil(majorSigma * sqrt(-2.*log(cutoff)))); |
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[275] | 136 | |
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[1187] | 137 | if(this->kernWidth == 0) this->kernWidth = size_t(2*kernelHW + 1); |
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[682] | 138 | else if(this->kernWidth < 2*kernelHW + 1){ |
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[913] | 139 | DUCHAMPWARN("GaussSmooth2D::define","You have provided a kernel smaller than optimal (" << this->kernWidth << " cf. " << 2*kernelHW + 1 <<")"); |
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[682] | 140 | } |
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[1279] | 141 | std::cout << "GaussSmooth2D - defined a kernel of full width " << this->kernWidth << " using cutoff="<<cutoff<< " and majorSigma="<<majorSigma<<"\n"; |
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[682] | 142 | |
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[275] | 143 | if(this->allocated) delete [] this->kernel; |
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[516] | 144 | this->kernel = new Type[this->kernWidth*this->kernWidth]; |
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[275] | 145 | this->allocated = true; |
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| 146 | this->stddevScale=0.; |
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[1189] | 147 | float posang = -1.*(this->kernPA+90.) * M_PI/180.; |
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[275] | 148 | |
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[1187] | 149 | float normalisation = 2. * M_PI * sqrt(sigmaX2*sigmaY2); |
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| 150 | for(size_t i=0;i<this->kernWidth;i++){ |
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| 151 | for(size_t j=0;j<this->kernWidth;j++){ |
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| 152 | float xpt = int(i-kernelHW)*sin(posang) - int(j-kernelHW)*cos(posang); |
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[275] | 153 | |
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[1187] | 154 | float ypt = int(i-kernelHW)*cos(posang) + int(j-kernelHW)*sin(posang); |
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[275] | 155 | float rsq = (xpt*xpt/sigmaX2) + (ypt*ypt/sigmaY2); |
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[1187] | 156 | this->kernel[i*this->kernWidth+j] = exp( -0.5 * rsq)/normalisation; |
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[1194] | 157 | this->stddevScale += kernel[i*this->kernWidth+j]*kernel[i*this->kernWidth+j]; |
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[275] | 158 | } |
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| 159 | } |
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[1187] | 160 | |
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| 161 | // std::cerr << "Normalisation = " << normalisation << ", kernSum = " << kernSum << ", kernel size = " << kernWidth << ", kernelHW = " << kernelHW <<", majorSigma = " << majorSigma << ", sigmaX2="<< sigmaX2 <<", sigmaY2="<<sigmaY2<<"\n"; |
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| 162 | |
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[1194] | 163 | // for(size_t i=0;i<this->kernWidth*this->kernWidth; i++) this->kernel[i] /= kernSum; |
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[275] | 164 | this->stddevScale = sqrt(this->stddevScale); |
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| 165 | } |
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| 166 | |
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[516] | 167 | template <class Type> |
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[1187] | 168 | Type *GaussSmooth2D<Type>::smooth(Type *input, size_t xdim, size_t ydim, EDGES edgeTreatment) |
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[275] | 169 | { |
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[528] | 170 | /// @details |
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| 171 | /// Smooth a given two-dimensional array, of dimensions xdim |
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| 172 | /// \f$\times\f$ ydim, with an elliptical gaussian. Simply runs as a |
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[1393] | 173 | /// front end to GaussSmooth2D::smooth(float *, int, int, vector<bool>) by |
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[528] | 174 | /// defining a mask that allows all pixels in the input array. |
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| 175 | /// |
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| 176 | /// \param input The 2D array to be smoothed. |
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| 177 | /// \param xdim The size of the x-dimension of the array. |
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| 178 | /// \param ydim The size of the y-dimension of the array. |
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| 179 | /// \return The smoothed array. |
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| 180 | |
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[516] | 181 | Type *smoothed; |
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[1393] | 182 | std::vector<bool> mask(xdim*ydim,true); |
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[682] | 183 | smoothed = this->smooth(input,xdim,ydim,mask,edgeTreatment); |
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[275] | 184 | return smoothed; |
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| 185 | } |
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| 186 | |
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[516] | 187 | template <class Type> |
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[1393] | 188 | Type *GaussSmooth2D<Type>::smooth(Type *input, size_t xdim, size_t ydim, std::vector<bool> mask, EDGES edgeTreatment) |
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[275] | 189 | { |
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[528] | 190 | /// @details |
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| 191 | /// Smooth a given two-dimensional array, of dimensions xdim |
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| 192 | /// \f$\times\f$ ydim, with an elliptical gaussian, where the |
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| 193 | /// boolean array mask defines which values of the array are valid. |
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| 194 | /// |
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| 195 | /// This function convolves the input array with the kernel that |
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| 196 | /// needs to have been defined. If it has not, the input array is |
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| 197 | /// returned unchanged. |
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| 198 | /// |
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| 199 | /// The mask should be the same size as the input array, and have |
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| 200 | /// values of true for entries that are considered valid, and false |
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| 201 | /// for entries that are not. For instance, arrays from FITS files |
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| 202 | /// should have the mask entries corresponding to BLANK pixels set |
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| 203 | /// to false. |
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| 204 | /// |
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| 205 | /// \param input The 2D array to be smoothed. |
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| 206 | /// \param xdim The size of the x-dimension of the array. |
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| 207 | /// \param ydim The size of the y-dimension of the array. |
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| 208 | /// \param mask The array showing which pixels in the input array |
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| 209 | /// are valid. |
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| 210 | /// \return The smoothed array. |
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[275] | 211 | |
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| 212 | if(!this->allocated) return input; |
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| 213 | else{ |
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| 214 | |
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[516] | 215 | Type *output = new Type[xdim*ydim]; |
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[275] | 216 | |
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[1187] | 217 | size_t pos,comp,xcomp,ycomp,fpos; |
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| 218 | int ct; |
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[516] | 219 | float fsum,kernsum=0; |
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[1187] | 220 | unsigned int kernelHW = this->kernWidth/2; |
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[275] | 221 | |
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[1187] | 222 | for(size_t i=0;i<this->kernWidth;i++) |
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| 223 | for(size_t j=0;j<this->kernWidth;j++) |
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[516] | 224 | kernsum += this->kernel[i*this->kernWidth+j]; |
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| 225 | |
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[1187] | 226 | for(size_t ypos = 0; ypos<ydim; ypos++){ |
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| 227 | for(size_t xpos = 0; xpos<xdim; xpos++){ |
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[275] | 228 | pos = ypos*xdim + xpos; |
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| 229 | |
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| 230 | if(!mask[pos]) output[pos] = input[pos]; |
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[682] | 231 | else if(edgeTreatment==TRUNCATE && |
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| 232 | ((xpos<=kernelHW)||((xdim-xpos)<=kernelHW)||(ypos<=kernelHW)||((ydim-ypos)<kernelHW))){ |
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| 233 | output[pos] = this->blankVal; |
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| 234 | } |
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[275] | 235 | else{ |
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| 236 | |
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| 237 | ct=0; |
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| 238 | fsum=0.; |
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| 239 | output[pos] = 0.; |
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| 240 | |
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[1187] | 241 | for(int yoff = -int(kernelHW); yoff<=int(kernelHW); yoff++){ |
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[275] | 242 | ycomp = ypos + yoff; |
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[1297] | 243 | if(ycomp<ydim){ |
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[275] | 244 | |
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[1187] | 245 | for(int xoff = -int(kernelHW); xoff<=int(kernelHW); xoff++){ |
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[275] | 246 | xcomp = xpos + xoff; |
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[1297] | 247 | if(xcomp<xdim){ |
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[275] | 248 | |
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| 249 | fpos = (xoff+kernelHW) + (yoff+kernelHW)*this->kernWidth; |
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| 250 | comp = ycomp*xdim + xcomp; |
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| 251 | if(mask[comp]){ |
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| 252 | ct++; |
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| 253 | fsum += this->kernel[fpos]; |
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| 254 | output[pos] += input[comp]*this->kernel[fpos]; |
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| 255 | } |
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| 256 | |
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| 257 | } |
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| 258 | } // xoff loop |
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| 259 | |
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| 260 | } |
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| 261 | }// yoff loop |
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[682] | 262 | // if(ct>0 && scaleByCoverage) output[pos] /= fsum; |
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| 263 | if(ct>0 && edgeTreatment==SCALEBYCOVERAGE) output[pos] *= kernsum/fsum; |
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[516] | 264 | |
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[275] | 265 | } // else{ |
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| 266 | |
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| 267 | } //xpos loop |
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| 268 | } //ypos loop |
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| 269 | |
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| 270 | return output; |
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| 271 | } |
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| 272 | |
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| 273 | } |
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