1 | //#--------------------------------------------------------------------------- |
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2 | //# SDLineFinder.cc: A class for automated spectral line search |
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3 | //#-------------------------------------------------------------------------- |
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4 | //# Copyright (C) 2004 |
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5 | //# ATNF |
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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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32 | |
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33 | // ASAP |
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34 | #include "SDLineFinder.h" |
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35 | |
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36 | // STL |
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37 | #include <iostream> |
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38 | |
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39 | using namespace asap; |
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40 | using namespace casa; |
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41 | using namespace std; |
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42 | using namespace boost::python; |
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43 | |
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44 | namespace asap { |
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45 | |
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46 | // An auxiliary class implementing one pass of the line search algorithm, |
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47 | // which uses a running mean. We define this class here because it is |
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48 | // used in SDLineFinder only. The incapsulation of this code into a separate |
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49 | // class will provide a possibility to add new algorithms with minor changes |
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50 | class LFRunningMean { |
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51 | // The input data to work with. Use reference symantics to avoid |
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52 | // an unnecessary copying |
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53 | const casa::Vector<casa::Float> &spectrum; // a buffer for the spectrum |
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54 | const casa::Vector<casa::Bool> &mask; // associated mask |
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55 | const std::pair<int,int> &edge; // start and stop+1 channels |
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56 | // to work with |
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57 | |
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58 | // statistics for running mean filtering |
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59 | casa::Float sum; // sum of fluxes |
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60 | casa::Float sumsq; // sum of squares of fluxes |
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61 | int box_chan_cntr; // actual number of channels in the box |
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62 | int max_box_nchan; // maximum allowed number of channels in the box |
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63 | // (calculated from boxsize and actual spectrum size) |
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64 | |
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65 | // temporary line edge channels and flag, which is True if the line |
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66 | // was detected in the previous channels. |
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67 | std::pair<int,int> cur_line; |
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68 | casa::Bool is_detected_before; |
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69 | int min_nchan; // A minimum number of consequtive |
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70 | // channels, which should satisfy |
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71 | // the detection criterion, to be |
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72 | // a detection |
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73 | casa::Float threshold; // detection threshold - the |
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74 | // minimal signal to noise ratio |
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75 | public: |
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76 | // set up the object with the references to actual data |
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77 | // as well as the detection criterion (min_nchan and threshold, see above) |
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78 | // and the number of channels in the running box |
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79 | LFRunningMean(const casa::Vector<casa::Float> &in_spectrum, |
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80 | const casa::Vector<casa::Bool> &in_mask, |
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81 | const std::pair<int,int> &in_edge, |
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82 | int in_max_box_nchan, |
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83 | int in_min_nchan = 3, |
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84 | casa::Float in_threshold = 5); |
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85 | |
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86 | // replace the detection criterion |
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87 | void setCriterion(int in_min_nchan, casa::Float in_threshold) throw(); |
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88 | |
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89 | // find spectral lines and add them into list |
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90 | void findLines(std::list<pair<int,int> > &lines) throw(casa::AipsError); |
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91 | |
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92 | protected: |
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93 | // supplementary function to control running mean calculations. |
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94 | // It adds a specified channel to the running mean box and |
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95 | // removes (ch-maxboxnchan+1)'th channel from there |
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96 | // Channels, for which the mask is false or index is beyond the |
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97 | // allowed range, are ignored |
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98 | void advanceRunningBox(int ch) throw(casa::AipsError); |
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99 | |
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100 | |
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101 | // test a channel against current running mean & rms |
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102 | // if channel specified is masked out or beyond the allowed indexes, |
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103 | // false is returned |
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104 | casa::Bool testChannel(int ch) const |
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105 | throw(std::exception, casa::AipsError); |
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106 | |
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107 | // process a channel: update curline and is_detected before and |
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108 | // add a new line to the list, if necessary using processCurLine() |
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109 | void processChannel(std::list<pair<int,int> > &lines, |
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110 | int ch) throw(casa::AipsError); |
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111 | |
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112 | // process the interval of channels stored in curline |
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113 | // if it satisfies the criterion, add this interval as a new line |
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114 | void processCurLine(std::list<pair<int,int> > &lines) throw(casa::AipsError); |
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115 | |
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116 | }; |
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117 | } // namespace asap |
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118 | |
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119 | /////////////////////////////////////////////////////////////////////////////// |
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120 | // |
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121 | // LFRunningMean - a running mean algorithm for line detection |
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122 | // |
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123 | // |
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124 | |
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125 | // set up the object with the references to actual data |
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126 | // as well as the detection criterion (min_nchan and threshold, see above) |
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127 | // and the number of channels in the running box |
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128 | LFRunningMean::LFRunningMean(const casa::Vector<casa::Float> &in_spectrum, |
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129 | const casa::Vector<casa::Bool> &in_mask, |
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130 | const std::pair<int,int> &in_edge, |
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131 | int in_max_box_nchan, |
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132 | int in_min_nchan, casa::Float in_threshold) : |
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133 | spectrum(in_spectrum), mask(in_mask), edge(in_edge), |
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134 | max_box_nchan(in_max_box_nchan), |
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135 | min_nchan(in_min_nchan),threshold(in_threshold) {} |
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136 | |
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137 | // replace the detection criterion |
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138 | void LFRunningMean::setCriterion(int in_min_nchan, casa::Float in_threshold) |
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139 | throw() |
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140 | { |
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141 | min_nchan=in_min_nchan; |
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142 | threshold=in_threshold; |
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143 | } |
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144 | |
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145 | |
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146 | // supplementary function to control running mean calculations. |
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147 | // It adds a specified channel to the running mean box and |
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148 | // removes (ch-max_box_nchan+1)'th channel from there |
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149 | // Channels, for which the mask is false or index is beyond the |
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150 | // allowed range, are ignored |
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151 | void LFRunningMean::advanceRunningBox(int ch) throw(AipsError) |
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152 | { |
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153 | if (ch>=edge.first && ch<edge.second) |
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154 | if (mask[ch]) { // ch is a valid channel |
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155 | ++box_chan_cntr; |
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156 | sum+=spectrum[ch]; |
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157 | sumsq+=square(spectrum[ch]); |
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158 | } |
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159 | int ch2remove=ch-max_box_nchan; |
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160 | if (ch2remove>=edge.first && ch2remove<edge.second) |
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161 | if (mask[ch2remove]) { // ch2remove is a valid channel |
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162 | --box_chan_cntr; |
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163 | sum-=spectrum[ch2remove]; |
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164 | sumsq-=square(spectrum[ch2remove]); |
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165 | } |
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166 | } |
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167 | |
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168 | // test a channel against current running mean & rms |
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169 | // if channel specified is masked out or beyond the allowed indexes, |
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170 | // false is returned |
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171 | Bool LFRunningMean::testChannel(int ch) const throw(exception, AipsError) |
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172 | { |
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173 | if (ch<edge.first || ch>=edge.second) return False; |
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174 | if (!mask[ch]) return False; |
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175 | DebugAssert(box_chan_cntr, AipsError); |
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176 | Float mean=sum/Float(box_chan_cntr); |
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177 | Float variance=sqrt(sumsq/Float(box_chan_cntr)-square(mean)); |
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178 | /* |
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179 | if (ch>3900 && ch<4100) |
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180 | cout<<"Tested "<<ch<<" mean="<<mean<<" variance="<<variance<<" sp-mean="<<spectrum[ch]-mean<<endl; |
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181 | */ |
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182 | return fabs(spectrum[ch]-mean)>=threshold*variance; |
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183 | } |
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184 | |
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185 | // process a channel: update cur_line and is_detected before and |
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186 | // add a new line to the list, if necessary |
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187 | void LFRunningMean::processChannel(std::list<pair<int,int> > &lines, |
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188 | int ch) throw(casa::AipsError) |
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189 | { |
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190 | try { |
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191 | if (testChannel(ch)) { |
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192 | if (is_detected_before) |
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193 | cur_line.second=ch+1; |
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194 | else { |
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195 | is_detected_before=True; |
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196 | cur_line.first=ch; |
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197 | cur_line.second=ch+1; |
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198 | } |
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199 | } else processCurLine(lines); |
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200 | } |
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201 | catch (const AipsError &ae) { |
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202 | throw; |
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203 | } |
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204 | catch (const exception &ex) { |
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205 | throw AipsError(String("SDLineFinder::processChannel - STL error: ")+ex.what()); |
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206 | } |
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207 | } |
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208 | |
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209 | // process the interval of channels stored in cur_line |
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210 | // if it satisfies the criterion, add this interval as a new line |
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211 | void LFRunningMean::processCurLine(std::list<pair<int,int> > &lines) |
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212 | throw(casa::AipsError) |
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213 | { |
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214 | try { |
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215 | if (is_detected_before) { |
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216 | if (cur_line.second-cur_line.first>min_nchan) { |
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217 | // it was a detection. We need to change the list |
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218 | Bool add_new_line=False; |
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219 | if (lines.size()) { |
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220 | for (int i=lines.back().second;i<cur_line.first;++i) |
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221 | if (mask[i]) { // one valid channel in between |
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222 | // means that we deal with a separate line |
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223 | add_new_line=True; |
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224 | break; |
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225 | } |
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226 | } else add_new_line=True; |
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227 | if (add_new_line) |
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228 | lines.push_back(cur_line); |
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229 | else lines.back().second=cur_line.second; |
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230 | } |
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231 | is_detected_before=False; |
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232 | } |
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233 | } |
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234 | catch (const AipsError &ae) { |
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235 | throw; |
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236 | } |
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237 | catch (const exception &ex) { |
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238 | throw AipsError(String("SDLineFinder::processCurLine - STL error: ")+ex.what()); |
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239 | } |
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240 | } |
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241 | |
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242 | // find spectral lines and add them into list |
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243 | void LFRunningMean::findLines(std::list<pair<int,int> > &lines) |
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244 | throw(casa::AipsError) |
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245 | { |
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246 | const int minboxnchan=4; |
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247 | |
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248 | // fill statistics for initial box |
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249 | box_chan_cntr=0; // no channels are currently in the box |
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250 | sum=0; // initialize statistics |
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251 | sumsq=0; |
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252 | int initial_box_ch=edge.first; |
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253 | for (;initial_box_ch<edge.second && box_chan_cntr<max_box_nchan; |
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254 | ++initial_box_ch) |
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255 | advanceRunningBox(initial_box_ch); |
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256 | |
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257 | if (initial_box_ch==edge.second) |
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258 | throw AipsError("LFRunningMean::findLines - too much channels are masked"); |
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259 | |
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260 | // actual search algorithm |
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261 | is_detected_before=False; |
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262 | |
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263 | if (box_chan_cntr>=minboxnchan) |
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264 | // there is a minimum amount of data. We can search in the |
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265 | // half of the initial box |
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266 | for (int n=edge.first;n<initial_box_ch-max_box_nchan/2;++n) |
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267 | processChannel(lines,n); |
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268 | |
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269 | // now the box can be moved. n+max_box_nchan/2 is a new index which haven't |
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270 | // yet been included in the running mean. |
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271 | for (int n=initial_box_ch-max_box_nchan/2;n<edge.second;++n) { |
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272 | advanceRunningBox(n+max_box_nchan/2); // update running mean & variance |
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273 | if (box_chan_cntr>=minboxnchan) // have enough data to process |
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274 | processChannel(lines,n); |
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275 | else processCurLine(lines); // just finish what was accumulated before |
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276 | } |
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277 | } |
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278 | |
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279 | // |
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280 | /////////////////////////////////////////////////////////////////////////////// |
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281 | |
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282 | |
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283 | // SDLineFinder - a class for automated spectral line search |
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284 | |
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285 | SDLineFinder::SDLineFinder() throw() : edge(0,0) |
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286 | { |
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287 | // detection threshold - the minimal signal to noise ratio |
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288 | threshold=3.; // 3 sigma is a default |
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289 | box_size=1./16.; // default box size for running mean calculations is |
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290 | // 1/16 of the whole spectrum |
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291 | // A minimum number of consequtive channels, which should satisfy |
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292 | // the detection criterion, to be a detection |
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293 | min_nchan=3; // default is 3 channels |
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294 | } |
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295 | |
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296 | SDLineFinder::~SDLineFinder() throw(AipsError) {} |
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297 | |
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298 | // set scan to work with (in_scan parameter), associated mask (in_mask |
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299 | // parameter) and the edge channel rejection (in_edge parameter) |
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300 | // if in_edge has zero length, all channels chosen by mask will be used |
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301 | // if in_edge has one element only, it represents the number of |
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302 | // channels to drop from both sides of the spectrum |
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303 | // in_edge is introduced for convinience, although all functionality |
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304 | // can be achieved using a spectrum mask only |
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305 | void SDLineFinder::setScan(const SDMemTableWrapper &in_scan, |
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306 | const std::vector<bool> &in_mask, |
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307 | const boost::python::tuple &in_edge) throw(AipsError) |
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308 | { |
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309 | try { |
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310 | scan=in_scan.getCP(); |
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311 | AlwaysAssert(!scan.null(),AipsError); |
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312 | if (scan->nRow()!=1) |
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313 | throw AipsError("SDLineFinder::setScan - in_scan contains more than 1 row." |
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314 | "Choose one first."); |
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315 | mask=in_mask; |
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316 | if (mask.nelements()!=scan->nChan()) |
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317 | throw AipsError("SDLineFinder::setScan - in_scan and in_mask have different" |
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318 | "number of spectral channels."); |
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319 | |
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320 | // number of elements in the in_edge tuple |
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321 | int n=extract<int>(in_edge.attr("__len__")()); |
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322 | if (n>2 || n<0) |
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323 | throw AipsError("SDLineFinder::setScan - the length of the in_edge parameter" |
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324 | "should not exceed 2"); |
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325 | if (!n) { |
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326 | // all spectrum, no rejection |
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327 | edge.first=0; |
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328 | edge.second=scan->nChan(); |
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329 | } else { |
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330 | edge.first=extract<int>(in_edge.attr("__getitem__")(0)); |
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331 | if (edge.first<0) |
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332 | throw AipsError("SDLineFinder::setScan - the in_edge parameter has a negative" |
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333 | "number of channels to drop"); |
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334 | if (edge.first>=scan->nChan()) |
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335 | throw AipsError("SDLineFinder::setScan - all channels are rejected by the in_edge parameter"); |
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336 | if (n==2) { |
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337 | edge.second=extract<int>(in_edge.attr("__getitem__")(1)); |
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338 | if (edge.second<0) |
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339 | throw AipsError("SDLineFinder::setScan - the in_edge parameter has a negative" |
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340 | "number of channels to drop"); |
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341 | edge.second=scan->nChan()-edge.second; |
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342 | } else edge.second=scan->nChan()-edge.first; |
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343 | if (edge.second<0 || (edge.second+edge.first)>scan->nChan()) |
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344 | throw AipsError("SDLineFinder::setScan - all channels are rejected by the in_edge parameter"); |
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345 | } |
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346 | } |
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347 | catch(const AipsError &ae) { |
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348 | // setScan is unsuccessfull, reset scan/mask/edge |
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349 | scan=CountedConstPtr<SDMemTable>(); // null pointer |
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350 | mask.resize(0); |
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351 | edge=pair<int,int>(0,0); |
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352 | throw; |
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353 | } |
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354 | } |
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355 | |
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356 | // search for spectral lines. Number of lines found is returned |
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357 | int SDLineFinder::findLines() throw(casa::AipsError) |
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358 | { |
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359 | const int minboxnchan=4; |
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360 | if (scan.null()) |
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361 | throw AipsError("SDLineFinder::findLines - a scan should be set first," |
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362 | " use set_scan"); |
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363 | DebugAssert(mask.nelements()==scan->nChan(), AipsError); |
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364 | int max_box_nchan=int(scan->nChan()*box_size); // number of channels in running |
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365 | // box |
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366 | if (max_box_nchan<2) |
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367 | throw AipsError("SDLineFinder::findLines - box_size is too small"); |
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368 | |
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369 | scan->getSpectrum(spectrum); |
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370 | |
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371 | lines.resize(0); // search from the scratch |
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372 | Vector<Bool> temp_mask(mask); |
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373 | size_t cursz; |
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374 | do { |
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375 | cursz=lines.size(); |
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376 | // line find algorithm |
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377 | LFRunningMean lfalg(spectrum,temp_mask,edge,max_box_nchan,min_nchan,threshold); |
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378 | lfalg.findLines(lines); |
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379 | temp_mask=getMask(); |
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380 | } while (cursz!=lines.size()); |
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381 | return int(lines.size()); |
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382 | } |
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383 | |
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384 | |
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385 | // get the mask to mask out all lines that have been found (default) |
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386 | // if invert=true, only channels belong to lines will be unmasked |
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387 | // Note: all channels originally masked by the input mask (in_mask |
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388 | // in setScan) or dropped out by the edge parameter (in_edge |
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389 | // in setScan) are still excluded regardless on the invert option |
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390 | std::vector<bool> SDLineFinder::getMask(bool invert) |
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391 | const throw(casa::AipsError) |
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392 | { |
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393 | try { |
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394 | if (scan.null()) |
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395 | throw AipsError("SDLineFinder::getMask - a scan should be set first," |
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396 | " use set_scan followed by find_lines"); |
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397 | DebugAssert(mask.nelements()==scan->nChan(), AipsError); |
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398 | /* |
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399 | if (!lines.size()) |
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400 | throw AipsError("SDLineFinder::getMask - one have to search for " |
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401 | "lines first, use find_lines"); |
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402 | */ |
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403 | std::vector<bool> res_mask(mask.nelements()); |
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404 | // iterator through lines |
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405 | std::list<std::pair<int,int> >::const_iterator cli=lines.begin(); |
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406 | for (int ch=0;ch<res_mask.size();++ch) |
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407 | if (ch<edge.first || ch>=edge.second) res_mask[ch]=false; |
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408 | else if (!mask[ch]) res_mask[ch]=false; |
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409 | else { |
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410 | res_mask[ch]=!invert; // no line by default |
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411 | if (cli==lines.end()) continue; |
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412 | if (ch>=cli->first && ch<cli->second) |
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413 | res_mask[ch]=invert; // this is a line |
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414 | if (ch>=cli->second) |
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415 | ++cli; // next line in the list |
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416 | } |
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417 | |
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418 | return res_mask; |
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419 | } |
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420 | catch (const AipsError &ae) { |
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421 | throw; |
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422 | } |
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423 | catch (const exception &ex) { |
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424 | throw AipsError(String("SDLineFinder::getMask - STL error: ")+ex.what()); |
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425 | } |
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426 | } |
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427 | |
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428 | // get range for all lines found. If defunits is true (default), the |
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429 | // same units as used in the scan will be returned (e.g. velocity |
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430 | // instead of channels). If defunits is false, channels will be returned |
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431 | std::vector<int> SDLineFinder::getLineRanges(bool defunits) |
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432 | const throw(casa::AipsError) |
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433 | { |
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434 | try { |
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435 | if (scan.null()) |
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436 | throw AipsError("SDLineFinder::getLineRanges - a scan should be set first," |
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437 | " use set_scan followed by find_lines"); |
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438 | DebugAssert(mask.nelements()==scan->nChan(), AipsError); |
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439 | |
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440 | if (!lines.size()) |
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441 | throw AipsError("SDLineFinder::getLineRanges - one have to search for " |
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442 | "lines first, use find_lines"); |
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443 | |
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444 | // temporary |
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445 | if (defunits) |
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446 | throw AipsError("SDLineFinder::getLineRanges - sorry, defunits=true have not " |
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447 | "yet been implemented"); |
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448 | // |
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449 | std::vector<int> res(2*lines.size()); |
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450 | // iterator through lines & result |
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451 | std::list<std::pair<int,int> >::const_iterator cli=lines.begin(); |
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452 | std::vector<int>::iterator ri=res.begin(); |
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453 | for (;cli!=lines.end() && ri!=res.end();++cli,++ri) { |
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454 | *ri=cli->first; |
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455 | if (++ri!=res.end()) |
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456 | *ri=cli->second-1; |
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457 | } |
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458 | return res; |
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459 | } |
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460 | catch (const AipsError &ae) { |
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461 | throw; |
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462 | } |
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463 | catch (const exception &ex) { |
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464 | throw AipsError(String("SDLineFinder::getLineRanges - STL error: ")+ex.what()); |
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465 | } |
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466 | } |
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467 | |
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468 | // concatenate two lists preserving the order. If two lines appear to |
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469 | // be adjacent, they are joined into the new one |
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470 | void SDLineFinder::addNewSearchResult(const std::list<pair<int, int> > &newlines) |
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471 | throw(AipsError) |
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472 | { |
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473 | try { |
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474 | for (std::list<pair<int,int> >::const_iterator cli=newlines.begin(); |
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475 | cli!=newlines.end();++cli) { |
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476 | // search for a right place for the new line |
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477 | //TODO |
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478 | } |
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479 | } |
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480 | catch (const AipsError &ae) { |
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481 | throw; |
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482 | } |
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483 | catch (const exception &ex) { |
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484 | throw AipsError(String("SDLineFinder::addNewSearchResult - STL error: ")+ex.what()); |
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485 | } |
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486 | |
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487 | } |
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