Plot span of fitted frequencies in vib_anayze.py.

diff --git a/calibcant/vib_analyze.py b/calibcant/vib_analyze.py
index cfa2c3e90e45663f409010cf18e1b9ef80359ac6..4c2843526d91bedf690cb6a848f0b8492e0954bc 100755 (executable)
--- a/calibcant/vib_analyze.py
+++ b/calibcant/vib_analyze.py
@@ -98,7 +98,7 @@ def vib_analyze(deflection_bits, freq, minFreq=500, maxFreq=7000,
         print "A = %g, \t B = %g, \t C = %g" % (A, B, C)
 
     vib_plot(deflection_bits, freq_axis, power, A, B, C,
-             plotVerbose=plotVerbose)
+             minFreq, maxFreq, plotVerbose=plotVerbose)
 
     # Our A is in uV**2, so convert back to Volts**2
     return lorentzian_area(A,B,C) * 1e-12
@@ -182,7 +182,7 @@ def fit_psd(freq_axis, psd_data, minFreq=500, maxFreq=7000) :
         print "guesses : %g, %g, %g" % (A_guess, B_guess, C_guess)
     if PLOT_GUESSED_LORENTZIAN:
         vib_plot(None, freq_axis, psd_data, A_guess, B_guess, C_guess,
-                 plotVerbose=True)
+                 minFreq, maxFreq, plotVerbose=True)
 
     # fit Lorentzian using Gnuplot's 'fit' command
     g = GnuplotBiDir.Gnuplot()
@@ -248,7 +248,7 @@ def vib_load(datafile=None) :
     return data
 
 def vib_plot(deflection_bits, freq_axis, power, A, B, C,
-             plotVerbose=True) :
+             minFreq=None, maxFreq=None, plotVerbose=True) :
     """
     If plotVerbose or config.PYLAB_VERBOSE == True, plot 3 subfigures:
      Time series (Vphoto vs sample index) (show any major drift events),
@@ -290,10 +290,16 @@ def vib_plot(deflection_bits, freq_axis, power, A, B, C,
             axes = common._pylab.subplot(111)
         common._pylab.hold(False)
         common._pylab.semilogy(freq_axis, power, 'r.-')
-        fitdata = C / ((A**2-freq_axis**2)**2 + (B*freq_axis)**2)
+        common._pylab.hold(True)
         xmin,xmax = axes.get_xbound()
         ymin,ymax = axes.get_ybound()
-        common._pylab.hold(True)
+        
+        if minFreq is not None and maxFreq is not None:
+            # highlight the region we're fitting in
+            common._pylab.axvspan(minFreq, maxFreq, facecolor='g', alpha=0.1,
+                                  zorder = -1)
+        
+        fitdata = C / ((A**2-freq_axis**2)**2 + (B*freq_axis)**2)
         common._pylab.plot(freq_axis, fitdata, 'b-');
         common._pylab.hold(False)
         axes.axis([xmin,xmax,ymin,ymax])