added more command line options

examples/findPeaks.py

@@ -52,6 +52,12 @@ parser.add_argument('-r','--rel_height',
 parser.add_argument('-f','--fit_range_factor',
                     help = "fit_range_factor: fit range = fit_range_factor * fwhm",
                     type=float, default=1.5)
+parser.add_argument('-t','--threshold',
+                    help = "threshold, i.e. minimum valid channel nmber",
+                    type=float, default=51)
+parser.add_argument('-n','--noplot', action='store_true')
+parser.add_argument('-v','--verbose', action='store_true')
+
 args = parser.parse_args()
 filename=args.filename
 # some constants for peak-finder
@@ -60,10 +66,13 @@ min_width = args.width       #  minimum width
 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
+verbose = args.verbose
+plot = not args.noplot
 
 # read data
-hst = np.loadtxt(filename, dtype=np.uint32) 
-bin_edges= np.linspace(0, 4096, 4097)
+hst = np.loadtxt(filename, dtype=np.uint32)
+bin_edges= np.linspace(0, len(hst), len(hst)+1, endpoint=True)
 
 # find maxima with scipy.signal.find_peaks()
 peaks, peak_props = find_peaks(hst,
@@ -96,7 +105,7 @@ for i, p in enumerate(peaks):
     base = (hst[left_bases[i]]+hst[right_bases[i]])/2.
    # print(p, wid, base)
 
-    mn = int(p-wid)
+    mn = max(min_channel, int(p-wid))
     mx = int(p+wid)
     bins = range(mn, mx+1)
     counts = hst[mn : mx]
@@ -120,7 +129,8 @@ for i, p in enumerate(peaks):
 
 # Anpassung ausführen:
     fit.do_fit()
-    fit.report()  # optionally, report fit results
+    if verbose:
+        fit.report()  # optionally, report fit results
     
 # Ergebnisse anzeigen und speichern:
     print("{} Peak {}: {:.2f} ± {:.2g} ( {:.2f} {:.1f}%  {:.1f}% )".format(i, p,
@@ -134,8 +144,9 @@ for i, p in enumerate(peaks):
     plot_ranges[i][0] = p-wid
     plot_ranges[i][1] = p+wid+1
 
-fit_results = np.append(fit_results, hdata)
-plot_ranges[len(peaks+1)][1] = 4000
-kafe2.plot(fits = fit_results, x_range = list(map(tuple, plot_ranges)),
+if plot:
+    fit_results = np.append(fit_results, hdata)
+    plot_ranges[len(peaks+1)][1] = 4000
+    kafe2.plot(fits = fit_results, x_range = list(map(tuple, plot_ranges)),
            x_label = "Channel number", y_label = "Counts",
            font_scale = 0.5, save=False)