Changeset 1232 for trunk/python

Timestamp:

09/01/06 13:14:11 (18 years ago)

Author:

mar637

Message:

Merge from Release2.1.0b tag

Location:

trunk/python

Files:

• asapfit.py (modified) (2 diffs)
• asapfitter.py (modified) (6 diffs)
• asapmath.py (modified) (2 diffs)
• asapplotter.py (modified) (1 diff)

trunk/python/asapfit.py

@@ -55 +55 @@
                   }
             comp.append(d)
+            k+=1
         out.append(comp)
         return out
+
+    def save(self, filename):
+        f = file(filename, 'w')
+        parstr = ""
+        for i in xrange(self.getcomponents()[0]):
+            pname = "P%d"% (i)
+            parstr += "%-12s " % (pname)
+        header = "#%-12s %s\n" % ("Function", parstr)
+        f.write(header)
+        i = 0
+        funcs=self.getfunctions()
+        pars=self.getparameters()
+        for c in self.getcomponents():
+            line = " %-12s " % (funcs[i])
+            for j in xrange(c):
+                line += "%3.8f " % (pars[i*c+j])
+            i+=1
+            f.write(line+"\n")
+        f.close()
 
     def _format_pars(self, pars, ftype, unit):
@@ -63 +83 @@
             i = 0
             for p in pars:
-                out += ' p%d = %3.3f %s,' % (i,p,unit)
+                out += ' p%d = %3.6f %s,' % (i,p,unit)
                 i+=1
             out = out[1:-1]
         elif ftype == 'gauss':
-            out += 'peak = %3.3f , centre = %3.3f %s, FWHM = %3.3f %s' % (pars[0],pars[1],unit,pars[2],unit)
+            out += 'peak = %3.6f , centre = %3.6f %s, FWHM = %3.6f %s' % (pars[0],pars[1],unit,pars[2],unit)
         return out

trunk/python/asapfitter.py

@@ -100 +100 @@
 
         self.fitter.setexpression(self.fitfunc,n)
+        self.fitted = False
         return
 
@@ -142 +143 @@
                 self.fitter.estimate()
         try:
+            fxdpar = list(self.fitter.getfixedparameters())
+            if len(fxdpar) and fxdpar.count(0) == 0:
+                 raise RuntimeError,"No point fitting, if all parameters are fixed."
             converged = self.fitter.fit()
             if not converged:
@@ -155 +159 @@
         return
 
-    def store_fit(self):
-        """
-        Store the fit parameters in the scantable.
+    def store_fit(self, filename=None):
+        """
+        Save the fit parameters.
+        Parameters:
+            filename:    if specified save as an ASCII file, if None (default)
+                         store it in the scnatable
         """
         if self.fitted and self.data is not None:
@@ -169 +176 @@
             fit.setcomponents(self.components)
             fit.setframeinfo(self.data._getcoordinfo())
-            self.data._addfit(fit,self._fittedrow)
+            if filename is not None:
+                import os
+                filename = os.path.expandvars(os.path.expanduser(filename))
+                if os.path.exists(filename):
+                    raise IOError("File '%s' exists." % filename)
+                fit.save(filename)
+            else:
+                self.data._addfit(fit,self._fittedrow)
 
     #def set_parameters(self, params, fixed=None, component=None):
@@ -224 +238 @@
         Set the Parameters of a 'Gaussian' component, set with set_function.
         Parameters:
-            peak, centre, fhwm:  The gaussian parameters
+            peak, centre, fwhm:  The gaussian parameters
             peakfixed,
             centerfixed,
@@ -352 +366 @@
             for i in range(len(pars)):
                 fix = ""
-                if fixed[i]: fix = "(fixed)"
+                if len(fixed) and fixed[i]: fix = "(fixed)"
                 if errors :
                     out += '  p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i])

trunk/python/asapmath.py

@@ -12 +12 @@
         scanav:   True averages each scan separately.
                   False (default) averages all scans together,
-        weight:   Weighting scheme. 'none, 'var' (1/var(spec)
-                  weighted), 'tsys' (1/Tsys**2 weighted), 'tint'
-                  (integration time weighted) or 'tintsys' (Tsys
-                  and tint). The default is 'tint'
+        weight:   Weighting scheme.
+                    'none'     (mean no weight)
+                    'var'      (1/var(spec) weighted)
+                    'tsys'     (1/Tsys**2 weighted)
+                    'tint'     (integration time weighted)
+                    'tintsys'  (Tint/Tsys**2)
+                    'median'   ( median averaging)
         align:    align the spectra in velocity before averaging. It takes
                   the time of the first spectrum in the first scantable
@@ -70 +73 @@
     else:
         alignedlst = lst
-    s = scantable(stm._average(alignedlst, mask, weight.upper(), scanav))
+    if weight.upper() == 'MEDIAN':
+        # median doesn't support list of scantables - merge first
+        merged = None
+        if len(alignedlst) > 1:
+            merged = merge(alignedlst)
+        else:
+            merged = alignedlst[0]
+        s = scantable(stm._averagechannel(merged, 'MEDIAN', scanav))
+        del merged
+    else:
+        s = scantable(stm._average(alignedlst, mask, weight.upper(), scanav))
     s._add_history("average_time",varlist)
     print_log()

trunk/python/asapplotter.py

@@ -123 +123 @@
         del self._plotter.axes.patches[-1]
     axvspan. __doc__ = matplotlib.axes.Axes.axvspan.__doc__
+
     def axhspan(self, *args, **kwargs):
-        self._axes_callback("ahvspan", *args, **kwargs)
+        self._axes_callback("axhspan", *args, **kwargs)
         # hack to preventy mpl from redrawing the patch
         # it seem to convert the patch into lines on every draw.