Changeset 2012 for trunk/python/scantable.py

Timestamp:

02/25/11 16:51:50 (13 years ago)

Author:

WataruKawasaki

Message:

New Development: Yes

JIRA Issue: Yes (CAS-2373, CAS-2620)

Ready for Test: Yes

Interface Changes: Yes

What Interface Changed: For Scantable::polyBaseline(), parameters and return value have been changed.

Test Programs:

Put in Release Notes: Yes

Module(s): sdbaseline, sd.linefinder

Description: (1) CAS-2373-related:

(1.1) Modified Scantable::polyBaseline() to have the row-based loop inside.

Now it fits and subtracts baseline for all rows and also output info
about the fitting result to logger and text file, while in the
previous version this method just did baseline fitting/subtraction
for one row only and had to be put inside a row-based loop at the
python side ("poly_baseline()" in scantable.py) and result output had
also to be controlled at the python side. Using a test data from NRO
45m telescope (348,000 rows, 512 channels), the processing time of
scantable.poly_baseline() has reduced from 130 minutes to 5-6 minutes.

(1.2) For accelerating the another polynomial fitting function, namely

scantable.auto_poly_baseline(), added a method
Scantable::autoPolyBaseline(). This basically does the same thing
with Scantable::polyBaseline(), but uses linefinfer also to
automatically flag the line regions.

(1.3) To make linefinder usable in Scantable class, added a method

linefinder.setdata(). This makes it possible to apply linefinder
for a float-list data given as a parameter, without setting scantable,
while it was indispensable to set scantable to use linefinger previously.

(2) CAS-2620-related:

Added Scantable::cubicSplineBaseline() and autoCubicSplineBaseline() for
fit baseline using the cubic spline function. Parameters include npiece
(number of polynomial pieces), clipthresh (clipping threshold), and
clipniter (maximum iteration number).

File:

• trunk/python/scantable.py (modified) (3 diffs)

trunk/python/scantable.py

@@ -1898 +1898 @@
         else: return s
 
+
+    @asaplog_post_dec
+    def cspline_baseline(self, insitu=None, mask=None, npiece=None, clipthresh=None, clipniter=None, plot=None, outlog=None, blfile=None):
+        """\
+        Return a scan which has been baselined (all rows) by cubic spline function (piecewise cubic polynomial).
+        Parameters:
+            insitu:     If False a new scantable is returned.
+                        Otherwise, the scaling is done in-situ
+                        The default is taken from .asaprc (False)
+            mask:       An optional mask
+            npiece:     Number of pieces. (default is 2)
+            clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
+            clipniter:  maximum number of iteration of 'clipthresh'-sigma clipping (default is 1)
+            plot:   *** CURRENTLY UNAVAILABLE, ALWAYS FALSE ***
+                        plot the fit and the residual. In this each
+                        indivual fit has to be approved, by typing 'y'
+                        or 'n'
+            outlog:     Output the coefficients of the best-fit
+                        function to logger (default is False)
+            blfile:     Name of a text file in which the best-fit
+                        parameter values to be written
+                        (default is "": no file/logger output)
+
+        Example:
+            # return a scan baselined by a cubic spline consisting of 2 pieces (i.e., 1 internal knot),
+            # also with 3-sigma clipping, iteration up to 4 times
+            bscan = scan.cspline_baseline(npiece=2,clipthresh=3.0,clipniter=4)
+        """
+        
+        varlist = vars()
+        
+        if insitu is None: insitu = rcParams["insitu"]
+        if insitu:
+            workscan = self
+        else:
+            workscan = self.copy()
+
+        nchan = workscan.nchan()
+        
+        if mask is None: mask = [True for i in xrange(nchan)]
+        if npiece is None: npiece = 2
+        if clipthresh is None: clipthresh = 3.0
+        if clipniter is None: clipniter = 1
+        if plot is None: plot = False
+        if outlog is None: outlog = False
+        if blfile is None: blfile = ""
+
+        outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile)))
+        
+        try:
+            #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. 
+            workscan._cspline_baseline(mask, npiece, clipthresh, clipniter, outlog, blfile)
+            
+            workscan._add_history("cspline_baseline", varlist)
+            
+            if insitu:
+                self._assign(workscan)
+            else:
+                return workscan
+            
+        except RuntimeError, e:
+            msg = "The fit failed, possibly because it didn't converge."
+            if rcParams["verbose"]:
+                asaplog.push(str(e))
+                asaplog.push(str(msg))
+                return
+            else:
+                raise RuntimeError(str(e)+'\n'+msg)
+
+
+    def auto_cspline_baseline(self, insitu=None, mask=None, npiece=None, clipthresh=None,
+                              clipniter=None, edge=None, threshold=None,
+                              chan_avg_limit=None, plot=None, outlog=None, blfile=None):
+        """\
+        Return a scan which has been baselined (all rows) by cubic spline
+        function (piecewise cubic polynomial).
+        Spectral lines are detected first using linefinder and masked out
+        to avoid them affecting the baseline solution.
+
+        Parameters:
+            insitu:     if False a new scantable is returned.
+                        Otherwise, the scaling is done in-situ
+                        The default is taken from .asaprc (False)
+            mask:       an optional mask retreived from scantable
+            npiece:     Number of pieces. (default is 2)
+            clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
+            clipniter:  maximum number of iteration of 'clipthresh'-sigma clipping (default is 1)
+            edge:       an optional number of channel to drop at
+                        the edge of spectrum. If only one value is
+                        specified, the same number will be dropped
+                        from both sides of the spectrum. Default
+                        is to keep all channels. Nested tuples
+                        represent individual edge selection for
+                        different IFs (a number of spectral channels
+                        can be different)
+            threshold:  the threshold used by line finder. It is
+                        better to keep it large as only strong lines
+                        affect the baseline solution.
+            chan_avg_limit:
+                        a maximum number of consequtive spectral
+                        channels to average during the search of
+                        weak and broad lines. The default is no
+                        averaging (and no search for weak lines).
+                        If such lines can affect the fitted baseline
+                        (e.g. a high order polynomial is fitted),
+                        increase this parameter (usually values up
+                        to 8 are reasonable). Most users of this
+                        method should find the default value sufficient.
+            plot:   *** CURRENTLY UNAVAILABLE, ALWAYS FALSE ***
+                        plot the fit and the residual. In this each
+                        indivual fit has to be approved, by typing 'y'
+                        or 'n'
+            outlog:     Output the coefficients of the best-fit
+                        function to logger (default is False)
+            blfile:     Name of a text file in which the best-fit
+                        parameter values to be written
+                        (default is "": no file/logger output)
+
+        Example:
+            bscan = scan.auto_cspline_baseline(npiece=3, insitu=False)
+        """
+
+        varlist = vars()
+
+        if insitu is None: insitu = rcParams['insitu']
+        if insitu:
+            workscan = self
+        else:
+            workscan = self.copy()
+
+        nchan = workscan.nchan()
+        
+        if mask is None: mask = [True for i in xrange(nchan)]
+        if npiece is None: npiece = 2
+        if clipthresh is None: clipthresh = 3.0
+        if clipniter is None: clipniter = 1
+        if edge is None: edge = (0, 0)
+        if threshold is None: threshold = 3
+        if chan_avg_limit is None: chan_avg_limit = 1
+        if plot is None: plot = False
+        if outlog is None: outlog = False
+        if blfile is None: blfile = ""
+
+        outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile)))
+        
+        from asap.asaplinefind import linefinder
+        from asap import _is_sequence_or_number as _is_valid
+
+        if not (isinstance(edge, list) or isinstance(edge, tuple)): edge = [ edge ]
+        individualedge = False;
+        if len(edge) > 1: individualedge = isinstance(edge[0], list) or isinstance(edge[0], tuple)
+
+        if individualedge:
+            for edgepar in edge:
+                if not _is_valid(edgepar, int):
+                    raise ValueError, "Each element of the 'edge' tuple has \
+                                       to be a pair of integers or an integer."
+        else:
+            if not _is_valid(edge, int):
+                raise ValueError, "Parameter 'edge' has to be an integer or a \
+                                   pair of integers specified as a tuple. \
+                                   Nested tuples are allowed \
+                                   to make individual selection for different IFs."
+
+            if len(edge) > 1:
+                curedge = edge
+            else:
+                curedge = edge + edge
+
+        try:
+            #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. 
+            if individualedge:
+                curedge = []
+                for i in xrange(len(edge)):
+                    curedge += edge[i]
+                
+            workscan._auto_cspline_baseline(mask, npiece, clipthresh, clipniter, curedge, threshold, chan_avg_limit, outlog, blfile)
+
+            workscan._add_history("auto_cspline_baseline", varlist)
+            
+            if insitu:
+                self._assign(workscan)
+            else:
+                return workscan
+            
+        except RuntimeError, e:
+            msg = "The fit failed, possibly because it didn't converge."
+            if rcParams["verbose"]:
+                asaplog.push(str(e))
+                asaplog.push(str(msg))
+                return
+            else:
+                raise RuntimeError(str(e)+'\n'+msg)
+
+
+    @asaplog_post_dec
+    def poly_baseline(self, insitu=None, mask=None, order=None, plot=None, outlog=None, blfile=None):
+        """\
+        Return a scan which has been baselined (all rows) by a polynomial.
+        Parameters:
+            insitu:     if False a new scantable is returned.
+                        Otherwise, the scaling is done in-situ
+                        The default is taken from .asaprc (False)
+            mask:       an optional mask
+            order:      the order of the polynomial (default is 0)
+            plot:       plot the fit and the residual. In this each
+                        indivual fit has to be approved, by typing 'y'
+                        or 'n'
+            outlog:     Output the coefficients of the best-fit
+                        function to logger (default is False)
+            blfile:     Name of a text file in which the best-fit
+                        parameter values to be written
+                        (default is "": no file/logger output)
+
+        Example:
+            # return a scan baselined by a third order polynomial,
+            # not using a mask
+            bscan = scan.poly_baseline(order=3)
+        """
+        
+        varlist = vars()
+        
+        if insitu is None: insitu = rcParams["insitu"]
+        if insitu:
+            workscan = self
+        else:
+            workscan = self.copy()
+
+        nchan = workscan.nchan()
+        
+        if mask is None: mask = [True for i in xrange(nchan)]
+        if order is None: order = 0
+        if plot is None: plot = False
+        if outlog is None: outlog = False
+        if blfile is None: blfile = ""
+
+        outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile)))
+        
+        try:
+            rows = xrange(workscan.nrow())
+            
+            #if len(rows) > 0: workscan._init_blinfo()
+
+            if plot:
+                if outblfile: blf = open(blfile, "a")
+                
+                f = fitter()
+                f.set_function(lpoly=order)
+                for r in rows:
+                    f.x = workscan._getabcissa(r)
+                    f.y = workscan._getspectrum(r)
+                    f.mask = mask_and(mask, workscan._getmask(r))    # (CAS-1434)
+                    f.data = None
+                    f.fit()
+                    
+                    f.plot(residual=True)
+                    accept_fit = raw_input("Accept fit ( [y]/n ): ")
+                    if accept_fit.upper() == "N":
+                        #workscan._append_blinfo(None, None, None)
+                        continue
+                    
+                    blpars = f.get_parameters()
+                    masklist = workscan.get_masklist(f.mask, row=r, silent=True)
+                    #workscan._append_blinfo(blpars, masklist, f.mask)
+                    workscan._setspectrum(f.fitter.getresidual(), r)
+                    
+                    if outblfile:
+                        rms = workscan.get_rms(f.mask, r)
+                        dataout = workscan.format_blparams_row(blpars["params"], blpars["fixed"], rms, str(masklist), r, True)
+                        blf.write(dataout)
+
+                f._p.unmap()
+                f._p = None
+
+                if outblfile: blf.close()
+            else:
+                workscan._poly_baseline(mask, order, outlog, blfile)
+            
+            workscan._add_history("poly_baseline", varlist)
+            
+            if insitu:
+                self._assign(workscan)
+            else:
+                return workscan
+            
+        except RuntimeError, e:
+            msg = "The fit failed, possibly because it didn't converge."
+            if rcParams["verbose"]:
+                asaplog.push(str(e))
+                asaplog.push(str(msg))
+                return
+            else:
+                raise RuntimeError(str(e)+'\n'+msg)
+
+
+    def auto_poly_baseline(self, insitu=None, mask=None, order=None, edge=None, threshold=None,
+                           chan_avg_limit=None, plot=None, outlog=None, blfile=None):
+        """\
+        Return a scan which has been baselined (all rows) by a polynomial.
+        Spectral lines are detected first using linefinder and masked out
+        to avoid them affecting the baseline solution.
+
+        Parameters:
+            insitu:     if False a new scantable is returned.
+                        Otherwise, the scaling is done in-situ
+                        The default is taken from .asaprc (False)
+            mask:       an optional mask retreived from scantable
+            order:      the order of the polynomial (default is 0)
+            edge:       an optional number of channel to drop at
+                        the edge of spectrum. If only one value is
+                        specified, the same number will be dropped
+                        from both sides of the spectrum. Default
+                        is to keep all channels. Nested tuples
+                        represent individual edge selection for
+                        different IFs (a number of spectral channels
+                        can be different)
+            threshold:  the threshold used by line finder. It is
+                        better to keep it large as only strong lines
+                        affect the baseline solution.
+            chan_avg_limit:
+                        a maximum number of consequtive spectral
+                        channels to average during the search of
+                        weak and broad lines. The default is no
+                        averaging (and no search for weak lines).
+                        If such lines can affect the fitted baseline
+                        (e.g. a high order polynomial is fitted),
+                        increase this parameter (usually values up
+                        to 8 are reasonable). Most users of this
+                        method should find the default value sufficient.
+            plot:       plot the fit and the residual. In this each
+                        indivual fit has to be approved, by typing 'y'
+                        or 'n'
+            outlog:     Output the coefficients of the best-fit
+                        function to logger (default is False)
+            blfile:     Name of a text file in which the best-fit
+                        parameter values to be written
+                        (default is "": no file/logger output)
+
+        Example:
+            bscan = scan.auto_poly_baseline(order=7, insitu=False)
+        """
+
+        varlist = vars()
+
+        if insitu is None: insitu = rcParams['insitu']
+        if insitu:
+            workscan = self
+        else:
+            workscan = self.copy()
+
+        nchan = workscan.nchan()
+        
+        if mask is None: mask = [True for i in xrange(nchan)]
+        if order is None: order = 0
+        if edge is None: edge = (0, 0)
+        if threshold is None: threshold = 3
+        if chan_avg_limit is None: chan_avg_limit = 1
+        if plot is None: plot = False
+        if outlog is None: outlog = False
+        if blfile is None: blfile = ""
+
+        outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile)))
+        
+        from asap.asaplinefind import linefinder
+        from asap import _is_sequence_or_number as _is_valid
+
+        if not (isinstance(edge, list) or isinstance(edge, tuple)): edge = [ edge ]
+        individualedge = False;
+        if len(edge) > 1: individualedge = isinstance(edge[0], list) or isinstance(edge[0], tuple)
+
+        if individualedge:
+            for edgepar in edge:
+                if not _is_valid(edgepar, int):
+                    raise ValueError, "Each element of the 'edge' tuple has \
+                                       to be a pair of integers or an integer."
+        else:
+            if not _is_valid(edge, int):
+                raise ValueError, "Parameter 'edge' has to be an integer or a \
+                                   pair of integers specified as a tuple. \
+                                   Nested tuples are allowed \
+                                   to make individual selection for different IFs."
+
+            if len(edge) > 1:
+                curedge = edge
+            else:
+                curedge = edge + edge
+
+        try:
+            rows = xrange(workscan.nrow())
+            
+            #if len(rows) > 0: workscan._init_blinfo()
+
+            if plot:
+                if outblfile: blf = open(blfile, "a")
+                
+                fl = linefinder()
+                fl.set_options(threshold=threshold,avg_limit=chan_avg_limit)
+                fl.set_scan(workscan)
+                f = fitter()
+                f.set_function(lpoly=order)
+
+                for r in rows:
+                    if individualedge:
+                        if len(edge) <= workscan.getif(r):
+                            raise RuntimeError, "Number of edge elements appear to " \
+                                  "be less than the number of IFs"
+                        else:
+                            curedge = edge[workscan.getif(r)]
+
+                    fl.find_lines(r, mask_and(mask, workscan._getmask(r)), curedge)  # (CAS-1434)
+
+                    f.x = workscan._getabcissa(r)
+                    f.y = workscan._getspectrum(r)
+                    f.mask = fl.get_mask()
+                    f.data = None
+                    f.fit()
+
+                    f.plot(residual=True)
+                    accept_fit = raw_input("Accept fit ( [y]/n ): ")
+                    if accept_fit.upper() == "N":
+                        #workscan._append_blinfo(None, None, None)
+                        continue
+
+                    blpars = f.get_parameters()
+                    masklist = workscan.get_masklist(f.mask, row=r, silent=True)
+                    #workscan._append_blinfo(blpars, masklist, f.mask)
+                    workscan._setspectrum(f.fitter.getresidual(), r)
+
+                    if outblfile:
+                        rms = workscan.get_rms(f.mask, r)
+                        dataout = workscan.format_blparams_row(blpars["params"], blpars["fixed"], rms, str(masklist), r, True)
+                        blf.write(dataout)
+                    
+                f._p.unmap()
+                f._p = None
+
+                if outblfile: blf.close()
+                
+            else:
+                if individualedge:
+                    curedge = []
+                    for i in xrange(len(edge)):
+                        curedge += edge[i]
+                
+                workscan._auto_poly_baseline(mask, order, curedge, threshold, chan_avg_limit, outlog, blfile)
+
+            workscan._add_history("auto_poly_baseline", varlist)
+            
+            if insitu:
+                self._assign(workscan)
+            else:
+                return workscan
+            
+        except RuntimeError, e:
+            msg = "The fit failed, possibly because it didn't converge."
+            if rcParams["verbose"]:
+                asaplog.push(str(e))
+                asaplog.push(str(msg))
+                return
+            else:
+                raise RuntimeError(str(e)+'\n'+msg)
+
+
+    ### OBSOLETE ##################################################################
     @asaplog_post_dec
     def old_poly_baseline(self, mask=None, order=0, plot=False, uselin=False, insitu=None, rows=None):
-        """\
+        """
         Return a scan which has been baselined (all rows) by a polynomial.
         
@@ -1985 +2449 @@
             raise RuntimeError(msg)
 
-    @asaplog_post_dec
-    def poly_baseline(self, mask=None, order=0, plot=False, batch=False, insitu=None, rows=None):
-        """\
-        Return a scan which has been baselined (all rows) by a polynomial.
-        Parameters:
-            mask:       an optional mask
-            order:      the order of the polynomial (default is 0)
-            plot:       plot the fit and the residual. In this each
-                        indivual fit has to be approved, by typing 'y'
-                        or 'n'. Ignored if batch = True. 
-            batch:      if True a faster algorithm is used and logs
-                        including the fit results are not output
-                        (default is False) 
-            insitu:     if False a new scantable is returned.
-                        Otherwise, the scaling is done in-situ
-                        The default is taken from .asaprc (False)
-            rows:       row numbers of spectra to be baselined.
-                        (default is None: for all rows)
-        Example:
-            # return a scan baselined by a third order polynomial,
-            # not using a mask
-            bscan = scan.poly_baseline(order=3)
-        """
+    def _init_blinfo(self):
+        """\
+        Initialise the following three auxiliary members:
+           blpars : parameters of the best-fit baseline, 
+           masklists : mask data (edge positions of masked channels) and 
+           actualmask : mask data (in boolean list), 
+        to keep for use later (including output to logger/text files). 
+        Used by poly_baseline() and auto_poly_baseline() in case of
+        'plot=True'. 
+        """
+        self.blpars = []
+        self.masklists = []
+        self.actualmask = []
+        return
+
+    def _append_blinfo(self, data_blpars, data_masklists, data_actualmask):
+        """\
+        Append baseline-fitting related info to blpars, masklist and
+        actualmask. 
+        """
+        self.blpars.append(data_blpars)
+        self.masklists.append(data_masklists)
+        self.actualmask.append(data_actualmask)
+        return
         
-        varlist = vars()
-        
-        if insitu is None: insitu = rcParams["insitu"]
-        if insitu:
-            workscan = self
-        else:
-            workscan = self.copy()
-
-        nchan = workscan.nchan()
-        
-        if mask is None:
-            mask = [True for i in xrange(nchan)]
-
-        try:
-            if rows == None:
-                rows = xrange(workscan.nrow())
-            elif isinstance(rows, int):
-                rows = [ rows ]
-            
-            if len(rows) > 0:
-                workscan.blpars = []
-                workscan.masklists = []
-                workscan.actualmask = []
-
-            if batch:
-                workscan._poly_baseline_batch(mask, order)
-            elif plot:
-                f = fitter()
-                f.set_function(lpoly=order)
-                for r in rows:
-                    f.x = workscan._getabcissa(r)
-                    f.y = workscan._getspectrum(r)
-                    f.mask = mask_and(mask, workscan._getmask(r))    # (CAS-1434)
-                    f.data = None
-                    f.fit()
-                    
-                    f.plot(residual=True)
-                    accept_fit = raw_input("Accept fit ( [y]/n ): ")
-                    if accept_fit.upper() == "N":
-                        self.blpars.append(None)
-                        self.masklists.append(None)
-                        self.actualmask.append(None)
-                        continue
-                    workscan._setspectrum(f.fitter.getresidual(), r)
-                    workscan.blpars.append(f.get_parameters())
-                    workscan.masklists.append(workscan.get_masklist(f.mask, row=r))
-                    workscan.actualmask.append(f.mask)
-                    
-                f._p.unmap()
-                f._p = None
-            else:
-                for r in rows:
-                    fitparams = workscan._poly_baseline(mask, order, r)
-                    params = fitparams.getparameters()
-                    fmtd = ", ".join(["p%d = %3.6f" % (i, v) for i, v in enumerate(params)])
-                    errors = fitparams.geterrors()
-                    fmask = mask_and(mask, workscan._getmask(r))
-
-                    workscan.blpars.append({"params":params,
-                                            "fixed": fitparams.getfixedparameters(),
-                                            "formatted":fmtd, "errors":errors})
-                    workscan.masklists.append(workscan.get_masklist(fmask, r, silent=True))
-                    workscan.actualmask.append(fmask)
-                    
-                    asaplog.push(fmtd)
-            
-            workscan._add_history("poly_baseline", varlist)
-            
-            if insitu:
-                self._assign(workscan)
-            else:
-                return workscan
-            
-        except RuntimeError, e:
-            msg = "The fit failed, possibly because it didn't converge."
-            if rcParams["verbose"]:
-                asaplog.push(str(e))
-                asaplog.push(str(msg))
-                return
-            else:
-                raise RuntimeError(str(e)+'\n'+msg)
-
-
-    def auto_poly_baseline(self, mask=None, edge=(0, 0), order=0,
-                           threshold=3, chan_avg_limit=1, plot=False,
-                           insitu=None, rows=None):
-        """\
-        Return a scan which has been baselined (all rows) by a polynomial.
-        Spectral lines are detected first using linefinder and masked out
-        to avoid them affecting the baseline solution.
-
-        Parameters:
-
-            mask:       an optional mask retreived from scantable
-
-            edge:       an optional number of channel to drop at the edge of
-                        spectrum. If only one value is
-                        specified, the same number will be dropped from
-                        both sides of the spectrum. Default is to keep
-                        all channels. Nested tuples represent individual
-                        edge selection for different IFs (a number of spectral
-                        channels can be different)
-
-            order:      the order of the polynomial (default is 0)
-
-            threshold:  the threshold used by line finder. It is better to
-                        keep it large as only strong lines affect the
-                        baseline solution.
-
-            chan_avg_limit:
-                        a maximum number of consequtive spectral channels to
-                        average during the search of weak and broad lines.
-                        The default is no averaging (and no search for weak
-                        lines). If such lines can affect the fitted baseline
-                        (e.g. a high order polynomial is fitted), increase this
-                        parameter (usually values up to 8 are reasonable). Most
-                        users of this method should find the default value
-                        sufficient.
-
-            plot:       plot the fit and the residual. In this each
-                        indivual fit has to be approved, by typing 'y'
-                        or 'n'
-
-            insitu:     if False a new scantable is returned.
-                        Otherwise, the scaling is done in-situ
-                        The default is taken from .asaprc (False)
-            rows:       row numbers of spectra to be processed.
-                        (default is None: for all rows)
-
-
-        Example::
-
-            scan2 = scan.auto_poly_baseline(order=7, insitu=False)
-
-        """
-        if insitu is None: insitu = rcParams['insitu']
-        varlist = vars()
-        from asap.asaplinefind import linefinder
-        from asap import _is_sequence_or_number as _is_valid
-
-        # check whether edge is set up for each IF individually
-        individualedge = False;
-        if len(edge) > 1:
-            if isinstance(edge[0], list) or isinstance(edge[0], tuple):
-                individualedge = True;
-
-        if not _is_valid(edge, int) and not individualedge:
-            raise ValueError, "Parameter 'edge' has to be an integer or a \
-            pair of integers specified as a tuple. Nested tuples are allowed \
-            to make individual selection for different IFs."
-
-        curedge = (0, 0)
-        if individualedge:
-            for edgepar in edge:
-                if not _is_valid(edgepar, int):
-                    raise ValueError, "Each element of the 'edge' tuple has \
-                                       to be a pair of integers or an integer."
-        else:
-            curedge = edge;
-
-        if not insitu:
-            workscan = self.copy()
-        else:
-            workscan = self
-
-        # setup fitter
-        f = fitter()
-        f.set_function(lpoly=order)
-
-        # setup line finder
-        fl = linefinder()
-        fl.set_options(threshold=threshold,avg_limit=chan_avg_limit)
-
-        fl.set_scan(workscan)
-
-        if mask is None:
-            mask = _n_bools(workscan.nchan(), True)
-        
-        if rows is None:
-            rows = xrange(workscan.nrow())
-        elif isinstance(rows, int):
-            rows = [ rows ]
-        
-        # Save parameters of baseline fits & masklists as a class attribute.
-        # NOTICE: It does not reflect changes in scantable!
-        if len(rows) > 0:
-            self.blpars=[]
-            self.masklists=[]
-            self.actualmask=[]
-        asaplog.push("Processing:")
-        for r in rows:
-            msg = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % \
-                (workscan.getscan(r), workscan.getbeam(r), workscan.getif(r), \
-                 workscan.getpol(r), workscan.getcycle(r))
-            asaplog.push(msg, False)
-
-            # figure out edge parameter
-            if individualedge:
-                if len(edge) >= workscan.getif(r):
-                    raise RuntimeError, "Number of edge elements appear to " \
-                                        "be less than the number of IFs"
-                    curedge = edge[workscan.getif(r)]
-
-            actualmask = mask_and(mask, workscan._getmask(r))    # (CAS-1434)
-
-            # setup line finder
-            fl.find_lines(r, actualmask, curedge)
-            
-            f.x = workscan._getabcissa(r)
-            f.y = workscan._getspectrum(r)
-            f.mask = fl.get_mask()
-            f.data = None
-            f.fit()
-
-            # Show mask list
-            masklist=workscan.get_masklist(f.mask, row=r, silent=True)
-            msg = "mask range: "+str(masklist)
-            asaplog.push(msg, False)
-
-            if plot:
-                f.plot(residual=True)
-                x = raw_input("Accept fit ( [y]/n ): ")
-                if x.upper() == 'N':
-                    self.blpars.append(None)
-                    self.masklists.append(None)
-                    self.actualmask.append(None)
-                    continue
-
-            workscan._setspectrum(f.fitter.getresidual(), r)
-            self.blpars.append(f.get_parameters())
-            self.masklists.append(masklist)
-            self.actualmask.append(f.mask)
-        if plot:
-            f._p.unmap()
-            f._p = None
-        workscan._add_history("auto_poly_baseline", varlist)
-        if insitu:
-            self._assign(workscan)
-        else:
-            return workscan
-
     @asaplog_post_dec
     def rotate_linpolphase(self, angle):
@@ -2744 +2968 @@
             self.set_freqframe(rcParams['scantable.freqframe'])
 
+
     def __getitem__(self, key):
         if key < 0: