- Timestamp:
- 03/30/11 21:43:43 (14 years ago)
- Location:
- branches/casa-prerelease/pre-asap
- Files:
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- 15 edited
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branches/casa-prerelease/pre-asap
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branches/casa-prerelease/pre-asap/Makefile
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branches/casa-prerelease/pre-asap/SConstruct
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branches/casa-prerelease/pre-asap/apps
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branches/casa-prerelease/pre-asap/external-alma
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branches/casa-prerelease/pre-asap/external-alma/atnf/pks/pks_maths.cc
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branches/casa-prerelease/pre-asap/getsvnrev.sh
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branches/casa-prerelease/pre-asap/python
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/trunk/python merged: 2081
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branches/casa-prerelease/pre-asap/python/scantable.py
r2047 r2082 2070 2070 2071 2071 @asaplog_post_dec 2072 def sinusoid_baseline(self, insitu=None, mask=None, minnwave=None, maxnwave=None, 2073 clipthresh=None, clipniter=None, plot=None, outlog=None, blfile=None): 2074 """\ 2075 Return a scan which has been baselined (all rows) by cubic spline function (piecewise cubic polynomial). 2076 Parameters: 2077 insitu: If False a new scantable is returned. 2078 Otherwise, the scaling is done in-situ 2079 The default is taken from .asaprc (False) 2080 mask: An optional mask 2081 minnwave: Minimum wave number in spectral window (default is 0) 2082 maxnwave: Maximum wave number in spectral window (default is 3) 2083 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 2084 clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 1) 2085 plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** 2086 plot the fit and the residual. In this each 2087 indivual fit has to be approved, by typing 'y' 2088 or 'n' 2089 outlog: Output the coefficients of the best-fit 2090 function to logger (default is False) 2091 blfile: Name of a text file in which the best-fit 2092 parameter values to be written 2093 (default is "": no file/logger output) 2072 def sinusoid_baseline(self, insitu=None, mask=None, nwave=None, maxwavelength=None, 2073 clipthresh=None, clipniter=None, plot=None, getresidual=None, outlog=None, blfile=None): 2074 """\ 2075 Return a scan which has been baselined (all rows) by sinusoidal functions. 2076 Parameters: 2077 insitu: If False a new scantable is returned. 2078 Otherwise, the scaling is done in-situ 2079 The default is taken from .asaprc (False) 2080 mask: An optional mask 2081 nwave: the maximum wave number of sinusoids within 2082 maxwavelength * (spectral range). 2083 The default is 3 (i.e., sinusoids with wave 2084 number of 0(=constant), 1, 2, and 3 are 2085 used for fitting). Also it is possible to 2086 explicitly specify all the wave numbers to 2087 be used, by giving a list including them 2088 (e.g. [0,1,2,15,16]). 2089 maxwavelength: the longest sinusoidal wavelength. The 2090 default is 1.0 (unit: spectral range). 2091 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 2092 clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 1) 2093 plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** 2094 plot the fit and the residual. In this each 2095 indivual fit has to be approved, by typing 'y' 2096 or 'n' 2097 getresidual: if False, returns best-fit values instead of 2098 residual. (default is True) 2099 outlog: Output the coefficients of the best-fit 2100 function to logger (default is False) 2101 blfile: Name of a text file in which the best-fit 2102 parameter values to be written 2103 (default is "": no file/logger output) 2094 2104 2095 2105 Example: 2096 2106 # return a scan baselined by a combination of sinusoidal curves having 2097 # wave numbers in spectral window from 1to 10,2107 # wave numbers in spectral window up to 10, 2098 2108 # also with 3-sigma clipping, iteration up to 4 times 2099 bscan = scan.sinusoid_baseline(maxnwave=10,clipthresh=3.0,clipniter=4) 2109 bscan = scan.sinusoid_baseline(nwave=10,clipthresh=3.0,clipniter=4) 2110 2111 Note: 2112 The best-fit parameter values output in logger and/or blfile are now 2113 based on specunit of 'channel'. 2100 2114 """ 2101 2115 … … 2110 2124 nchan = workscan.nchan() 2111 2125 2112 if mask is None: mask = [True for i in xrange(nchan)] 2113 if minnwave is None: minnwave = 0 2114 if maxnwave is None: maxnwave = 3 2115 if clipthresh is None: clipthresh = 3.0 2116 if clipniter is None: clipniter = 1 2117 if plot is None: plot = False 2118 if outlog is None: outlog = False 2119 if blfile is None: blfile = "" 2120 2126 if mask is None: mask = [True for i in xrange(nchan)] 2127 if nwave is None: nwave = 3 2128 if maxwavelength is None: maxwavelength = 1.0 2129 if clipthresh is None: clipthresh = 3.0 2130 if clipniter is None: clipniter = 1 2131 if plot is None: plot = False 2132 if getresidual is None: getresidual = True 2133 if outlog is None: outlog = False 2134 if blfile is None: blfile = "" 2135 2136 if isinstance(nwave, int): 2137 in_nwave = nwave 2138 nwave = [] 2139 for i in xrange(in_nwave+1): nwave.append(i) 2140 2121 2141 outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) 2122 2142 2123 2143 try: 2124 #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic splinefitting is implemented as a fitter method.2125 workscan._sinusoid_baseline(mask, minnwave, maxnwave, clipthresh, clipniter, outlog, blfile)2144 #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. 2145 workscan._sinusoid_baseline(mask, nwave, maxwavelength, clipthresh, clipniter, getresidual, outlog, blfile) 2126 2146 2127 2147 workscan._add_history("sinusoid_baseline", varlist) … … 2142 2162 2143 2163 2144 def auto_sinusoid_baseline(self, insitu=None, mask=None, minnwave=None, maxnwave=None,2164 def auto_sinusoid_baseline(self, insitu=None, mask=None, nwave=None, maxwavelength=None, 2145 2165 clipthresh=None, clipniter=None, edge=None, threshold=None, 2146 chan_avg_limit=None, plot=None, outlog=None, blfile=None):2166 chan_avg_limit=None, plot=None, getresidual=None, outlog=None, blfile=None): 2147 2167 """\ 2148 2168 Return a scan which has been baselined (all rows) by cubic spline … … 2152 2172 2153 2173 Parameters: 2154 insitu: if False a new scantable is returned. 2155 Otherwise, the scaling is done in-situ 2156 The default is taken from .asaprc (False) 2157 mask: an optional mask retreived from scantable 2158 minnwave: Minimum wave number in spectral window (default is 0) 2159 maxnwave: Maximum wave number in spectral window (default is 3) 2160 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 2161 clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 1) 2162 edge: an optional number of channel to drop at 2163 the edge of spectrum. If only one value is 2164 specified, the same number will be dropped 2165 from both sides of the spectrum. Default 2166 is to keep all channels. Nested tuples 2167 represent individual edge selection for 2168 different IFs (a number of spectral channels 2169 can be different) 2170 threshold: the threshold used by line finder. It is 2171 better to keep it large as only strong lines 2172 affect the baseline solution. 2173 chan_avg_limit: 2174 a maximum number of consequtive spectral 2175 channels to average during the search of 2176 weak and broad lines. The default is no 2177 averaging (and no search for weak lines). 2178 If such lines can affect the fitted baseline 2179 (e.g. a high order polynomial is fitted), 2180 increase this parameter (usually values up 2181 to 8 are reasonable). Most users of this 2182 method should find the default value sufficient. 2183 plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** 2184 plot the fit and the residual. In this each 2185 indivual fit has to be approved, by typing 'y' 2186 or 'n' 2187 outlog: Output the coefficients of the best-fit 2188 function to logger (default is False) 2189 blfile: Name of a text file in which the best-fit 2190 parameter values to be written 2191 (default is "": no file/logger output) 2174 insitu: if False a new scantable is returned. 2175 Otherwise, the scaling is done in-situ 2176 The default is taken from .asaprc (False) 2177 mask: an optional mask retreived from scantable 2178 nwave: the maximum wave number of sinusoids within 2179 maxwavelength * (spectral range). 2180 The default is 3 (i.e., sinusoids with wave 2181 number of 0(=constant), 1, 2, and 3 are 2182 used for fitting). Also it is possible to 2183 explicitly specify all the wave numbers to 2184 be used, by giving a list including them 2185 (e.g. [0,1,2,15,16]). 2186 maxwavelength: the longest sinusoidal wavelength. The 2187 default is 1.0 (unit: spectral range). 2188 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 2189 clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 1) 2190 edge: an optional number of channel to drop at 2191 the edge of spectrum. If only one value is 2192 specified, the same number will be dropped 2193 from both sides of the spectrum. Default 2194 is to keep all channels. Nested tuples 2195 represent individual edge selection for 2196 different IFs (a number of spectral channels 2197 can be different) 2198 threshold: the threshold used by line finder. It is 2199 better to keep it large as only strong lines 2200 affect the baseline solution. 2201 chan_avg_limit:a maximum number of consequtive spectral 2202 channels to average during the search of 2203 weak and broad lines. The default is no 2204 averaging (and no search for weak lines). 2205 If such lines can affect the fitted baseline 2206 (e.g. a high order polynomial is fitted), 2207 increase this parameter (usually values up 2208 to 8 are reasonable). Most users of this 2209 method should find the default value sufficient. 2210 plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** 2211 plot the fit and the residual. In this each 2212 indivual fit has to be approved, by typing 'y' 2213 or 'n' 2214 getresidual: if False, returns best-fit values instead of 2215 residual. (default is True) 2216 outlog: Output the coefficients of the best-fit 2217 function to logger (default is False) 2218 blfile: Name of a text file in which the best-fit 2219 parameter values to be written 2220 (default is "": no file/logger output) 2192 2221 2193 2222 Example: 2194 bscan = scan.auto_sinusoid_baseline(maxnwave=10, insitu=False) 2223 bscan = scan.auto_sinusoid_baseline(nwave=10, insitu=False) 2224 2225 Note: 2226 The best-fit parameter values output in logger and/or blfile are now 2227 based on specunit of 'channel'. 2195 2228 """ 2196 2229 … … 2205 2238 nchan = workscan.nchan() 2206 2239 2207 if mask is None: mask= [True for i in xrange(nchan)]2208 if minnwave is None: minnwave = 02209 if max nwave is None: maxnwave = 32210 if clipthresh is None: clipthresh= 3.02211 if clipniter is None: clipniter= 12212 if edge is None: edge = (0,0)2213 if threshold is None: threshold= 32240 if mask is None: mask = [True for i in xrange(nchan)] 2241 if nwave is None: nwave = 3 2242 if maxwavelength is None: maxwavelength = 1.0 2243 if clipthresh is None: clipthresh = 3.0 2244 if clipniter is None: clipniter = 1 2245 if edge is None: edge = (0,0) 2246 if threshold is None: threshold = 3 2214 2247 if chan_avg_limit is None: chan_avg_limit = 1 2215 if plot is None: plot = False 2216 if outlog is None: outlog = False 2217 if blfile is None: blfile = "" 2248 if plot is None: plot = False 2249 if getresidual is None: getresidual = True 2250 if outlog is None: outlog = False 2251 if blfile is None: blfile = "" 2218 2252 2219 2253 outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) … … 2221 2255 from asap.asaplinefind import linefinder 2222 2256 from asap import _is_sequence_or_number as _is_valid 2257 2258 if isinstance(nwave, int): 2259 in_nwave = nwave 2260 nwave = [] 2261 for i in xrange(in_nwave+1): nwave.append(i) 2223 2262 2224 2263 if not (isinstance(edge, list) or isinstance(edge, tuple)): edge = [ edge ] … … 2244 2283 2245 2284 try: 2246 #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic splinefitting is implemented as a fitter method.2285 #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. 2247 2286 if individualedge: 2248 2287 curedge = [] … … 2250 2289 curedge += edge[i] 2251 2290 2252 workscan._auto_sinusoid_baseline(mask, minnwave, maxnwave, clipthresh, clipniter, curedge, threshold, chan_avg_limit, outlog, blfile)2291 workscan._auto_sinusoid_baseline(mask, nwave, maxwavelength, clipthresh, clipniter, curedge, threshold, chan_avg_limit, getresidual, outlog, blfile) 2253 2292 2254 2293 workscan._add_history("auto_sinusoid_baseline", varlist) … … 2295 2334 # also with 3-sigma clipping, iteration up to 4 times 2296 2335 bscan = scan.cspline_baseline(npiece=2,clipthresh=3.0,clipniter=4) 2336 2337 Note: 2338 The best-fit parameter values output in logger and/or blfile are now 2339 based on specunit of 'channel'. 2297 2340 """ 2298 2341 … … 2388 2431 Example: 2389 2432 bscan = scan.auto_cspline_baseline(npiece=3, insitu=False) 2433 2434 Note: 2435 The best-fit parameter values output in logger and/or blfile are now 2436 based on specunit of 'channel'. 2390 2437 """ 2391 2438 -
branches/casa-prerelease/pre-asap/src
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/trunk/src merged: 2081
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branches/casa-prerelease/pre-asap/src/SConscript
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branches/casa-prerelease/pre-asap/src/STLineFinder.cpp
r2012 r2082 1203 1203 vel = scan->getAbcissa(last_row_used); 1204 1204 } else { 1205 for ( int i = 0; i < spectrum.nelements(); ++i)1205 for (uInt i = 0; i < spectrum.nelements(); ++i) 1206 1206 vel.push_back((double)i); 1207 1207 } -
branches/casa-prerelease/pre-asap/src/Scantable.cpp
r2065 r2082 1764 1764 { 1765 1765 ofstream ofs; 1766 String coordInfo ;1766 String coordInfo = ""; 1767 1767 bool hasSameNchan = true; 1768 1768 bool outTextFile = false; … … 1781 1781 Fitter fitter = Fitter(); 1782 1782 fitter.setExpression("poly", order); 1783 //fitter.setIterClipping(thresClip, nIterClip); 1783 1784 1784 1785 int nRow = nrow(); … … 1798 1799 { 1799 1800 ofstream ofs; 1800 String coordInfo ;1801 String coordInfo = ""; 1801 1802 bool hasSameNchan = true; 1802 1803 bool outTextFile = false; … … 1815 1816 Fitter fitter = Fitter(); 1816 1817 fitter.setExpression("poly", order); 1818 //fitter.setIterClipping(thresClip, nIterClip); 1817 1819 1818 1820 int nRow = nrow(); … … 1856 1858 } 1857 1859 1858 void Scantable::cubicSplineBaseline(const std::vector<bool>& mask, int nPiece, float thresClip, int nIterClip, bool outLogger, const std::string& blfile) { 1860 void Scantable::cubicSplineBaseline(const std::vector<bool>& mask, int nPiece, float thresClip, int nIterClip, bool outLogger, const std::string& blfile) 1861 { 1859 1862 ofstream ofs; 1860 String coordInfo ;1863 String coordInfo = ""; 1861 1864 bool hasSameNchan = true; 1862 1865 bool outTextFile = false; … … 1875 1878 //Fitter fitter = Fitter(); 1876 1879 //fitter.setExpression("cspline", nPiece); 1880 //fitter.setIterClipping(thresClip, nIterClip); 1877 1881 1878 1882 int nRow = nrow(); … … 1881 1885 for (int whichrow = 0; whichrow < nRow; ++whichrow) { 1882 1886 chanMask = getCompositeChanMask(whichrow, mask); 1883 //fitBaseline(chanMask, whichrow, fitter , thresClip, nIterClip);1887 //fitBaseline(chanMask, whichrow, fitter); 1884 1888 //setSpectrum(fitter.getResidual(), whichrow); 1885 std::vector<int> piece Ranges;1889 std::vector<int> pieceEdges; 1886 1890 std::vector<float> params; 1887 std::vector<float> res = doCubicSplineFitting(getSpectrum(whichrow), chanMask, pieceRanges, params, nPiece, thresClip, nIterClip, true);1891 std::vector<float> res = doCubicSplineFitting(getSpectrum(whichrow), chanMask, nPiece, pieceEdges, params, thresClip, nIterClip, true); 1888 1892 setSpectrum(res, whichrow); 1889 1893 // 1890 1894 1891 std::vector<bool> fixed; 1892 fixed.clear(); 1893 outputFittingResult(outLogger, outTextFile, chanMask, whichrow, coordInfo, hasSameNchan, ofs, "cubicSplineBaseline()", pieceRanges, params, fixed); 1895 outputFittingResult(outLogger, outTextFile, chanMask, whichrow, coordInfo, hasSameNchan, ofs, "cubicSplineBaseline()", pieceEdges, params); 1894 1896 } 1895 1897 … … 1900 1902 { 1901 1903 ofstream ofs; 1902 String coordInfo ;1904 String coordInfo = ""; 1903 1905 bool hasSameNchan = true; 1904 1906 bool outTextFile = false; … … 1917 1919 //Fitter fitter = Fitter(); 1918 1920 //fitter.setExpression("cspline", nPiece); 1921 //fitter.setIterClipping(thresClip, nIterClip); 1919 1922 1920 1923 int nRow = nrow(); … … 1950 1953 1951 1954 1952 //fitBaseline(chanMask, whichrow, fitter , thresClip, nIterClip);1955 //fitBaseline(chanMask, whichrow, fitter); 1953 1956 //setSpectrum(fitter.getResidual(), whichrow); 1954 std::vector<int> piece Ranges;1957 std::vector<int> pieceEdges; 1955 1958 std::vector<float> params; 1956 std::vector<float> res = doCubicSplineFitting(getSpectrum(whichrow), chanMask, pieceRanges, params, nPiece, thresClip, nIterClip, true);1959 std::vector<float> res = doCubicSplineFitting(getSpectrum(whichrow), chanMask, nPiece, pieceEdges, params, thresClip, nIterClip, true); 1957 1960 setSpectrum(res, whichrow); 1958 1961 // 1959 1962 1960 std::vector<bool> fixed; 1961 fixed.clear(); 1962 outputFittingResult(outLogger, outTextFile, chanMask, whichrow, coordInfo, hasSameNchan, ofs, "autoCubicSplineBaseline()", pieceRanges, params, fixed); 1963 outputFittingResult(outLogger, outTextFile, chanMask, whichrow, coordInfo, hasSameNchan, ofs, "autoCubicSplineBaseline()", pieceEdges, params); 1963 1964 } 1964 1965 … … 1966 1967 } 1967 1968 1968 std::vector<float> Scantable::doCubicSplineFitting(const std::vector<float>& data, const std::vector<bool>& mask, std::vector<int>& idxEdge, std::vector<float>& params, int nPiece, float thresClip, int nIterClip, bool getResidual) { 1969 std::vector<float> Scantable::doCubicSplineFitting(const std::vector<float>& data, const std::vector<bool>& mask, int nPiece, std::vector<int>& idxEdge, std::vector<float>& params, float thresClip, int nIterClip, bool getResidual) 1970 { 1971 if (data.size() != mask.size()) { 1972 throw(AipsError("data and mask sizes are not identical")); 1973 } 1969 1974 if (nPiece < 1) { 1970 1975 throw(AipsError("wrong number of the sections for fitting")); 1971 }1972 if (data.size() != mask.size()) {1973 throw(AipsError("data and mask have different size"));1974 1976 } 1975 1977 … … 1984 1986 } 1985 1987 1986 int nData = x.size(); 1987 int nElement = (int)(floor(floor((double)(nData/nPiece))+0.5)); 1988 int initNData = x.size(); 1989 1990 int nElement = (int)(floor(floor((double)(initNData/nPiece))+0.5)); 1988 1991 std::vector<double> invEdge; 1989 1990 1992 idxEdge.clear(); 1991 1993 idxEdge.push_back(x[0]); 1992 1993 1994 for (int i = 1; i < nPiece; ++i) { 1994 1995 int valX = x[nElement*i]; … … 1996 1997 invEdge.push_back(1.0/(double)valX); 1997 1998 } 1998 1999 1999 idxEdge.push_back(x[x.size()-1]+1); 2000 2000 2001 std::vector<double> x1, x2, x3, z1, x1z1, x2z1, x3z1, r1; 2001 int nData = initNData; 2002 int nDOF = nPiece + 3; //number of parameters to solve, namely, 4+(nPiece-1). 2003 2004 std::vector<double> x1, x2, x3, z1, x1z1, x2z1, x3z1, r1, residual; 2002 2005 for (int i = 0; i < nChan; ++i) { 2003 2006 double di = (double)i; … … 2011 2014 x3z1.push_back(dD*di*di*di); 2012 2015 r1.push_back(0.0); 2013 } 2014 2015 int currentNData = nData; 2016 int nDOF = nPiece + 3; //number of parameters to solve, namely, 4+(nPiece-1). 2016 residual.push_back(0.0); 2017 } 2017 2018 2018 2019 for (int nClip = 0; nClip < nIterClip+1; ++nClip) { … … 2128 2129 for (int i = idxEdge[n]; i < idxEdge[n+1]; ++i) { 2129 2130 r1[i] = a0 + a1*x1[i] + a2*x2[i] + a3*x3[i]; 2131 residual[i] = z1[i] - r1[i]; 2130 2132 } 2131 2133 params.push_back(a0); … … 2147 2149 break; 2148 2150 } else { 2149 std::vector<double> rz;2150 2151 double stdDev = 0.0; 2151 2152 for (int i = 0; i < nChan; ++i) { 2152 double val = abs(r1[i] - z1[i]); 2153 rz.push_back(val); 2154 stdDev += val*val*(double)maskArray[i]; 2153 stdDev += residual[i]*residual[i]*(double)maskArray[i]; 2155 2154 } 2156 2155 stdDev = sqrt(stdDev/(double)nData); … … 2159 2158 int newNData = 0; 2160 2159 for (int i = 0; i < nChan; ++i) { 2161 if ( rz[i]>= thres) {2160 if (abs(residual[i]) >= thres) { 2162 2161 maskArray[i] = 0; 2163 2162 } … … 2166 2165 } 2167 2166 } 2168 if (newNData == currentNData) {2167 if (newNData == nData) { 2169 2168 break; //no more flag to add. iteration stops. 2170 2169 } else { 2171 currentNData = newNData;2170 nData = newNData; 2172 2171 } 2173 2172 } … … 2177 2176 if (getResidual) { 2178 2177 for (int i = 0; i < nChan; ++i) { 2179 result.push_back((float) (z1[i] - r1[i]));2178 result.push_back((float)residual[i]); 2180 2179 } 2181 2180 } else { … … 2188 2187 } 2189 2188 2190 void Scantable::sinusoidBaseline(const std::vector<bool>& mask, int nMinWavesInSW, int nMaxWavesInSW, float thresClip, int nIterClip, bool outLogger, const std::string& blfile) { 2189 void Scantable::sinusoidBaseline(const std::vector<bool>& mask, const std::vector<int>& nWaves, float maxWaveLength, float thresClip, int nIterClip, bool getResidual, bool outLogger, const std::string& blfile) 2190 { 2191 2191 ofstream ofs; 2192 String coordInfo ;2192 String coordInfo = ""; 2193 2193 bool hasSameNchan = true; 2194 2194 bool outTextFile = false; … … 2206 2206 2207 2207 //Fitter fitter = Fitter(); 2208 //fitter.setExpression("sinusoid", nMaxWavesInSW); 2208 //fitter.setExpression("sinusoid", nWaves); 2209 //fitter.setIterClipping(thresClip, nIterClip); 2209 2210 2210 2211 int nRow = nrow(); … … 2213 2214 for (int whichrow = 0; whichrow < nRow; ++whichrow) { 2214 2215 chanMask = getCompositeChanMask(whichrow, mask); 2215 //fitBaseline(chanMask, whichrow, fitter , thresClip, nIterClip);2216 //fitBaseline(chanMask, whichrow, fitter); 2216 2217 //setSpectrum(fitter.getResidual(), whichrow); 2217 std::vector<int> pieceRanges;2218 2218 std::vector<float> params; 2219 std::vector<float> res = doSinusoidFitting(getSpectrum(whichrow), chanMask, nMinWavesInSW, nMaxWavesInSW, params, thresClip, nIterClip, true); 2219 //std::vector<float> res = doSinusoidFitting(getSpectrum(whichrow), chanMask, nWaves, params, thresClip, nIterClip, true); 2220 std::vector<float> res = doSinusoidFitting(getSpectrum(whichrow), chanMask, nWaves, maxWaveLength, params, thresClip, nIterClip, getResidual); 2220 2221 setSpectrum(res, whichrow); 2221 2222 // 2222 2223 2223 std::vector<bool> fixed; 2224 fixed.clear(); 2225 outputFittingResult(outLogger, outTextFile, chanMask, whichrow, coordInfo, hasSameNchan, ofs, "sinusoidBaseline()", pieceRanges, params, fixed); 2224 outputFittingResult(outLogger, outTextFile, chanMask, whichrow, coordInfo, hasSameNchan, ofs, "sinusoidBaseline()", params); 2226 2225 } 2227 2226 … … 2229 2228 } 2230 2229 2231 void Scantable::autoSinusoidBaseline(const std::vector<bool>& mask, int nMinWavesInSW, int nMaxWavesInSW, float thresClip, int nIterClip, const std::vector<int>& edge, float threshold, int chanAvgLimit, bool outLogger, const std::string& blfile)2230 void Scantable::autoSinusoidBaseline(const std::vector<bool>& mask, const std::vector<int>& nWaves, float maxWaveLength, float thresClip, int nIterClip, const std::vector<int>& edge, float threshold, int chanAvgLimit, bool getResidual, bool outLogger, const std::string& blfile) 2232 2231 { 2233 2232 ofstream ofs; 2234 String coordInfo ;2233 String coordInfo = ""; 2235 2234 bool hasSameNchan = true; 2236 2235 bool outTextFile = false; … … 2248 2247 2249 2248 //Fitter fitter = Fitter(); 2250 //fitter.setExpression("sinusoid", nMaxWavesInSW); 2249 //fitter.setExpression("sinusoid", nWaves); 2250 //fitter.setIterClipping(thresClip, nIterClip); 2251 2251 2252 2252 int nRow = nrow(); … … 2282 2282 2283 2283 2284 //fitBaseline(chanMask, whichrow, fitter , thresClip, nIterClip);2284 //fitBaseline(chanMask, whichrow, fitter); 2285 2285 //setSpectrum(fitter.getResidual(), whichrow); 2286 std::vector<int> pieceRanges;2287 2286 std::vector<float> params; 2288 std::vector<float> res = doSinusoidFitting(getSpectrum(whichrow), chanMask, n MinWavesInSW, nMaxWavesInSW, params, thresClip, nIterClip, true);2287 std::vector<float> res = doSinusoidFitting(getSpectrum(whichrow), chanMask, nWaves, maxWaveLength, params, thresClip, nIterClip, getResidual); 2289 2288 setSpectrum(res, whichrow); 2290 2289 // 2291 2290 2292 std::vector<bool> fixed; 2293 fixed.clear(); 2294 outputFittingResult(outLogger, outTextFile, chanMask, whichrow, coordInfo, hasSameNchan, ofs, "autoSinusoidBaseline()", pieceRanges, params, fixed); 2291 outputFittingResult(outLogger, outTextFile, chanMask, whichrow, coordInfo, hasSameNchan, ofs, "autoSinusoidBaseline()", params); 2295 2292 } 2296 2293 … … 2298 2295 } 2299 2296 2300 std::vector<float> Scantable::doSinusoidFitting(const std::vector<float>& data, const std::vector<bool>& mask, int nMinWavesInSW, int nMaxWavesInSW, std::vector<float>& params, float thresClip, int nIterClip, bool getResidual) { 2297 std::vector<float> Scantable::doSinusoidFitting(const std::vector<float>& data, const std::vector<bool>& mask, const std::vector<int>& waveNumbers, float maxWaveLength, std::vector<float>& params, float thresClip, int nIterClip, bool getResidual) 2298 { 2301 2299 if (data.size() != mask.size()) { 2302 throw(AipsError("data and mask have different size")); 2303 } 2304 if ((nMinWavesInSW < 0) || (nMaxWavesInSW < 0)) { 2300 throw(AipsError("data and mask sizes are not identical")); 2301 } 2302 if (data.size() < 2) { 2303 throw(AipsError("data size is too short")); 2304 } 2305 if (waveNumbers.size() == 0) { 2306 throw(AipsError("missing wave number info")); 2307 } 2308 std::vector<int> nWaves; // sorted and uniqued array of wave numbers 2309 nWaves.reserve(waveNumbers.size()); 2310 copy(waveNumbers.begin(), waveNumbers.end(), back_inserter(nWaves)); 2311 sort(nWaves.begin(), nWaves.end()); 2312 std::vector<int>::iterator end_it = unique(nWaves.begin(), nWaves.end()); 2313 nWaves.erase(end_it, nWaves.end()); 2314 2315 int minNWaves = nWaves[0]; 2316 if (minNWaves < 0) { 2305 2317 throw(AipsError("wave number must be positive or zero (i.e. constant)")); 2306 } else { 2307 if (nMaxWavesInSW < nMinWavesInSW) { 2308 int temp = nMaxWavesInSW; 2309 nMaxWavesInSW = nMinWavesInSW; 2310 nMinWavesInSW = temp; 2311 } 2312 } 2318 } 2319 bool hasConstantTerm = (minNWaves == 0); 2313 2320 2314 2321 int nChan = data.size(); … … 2322 2329 } 2323 2330 2324 int nData = x.size(); 2325 2326 std::vector<double> x1, x2, x3, z1, x1z1, x2z1, x3z1, r1; 2331 int initNData = x.size(); 2332 2333 int nData = initNData; 2334 int nDOF = nWaves.size() * 2 - (hasConstantTerm ? 1 : 0); //number of parameters to solve. 2335 2336 const double PI = 6.0 * asin(0.5); // PI (= 3.141592653...) 2337 double baseXFactor = 2.0*PI/(double)maxWaveLength/(double)(nChan-1); //the denominator (nChan-1) should be changed to (xdata[nChan-1]-xdata[0]) for accepting x-values given in velocity or frequency when this function is moved to fitter. 2338 2339 // xArray : contains elemental values for computing the least-square matrix. 2340 // xArray.size() is nDOF and xArray[*].size() is nChan. 2341 // Each xArray element are as follows: 2342 // xArray[0] = {1.0, 1.0, 1.0, ..., 1.0}, 2343 // xArray[2n-1] = {sin(nPI/L*x[0]), sin(nPI/L*x[1]), ..., sin(nPI/L*x[nChan])}, 2344 // xArray[2n] = {cos(nPI/L*x[0]), cos(nPI/L*x[1]), ..., cos(nPI/L*x[nChan])}, 2345 // where (1 <= n <= nMaxWavesInSW), 2346 // or, 2347 // xArray[2n-1] = {sin(wn[n]PI/L*x[0]), sin(wn[n]PI/L*x[1]), ..., sin(wn[n]PI/L*x[nChan])}, 2348 // xArray[2n] = {cos(wn[n]PI/L*x[0]), cos(wn[n]PI/L*x[1]), ..., cos(wn[n]PI/L*x[nChan])}, 2349 // where wn[n] denotes waveNumbers[n] (1 <= n <= waveNumbers.size()). 2350 std::vector<std::vector<double> > xArray; 2351 if (hasConstantTerm) { 2352 std::vector<double> xu; 2353 for (int j = 0; j < nChan; ++j) { 2354 xu.push_back(1.0); 2355 } 2356 xArray.push_back(xu); 2357 } 2358 for (uInt i = (hasConstantTerm ? 1 : 0); i < nWaves.size(); ++i) { 2359 double xFactor = baseXFactor*(double)nWaves[i]; 2360 std::vector<double> xs, xc; 2361 xs.clear(); 2362 xc.clear(); 2363 for (int j = 0; j < nChan; ++j) { 2364 xs.push_back(sin(xFactor*(double)j)); 2365 xc.push_back(cos(xFactor*(double)j)); 2366 } 2367 xArray.push_back(xs); 2368 xArray.push_back(xc); 2369 } 2370 2371 std::vector<double> z1, r1, residual; 2327 2372 for (int i = 0; i < nChan; ++i) { 2328 double di = (double)i; 2329 double dD = (double)data[i]; 2330 x1.push_back(di); 2331 x2.push_back(di*di); 2332 x3.push_back(di*di*di); 2333 z1.push_back(dD); 2334 x1z1.push_back(di*dD); 2335 x2z1.push_back(di*di*dD); 2336 x3z1.push_back(di*di*di*dD); 2373 z1.push_back((double)data[i]); 2337 2374 r1.push_back(0.0); 2338 } 2339 2340 int currentNData = nData; 2341 int nDOF = nMaxWavesInSW + 1; //number of parameters to solve. 2375 residual.push_back(0.0); 2376 } 2342 2377 2343 2378 for (int nClip = 0; nClip < nIterClip+1; ++nClip) { 2344 //xMatrix : horizontal concatenation of the least-sq. matrix (left) and an 2345 //identity matrix (right). 2346 //the right part is used to calculate the inverse matrix of the left part. 2379 // xMatrix : horizontal concatenation of 2380 // the least-sq. matrix (left) and an 2381 // identity matrix (right). 2382 // the right part is used to calculate the inverse matrix of the left part. 2347 2383 double xMatrix[nDOF][2*nDOF]; 2348 2384 double zMatrix[nDOF]; … … 2355 2391 } 2356 2392 2357 for (int i = 0; i < currentNData; ++i) { 2358 if (maskArray[i] == 0) continue; 2359 xMatrix[0][0] += 1.0; 2360 xMatrix[0][1] += x1[i]; 2361 xMatrix[0][2] += x2[i]; 2362 xMatrix[0][3] += x3[i]; 2363 xMatrix[1][1] += x2[i]; 2364 xMatrix[1][2] += x3[i]; 2365 xMatrix[1][3] += x2[i]*x2[i]; 2366 xMatrix[2][2] += x2[i]*x2[i]; 2367 xMatrix[2][3] += x3[i]*x2[i]; 2368 xMatrix[3][3] += x3[i]*x3[i]; 2369 zMatrix[0] += z1[i]; 2370 zMatrix[1] += x1z1[i]; 2371 zMatrix[2] += x2z1[i]; 2372 zMatrix[3] += x3z1[i]; 2393 for (int k = 0; k < nChan; ++k) { 2394 if (maskArray[k] == 0) continue; 2395 2396 for (int i = 0; i < nDOF; ++i) { 2397 for (int j = i; j < nDOF; ++j) { 2398 xMatrix[i][j] += xArray[i][k] * xArray[j][k]; 2399 } 2400 zMatrix[i] += z1[k] * xArray[i][k]; 2401 } 2373 2402 } 2374 2403 … … 2411 2440 } 2412 2441 //compute a vector y which consists of the coefficients of the sinusoids forming the 2413 //best-fit curves (a0, b0,a1,b1,...), namely, a* and b* are of sine and cosine functions,2414 // respectively.2442 //best-fit curves (a0,s1,c1,s2,c2,...), where a0 is constant and s* and c* are of sine 2443 //and cosine functions, respectively. 2415 2444 std::vector<double> y; 2445 params.clear(); 2416 2446 for (int i = 0; i < nDOF; ++i) { 2417 2447 y.push_back(0.0); … … 2419 2449 y[i] += xMatrix[i][nDOF+j]*zMatrix[j]; 2420 2450 } 2421 } 2422 2423 double a0 = y[0]; 2424 double a1 = y[1]; 2425 double a2 = y[2]; 2426 double a3 = y[3]; 2427 params.clear(); 2451 params.push_back(y[i]); 2452 } 2428 2453 2429 2454 for (int i = 0; i < nChan; ++i) { 2430 r1[i] = a0 + a1*x1[i] + a2*x2[i] + a3*x3[i]; 2431 } 2432 params.push_back(a0); 2433 params.push_back(a1); 2434 params.push_back(a2); 2435 params.push_back(a3); 2436 2455 r1[i] = y[0]; 2456 for (int j = 1; j < nDOF; ++j) { 2457 r1[i] += y[j]*xArray[j][i]; 2458 } 2459 residual[i] = z1[i] - r1[i]; 2460 } 2437 2461 2438 2462 if ((nClip == nIterClip) || (thresClip <= 0.0)) { 2439 2463 break; 2440 2464 } else { 2441 std::vector<double> rz;2442 2465 double stdDev = 0.0; 2443 2466 for (int i = 0; i < nChan; ++i) { 2444 double val = abs(r1[i] - z1[i]); 2445 rz.push_back(val); 2446 stdDev += val*val*(double)maskArray[i]; 2467 stdDev += residual[i]*residual[i]*(double)maskArray[i]; 2447 2468 } 2448 2469 stdDev = sqrt(stdDev/(double)nData); … … 2451 2472 int newNData = 0; 2452 2473 for (int i = 0; i < nChan; ++i) { 2453 if ( rz[i]>= thres) {2474 if (abs(residual[i]) >= thres) { 2454 2475 maskArray[i] = 0; 2455 2476 } … … 2458 2479 } 2459 2480 } 2460 if (newNData == currentNData) {2461 break; //no additional flag. finish iteration.2481 if (newNData == nData) { 2482 break; //no more flag to add. iteration stops. 2462 2483 } else { 2463 currentNData = newNData;2484 nData = newNData; 2464 2485 } 2465 2486 } … … 2469 2490 if (getResidual) { 2470 2491 for (int i = 0; i < nChan; ++i) { 2471 result.push_back((float) (z1[i] - r1[i]));2492 result.push_back((float)residual[i]); 2472 2493 } 2473 2494 } else { … … 2482 2503 void Scantable::fitBaseline(const std::vector<bool>& mask, int whichrow, Fitter& fitter) 2483 2504 { 2484 std::vector<double> abcsd= getAbcissa(whichrow);2485 std::vector<float> abc s;2486 for (uInt i = 0; i < abcsd.size(); ++i) {2487 abc s.push_back((float)abcsd[i]);2505 std::vector<double> dAbcissa = getAbcissa(whichrow); 2506 std::vector<float> abcissa; 2507 for (uInt i = 0; i < dAbcissa.size(); ++i) { 2508 abcissa.push_back((float)dAbcissa[i]); 2488 2509 } 2489 2510 std::vector<float> spec = getSpectrum(whichrow); 2490 2511 2491 fitter.setData(abc s, spec, mask);2512 fitter.setData(abcissa, spec, mask); 2492 2513 fitter.lfit(); 2493 2514 } … … 2552 2573 2553 2574 /* for cspline. will be merged once cspline is available in fitter (2011/3/10 WK) */ 2554 void Scantable::outputFittingResult(bool outLogger, bool outTextFile, const std::vector<bool>& chanMask, int whichrow, const casa::String& coordInfo, bool hasSameNchan, ofstream& ofs, const casa::String& funcName, const std::vector<int>& edge, const std::vector<float>& params , const std::vector<bool>& fixed) {2575 void Scantable::outputFittingResult(bool outLogger, bool outTextFile, const std::vector<bool>& chanMask, int whichrow, const casa::String& coordInfo, bool hasSameNchan, ofstream& ofs, const casa::String& funcName, const std::vector<int>& edge, const std::vector<float>& params) { 2555 2576 if (outLogger || outTextFile) { 2556 2577 float rms = getRms(chanMask, whichrow); 2557 2578 String masklist = getMaskRangeList(chanMask, whichrow, coordInfo, hasSameNchan); 2579 std::vector<bool> fixed; 2580 fixed.clear(); 2558 2581 2559 2582 if (outLogger) { … … 2568 2591 2569 2592 /* for sinusoid. will be merged once sinusoid is available in fitter (2011/3/10 WK) */ 2570 void Scantable::outputFittingResult(bool outLogger, bool outTextFile, const std::vector<bool>& chanMask, int whichrow, const casa::String& coordInfo, bool hasSameNchan, ofstream& ofs, const casa::String& funcName, const std::vector<float>& params , const std::vector<bool>& fixed) {2593 void Scantable::outputFittingResult(bool outLogger, bool outTextFile, const std::vector<bool>& chanMask, int whichrow, const casa::String& coordInfo, bool hasSameNchan, ofstream& ofs, const casa::String& funcName, const std::vector<float>& params) { 2571 2594 if (outLogger || outTextFile) { 2572 2595 float rms = getRms(chanMask, whichrow); 2573 2596 String masklist = getMaskRangeList(chanMask, whichrow, coordInfo, hasSameNchan); 2597 std::vector<bool> fixed; 2598 fixed.clear(); 2574 2599 2575 2600 if (outLogger) { -
branches/casa-prerelease/pre-asap/src/Scantable.h
r2065 r2082 522 522 const std::string& blfile=""); 523 523 void sinusoidBaseline(const std::vector<bool>& mask, 524 int nMinWavesInSW,525 int nMaxWavesInSW,524 const std::vector<int>& nWaves, 525 float maxWaveLength, 526 526 float thresClip, 527 527 int nIterClip, 528 bool getResidual=true, 528 529 bool outLogger=false, 529 530 const std::string& blfile=""); 530 531 void autoSinusoidBaseline(const std::vector<bool>& mask, 531 int nMinWavesInSW,532 int nMaxWavesInSW,532 const std::vector<int>& nWaves, 533 float maxWaveLength, 533 534 float thresClip, 534 535 int nIterClip, … … 536 537 float threshold=3.0, 537 538 int chanAvgLimit=1, 539 bool getResidual=true, 538 540 bool outLogger=false, 539 541 const std::string& blfile=""); … … 672 674 std::vector<float> doCubicSplineFitting(const std::vector<float>& data, 673 675 const std::vector<bool>& mask, 676 int nPiece, 674 677 std::vector<int>& idxEdge, 675 678 std::vector<float>& params, 676 int nPiece=2,677 679 float thresClip=3.0, 678 680 int nIterClip=1, … … 680 682 std::vector<float> doSinusoidFitting(const std::vector<float>& data, 681 683 const std::vector<bool>& mask, 682 int nMinWavesInSW,683 int nMaxWavesInSW,684 const std::vector<int>& waveNumbers, 685 float maxWaveLength, 684 686 std::vector<float>& params, 685 687 float thresClip=3.0, … … 698 700 //std::vector<bool> getCompositeChanMask(int whichrow, const std::vector<bool>& inMask, const std::vector<int>& edge, const int minEdgeSize, STLineFinder& lineFinder); 699 701 void outputFittingResult(bool outLogger, bool outTextFile, const std::vector<bool>& chanMask, int whichrow, const casa::String& coordInfo, bool hasSameNchan, std::ofstream& ofs, const casa::String& funcName, Fitter& fitter); 700 void outputFittingResult(bool outLogger, bool outTextFile, const std::vector<bool>& chanMask, int whichrow, const casa::String& coordInfo, bool hasSameNchan, std::ofstream& ofs, const casa::String& funcName, const std::vector<int>& edge, const std::vector<float>& params , const std::vector<bool>& fixed);701 void outputFittingResult(bool outLogger, bool outTextFile, const std::vector<bool>& chanMask, int whichrow, const casa::String& coordInfo, bool hasSameNchan, std::ofstream& ofs, const casa::String& funcName, const std::vector<float>& params , const std::vector<bool>& fixed);702 void outputFittingResult(bool outLogger, bool outTextFile, const std::vector<bool>& chanMask, int whichrow, const casa::String& coordInfo, bool hasSameNchan, std::ofstream& ofs, const casa::String& funcName, const std::vector<int>& edge, const std::vector<float>& params); 703 void outputFittingResult(bool outLogger, bool outTextFile, const std::vector<bool>& chanMask, int whichrow, const casa::String& coordInfo, bool hasSameNchan, std::ofstream& ofs, const casa::String& funcName, const std::vector<float>& params); 702 704 703 705 void applyChanFlag( casa::uInt whichrow, const std::vector<bool>& msk, casa::uChar flagval); -
branches/casa-prerelease/pre-asap/src/ScantableWrapper.h
r2047 r2082 269 269 { table_->autoCubicSplineBaseline(mask, npiece, clipthresh, clipniter, edge, threshold, chan_avg_limit, outlog, blfile); } 270 270 271 void sinusoidBaseline(const std::vector<bool>& mask, int minnwave, int maxnwave, float clipthresh, int clipniter, bool outlog=false, const std::string& blfile="")272 { table_->sinusoidBaseline(mask, minnwave, maxnwave, clipthresh, clipniter, outlog, blfile); }273 274 void autoSinusoidBaseline(const std::vector<bool>& mask, int minnwave, int maxnwave, float clipthresh, int clipniter, const std::vector<int>& edge, float threshold=5.0, int chan_avg_limit=1, bool outlog=false, const std::string& blfile="")275 { table_->autoSinusoidBaseline(mask, minnwave, maxnwave, clipthresh, clipniter, edge, threshold, chan_avg_limit, outlog, blfile); }271 void sinusoidBaseline(const std::vector<bool>& mask, const std::vector<int>& nwave, float maxwavelength, float clipthresh, int clipniter, bool getresidual=true, bool outlog=false, const std::string& blfile="") 272 { table_->sinusoidBaseline(mask, nwave, maxwavelength, clipthresh, clipniter, getresidual, outlog, blfile); } 273 274 void autoSinusoidBaseline(const std::vector<bool>& mask, const std::vector<int>& nwave, float maxwavelength, float clipthresh, int clipniter, const std::vector<int>& edge, float threshold=5.0, int chan_avg_limit=1, bool getresidual=true, bool outlog=false, const std::string& blfile="") 275 { table_->autoSinusoidBaseline(mask, nwave, maxwavelength, clipthresh, clipniter, edge, threshold, chan_avg_limit, getresidual, outlog, blfile); } 276 276 277 277 float getRms(const std::vector<bool>& mask, int whichrow)
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