added option to select size of smoothing window

examples/findPeaks.py

@@ -55,6 +55,9 @@ parser.add_argument('-f','--fit_range_factor',
 parser.add_argument('-t','--threshold',
                     help = "threshold, i.e. minimum valid channel nmber (51)",
                     type=float, default=51)
+parser.add_argument('-s','--smooth',
+                    help = "smoothing-window size (5) ",
+                    type=float, default=5)
 parser.add_argument('-n','--noplot', action='store_true')
 parser.add_argument('-k','--kafe2_plots', action='store_true')
 parser.add_argument('-v','--verbose', action='store_true')
@@ -68,6 +71,8 @@ rel_height = args.rel_height     #  width at half peak height (i.e. FWHM)
 # constants for fit range 
 fit_range_factor = args.fit_range_factor # fit range = fit_range_factor * fwhm
 min_channel = args.threshold # threshold for min. valid channel number
+smoothing_window = args.smooth
+
 verbose = args.verbose
 plot = not args.noplot
 kafe2_plots = args.kafe2_plots
@@ -81,7 +86,10 @@ bin_edges= np.linspace(0, len(hst), len(hst)+1, endpoint=True)
 
 # find maxima with scipy.signal.find_peaks()
 #  firts, smoothen data to reduce statistical noise
-hst_s = meanFilter(hst, max(1, min_width//4))
+if smoothing_window > 1:
+    hst_s = meanFilter(hst, smoothing_window)
+else:
+    hst_s = hst
 # search for peaks
 peaks, peak_props = find_peaks(hst_s,
                                prominence=min_prominence,
@@ -173,7 +181,7 @@ if plot:
     ax0.plot(xhst, hst_s, 'b-', linewidth=1, zorder=2, label = 'smoothed channel counts')
     ax0.errorbar(xhst, hst, yerr=np.sqrt(hst), zorder=1, label='channel counts',
                  fmt='.', color='grey', markersize=2, linewidth=2, alpha=0.5, )
-    ax0.plot(peaks, hst_s[peaks], '*', color='red', markersize=10, zorder=3,
+    ax0.plot(peaks, hst_s[peaks], 'x', color='red', markersize=10, zorder=3,
              label='result of find_peaks()')
     ax0.legend(loc = 'best')