changes 2025-01-20

CHAOSa.py

@@ -49,6 +49,9 @@ parser.add_argument("-deltaT", action='store_true', help = "saves deltatimes bet
 
 parser.add_argument("-nameadd", type=str, nargs='+', help = "custom nameadd to add to filename")
 
+
+parser.add_argument("-Denergy",  action='store_true', help = ' ')
+
 args = parser.parse_args()
 
 file = args.file
@@ -72,6 +75,8 @@ from histframe import CmV
 from histframe import CmV_v
 from histframe import isCut
 from histframe import isMask_1D
+from histframe import get_MeV_mean
+from histframe import get_MeV
 
 
 names = hf.names
@@ -214,6 +219,9 @@ def main():
     if args.deltaT:
         generate_deltaTimes()
         
+    if args.Denergy:
+        generate_hist_D_MeV()
+        
     if args.hist:
         generate_hist()
         
@@ -325,7 +333,8 @@ def generate_hist():
                 if l[0] == 'EI' and len(l)>3*18 and conditions(l,args) and isFloat(args,timestamp):
                     for i,chan in enumerate(chans):
                         b = value_HL(l,chan,u) 
-                        if minV <= b <= maxV and isMask_1D(l,args.mask,T):
+                        b = value
+                        if minV <= b <= maxV:
                             xb = int((b-minV)/resV)
                             hist[xb,i+1] += 1                                                               
                                 
@@ -333,6 +342,41 @@ def generate_hist():
     frame.to_csv(f'histograms/{filename}{nameadd}.1dhist', sep = ' ', index = False)
     print(f'histograms/{filename}{nameadd}.1dhist was created')
     
+    ################ 1D HISTOGRAM D in MeV ############################################################
+def generate_hist_D_MeV():
+    minV = 0
+    maxV = 50
+    resV = 0.1
+    bin = int((maxV-minV)/resV)
+        
+    hist = np.zeros((bin+1,2))
+      
+    for i in range(0,bin+1):
+        hist[i][0]=minV + resV*i
+
+    with fileinput.input(files=(file), encoding="utf-8", errors='ignore') as f: 
+        timestamp = 0
+        T=None
+        for line in f:
+            if not line.strip() or len(line.split()) < 9:
+                continue
+            l = line.split()
+            if not any(x in l for x in ['EOF', 'X', 'xF']):
+                if l[0] == 'H':
+                    timestamp = int(l[1])
+                    T = get_T(float(l[8]))
+                if l[0] == 'EI' and len(l)>3*18 and conditions(l,args) and isFloat(args,timestamp):
+                    #T=15
+                    b = value_HL(l,'D1',u)+value_HL(l,'D2',u) 
+                    bx = get_MeV(b,T)
+                    if minV <= bx <= maxV:
+                        xb = int((b-minV)/resV)
+                        hist[xb,1] += 1                                                               
+                                    
+    frame = pd.DataFrame(hist, columns = ['MeV'] + ['D'])
+    frame.to_csv(f'histograms/{filename}_D_MeV.1dhist', sep = ' ', index = False)
+    print(f'histograms/{filename}_D_MeV.1dhist was created')
+    
 def generate_hist_xlog():
     minX = 0.01
     maxX = 100
@@ -470,7 +514,7 @@ def generate_2d_hist_logy():
 ############ 2D HISTOGRAMM MIT LOGARITMISCHER XY_SKALE (FISCH) ######################################
 
 def generate_2d_hist_logxy():  
-    minY = 0.01
+    minY = 0.1
     #minY = 50
     maxY = 100
     maxY = 3500
@@ -490,7 +534,7 @@ def generate_2d_hist_logxy():
     #A1 vs A2
     maxX = 100000
     maxY = 100000
-    maxY = 10
+    #maxY = 10
     
     #maxX=3500
     #maxY=3500

CHAOScustom.py

@@ -119,25 +119,27 @@ def get_valuesZ(l,T):
     z = value(l,"B")
     return x2,y,z
 
+###################################################################################################
+
 def get_values(l,T):
     #y = max(value(l,"C1H"),value(l,"C2H"))/value(l,"EH")q
-    #y = min(value_HL(l,"A",u),value_HL(l,"C",u))/max(value(l,"E1",u),value(l,"E2",u),value(l,"E3",u))
+    y = min(value_HL(l,"A",u),value_HL(l,"C",u))/max(value(l,"E1",u),value(l,"E2",u),value(l,"E3",u))
     
     #y = value(l,"A",u)/1000
     #y = value(l,"C",u)/1000
     
-    y = min(value_HL(l,"A",u),value_HL(l,"C",u))/1000
+    #y = min(value_HL(l,"A",u),value_HL(l,"C",u))/1000
     
     x = value_HL(l,"D1",u)+value_HL(l,"D2",u)
     x2 = get_MeV(x,T)
     return x2,y
 
 
-cuts = ['A','hB','C','AeqC','D']
+cuts = ['A','hB','C','AeqC','D','E123']
 
-#filename = "chaos-fish-cut"+ "".join(cuts)+"~min(A,C)dE-D.2dhist2log"
-filename = "chaos-fish_Cut"+ "".join(cuts)+"~min(A,C)-D.2dhist2log"
-folder = "hists_sim"
+filename = "chaos20_Cut"+ "".join(cuts)+"~min(A,C)dE-D.2dhist2log"
+#filename = "chaos20_Cut"+ "".join(cuts)+"~min(A,C)-D.2dhist2log"
+folder = "hists_fish"
 
 # filename = "chaos-dE-cut"+ "".join(cuts)+"~A-D.2dhist2log"
 # folder = "hists_dEdx"

CHAOShk.py

@@ -201,7 +201,6 @@ def Do_hist():
                             if b>=minV and b<=maxV:
                                 xb = int((b-minV)/resV)
                                 hist[xb,i+1] += 1                                                               
-                                
     frame = pd.DataFrame(hist, columns = [energy] + name)
     frame.to_csv('histograms/'+filename+nameadd+'.hist', sep = ' ', index = False)
  
@@ -239,6 +238,7 @@ def Do_HC():
                       Rntc = 33e3 * Vntc / (Vana - Vntc)
                       Tntc = b / (np.log(Rntc / R25) + b / 298) - 273
                       HV = (float(l[11]) / 0x8000 - 1) * 5.12 * 281
+                      HV = (HV-float(0x8000))*(5.12/float(0x8000))*303
 
                 # Applying cuts for valid voltages and currents
                   validV = all(0 <= v < 100 for v in [Vprim, Vana, Vdrv]) and (0 <= HV <= 1100) and (-20 < Tntc < 150)

CHAOSx.py

@@ -70,6 +70,8 @@ from histframe import get_T
 from histframe import CmV
 from histframe import isCut
 from histframe import isMask_1D
+from histframe import get_MeV
+from histframe import get_MeV_H
 
 name = hf.names
 ch = hf.ch
@@ -276,9 +278,13 @@ def generate_deltaTimes():
 ################ 1D HISTOGRAM ############################################################
 
 def generate_hist():
+    minV = 0
+    maxV = 30
+    resV = 0.1
     bin = int((maxV-minV)/resV)
     
     hist = np.zeros((bin+1,18+1))
+    #Arbeithist = np.zeros((bin+1,9))
   
     for i in range(0,bin+1):
         hist[i][0]=minV + resV*i
@@ -297,12 +303,31 @@ def generate_hist():
                 if l[0] == 'EI' and len(l)>3*18 and conditions(l,args) and isFloat(args,timestamp):
                     for i, chan in enumerate(chans):
                         b = CmV(l,ch[chan])*u[chan] 
-                        if minV <= b <= maxV and isMask_1D(l, args.mask,T):
+                        if minV <= b <= maxV:
                             xb = int((b-minV)/resV)
-                            hist[xb,i+1] += 1                                                               
+                            hist[xb,i+1] += 1       
+                    # i=0
+                    # if 19.0 <= T < 21.0:
+                    #     i = 4
+                    # elif 17.0 <= T < 19.0:
+                    #     i = 3
+                    # elif 15.0 <= T < 17.0:
+                    #     i = 2
+                    # elif 13.0 <= T < 15.0:
+                    #     i = 1
+                    # if i >0:
+                    #     a = CmV(l,ch[9])*u[9]+CmV(l,ch[11])*u[11]  
+                    #     b = get_MeV(a,T)
+                    #     if minV <= b <= maxV:
+                    #         xb = int((b-minV)/resV)
+                    #         hist[xb,i] += 1     
+                    #         c = get_MeV_H(a,T)  
+                    #         xc = int((c-minV)/resV)
+                    #         hist[xc,4+i] += 1                                                  
                                 
     frame = pd.DataFrame(hist, columns = [energy] + name)
-    frame.to_csv(f'histograms/{filename}{nameadd}.1dhist', sep = ' ', index = False)
+    #frame = pd.DataFrame(hist, columns = [energy] + ['14','16','18','20']+['14H','16H','18H','20H'])
+    frame.to_csv(f'histograms/{filename}{nameadd}_T_MeV.1dhist', sep = ' ', index = False)
     print(f'histograms/{filename}{nameadd}.1dhist was created')
     
     

histframe.py

@@ -34,15 +34,18 @@ names[14] = "EL";  ch[14] = 0;  thr[14] = 10; s[14] = 1.0;  u[14] = 4.55; v[14]
 names[15] = "E1";  ch[15] = 8;  thr[15] = 8;  s[15] = 2.2;  u[15] = 11.32
 names[16] = "E2";  ch[16] = 5;  thr[16] = 8;  s[16] = 2.2;  u[16] = 11.32
 names[17] = "E3";  ch[17] = 2;  thr[17] = 8;  s[17] = 2.2;  u[17] = 11.32
-thr[9]=30
-thr[11]=30
+
+thr[9]=60
+thr[11]=60
 
 thr[0] = 8
 thr[2] = 14
 thr[5] = 7
 thr[7] = 13
 
-thr[15] = 5; thr[16] = 5; thr[17] = 5
+thr[13] = 14.73
+
+thr[15] = 6.64; thr[16] = 6.54; thr[17] = 6.54
 
 names_a = ["A1", "A2", "B", "C1", "C2", "D1", "D2", "E", "E1", "E2", "E3"]
 boundary = 2500 #mV
@@ -56,8 +59,8 @@ minV = 0
 maxV = 3500
 resV = 0.838214/2
 
-#pol = [1.88909231e-04, -6.84421799e-03, -3.28911747e+00,  3.24630271e+02]
-pol = [ 2.89915947e-03, -1.05037109e-01, -5.04775548e+01,  4.98204836e+03]
+#pol = [ 2.89915947e-03, -1.05037109e-01, -5.04775548e+01,  4.98204836e+03]
+pol = [2.36849137e-03, -1.06835334e-01, -5.25201198e+01,  5.30730515e+03] # mein Polynom, Hannes Datenpunkte
 
 
 def get_T(x):
@@ -73,9 +76,18 @@ def get_T(x):
 def polynom(T,  a,b,c,d):
     return np.multiply(np.multiply(np.multiply(a,T),T),T)+np.multiply(np.multiply(b,T),T)+np.multiply(c,T)+d
 
+def line_H(T):
+    return np.multiply(T,-57)+5392
+
 def get_MeV(keV,T):
     return keV/0.00362/polynom(T,*pol)
 
+def get_MeV_mean(keV):
+    return keV/0.00362/polynom(15,*pol)
+
+def get_MeV_H(keV,T):
+    return keV/0.00362/line_H(T)
+
 # def get_keV15(keV,T):
 #     return keV * polynom(15, *pol) / polynom(T, *pol)/ 0.00362
 
@@ -159,12 +171,13 @@ def isCut(l, cut):
         if a1 < 7.5 and a2 <= a1+11: return False
         if a2 > 12 and a1 > 7.5 and 0.01*a1 < a2 < 1/0.01*a1: return False
         
+        
     if "C" in cut:
         c1 = value_HL(l,"C1",u)
-        c2 = value_HL(l,"C2",u)
+        c2 = value_HL(l,"C2",u)  
         if c1 < 7.5 and c2 <= c1+11: return False
         if c2 > 12 and c1 > 7.5 and 0.01*c1 < c2 < 1/0.01*c1: return False
-
+        
         
     if "AeqC" in cut:
         a = value_HL(l,"A",u)

xplot.py

@@ -89,23 +89,27 @@ def do_1dhist():
     
     for ch in channels:    
         if not Itime==None:
-            plt.step(data[energy], np.multiply(data[ch], f*3600/resV/Itime),label=ch)
+            plt.step(data[energy], np.multiply(data[ch], f*3600/resV/Itime),label=ch, lw=2)
         else:
             plt.step(data[energy], data[ch], label=ch)
             
-    limits = args.limits if args.limits else [-100, 10000, 0.1, 100000]
-    #limits = args.limits if args.limits else [0, 500, 1, 100]
+    #limits = args.limits if args.limits else [-100, 10000, 0.1, 100000]
+    limits = args.limits if args.limits else [0, 100, 10, 10000]
     
-    border = True
+    border = False
     
     if border:
         plt.axvline(x=2500, color='black', linestyle='--', linewidth=2, label='Gain switching at 2500 $mV$')
         
     #plt.axvline(x=0.5, color='r', linestyle = '-', lw=1.5,)
     #plt.axvline(x=2, color='r', linestyle = '-', lw=1.5,)
-        
-    #plt.axvline(x=20, color='blue', linestyle='--', linewidth=2, label='20 mV (flight)')
-    #plt.axvline(x=30, color='black', linestyle='--', linewidth=2, label='30 mV (data analysis)')
+    #plt.axvline(x=6.5, color='k', linestyle = '--', lw=2, label = 'thr(E123) = 6.5 mV') 6.593
+    #plt.axvline(x=14, color='r', linestyle = '--', lw=2, label = 'thr(E) = 14 mV') 
+    #plt.axvline(x=67, color='k', linestyle = '--', lw=2, label = 'thr(E123) = 67 keV') 
+    #plt.axvline(x=60, color='r', linestyle = '--', lw=2, label = 'thr(E) = 67 keV')
+    
+    plt.axvline(x=20, color='blue', linestyle='--', linewidth=2, label='20 mV (flight)')
+    plt.axvline(x=60, color='black', linestyle='--', linewidth=2, label='60 mV (data analysis)')
     
     plot_layout(title, energy, limits,None,None,None)
     
@@ -177,8 +181,8 @@ def do_2dhist():
 
     c = np.array(data)[:,1:].T
     
-    Dcuts = False
-    ACcuts =False
+    Dcuts = True
+    ACcuts = False
     AeqC = False
     Ecuts = False
     Lowcal = False
@@ -193,8 +197,8 @@ def do_2dhist():
             plt.plot(x_edges,np.add(np.divide(x_edges,0.85),30), 'r-', lw=2)
             #plt.plot([0, 30], [30, 30], 'r--', lw=2)
             #plt.plot([30, 30], [30, 0], 'r--', lw=2)
-            plt.axhline(y=30, color='r', linestyle = '--', lw=1.5,label = "         $D1H, D2H > 30$ mV")
-            plt.axvline(x=30, color='r', linestyle = '--', lw=1.5,)
+            plt.axhline(y=60, color='r', linestyle = '--', lw=1.5,label = "         $D1H, D2H > 60$ mV")
+            plt.axvline(x=60, color='r', linestyle = '--', lw=1.5,)
             
         if ACcuts:
             plt.axhline(y=15, color='r', linestyle = '-', lw=1.5, label = "thr['C1H'] = 10 mV; thr['C2H'] = 15 mV")
@@ -218,8 +222,8 @@ def do_2dhist():
             plt.plot(x_edges,np.add(np.divide(x_edges,0.85),30), 'r-', lw=2)
             #plt.plot([0, 30], [30, 30], 'r--', lw=2)
             #plt.plot([30, 30], [30, 0], 'r--', lw=2)
-            plt.axhline(y=30, color='r', linestyle = '--', lw=1.5,label = "         $D1H, D2H > 30$ mV")
-            plt.axvline(x=30, color='r', linestyle = '--', lw=1.5,)
+            plt.axhline(y=60, color='r', linestyle = '--', lw=1.5,label = "         $D1H, D2H > 60$ mV")
+            plt.axvline(x=60, color='r', linestyle = '--', lw=1.5,)
             
             
         if Ecuts:
@@ -227,93 +231,60 @@ def do_2dhist():
             plt.axhline(y=6.5, color='r', linestyle = '--', lw=2)
             # plt.axvline(x=5, color='r', linestyle = '--', lw=1.5, label = "thr['E123'] = 5 mV")
             # plt.axhline(y=5, color='r', linestyle = '--', lw=1.5)
-            # xx = np.linspace(0.1, 250000, 2500000)
-            # a=0
-            # b=0
-            # while xx[a]<5:
-            #     a+=1
-            # while (xx[b]-5)/0.4<5:
-            #     b+=1
-                
-            # #plt.plot(x_edges,np.multiply(x_edges,0.01), 'r--', lw=1, label=("Relative cuts: E1/E2&E2/E1 < 1%"))
-            # # plt.plot(x_edges,np.multiply(x_edges,1/0.01), 'r--', lw=1)
             
-            # # plt.plot(xx[:a],0.4*xx[:a]+5,color='magenta',label='E2(E1) = 0.4*E1+5 mV', lw=2)
-            # # plt.plot(xx[a:],0.4*xx[a:]+5,linestyle=':',color='magenta',lw=2)
-            
-            # # plt.plot(xx[:b],(xx[:b]-5)/0.4,color='magenta', lw=2)
-            # # plt.plot(xx[b:],(xx[b:]-5)/0.4,linestyle=':',color='magenta',lw=2)
-            
-            # # plt.plot(xx[a:b],-1*xx[a:b]+12,color='orange',label = 'E2(E1) = -E1+12 mV')
-            # # plt.plot(xx,-1*xx+12,linestyle=':',color='orange')
-            # # plt.plot(xx,-1*xx+12,linestyle=':',color='orange')
-            
-            # plt.plot(xx[:a],0.4*xx[:a]+5,color='k',label='cutting lines', lw=2)  
-            # plt.plot(xx[:b],(xx[:b]-5)/0.4,color='k', lw=2)         
-            # plt.plot(xx[a:b],-1*xx[a:b]+12,color='k')
-
-            # xx = np.linspace(0.1, 100000, 1000000)
-            # a=0
-            # alpha=0.2
-            # while xx[a]<5:
-            #     a+=1
-            #     b=a
-            # while xx[b]<7:
-            #     b+=1
-            # plt.fill_between(xx[:a], 0, 0.4*xx[:a]+5, color='red', alpha=alpha, label ='noise')
-            # plt.fill_between(xx[a-1:b], (xx[a-1:b]-5)/0.4, -xx[a-1:b]+12, color='red', alpha=alpha)
-            
-            # plt.fill_between(xx[:a], 3500, 0.4*xx[:a]+5, color='green', alpha=alpha, label ='clean data')
-            # plt.fill_between(xx[a-1:b], (xx[a-1:b]-5)/0.4,0, color='green', alpha=alpha)
-            # plt.fill_between(xx[a-1:b], -xx[a-1:b] + 12, 3500, color='green', alpha=alpha, antialiased=False)
-            # plt.fill_between(xx[b-1:], 0, 3500, color='green', alpha=alpha, antialiased=False)
 
         if AeqC:
             a=2
             b=0
             xx = np.linspace(0.1, 100000, 1000000)
-            #plt.plot(xx, a*xx-b, 'r-', label='A = '+str(a)+'C  |  C = '+str(a)+'A')
-            #plt.plot(xx, (xx+b)/a, 'r-')
-            plt.axhline(y=a, color='r', linestyle = '-', lw=1.5, label='A = '+str(a)+'C  |  C = '+str(a)+'A',)
-            plt.axhline(y=1/a, color='r', linestyle = '-', lw=1.5,)
+            plt.plot(xx, a*xx-b, 'r-', lw=1.5, label='A = '+str(a)+'C  |  C = '+str(a)+'A')
+            plt.plot(xx, (xx+b)/a, 'r-', lw=1.5)
+            #plt.axhline(y=a, color='r', linestyle = '-', lw=1.5, label='A = '+str(a)+'C  |  C = '+str(a)+'A',)
+            #plt.axhline(y=1/a, color='r', linestyle = '-', lw=1.5,)
 
             #plt.plot([7.5, 10000, 10000, 7.5, 7.5], [7.5, 7.5, 10000, 10000, 7.5], color='r', linewidth=1, label = 'zoom')
             
 
             
         if ACcuts:
-            plt.axvline(x=7.5, color='r', linestyle = '-', lw=2, label = "thr(C1) = 7.5 mV")
-            plt.axhline(y=12, color='r', linestyle = '-', lw=2, label = "thr(C2) = 12 mV")
+            # plt.axvline(x=7.5, color='r', linestyle = '-', lw=3, label = "thr(C1) = 7.5 mV")
+            # plt.axhline(y=12, color='r', linestyle = '-', lw=3, label = "thr(C2) = 12 mV")
 
-            plt.plot(x_edges,np.multiply(x_edges,0.01), 'r--', lw=2, label=("Relative cuts: Q < 1%"))
-            plt.plot(x_edges,np.multiply(x_edges,1/0.01), 'r--', lw=2)
+            # plt.plot(x_edges,np.multiply(x_edges,0.01), 'r--', lw=2, label=("Relative cuts: Q < 1%"))
+            # plt.plot(x_edges,np.multiply(x_edges,1/0.01), 'r--', lw=2)
             
             xx = np.linspace(0.1, 100000, 1000000)
             a=0
             while xx[a]<7.5:
               a+=1
+              
+            b=a
+            while xx[b]<1195:
+                b+=1
            
-            plt.plot(xx[:a],1.0*xx[:a]+11,color='orange',label='C2 = C1+11 mV', lw=2)
-            plt.plot(xx[a:],1.0*xx[a:]+11,linestyle=':',color='orange',lw=2)
-            
+            # plt.plot(xx[:a],1.0*xx[:a]+11,color='k', lw=5)
+            # plt.plot(xx[a:],1.0*xx[a:]+11,linestyle='-',color='k',lw=3)
+            # plt.plot(xx[:a],1.0*xx[:a]+11,color='orange',label='C2 = C1+11 mV', lw=3)
+            # plt.plot(xx[a:],1.0*xx[a:]+11,linestyle=':',color='orange',lw=3)
          
-            # plt.plot(xx[:a],1.0*xx[:a]+11,color='k', lw=1)
-            # plt.plot(x_edges,np.multiply(x_edges,0.01), 'k--', lw=1)
-            # plt.plot(x_edges,np.multiply(x_edges,1/0.01), 'k--', lw=1)
-            # plt.axvline(x=7.5, color='k', linestyle = '-', lw=1)
-            # plt.axhline(y=12, color='k', linestyle = '-', lw=1)
+            plt.plot(xx[:a],1.0*xx[:a]+11,color='k', lw=1)
+            plt.plot(xx[b:],np.multiply(xx[b:],0.01), 'k--', lw=1)
+            plt.plot(xx[a:],np.multiply(xx[a:],1/0.01), 'k--', lw=1)
+            plt.plot(xx[a:],len(xx[a:])*[12],color='k', linestyle = '-', lw=1)
+            plt.axvline(x=7.5, color='k', linestyle = '-', lw=1)
+            #plt.axhline(y=12, color='k', linestyle = '-', lw=1, xmin=7.5, xmax=100000)
          
-            # alpha=0.3
+            alpha=0.3
 
-            # plt.fill_between(xx[:a], 0, 1.0*xx[:a]+11, color='red', alpha=alpha, label ='noise')
+            plt.fill_between(xx[:a], 0, 1.0*xx[:a]+11, color='red', alpha=alpha, label ='noise')
             
-            # plt.fill_between(xx[:a], 100000,1.0*xx[:a]+11, color='green', alpha=alpha, label ='clean data')
-            # plt.fill_between(xx[a:], 0,12, color='green', alpha=alpha)
+            plt.fill_between(xx[:a], 100000,1.0*xx[:a]+11, color='green', alpha=alpha, label ='clean data')
+            plt.fill_between(xx[a:], 0,12, color='green', alpha=alpha)
             
-            # plt.fill_between(xx[a:], np.maximum(0.01 * xx[a:],12),12, color='b', alpha=alpha, label = 'crosstalk')
-            # plt.fill_between(xx[a:], 1/0.01*xx[a:],100000, color='b', alpha=alpha)
+            plt.fill_between(xx[a:], np.maximum(0.01 * xx[a:],12),12, color='b', alpha=alpha, label = 'crosstalk')
+            plt.fill_between(xx[a:], 1/0.01*xx[a:],100000, color='b', alpha=alpha)
             
-            # plt.fill_between(xx[a:], 1/0.01*xx[a:],np.maximum(0.01 * xx[a:], 12), color='orange', alpha=alpha, label = 'dual hits')
+            plt.fill_between(xx[a:], 1/0.01*xx[a:],np.maximum(0.01 * xx[a:], 12), color='orange', alpha=alpha, label = 'dual hits')
             
             
         if mask_He:
@@ -327,8 +298,8 @@ def do_2dhist():
         cbar = plt.colorbar(contour, orientation = 'vertical', shrink = 0.95, pad = 0.1)
      
     else:
-        #cb = plt.pcolormesh(x_edges, y_edges,c, cmap = cmap, shading='nearest', vmin=vmin, vmax = 2000,norm='log')  
-        cb = plt.pcolormesh(x_edges, y_edges,c, cmap = cmap, shading='auto', vmin=vmin, norm='log')
+        cb = plt.pcolormesh(x_edges, y_edges,c, cmap = cmap, shading='nearest', vmin=vmin, vmax = 2000,norm='log')  
+        #cb = plt.pcolormesh(x_edges, y_edges,c, cmap = cmap, shading='auto', vmin=vmin, norm='log')
         #cb = plt.pcolormesh(np.multiply(x_edges,f), y_edges,c, cmap = cmap, shading='nearest', vmin=vmin, vmax=30, norm='log')    
         cbar = plt.colorbar(cb, orientation = 'vertical', shrink = 0.95, pad = 0.1)
         
@@ -386,13 +357,14 @@ def read_Itime(file, end):
 ###############################################################################
 
 def plot_layout(title, energy, limits, x, y, cbar):
-    fs = 17
-    fs = 20
+    fs = 15
+    fs = 24
 
     if x == None and y == None:
         add = ""
         if energy == 'keV':
             add = '$_{Si}$'
+        add = ""
         ylab = 'counts / h / ' + energy + add
         xlab = 'signal in ' + energy + add
         plt.yscale('log')
@@ -405,12 +377,12 @@ def plot_layout(title, energy, limits, x, y, cbar):
             xlab = x + ' in number of $e_{ph}$'    
 
         if 'd' in y:
-            ylab = y.split('d')[0] + '/' + y.split('d')[1]
+            ylab = y.split('d')[0] + ' / ' + y.split('d')[1]
             plt.yscale('log')
             
     #ylab=y
     #xlab=x
-    plt.yscale('log')
+    #plt.yscale('log')
 
     plt.ylabel(ylab, fontsize=fs + 5)
     plt.xlabel(xlab, fontsize=fs + 5)
@@ -434,7 +406,7 @@ def plot_layout(title, energy, limits, x, y, cbar):
         cbar.ax.tick_params(labelsize=fs)
     
     if plt.gca().get_legend_handles_labels()[0]:  # Gibt eine Liste von Künstlern (Handles) und Labels zurück
-        plt.legend(fontsize=fs, loc="upper right",ncol=3)
+        plt.legend(fontsize=fs-1, loc="upper right",ncol=1)
         #plt.legend(fontsize=fs+5, loc="upper right")