testimpulse.py

@@ -1,120 +0,0 @@
-import numpy as np
-from matplotlib import pyplot as plt
-import scipy
-
-plt.rcParams["figure.figsize"] = (15,8)
-plt.rcParams['xtick.labelsize'] = 15
-plt.rcParams['ytick.labelsize'] = 15
-plt.rcParams['axes.labelsize'] = 20
-plt.rcParams['axes.titlesize']=25
-plt.rcParams['legend.fontsize']=20
-plt.rcParams['savefig.bbox']='tight'
-
-def gauss(x, *p):
-    A, mu, sigma = p
-    return A*np.exp(-(x-mu)**2/(2.*sigma**2))
-
-
-def fwhm(a):
-    p,cov=scipy.optimize.curve_fit(gauss,xdata=np.arange(len(a)),ydata=a,p0=[150,3880,20])
-    #plt.plot(gauss(np.arange(len(a)),*p))
-    return abs(2*np.sqrt(2*np.log(2))*p[2])
-
-'''
-def fwhm(a):
-    h=max(a)/2
-    u=False
-    k=0
-    for i in a:
-        if not u:
-            if i<=h:
-                k+=1
-                continue
-            else:
-                u=k
-                k+=1
-        else:
-            if i>=h:
-                k+=1
-                continue
-            else:
-                o=k
-                break  
-    return o-u
-'''
-c0=np.loadtxt('data/c0.TKA')
-c20=np.loadtxt('data/c20.TKA')
-c95=np.loadtxt('data/c95.TKA')
-c245=np.loadtxt('data/c245.TKA')
-c320=np.loadtxt('data/c320.TKA')
-c1020=np.loadtxt('data/c1020.TKA')
-c1770=np.loadtxt('data/c1770.TKA')
-
-cv0=np.loadtxt('data/cv0.TKA')
-cv1=np.loadtxt('data/cv1.TKA')
-cv2=np.loadtxt('data/cv2.TKA')
-cv3=np.loadtxt('data/cv3.TKA')
-cv4=np.loadtxt('data/cv4.TKA')
-cv5=np.loadtxt('data/cv5.TKA')
-cv10=np.loadtxt('data/cv10.TKA')
-cv40=np.loadtxt('data/cv40.TKA')
-
-halbC=[]
-for c in [c0,c20,c95,c245,c320,c1020,c1770]:
-    halbC.append(fwhm(c))
-    #plt.plot(c,'b')
-#plt.show()
-
-halbV=[]
-for v in [cv0,cv1,cv2,cv3,cv4,cv5,cv10,cv40]:
-    halbV.append(fwhm(v))
-    #plt.plot(v,'r')
-#plt.show()
-
-halbC=np.array(halbC)
-halbV=np.array(halbV)
-fig,axs=plt.subplots()
-axs.plot(halbC,[0,20,95,245,320,1020,1770],'b',label='Detektor mit verschiedenen Spannungen')
-axs.plot(halbC,[0,20,95,245,320,1020,1770],'r',label='Kapazitive Lasten')
-axs.legend(loc=1)
-axs2=axs.twinx()
-axs2.plot(halbV,[0,1,2,3,4,5,10,40],'b')
-axs2.set_ylabel('In Sperrichtung angelegte Spannung [V]')
-axs.set_ylabel('Kapazitive Last [pF]')
-axs.set_xlabel('Halbwertsbreite [bins]')
-axs.axvline(halbV[-1],c='black',linestyle='--')
-axs.axhline(277.35,xmax=0.313,c='black',linestyle='--')
-plt.show()
-
-
-lin10=np.loadtxt('data/linear10.TKA')
-lin15=np.loadtxt('data/linear15.TKA')
-lin20=np.loadtxt('data/linear20.TKA')
-lin25=np.loadtxt('data/linear25.TKA')
-lin30=np.loadtxt('data/linear30.TKA')
-lin35=np.loadtxt('data/linear35.TKA')
-lin40=np.loadtxt('data/linear40.TKA')
-lin45=np.loadtxt('data/linear45.TKA')
-lin50=np.loadtxt('data/linear50.TKA')
-lin55=np.loadtxt('data/linear55.TKA')
-linmax=[]
-for l in [lin10,lin15,lin20,lin25,lin30,lin35,lin40,lin45,lin50,lin55]:
-    plt.plot(l)
-    linmax.append(np.argmax(l))
-
-plt.show()
-
-
-
-def lin(x,a,b):
-    return a*x+b
-
-linmax=np.array(linmax)
-A=np.array([1,1.5,2,2.5,3,3.5,4,4.5,5,5.5])
-p,cov=scipy.optimize.curve_fit(lin,A,linmax)
-
-plt.scatter(A,linmax,c='r')
-plt.plot(A,lin(A,p[0],p[1]),label=r'Fit pixel(E)=678$\frac{1}{MeV}\cdot$E[MeV]+163',c='b')
-plt.legend()
-plt.show()
-print(p,cov)