[37] | 1 | //#--------------------------------------------------------------------------- |
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| 2 | //# MathUtilities.cc: General math operations |
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| 3 | //#--------------------------------------------------------------------------- |
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| 4 | //# Copyright (C) 2004 |
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[125] | 5 | //# ATNF |
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[37] | 6 | //# |
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| 7 | //# This program is free software; you can redistribute it and/or modify it |
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| 8 | //# under the terms of the GNU General Public License as published by the Free |
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| 9 | //# Software Foundation; either version 2 of the License, or (at your option) |
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| 10 | //# any later version. |
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| 11 | //# |
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| 12 | //# This program is distributed in the hope that it will be useful, but |
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| 13 | //# WITHOUT ANY WARRANTY; without even the implied warranty of |
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| 14 | //# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General |
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| 15 | //# Public License for more details. |
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| 16 | //# |
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| 17 | //# You should have received a copy of the GNU General Public License along |
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| 18 | //# with this program; if not, write to the Free Software Foundation, Inc., |
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| 19 | //# 675 Massachusetts Ave, Cambridge, MA 02139, USA. |
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| 20 | //# |
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| 21 | //# Correspondence concerning this software should be addressed as follows: |
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| 22 | //# Internet email: Malte.Marquarding@csiro.au |
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| 23 | //# Postal address: Malte Marquarding, |
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| 24 | //# Australia Telescope National Facility, |
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| 25 | //# P.O. Box 76, |
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| 26 | //# Epping, NSW, 2121, |
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| 27 | //# AUSTRALIA |
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| 28 | //# |
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| 29 | //# $Id: |
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| 30 | //#--------------------------------------------------------------------------- |
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| 31 | |
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[125] | 32 | #include <casa/aips.h> |
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[176] | 33 | #include <casa/Arrays/Vector.h> |
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[1373] | 34 | #include <casa/Arrays/Slice.h> |
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[137] | 35 | #include <casa/Arrays/MaskedArray.h> |
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[136] | 36 | #include <casa/Arrays/MaskArrMath.h> |
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[465] | 37 | #include <casa/Arrays/VectorSTLIterator.h> |
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[136] | 38 | #include <casa/BasicSL/String.h> |
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[1373] | 39 | #include <scimath/Mathematics/MedianSlider.h> |
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[1819] | 40 | #include <casa/Exceptions/Error.h> |
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[37] | 41 | |
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[1570] | 42 | #include <scimath/Fitting/LinearFit.h> |
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| 43 | #include <scimath/Functionals/Polynomial.h> |
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| 44 | #include <scimath/Mathematics/AutoDiff.h> |
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| 45 | |
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| 46 | |
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[125] | 47 | #include "MathUtils.h" |
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| 48 | |
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| 49 | using namespace casa; |
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| 50 | |
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[829] | 51 | float mathutil::statistics(const String& which, |
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[996] | 52 | const MaskedArray<Float>& data) |
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[136] | 53 | { |
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| 54 | String str(which); |
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| 55 | str.upcase(); |
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[1819] | 56 | if (str.matches(String("MIN"))) { |
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[829] | 57 | return min(data); |
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[1819] | 58 | } else if (str.matches(String("MAX"))) { |
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[136] | 59 | return max(data); |
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[1819] | 60 | } else if (str.matches(String("SUMSQ"))) { |
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[136] | 61 | return sumsquares(data); |
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[1819] | 62 | } else if (str.matches(String("SUM"))) { |
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[136] | 63 | return sum(data); |
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[1819] | 64 | } else if (str.matches(String("MEAN"))) { |
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[136] | 65 | return mean(data); |
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[1819] | 66 | } else if (str.matches(String("VAR"))) { |
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[829] | 67 | return variance(data); |
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[1819] | 68 | } else if (str.matches(String("STDDEV"))) { |
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[136] | 69 | return stddev(data); |
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[1819] | 70 | } else if (str.matches(String("AVDEV"))) { |
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[136] | 71 | return avdev(data); |
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[1819] | 72 | } else if (str.matches(String("RMS"))) { |
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[136] | 73 | uInt n = data.nelementsValid(); |
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| 74 | return sqrt(sumsquares(data)/n); |
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[1819] | 75 | } else if (str.matches(String("MEDIAN"))) { |
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[136] | 76 | return median(data); |
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[1819] | 77 | } else { |
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| 78 | String msg = str + " is not a valid type of statistics"; |
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| 79 | throw(AipsError(msg)); |
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| 80 | } |
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[996] | 81 | return 0.0; |
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[136] | 82 | } |
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[176] | 83 | |
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[1819] | 84 | IPosition mathutil::minMaxPos(const String& which, |
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| 85 | const MaskedArray<Float>& data) |
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| 86 | { |
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| 87 | Float minVal, maxVal; |
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| 88 | IPosition minPos(data.ndim(), 0), maxPos(data.ndim(), 0); |
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| 89 | minMax(minVal, maxVal, minPos, maxPos, data); |
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| 90 | String str(which); |
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| 91 | str.upcase(); |
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| 92 | if (str.contains(String("MIN"))) { |
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| 93 | return minPos; |
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| 94 | } else if (str.contains(String("MAX"))) { |
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| 95 | return maxPos; |
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| 96 | } else { |
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| 97 | String msg = str + " is not a valid type of statistics"; |
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| 98 | throw(AipsError(msg)); |
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| 99 | } |
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| 100 | //return 0.0; |
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| 101 | } |
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[829] | 102 | |
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[209] | 103 | void mathutil::replaceMaskByZero(Vector<Float>& data, const Vector<Bool>& mask) |
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[176] | 104 | { |
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| 105 | for (uInt i=0; i<data.nelements(); i++) { |
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| 106 | if (!mask[i]) data[i] = 0.0; |
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| 107 | } |
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| 108 | } |
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[382] | 109 | |
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| 110 | |
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[829] | 111 | std::vector<std::string> mathutil::tovectorstring(const Vector<String>& in) |
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[382] | 112 | { |
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[465] | 113 | std::vector<std::string> out; |
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[1412] | 114 | out.reserve(in.nelements()); |
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| 115 | for (Array<String>::const_iterator it = in.begin(); it != in.end(); ++it) { |
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[465] | 116 | out.push_back(*it); |
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| 117 | } |
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| 118 | return out; |
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| 119 | } |
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| 120 | |
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[829] | 121 | Vector<String> mathutil::toVectorString(const std::vector<std::string>& in) |
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[465] | 122 | { |
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| 123 | Vector<String> out(in.size()); |
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[1412] | 124 | Array<String>::iterator oit = out.begin(); |
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| 125 | for (std::vector<std::string>::const_iterator it=in.begin() ; |
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| 126 | it != in.end(); ++it,++oit) { |
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| 127 | *oit = *it; |
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[465] | 128 | } |
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| 129 | return out; |
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| 130 | } |
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[1325] | 131 | |
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| 132 | void mathutil::hanning(Vector<Float>& out, Vector<Bool>& outmask, |
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| 133 | const Vector<Float>& in, const Vector<Bool>& mask, |
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| 134 | Bool relaxed, Bool ignoreOther) { |
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[2163] | 135 | (void) ignoreOther; //suppress unused warning |
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[1325] | 136 | Vector< Vector<Float> > weights(8); |
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| 137 | Vector<Float> vals(3); |
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| 138 | vals = 0.0;weights[0] = vals;// FFF |
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| 139 | vals[0] = 1.0; vals[1] = 0.0; vals[2] = 0.0; weights[1] = vals;// TFF |
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| 140 | vals[0] = 0.0; vals[1] = 1.0; vals[2] = 0.0; weights[2] = vals;// FTF |
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| 141 | vals[0] = 1.0/3.0; vals[1] = 2.0/3.0; vals[2] = 0.0; weights[3] = vals;// TTF |
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| 142 | vals[0] = 0.0; vals[1] = 0.0; vals[2] = 1.0;weights[4] = vals;// FFT |
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| 143 | vals[0] = 0.5; vals[1] = 0.0; vals[2] = 0.5; weights[5] = vals;// TFT |
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| 144 | vals[0] = 0.0; vals[1] = 2.0/3.0; vals[2] = 1.0/3.0; weights[6] = vals;// FTT |
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| 145 | vals[0] = 0.25; vals[1] = 0.5; vals[2] = 0.25; weights[7] = vals;// TTT |
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| 146 | // Chris' case |
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| 147 | Vector<Bool> weighted(8); |
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| 148 | if (relaxed) { |
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| 149 | weighted = False; |
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| 150 | weighted[7] = True; |
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| 151 | |
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| 152 | } else { |
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| 153 | weighted = True; |
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| 154 | weighted[0] = False; |
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| 155 | } |
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| 156 | |
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| 157 | out.resize(in.nelements()); |
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| 158 | outmask.resize(mask.nelements()); |
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| 159 | // make special case for first and last |
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| 160 | /// ...here |
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| 161 | // loop from 1..n-2 |
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| 162 | out.resize(in.nelements()); |
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| 163 | out[0] = in[0];out[out.nelements()-1] = in[in.nelements()-1]; |
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| 164 | outmask.resize(mask.nelements()); |
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[2125] | 165 | outmask[0] = mask[0]; outmask[outmask.nelements()-1] = mask[mask.nelements()-1]; |
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[1325] | 166 | uInt m;Vector<Float>* w; |
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| 167 | for (uInt i=1; i < out.nelements()-1;++i) { |
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| 168 | m = mask[i-1] + 2*mask[i] + 4*mask[i+1]; |
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| 169 | w = &(weights[m]); |
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| 170 | if (weighted[m]) { |
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| 171 | out[i] = (*w)[0]*in[i-1] + (*w)[1]*in[i] + (*w)[2]*in[i+1]; |
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| 172 | } else { // mask it |
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| 173 | out[i] = in[i];//use arbitrary value |
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| 174 | } |
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[2125] | 175 | outmask[i] = mask[i]; |
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[1325] | 176 | } |
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| 177 | } |
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[1373] | 178 | |
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| 179 | |
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| 180 | void mathutil::runningMedian(Vector<Float>& out, Vector<Bool>& outflag, |
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| 181 | const Vector<Float>& in, const Vector<Bool>& flag, |
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| 182 | float width) |
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| 183 | { |
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[2163] | 184 | uInt hwidth = Int(width+0.5); |
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| 185 | uInt fwidth = hwidth*2+1; |
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[1373] | 186 | out.resize(in.nelements()); |
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| 187 | outflag.resize(flag.nelements()); |
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| 188 | MedianSlider ms(hwidth); |
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| 189 | Slice sl(0, fwidth-1); |
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[1570] | 190 | Float medval = ms.add(const_cast<Vector<Float>& >(in)(sl), |
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[1373] | 191 | const_cast<Vector<Bool>& >(flag)(sl)); |
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[2163] | 192 | (void) medval;//suppress unused warning |
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[1373] | 193 | uInt n = in.nelements(); |
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| 194 | for (uInt i=hwidth; i<(n-hwidth); ++i) { |
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| 195 | // add data value |
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[1570] | 196 | out[i] = ms.add(in[i+hwidth], flag[i+hwidth]); |
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| 197 | outflag[i] = (ms.nval() == 0); |
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[1373] | 198 | } |
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[1570] | 199 | // replicate edge values from first value with full width of values |
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[1373] | 200 | for (uInt i=0;i<hwidth;++i) { |
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| 201 | out[i] = out[hwidth]; |
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[1570] | 202 | outflag[i] = outflag[hwidth]; |
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[1373] | 203 | out[n-1-i] = out[n-1-hwidth]; |
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[1570] | 204 | outflag[n-1-i] = outflag[n-1-hwidth]; |
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[1373] | 205 | } |
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| 206 | } |
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[1570] | 207 | |
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| 208 | void mathutil::polyfit(Vector<Float>& out, Vector<Bool>& outmask, |
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| 209 | const Vector<Float>& in, const Vector<Bool>& mask, |
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| 210 | float width, int order) |
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| 211 | { |
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[2163] | 212 | uInt hwidth = Int(width+0.5); |
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| 213 | uInt fwidth = hwidth*2+1; |
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[1570] | 214 | out.resize(in.nelements()); |
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| 215 | outmask.resize(mask.nelements()); |
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| 216 | LinearFit<Float> fitter; |
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| 217 | Polynomial<Float> poly(order); |
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| 218 | fitter.setFunction(poly); |
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| 219 | Vector<Float> sigma(fwidth); |
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| 220 | sigma = 1.0; |
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| 221 | Vector<Float> parms; |
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| 222 | Vector<Float> x(fwidth); |
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| 223 | indgen(x); |
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| 224 | |
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| 225 | uInt n = in.nelements(); |
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| 226 | |
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| 227 | for (uInt i=hwidth; i<(n-hwidth); ++i) { |
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| 228 | // add data value |
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| 229 | if (mask[i]) { |
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| 230 | Slice sl(i-hwidth, fwidth); |
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| 231 | const Vector<Float> &y = const_cast<Vector<Float>& >(in)(sl); |
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| 232 | const Vector<Bool> &m = const_cast<Vector<Bool>& >(mask)(sl); |
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| 233 | parms = fitter.fit(x, y, sigma, &m); |
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| 234 | |
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| 235 | poly.setCoefficients(parms); |
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| 236 | out[i] = poly(x[hwidth]);//cout << in[i] <<"->"<<out[i]<<endl; |
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| 237 | } else { |
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| 238 | out[i] = in[i]; |
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| 239 | } |
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| 240 | outmask[i] = mask[i]; |
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| 241 | } |
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| 242 | // replicate edge values from first value with full width of values |
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| 243 | for (uInt i=0;i<hwidth;++i) { |
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| 244 | out[i] = out[hwidth]; |
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| 245 | outmask[i] = outmask[hwidth]; |
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| 246 | out[n-1-i] = out[n-1-hwidth]; |
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| 247 | outmask[n-1-i] = outmask[n-1-hwidth]; |
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| 248 | } |
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| 249 | } |
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