CHANGE BigBGO.py

BigBGO.py

@@ -16,6 +16,8 @@ parser.add_argument("-xray", action='store_true', help = "if chosen, only xray d
 parser.add_argument("-trigger", action='store_true', help = "if chosen, only data triggered on T1 is beeing considered")  # on/off flag
 parser.add_argument("-plot", action='store_true', help = "if chosen, histogramms are beeing plotted, not saved to csv")  # on/off flag
 parser.add_argument("-sum", action='store_true', help = "if chosen, sums of A and B in keV will be histogrammed")  # on/off flag
+parser.add_argument("-two", action='store_true', help = "if chosen, functions function for two diodes A1 and A2")  # on/off flag
+parser.add_argument("-mV", action='store_true', help = "if chosen, data will not be changed to keV")  # on/off flag
 args = parser.parse_args()
 
 if args.verbose == None:
@@ -53,6 +55,11 @@ F2 =  1; thr[4] = 100;ch[4] = F2; name[4]="F2"#; u[4] = 1.0 #???
 B1 = 16; thr[5] = 12; ch[5] = B1; name[5]="B1"; u[5] = 1/0.674
 B2 = 13; thr[6] = 12; ch[6] = B2; name[6]="B2"; u[6] = 1/0.668
 
+energy = 'keV'
+if args.mV:
+    energy = 'mV'
+    u = [1.0,1.0,1.0,1.0,1.0,1.0,1.0]
+
 
 def main(): 
 
@@ -63,11 +70,14 @@ def main():
         outfile.write(str(Itime))
         outfile.close()
 
+    
+    
     nameadd = 'h'
     if args.xray: nameadd = nameadd + '_xray'
     if args.muon: nameadd = nameadd + '_muon'
     if args.trigger: nameadd = nameadd + '_trigger'
     if args.sum: nameadd = nameadd + '_sum'
+    if args.mV: nameadd = nameadd + '_mV'
 
     if args.hist:
         with fileinput.input(files=(file), encoding="utf-8") as f:
@@ -83,7 +93,7 @@ def main():
         h = do_hist(data)
         if args.plot:
             for i in range(0,len(ch)):
-                plt.plot(h['mV'], h[name[i]], label = name[i])
+                plt.plot(h[energy], h[name[i]], label = name[i])
                 plt.yscale('log')
             plt.show()
         else:
@@ -98,13 +108,17 @@ def main():
                     if l[0] == 'EI':
                         if not args.trigger or (args.trigger and CmV(l,ch[3]) >= thr[3]):
                             if not args.muon or (args.muon and ismuon(l)):  
-                                data[0].append(CmV(l,ch[0])*u[0]+CmV(l,ch[1])*u[1]+CmV(l,ch[2])*u[2])
+                                if not args.two:
+                                    data[0].append(CmV(l,ch[0])*u[0]+CmV(l,ch[1])*u[1]+CmV(l,ch[2])*u[2])
+                                else:
+                                    #data[0].append(CmV(l,ch[1])*u[1]+CmV(l,ch[2])*u[2])
+                                    data[0].append(CmV(l,ch[0])*u[0]+CmV(l,ch[1])*u[1])
                                 data[1].append(CmV(l,ch[5])*u[5]+CmV(l,ch[6])*u[6])
 
         h = do_hist_sum(data)
         if args.plot:
-            plt.plot(h['keV'], h['sumA'], label = 'sumA')
+            plt.plot(h[energy], h['sumA'], label = 'sumA')
-            plt.plot(h['keV'], h['sumB'], label = 'sumB')
+            plt.plot(h[energy], h['sumB'], label = 'sumB')
             plt.yscale('log')
             plt.show()
         else:
@@ -135,20 +149,20 @@ def Cphase(line, i):
 def do_hist(data):
     bin = int((maxV-minV)/resV)
     hist, bins = np.histogram(data[0], bins=bin, range=(minV,maxV), density=False)
-    df = pd.DataFrame({'keV':bins[1:]/2+ bins[:-1]/2, name[0]: hist})
+    df = pd.DataFrame({energy:bins[1:]/2+ bins[:-1]/2, name[0]: hist})
     for i in range(1, len(ch)):
         hist, bins = np.histogram(data[i], bins=bin, range=(minV,maxV), density=False)
-        df1 = pd.DataFrame({'keV':bins[1:]/2+ bins[:-1]/2, name[i]: hist})
+        df1 = pd.DataFrame({energy:bins[1:]/2+ bins[:-1]/2, name[i]: hist})
-        df = pd.merge(df, df1 , left_on = 'keV', right_on = 'keV')
+        df = pd.merge(df, df1 , left_on = energy, right_on = energy)
     return df
 
 def do_hist_sum(data):
     bin = int((maxV-minV)/resV)
     hist, bins = np.histogram(data[0], bins=bin, range=(minV,maxV), density=False)
-    df = pd.DataFrame({'keV':bins[1:]/2+ bins[:-1]/2, 'sumA': hist})
+    df = pd.DataFrame({energy:bins[1:]/2+ bins[:-1]/2, 'sumA': hist})
     hist, bins = np.histogram(data[1], bins=bin, range=(minV,maxV), density=False)
-    df1 = pd.DataFrame({'keV':bins[1:]/2+ bins[:-1]/2, 'sumB': hist})
+    df1 = pd.DataFrame({energy:bins[1:]/2+ bins[:-1]/2, 'sumB': hist})
-    df = pd.merge(df, df1 , left_on = 'keV', right_on = 'keV')
+    df = pd.merge(df, df1 , left_on = energy, right_on = energy)
     return df
 
 
@@ -162,8 +176,10 @@ def isXray(l):
     else: return False
 
 def ismuon(l):
-    if CmV(l,B1) >= thr[5] and CmV(l,B2) >= thr[6] and \
+    if not args.two and CmV(l,B1) >= thr[5] and CmV(l,B2) >= thr[6] and \
     CmV(l,A1) >= thr[0] and CmV(l,A2) >= thr[1] and CmV(l,A3) >= thr[2]: return True
+    if args.two and CmV(l,B1) >= thr[5] and CmV(l,B2) >= thr[6] and \
+    CmV(l,A1) >= thr[0] and CmV(l,A2) >= thr[1]: return True
     else: return False
 
 

landau_sum.py

@@ -21,7 +21,12 @@ file = 'data/2023-07-24-BigBGO-Bi207h_muon_sum'
 tit = "Comparison sumA(3)-sumB(2) of '2023-07-24-BigBGO-Bi207'"  
 
 #file = 'data/2023-07-29-BigBGO-Bi207-2h_muon_sum'    
-#tit = "Comparison sumA(3)-sumB(2) of '2023-07-29-BigBGO-Bi207'"
+#tit = "Comparison sumA(3)-sumB(2) of '2023-07-29-BigBGO-Bi207-2'"
+a = 610
+b = 1100
+
+file = 'data/2023-08-07-BigBGO-3h_muon_sum'    
+tit = "Comparison sumA(2 120°)-sumB(2) of '2023-08-07-BigBGO-3'"
 
 keV = True
 plt.figure(figsize=(17,12))
@@ -37,8 +42,6 @@ while len(f) > 0:
     else:
         f=f[:-1]
 
-a = 610
-b=1100
 startparams = [4000,230,30,25,170]
 energy = 'keV'
 resV = 0.838214/2
@@ -74,8 +77,9 @@ plt.title(tit, fontsize = fs+10, pad = 15)
 plt.yscale('log')
 plt.ylabel(ylab, fontsize = fs+5)
 plt.xlabel(xlab, fontsize=fs+5)
-plt.ylim(5,100)
+#plt.ylim(5,100) #1
-#plt.ylim(2,30)
+#plt.ylim(2,30) #2
+plt.ylim(0.9,50) #3
 plt.xlim(100,450) 
 
 #plt.show()

landau_trigger.py

@@ -13,20 +13,29 @@ from fit_functions import mips
 
 # file = 'data/2023-07-24-BigBGO-Bi207h_muon_trigger'    
 # tit = "Comparison of single diodes when T1 has triggered '2023-07-24-BigBGO-Bi207'"
-a = [190,183,180,233,215]
+# a = [190,183,180,233,215]
-b = [295,285,290,365,365]
+# b = [295,285,290,365,365]
 
-file = 'data/2023-07-29-BigBGO-Bi207-2h_muon_trigger' 
+# file = 'data/2023-07-29-BigBGO-Bi207-2h_muon_trigger' 
-tit = "Comparison of single diodes when T1 has triggered '2023-07-29-BigBGO-Bi207-2'"
+# tit = "Comparison of single diodes when T1 has triggered '2023-07-29-BigBGO-Bi207-2'"
-a = [175,175,190,215,225]
+# a = [175,175,190,215,225]
-b = [320,320,350,380,380]
+# b = [320,320,350,380,380]
+#startparams = [[150,85,10,4,100],[141,72,11,4,100],[141,72,11,4,100],[110,125,15,4,100],[110,110,16,4,100]]
+#channels=['A1','A2','A3','B1','B2']
+
+file = 'data/2023-08-07-BigBGO-3h_muon_trigger' 
+tit = "Comparison of single diodes when T1 has triggered '2023-08-07-BigBGO-3'"
+a = [175,210,210,220]
+b = [320,350,350,350]
+channels=['A2','A3','B1','B2']
+startparams = [[150,95,10,4,100],[141,115,11,4,100],[141,115,11,4,100],[110,125,15,4,100]]
 
 keV = True
 plt.figure(figsize=(17,12))
 
 data = pd.read_csv(file+'.hist', sep = ' ', delim_whitespace=False, skiprows=0)
 ch = pd.read_csv(file+'.hist', sep = ' ', nrows=0)
-channels=['A1','A2','A3','B1','B2']
+
     
 f = file
 Itime = None
@@ -38,7 +47,6 @@ while len(f) > 0:
         f=f[:-1]
 
 energy = 'keV'
-startparams = [[150,85,10,4,100],[141,72,11,4,100],[141,72,11,4,100],[110,125,15,4,100],[110,110,16,4,100]]
 
 resV = 0.838214/2
 # plt.plot(data[energy], np.multiply(mips(data[energy], 150, 75, 15), 3600/resV/Itime),'--',label = '1')
@@ -47,8 +55,8 @@ resV = 0.838214/2
 # plt.plot(data[energy], np.multiply(lan(data[energy], 140,75,15,4,100), 3600/resV/Itime), '--', label ='1')
 # plt.plot(data[energy], np.multiply(lan(data[energy], 140,75,15,4,100), 3600/resV/Itime), '--', label ='2')
 # plt.plot(data[energy], np.multiply(lan(data[energy], 140,75,15,4,100), 3600/resV/Itime), '--', label ='3')
-# plt.axvline(data[energy][a])
+# plt.axvline(data[energy][a[1]])
-# plt.axvline(data[energy][a1], color = 'r')
+# plt.axvline(data[energy][b[1]], color = 'r')
 
 for i in range (0,len(channels)):   
         ch = channels[i]
@@ -82,9 +90,10 @@ plt.yscale('log')
 plt.ylabel(ylab, fontsize = fs+5)
 plt.xlabel(xlab, fontsize=fs+5)
 plt.ylim(0.03,6)
+plt.ylim(0.03,2) #two
 
 plt.xlim(0,300) 
 
-#plt.show()
+plt.show()
-plt.savefig('plots/landau_'+file.split('/')[-1])
+#plt.savefig('plots/landau_'+file.split('/')[-1])
-plt.savefig('plots/landau_'+file.split('/')[-1]+'.pdf')
+#plt.savefig('plots/landau_'+file.split('/')[-1]+'.pdf')