Update PeakOTron.py

PeakOTron.py

@@ -1482,6 +1482,9 @@ class PeakOTron:
         idxs_peaks, _ = find_peaks(density_bgsub,
                                    distance=kwargs["peak_dist_nG"]*G_fft)
         
+        if(len(idxs_peaks)<2):
+            raise Exception("Less than 2 peaks found in spectrum. Spectrum cannot be fitted.")
+
 
         ########################################################################################################
         ##  Find peaks widths with scipy 'peak_widths'. 'peak_rel_height' is used to find the appropriate width criterion.
@@ -1533,6 +1536,9 @@ class PeakOTron:
         idxs_peak_widths = idxs_peak_widths[_idxs_sort]
         
 
+        if(len(idxs_peaks)<2):
+            raise Exception("Less than 2 peaks found in spectrum. Spectrum cannot be fitted.")
+        
          ########################################################################################################
         ##  Calculate and store bin statistic information.
         ########################################################################################################
@@ -1725,9 +1731,55 @@ class PeakOTron:
         mu_DCR = DCR*(kwargs["t_0"] + kwargs["t_gate"])
         
         ########################################################################################################
-        ## Store results in the class for fitting/reference.
+        ## Check for nans and correct as necessary.
         ########################################################################################################
 
+        if(np.isnan(Q_0)):
+            if(self._verbose):
+                print("Q_0 returned nan in prefit. Setting Q_0 to 1 bin"):
+                Q_0 = 1
+                dQ_0 = 0.1
+
+        if(np.isnan(G)):
+            if(self._verbose):
+                print("G returned nan in prefit. Setting G to 1 bin"):
+                G = 1
+                dG = 0.1
+
+        if(np.isnan(mu)):
+            if(self._verbose):
+                print("mu returned nan in prefit. Setting mu to 1 p.e."):
+                mu = 1
+                dmu = 0.1
+
+        if(np.isnan(lbda)):
+            if(self._verbose):
+                print("lbda returned nan in prefit. Setting lbda to 1e-2."):
+                lbda = 1e-2
+                dlbda = 0.1
+
+
+        if(np.isnan(sigma_0)):
+            if(self._verbose):
+                print("sigma_0 returned nan in prefit. Setting sigma_0 to 1 bin."):
+                sigma_0 = 1
+                dsigma_0 = 0.1
+
+        if(np.isnan(sigma_1)):
+            if(self._verbose):
+                print("sigma_0 returned nan in prefit. Setting sigma_1 to 1 bin."):
+                sigma_1 = 1
+                dsigma_1 = 0.1
+
+        if(np.isnan(DCR)):
+            if(self._verbose):
+                print("DCR returned nan in prefit. Setting DCR to 1e-9 GHz."):
+                DCR = 1e-9
+                dDCR = 1e-2
+
+        ########################################################################################################
+        ## Store results in the class for fitting/reference.
+        ########################################################################################################
 
         self._hist_data["data"] = data
         self._hist_data["bw"] = bw