Changeset 2447 for trunk/python

Timestamp:

03/29/12 15:20:23 (13 years ago)

Author:

Malte Marquarding

Message:

Issue #264: silence skydip.

File:

• trunk/python/opacity.py (modified) (2 diffs)

trunk/python/opacity.py

@@ -7 +7 @@
 from asap.selector import selector
 from asap._asap import atmosphere
-
+from asap import rcParams
 
 class model(object):
@@ -151 +151 @@
         plot:       Plot each fit (airmass vs. Tsys). Default is 'False'
     """
-    if plot:
-        from matplotlib import pylab
-    scan = _import_data(data)
-    f = fitter()
-    f.set_function(poly=1)
-    sel = selector()
-    basesel = scan.get_selection()
-    inos = scan.getifnos()
-    pnos = scan.getpolnos()
-    opacities = []
-    om = model(temperature, pressure, humidity)
-    for ino in inos:
-        sel.set_ifs(ino)
-        opacity = []
-        fits = []
-        airms = []
-        tsyss = []
+    # quiten output
+    verbose = rcParams["verbose"]
+    rcParams["verbose"] = False
+    try:
         if plot:
-            pylab.cla()
-            pylab.ioff()
-            pylab.clf()
-            pylab.xlabel("Airmass")
-            pylab.ylabel(r"$T_{sys}$")
-        for pno in pnos:
-            sel.set_polarisations(pno)
-            scan.set_selection(basesel+sel)
-            freq = scan.get_coordinate(0).get_reference_value()/1e9
-            freqstr = "%0.4f GHz" % freq
-            tsys = scan.get_tsys()
-            elev = scan.get_elevation()
-            airmass = [ 1./math.sin(i) for i in elev ]
-            airms.append(airmass)
-            tsyss.append(tsys)
-            f.set_data(airmass, tsys)
-            f.fit()
-            fits.append(f.get_fit())
-            params = f.get_parameters()["params"]
-            opacity.append(params[1]/tsky)
-        if averagepol:
-            opacities.append(sum(opacity)/len(opacity))
-        else:
-            opacities += opacity
+            from matplotlib import pylab
+        scan = _import_data(data)
+        f = fitter()
+        f.set_function(poly=1)
+        sel = selector()
+        basesel = scan.get_selection()
+        inos = scan.getifnos()
+        pnos = scan.getpolnos()
+        opacities = []
+        om = model(temperature, pressure, humidity)
+        for ino in inos:
+            sel.set_ifs(ino)
+            opacity = []
+            fits = []
+            airms = []
+            tsyss = []
+            if plot:
+                pylab.cla()
+                pylab.ioff()
+                pylab.clf()
+                pylab.xlabel("Airmass")
+                pylab.ylabel(r"$T_{sys}$")
+            for pno in pnos:
+                sel.set_polarisations(pno)
+                scan.set_selection(basesel+sel)
+                freq = scan.get_coordinate(0).get_reference_value()/1e9
+                freqstr = "%0.4f GHz" % freq
+                tsys = scan.get_tsys()
+                elev = scan.get_elevation()
+                airmass = [ 1./math.sin(i) for i in elev ]
+                airms.append(airmass)
+                tsyss.append(tsys)
+                f.set_data(airmass, tsys)
+                f.fit()
+                fits.append(f.get_fit())
+                params = f.get_parameters()["params"]
+                opacity.append(params[1]/tsky)
+            if averagepol:
+                opacities.append(sum(opacity)/len(opacity))
+            else:
+                opacities += opacity
+            if plot:
+                colors = ['b','g','k']
+                n = len(airms)
+                for i in range(n):
+                    pylab.plot(airms[i], tsyss[i], 'o', color=colors[i])
+                    pylab.plot(airms[i], fits[i], '-', color=colors[i])
+                    pylab.figtext(0.7,0.3-(i/30.0),
+                                      r"$\tau_{fit}=%0.2f$" % opacity[i],
+                                      color=colors[i])
+                if averagepol:
+                    pylab.figtext(0.7,0.3-(n/30.0),
+                                      r"$\tau_{avg}=%0.2f$" % opacities[-1],
+                                      color='r')
+                    n +=1
+                pylab.figtext(0.7,0.3-(n/30.0),
+                              r"$\tau_{model}=%0.2f$" % om.get_opacities(freq*1e9),
+                              color='grey')
+
+                pylab.title("IF%d : %s" % (ino, freqstr))
+
+                pylab.ion()
+                pylab.draw()
+                raw_input("Hit <return> for next fit...")
+            sel.reset()
+
+        scan.set_selection(basesel)
         if plot:
-            colors = ['b','g','k']
-            n = len(airms)
-            for i in range(n):
-                pylab.plot(airms[i], tsyss[i], 'o', color=colors[i])
-                pylab.plot(airms[i], fits[i], '-', color=colors[i])
-                pylab.figtext(0.7,0.3-(i/30.0),
-                                  r"$\tau_{fit}=%0.2f$" % opacity[i],
-                                  color=colors[i])
-            if averagepol:
-                pylab.figtext(0.7,0.3-(n/30.0),
-                                  r"$\tau_{avg}=%0.2f$" % opacities[-1],
-                                  color='r')
-                n +=1
-            pylab.figtext(0.7,0.3-(n/30.0),
-                          r"$\tau_{model}=%0.2f$" % om.get_opacities(freq*1e9),
-                          color='grey')
-
-            pylab.title("IF%d : %s" % (ino, freqstr))
-
-            pylab.ion()
-            pylab.draw()
-            raw_input("Hit <return> for next fit...")
-        sel.reset()
-
-    scan.set_selection(basesel)
-    if plot:
-        pylab.close()
-    return opacities
+            pylab.close()
+        return opacities
+    finally:
+        rcParams["verbose"] = verbose