script for convert .t3pa files to .t3pa_cls
.t3pa file example:
Index $\quad$ Matrix $\quad$ Index $\quad$ ToA $\quad$ ToT $\quad$ FToA $\quad$ Overflow
0 $\quad$ 4574 $\quad$ 832 $\quad$ 29 $\quad$ 6 $\quad$ 0
1 $\quad$ 4831 $\quad$ 832 $\quad$ 35 $\quad$ 7 $\quad$ 0
2 $\quad$ 4575 $\quad$ 832 $\quad$ 100 $\quad$ 8 $\quad$ 0
3 $\quad$ 31031 $\quad$ 1745 $\quad$ 22 $\quad$ 11 $\quad$ 0
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.t3pa_cls file example:
% Index $\quad$ Matrix Index $\quad$ [ RowNo, ClmNo ] $\quad$ ToA $\quad$ FToA $\quad$ ( ToA_in_ns ) $\quad$ ToT ( ToT_in_keV ) $\quad$ Overflow
# 1, $\quad$ Nunmasked = 3, $\quad$ Nmasked = 0, $\quad$ Ntot = 3 # Tfirst = 2.0787500000000000e+04 ns, $\quad$ Tlast = 2.0790625000000000e+04 ns, $\quad$ dT = 3.125000 ns, $\quad$ Etot = 64.428148 keV
2 $\quad$ 4575 $\quad$ [ 17, 223 ] $\quad$ 832 $\quad$ 8 $\quad$ ( 2.0787500000000000e+04 ns ) $\quad$ 100 $\quad$ ( 37.867914 keV ) $\quad$ 0
1 $\quad$ 4831 $\quad$ [ 18, 223 ] $\quad$ 832 $\quad$ 7 $\quad$ ( 2.0789062500000000e+04 ns ) $\quad$ 35 $\quad$ ( 14.733453 keV ) $\quad$ 0
0 $\quad$ 4574 $\quad$ [ 17, 222 ] $\quad$ 832 $\quad$ 6 $\quad$ ( 2.0790625000000000e+04 ns ) $\quad$ 29 $\quad$ ( 11.826781 keV ) $\quad$ 0
# 2, $\quad$ Nunmasked = 3, $\quad$ Nmasked = 0, $\quad$ Ntot = 3 # Tfirst = 4.3601562500000000e+04 ns, $\quad$ Tlast = 4.3607812500000000e+04 ns, $\quad$ dT = 6.250000 ns, $\quad$ Etot = 63.577435 keV
5 $\quad$ 30775 $\quad$ [ 120, 55 ] $\quad$ 1745 $\quad$ 15 $\quad$ ( 4.3601562500000000e+04 ns ) $\quad$ 99 $\quad$ ( 37.617059 keV ) $\quad$ 0
4 $\quad$ 30776 $\quad$ [ 120, 56 ] $\quad$ 1745 $\quad$ 13 $\quad$ ( 4.3604687500000000e+04 ns ) $\quad$ 44 $\quad$ ( 14.715446 keV ) $\quad$ 0
3 $\quad$ 31031 $\quad$ [ 121, 55 ] $\quad$ 1745 $\quad$ 11 $\quad$ ( 4.3607812500000000e+04 ns ) $\quad$2 2 $\quad$ ( 11.244929 keV ) $\quad$ 0
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import numpy as np
#import pandas as pd
import matplotlib.pyplot as plt
from urllib.error import HTTPError # recognise the error stemming from missing data
#import urllib
import urllib.request
#Define an exception which will be raised if the data is missing and stop the notebook execution
class StopExecution(Exception):
def _render_traceback_(self):
pass
#shot_no = 36529 #test discharge for which the notebook will definitely work
shot_no = 43624
shot = shot_no
identifier='H03-W0051_shot_'+str(shot)+'_450V'
detector = 'H03-W0051'
ds = np.DataSource('/tmp') # temporary storage for downloaded files
scalars_URL = 'http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/PlasmaDetection/Results/{name}'
def get_scalar(shot_no, name):
return float(ds.open(scalars_URL.format(shot_no=shot_no, name=name)).read())
t_plasma_start = get_scalar(shot_no, 't_plasma_start')
t_plasma_end = get_scalar(shot_no, 't_plasma_end')
is_plasma = get_scalar(shot_no, 'b_plasma')
def get_file(shot, identifier):
#Pick the discharge to analyse
URL = 'http://golem.fjfi.cvut.cz/shots/{shot}/Diagnostics/TimepixDetector/H03/{identifier}.t3pa'
url = URL.format(shot=shot, identifier=identifier)
try:
file_name_t3pa=url
with urllib.request.urlopen(file_name_t3pa) as ft3pa:
line = ft3pa.readline()
line = line.decode('utf‐8')
ft3pa.close
except HTTPError:
print('File not found at %s. Aborting notebook execution.' % url)
raise StopExecution
return file_name_t3pa
def get_file_calib(name_calib):
#Pick the discharge to analyse
URL = 'http://golem.fjfi.cvut.cz/shots/{shot}/Diagnostics/TimepixDetector/calib_matrix_H03/{name_calib}.txt'
url = URL.format(shot=shot, name_calib=name_calib)
#print(url)
try:
file_calib=url
with urllib.request.urlopen(file_calib) as calib:
line = calib.readline()
line = line.decode('utf‐8')
calib.close
except HTTPError:
print('File not found at %s. Aborting notebook execution.' % url)
raise StopExecution
return file_calib
def load_calib(file_calib):
with urllib.request.urlopen(file_calib) as fc:
calib=[] #vytvoreni 1D pole
for i in range(0,256): #tj. rozsah 0-255
temp = [] # docasne pole
for j in range(0,256):
temp.append(0) #naplneni docasneho pole 0
calib.append(temp) #naplneni pole a[] docasnym polem temp
for i in range(0,256): #nacteni calib matice do pole calib
line = fc.readline()
line = line.decode('utf‐8')
word=line.strip().split(' ')
for j in range(0,256):
calib[i][j]=float(word[j]) #i = radek, j = sloupec0
fc.close
return calib
def load_t3pa_file(file_t3pa):
index=[]
matrix_index=[]
ToA=[]
ToT=[]
FToA=[]
overflow=[]
pocet_udalosti = 0
with urllib.request.urlopen(file_t3pa) as ft3pa:
line = ft3pa.readline()
line = line.decode('utf‐8')
while True:
line = ft3pa.readline()
line = line.decode('utf‐8')
word=line.strip().split('\t') #v t3pa souboru je oddelovac \t
if line == '':
break
index.append(word[0])
matrix_index.append(word[1])
ToA.append(float(word[2]))
ToT.append(float(word[3]))
FToA.append(float(word[4]))
overflow.append(float(word[5]))
pocet_udalosti = pocet_udalosti + 1
ft3pa.close
return index, matrix_index, ToA, ToT, FToA, overflow, pocet_udalosti
def noise(index, matrix_index, ToA, ToT, FToA, overflow, pocet_udalosti): #tuto fci nemus9m explicitn2 volat - volam ji v fci load_t3pa
pocet=int(0) #pocet sumicich pixelu
konst=int(len(index)/1000)+1
noise_matrix_index=[]
for i in range(0,konst):
pom = [] # pomocne pole
k=0 #pomocna promenna - udava, kolik je v czklu ve skutecnosti udalosti - aby nebyla chyba 'list index out of range'
for j in range(0,1001):
if i*1000+j>=len(index):
break
pom.append(matrix_index[i*1000+j])
k=k+1
for m in range(0,k):
count=int(0) #pocet vvyskytu stejneho matrix index behem 1000 udalosti
index_=int(-1) #budu testovat, jestli pixel na ktery koukam je sumici (abych ho nezapocital 2x)
for p in range(0,pocet):
#index=int(p)
if pom[m]==noise_matrix_index[p]:
index_=p #pixel na ktery jsem uz koukal a byl sumici
break
if index_ >=0 and pom[m]==noise_matrix_index[index_]:
continue
for l in range(0,k):
if pom[m]==pom[l]:
count=count+1
####podminka na sumici pixely
if count>=50: #kdyz se pixel vyskytne behem tisice udalosti vicekrat nez toto cislo, je sumici
noise_matrix_index.append(pom[m])
#noise_matrix_index[pocet]=pom[i]
pocet=pocet+1
pom.clear()
pocet_udalosti=len(index)
for n in range (0,pocet_udalosti):
for o in range(0,len(noise_matrix_index)):
if n >=pocet_udalosti:
break
if(matrix_index[n]==noise_matrix_index[o]):
del matrix_index[n]
del index[n]
del ToA[n]
del ToT[n]
del FToA[n]
del overflow[n]
pocet_udalosti=pocet_udalosti-1
continue
return pocet_udalosti,index, matrix_index, ToA, ToT, FToA, overflow
def t3pa_data(pocet_udalosti,index, matrix_index, ToA, ToT, FToA, overflow):
#rovnou vyhodim sumici pixely
pocet_udalosti,index, matrix_index, ToA, ToT, FToA, overflow=noise(index, matrix_index, ToA, ToT, FToA, overflow, pocet_udalosti)
RowNo=[]
ClmNo=[]
for i in range(0,len(matrix_index)):
RowNo.append(int(int(matrix_index[i]))//int(256))
ClmNo.append(int(int(matrix_index[i]))%int(256))
return index, matrix_index, ToA, ToT, FToA, overflow, pocet_udalosti, RowNo, ClmNo
def hit_map(detector,hit_map_fig,RowNo,ClmNo):
plt.hist2d(RowNo,ClmNo,bins=(256,256),cmap='Blues')
cb=plt.colorbar()
cb.set_label('Counts in pixel')
plt.xlabel('x [pixel]')
plt.ylabel('y [pixel]')
plt.title(detector)
plt.savefig(hit_map_fig, dpi = 1000)
return
def energy(a, b, c, t, ToT, pocet_udalosti, RowNo, ClmNo):
E=[] #energy in keV
for i in range (0,pocet_udalosti):
sqrt=float(0.0)
e1=float(0.0)
e2=float(0.0)
# promenna sqrt je vnitrek odmocniny
sqrt = (((float(b[RowNo[i]][ClmNo[i]])+float(a[RowNo[i]][ClmNo[i]])*float(t[RowNo[i]][ClmNo[i]])-float(ToT[i])))*(((float(b[RowNo[i]][ClmNo[i]])+float(a[RowNo[i]][ClmNo[i]])*float(t[RowNo[i]][ClmNo[i]])-float(ToT[i])))) + (float(4)*float(a[RowNo[i]][ClmNo[i]])*float(c[RowNo[i]][ClmNo[i]]))) #zmena oproti verzi VI
if float(sqrt)<float(0):
E.append(float(0))
else:
'''
V kalibracni matici a se obcas vyskytne 0 -> ve vypoctu energie
je tim padem deleni nulou -> energie diverguje. Jak to vyresit?
zatim polozim energii = 0 (kdyz a=0), pak se uvidi
nakonec udelam limitu vyrazu energie pro a->0 (L'hopital)
'''
if a[RowNo[i]][ClmNo[i]]==0:
e1=((float(t[RowNo[i]][ClmNo[i]]))/float(2)) + ((((float(b[RowNo[i]][ClmNo[i]])+float(a[RowNo[i]][ClmNo[i]])*float(t[RowNo[i]][ClmNo[i]])-float(ToT[i]))*(float(t[RowNo[i]][ClmNo[i]]))) - 2*(float(c[RowNo[i]][ClmNo[i]])))/(float(2)*np.sqrt(float(sqrt))))
e2=((float(t[RowNo[i]][ClmNo[i]]))/float(2)) - ((((float(b[RowNo[i]][ClmNo[i]])+float(a[RowNo[i]][ClmNo[i]])*float(t[RowNo[i]][ClmNo[i]])-float(ToT[i]))*(float(t[RowNo[i]][ClmNo[i]]))) - 2*(float(c[RowNo[i]][ClmNo[i]])))/(float(2)*np.sqrt(float(sqrt))))
else:
e1=((-(float(b[RowNo[i]][ClmNo[i]]) - (float(a[RowNo[i]][ClmNo[i]])*float(t[RowNo[i]][ClmNo[i]]))-float(ToT[i])))+np.sqrt(float(sqrt)))/(float(2)*float(a[RowNo[i]][ClmNo[i]]))
e2=((-(float(b[RowNo[i]][ClmNo[i]]) - (float(a[RowNo[i]][ClmNo[i]])*float(t[RowNo[i]][ClmNo[i]]))-float(ToT[i])))-np.sqrt(float(sqrt)))/(float(2)*float(a[RowNo[i]][ClmNo[i]]))
if a[RowNo[i]][ClmNo[i]]<0:
e1=-1
e2=-1
if e1<0 and e2<0:
E.append(float(0))
if e1>=0 and e1>e2:
E.append(float(e1))
if e2>=0 and e2>e1:
E.append(float(e2))
return E
def Time(ToA, FToA, pocet_udalosti, RowNo, ClmNo):
T=[] #time in ns
for i in range (0,pocet_udalosti):
Time=float(0.0)
Time=(float(ToA[i])-((float(FToA[i])/float(16))))*float(25)
T.append(float(Time))
return T
def remove_interactions_with_zero_energy(index, matrix_index, ToA, ToT, FToA, overflow, RowNo, ClmNo, E, T):
i=0
treshold=5.015347
while i < len(T):
if E[i]<treshold: #E[i] < energy treshold
index.pop(i)
matrix_index.pop(i)
ToA.pop(i)
ToT.pop(i)
FToA.pop(i)
overflow.pop(i)
RowNo.pop(i)
ClmNo.pop(i)
E.pop(i)
T.pop(i)
continue
i=i+1
return index, matrix_index, ToA, ToT, FToA, overflow, RowNo, ClmNo, E, T
def clustering_new(index, matrix_index, ToA, ToT, FToA, overflow, RowNo, ClmNo, E, T):
dT=float(50)
indexCl, TCl,ECl, matrix_indexCl, ToACl,ToTCl,FToACl,RowNoCl,ClmNoCl,overflowCl=[],[],[],[],[],[],[],[],[],[]
StartLastElem=len(T)-1
indexCl.append(int(index[StartLastElem]))
TCl.append(float(T[StartLastElem]))
ECl.append(float(E[StartLastElem]))
matrix_indexCl.append(int(matrix_index[StartLastElem]))
RowNoCl.append(int(RowNo[StartLastElem]))
ClmNoCl.append(int(ClmNo[StartLastElem]))
ToACl.append(float(ToA[StartLastElem]))
ToTCl.append(float(ToT[StartLastElem]))
FToACl.append(float(FToA[StartLastElem]))
overflowCl.append(float(overflow[StartLastElem]))
del index[StartLastElem]
del T[StartLastElem]
del E[StartLastElem]
del matrix_index[StartLastElem]
del RowNo[StartLastElem]
del ClmNo[StartLastElem]
del ToA[StartLastElem]
del ToT[StartLastElem]
del FToA[StartLastElem]
del overflow[StartLastElem]
j=1
pom=float(TCl[0]+dT)
while(j >0):
if(len(T) == 0):
break
k=0
j=0
while (k<=(len(TCl)-1)):
i=len(T)-1
if(len(T) == 0):
break
pocet_sousedu=0 #pocet sousednich pixelu - mohou byt maximalne 4
delka=0
# verze X
count=0 #pomocna promanna, kterou urcuji, ze se ma nasledujici cyklus while projit jeste jednou, pokud je i = -1
while(float(T[i])<=(pom)):
delka=delka+1
if(((((int(RowNoCl[k]))==(int(RowNo[i])+1))or((int(RowNoCl[k]))==(int(RowNo[i])-1))) and ((int(ClmNoCl[k]))==(int(ClmNo[i])))) or (((int(RowNoCl[k]))==(int(RowNo[i]))) and (((int(ClmNoCl[k]))==(int(ClmNo[i])+1))or((int(ClmNoCl[k]))==(int(ClmNo[i])-1))))):
#beru jen pixely, které mají společnou jednu stranu.
#pixely, kter0 spolu sousedí přes roh neuvažuji
indexCl.append(int(index[i]))
TCl.append(float(T[i]))
ECl.append(float(E[i]))
matrix_indexCl.append(int(matrix_index[i]))
RowNoCl.append(int(RowNo[i]))
ClmNoCl.append(int(ClmNo[i]))
ToACl.append(float(ToA[i]))
ToTCl.append(float(ToT[i]))
FToACl.append(float(FToA[i]))
overflowCl.append(float(overflow[i]))
# Removes i-th Row
del index[i]
del T[i]
del E[i]
del matrix_index[i]
del RowNo[i]
del ClmNo[i]
del ToA[i]
del ToT[i]
del FToA[i]
del overflow[i]
j=j+1
i=len(T)-1
pocet_sousedu=pocet_sousedu+1
if(len(T) == 0):
break
if(pocet_sousedu==4):
break
continue
i=i-1
if(i==-1): # verze X
count=count+1
if(i<0 and len(T)>0): # verze X
i=0
if(count>1):
break
if(i>=len(T)):
break
k=k+1
if(len(TCl)>2):
indexCl, TCl, ECl, matrix_indexCl, RowNoCl, ClmNoCl, ToACl, ToTCl, FToACl, overflowCl = insertionSort(indexCl, TCl, ECl, matrix_indexCl, RowNoCl, ClmNoCl, ToACl, ToTCl, FToACl, overflowCl)
return T, indexCl,TCl, ECl, matrix_indexCl, RowNoCl, ClmNoCl, ToACl, ToTCl, FToACl, overflowCl
def insertionSort(indexCl, TCl, ECl, matrix_indexCl, RowNoCl, ClmNoCl, ToACl, ToTCl, FToACl, overflowCl):
# Function to do insertion sort
# Traverse through 1 to len(arr)
for i in range(1, len(TCl)):
key = TCl[i]
# Move elements of arr[0..i-1], that are
# greater than key, to one position ahead
# of their current position
#ostatni
key1 = indexCl[i]
key2 = ECl[i]
key3 = matrix_indexCl[i]
key4 = RowNoCl[i]
key5 = ClmNoCl[i]
key6 = ToACl[i]
key7 = ToTCl[i]
key8 = FToACl[i]
key9 = overflowCl[i]
j = i-1
while j >= 0 and key < TCl[j] :
TCl[j + 1] = TCl[j]
#ostatni
indexCl[j + 1] = indexCl[j]
ECl[j + 1] = ECl[j]
matrix_indexCl[j + 1] = matrix_indexCl[j]
RowNoCl[j + 1] = RowNoCl[j]
ClmNoCl[j + 1] = ClmNoCl[j]
ToACl[j + 1] = ToACl[j]
ToTCl[j + 1] = ToTCl[j]
FToACl[j + 1] = FToACl[j]
overflowCl[j + 1] = overflowCl[j]
j -= 1
TCl[j + 1] = key
#ostatni
indexCl[j + 1] = key1
ECl[j + 1] = key2
matrix_indexCl[j + 1] = key3
RowNoCl[j + 1] =key4
ClmNoCl[j + 1] = key5
ToACl[j + 1] = key6
ToTCl[j + 1] = key7
FToACl[j + 1] = key8
overflowCl [j + 1] = key9
return indexCl, TCl, ECl, matrix_indexCl, RowNoCl, ClmNoCl, ToACl, ToTCl, FToACl, overflowCl
def file_t3pa_cls_new(file_t3pa_cls,T):
with open(file_t3pa_cls, "w", encoding="utf-8") as t3pa_cls:
t3pa_cls.write('%\n')
t3pa_cls.write('% Index Matrix Index [ RowNo, ClmNo ] ToA FToA ( ToA_in_ns ) ToT ( ToT_in_keV ) Overflow\n')
t3pa_cls.write('\n')
i=1
T_first=[]
E_tot=[]
while(len(T) > 0):
T, indexCl,TCl, ECl, matrix_indexCl, RowNoCl, ClmNoCl, ToACl, ToTCl, FToACl, overflowCl = clustering_new(index, matrix_index, ToA, ToT, FToA, overflow, RowNo, ClmNo, E, T)
Tfirst=float(TCl[0])
Tlast=float(TCl[len(TCl)-1])
dT=Tlast-Tfirst
Etot=float(0)
for k in range(0,len(TCl)):
Etot=Etot+float(ECl[k])
T_first.append(float(Tfirst))
dT=Tlast-Tfirst
E_tot.append(float(Etot))
t3pa_cls.write('# '+str(i)+', Nunmasked = '+str(len(TCl))+', Nmasked = 0, Ntot = '+str(len(TCl))+'\n')
t3pa_cls.write('# Tfirst = '+str(Tfirst)+' ns, Tlast = '+str(Tlast)+' ns, dT = '+str(dT)+' ns, Etot = '+str(Etot)+' keV\n')
for j in range(0,len(TCl)):
t3pa_cls.write(str(indexCl[j])+' '+str(matrix_indexCl[j])+' [ '+str(RowNoCl[j])+', '+str(ClmNoCl[j])+' ] '+str(ToACl[j])+' '+str(FToACl[j])+' ( '+str(TCl[j])+' ns ) '+str(ToTCl[j])+' ( '+str(ECl[j])+' keV ) '+str(overflowCl[j])+'\n')
t3pa_cls.write('\n')
i=i+1
t3pa_cls.close
return T_first, E_tot
def energy_spectrum_in_time(Tfirst, Etot): #dela histogram - energie zaznamenana v case
pom = 0
dt=100 #(ns) time width of 1 bin
T_first=0 #cas, kdy prisel trigger a yacalo mereni
T_last=(max(Tfirst)) #posledni z Tfirst
Delta_T = T_last - T_first
poc = int(int(Delta_T) / float(dt)) + 1 #pocet casovych oken
T_int_first=[] #cas
E=[] #energie
for i in range(0,poc):
T_int_first.append((i*dt) + dt/2)
E.append(0)
#XII
for j in range(0,len(Tfirst)):
time_index=0
time_index=int(((Tfirst[j]-T_first)/dt))
if float(Tfirst[j]-T_first) >= (T_int_first[time_index] - dt / 2) and float(Tfirst[j]-T_first) < (T_int_first[time_index] + dt / 2):
E[time_index]=float(E[time_index])+float(Etot[j])
pom=pom+1
for l in range(0,len(T_int_first)):
T_int_first[l]=T_int_first[l]+T_first
caption, T_int_first = energy_in_time_hist(T_int_first, E, figure_E_in_time_hist, t_plasma_start, t_plasma_end, is_plasma, dt)
return dt, caption, T_int_first, E
def energy_in_time_hist(T_int_first, E,figure_E_in_time_hist, t_plasma_start, t_plasma_end, is_plasma, dt):
plt.rcParams.update({'font.size': 20})
fig, ax = plt.subplots(figsize =(10, 7))
for k in range(0,len(T_int_first)):
T_int_first[k] = T_int_first[k] / 1000000
plt.plot(T_int_first, E)
plt.title(detector+', #'+str(shot_no))
plt.xlabel('Time [ms]')
plt.ylabel('Energy [keV]')
if is_plasma == 1:
for t in (t_plasma_start, t_plasma_end):
plt.axvline(t, color='k', linestyle='--')
plt.xlim([0, (t_plasma_start + t_plasma_end)])
else:
plt.xlim(0,)
plt.ylim(0,) #10 000 keV
plt.savefig(figure_E_in_time_hist, dpi = 1000)
caption = '# x = time in ms, count = energy in keV, dT= '+str(dt)+' ns'
return caption, T_int_first
def hits_in_time_hist_new(T, dt, t_plasma_start, t_plasma_end, is_plasma,figure_count_in_time_hist):
pom = 0
T_first=0 #cas, kdy prisel trigger a yacalo mereni
T_last=(max(T)) #posledni z Tfirst
Delta_T = T_last - T_first
poc = int(int(Delta_T) / float(dt)) + 1 #pocet casovych oken
T_hit=[] #cas
count=[] #energie
for i in range(0,poc):
T_hit.append((i*dt) + dt/2)
count.append(0)
for j in range(0,len(T)):
time_index=0
time_index=int(((T[j]-T_first)/dt))
k=time_index
for j in range(0,len(T)):
time_index=0
time_index=int(((T[j]-T_first)/dt))
if float(T[j]-T_first) >= (T_hit[time_index] - dt / 2) and float(T[j]-T_first) < (T_hit[time_index] + dt / 2):
count[time_index] = count[time_index] + 1
pom=pom+1
for l in range(0,len(T_hit)):
T_hit[l]=T_hit[l]+T_first
plt.rcParams.update({'font.size': 20})
fig, ax = plt.subplots(figsize =(10, 7))
for k in range(0,len(T_hit)):
T_hit[k] = T_hit[k] / 1000000
plt.plot(T_hit, count)
plt.title(detector+', #'+str(shot_no))
plt.xlabel('Time [ms]')
plt.ylabel('Count')
if is_plasma == 1:
for t in (t_plasma_start, t_plasma_end):
plt.axvline(t, color='k', linestyle='--')
plt.xlim([0, (t_plasma_start + t_plasma_end)])
else:
plt.xlim(0,)
plt.ylim(0,) #10 000 keV
plt.savefig(figure_count_in_time_hist, dpi = 1000)
caption = '# x = time in ms, dT= '+str(dt)+' ns'
return caption, T_hit,count
def energy_spectrum(Etot):
E_min=0
dE=5 #keV
E_max=max(Etot)
pocet=(E_max//dE) + 3
pocet=int(pocet)
E_max=float(dE*pocet)
xle=[]
xre=[]
xmean=[]
for p in range (0,pocet):
xle.append(E_min + (p * (E_max - E_min)) / pocet)
xre.append(xle[p]+dE)
xmean.append((xle[p] + xre[p]) / 2)
count=[]
for l in range(0,pocet):
count.append(0)
#XII
for i in range(0,len(Etot)):
E_index=int(((Etot[i]-E_min)/dE))
if ((xle[E_index] <= Etot[i]) and (Etot[i] < xre[E_index])):
count[E_index]=count[E_index]+1
plt.rcParams.update({'font.size': 20})
fig, ax = plt.subplots(figsize =(10, 7))
ax.hist(Etot, bins = xle)
plt.title(detector+', #'+str(shot_no))
plt.xlabel('Energy [keV]')
plt.ylabel('Count')
plt.xlim(0,)
ax.set_yscale('log') #log scale y
caption = '# x = energy in keV, dE= '+str(dE)+' keV'
plt.savefig(figure_E_hist, dpi = 1000)
return caption, xmean,count, xle, Etot
def hist_file(file_hist, xmean, count, caption ):
with open(file_hist, "w", encoding="utf-8") as hist:
hist.write('#\n')
hist.write('#'+str(caption)+'\n')
hist.write('# x_mean count\n')
hist.write('\n')
for m in range(0,len(xmean)):
hist.write(str(xmean[m])+' '+str(count[m])+'\n')
hist.close
return T_first, E_tot
def multiplot(icon_fig, x1,y1,x2,y2):
plt.rcParams.update({'font.size': 20})
fig, ax = plt.subplots(nrows=2,figsize =(10, 7))
ax[0].plot(x1, y1)
ax[0].set_xlabel('Time [ms]')
ax[0].set_ylabel('Energy [keV]')
if is_plasma == 1:
for t in (t_plasma_start, t_plasma_end):
ax[0].axvline(t, color='k', linestyle='--')
ax[0].set_xlim([0, (t_plasma_start + t_plasma_end)])
else:
ax[0].set_xlim(0,)
ax[0].set_ylim(0,) #keV
ax[1].hist(y2, bins = x2)
ax[1].set_xlabel('Energy [keV]')
ax[1].set_ylabel('Count')
ax[1].set_xlim(0,)
#ax[1].set_ylim(0,)
ax[1].set_yscale('log') #log scale y
fig.subplots_adjust(hspace=0.3)
plt.savefig(icon_fig, dpi = 1000)
return
#soubory, ktere ctu
#read files
t3pa=get_file(shot, identifier)
name_calib='caliba'
caliba=get_file_calib(name_calib)
name_calib='calibb'
calibb=get_file_calib(name_calib)
name_calib='calibc'
calibc=get_file_calib(name_calib)
name_calib='calibt'
calibt=get_file_calib(name_calib)
#vytvorene soubory:
#created files
t3pa_cls='H03-W0051_shot_'+str(shot)+'_450V.t3pa_cls'
E_hist='H03-W0051_shot_'+str(shot)+'_450V_E_hist.txt'
E_in_time_hist='H03-W0051_shot_'+str(shot)+'_450V_discharge_energy.txt'
count_in_time_hist= 'H03-W0051_shot_'+str(shot)+'_450V_discharge_hits.txt'
#created figures
icon_fig='icon-fig'
figure_E_in_time_hist='discharge_energy'
figure_count_in_time_hist='discharge_hits'
figure_E_hist='Energy_spectrum'
hit_map_fig='hit-map'
#nactu jednotlive kalibracni matice - abych to nemusel delat v kazde funkci
a=load_calib(caliba)
b=load_calib(calibb)
c=load_calib(calibc)
t=load_calib(calibt)
#nactu a urcim jednotlive hodnoty - abych to nemusel delat v kazde funkci
index, matrix_index, ToA, ToT, FToA, overflow, pocet_udalosti = load_t3pa_file(t3pa)
index, matrix_index, ToA, ToT, FToA, overflow, pocet_udalosti, RowNo, ClmNo = t3pa_data(pocet_udalosti,index, matrix_index, ToA, ToT, FToA, overflow)
raw data
#hit map
hit_map(detector,hit_map_fig,RowNo,ClmNo)
Energy and time calculation from raw data.
E=energy(a, b, c, t, ToT, pocet_udalosti, RowNo, ClmNo)
T=Time(ToA, FToA, pocet_udalosti, RowNo, ClmNo)
index, matrix_index, ToA, ToT, FToA, overflow, RowNo, ClmNo, E, T = remove_interactions_with_zero_energy(index, matrix_index, ToA, ToT, FToA, overflow, RowNo, ClmNo, E, T)
#sort by time
T, index, matrix_index, ToA, ToT, FToA, overflow, RowNo, ClmNo, E = (list(t) for t in zip(*sorted(zip(T, index, matrix_index, ToA, ToT, FToA, overflow, RowNo, ClmNo, E), reverse=True))) #serazeni od nejvetsiho po nejmensi
T_pom=T.copy()
#save to file
T_first, E_tot = file_t3pa_cls_new(t3pa_cls,T)
dt, caption, T_int_first, E = energy_spectrum_in_time(T_first, E_tot)
hist_file(E_in_time_hist, T_int_first, E, caption);
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caption, xmean,count, xle, Etot = energy_spectrum(E_tot)
hist_file(E_hist, xmean, count, caption);
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caption, T_hit,count = hits_in_time_hist_new(T_pom, dt, t_plasma_start, t_plasma_end, is_plasma, figure_count_in_time_hist)
hist_file(count_in_time_hist, T_hit, count, caption);
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76.37142048177805, 5.257503154359549, 66.54999858166991, 97.27977467129567, 32.92937503048999, 54.963401983260454, 27.921461364362436, 14.700214437309388, 217.24145866954817, 43.1240276265879, 53.079853156964646, 66.7686039228734, 79.91029818230867, 74.53117870640148, 248.3069823429092, 27.938985349178395, 81.06776974383185, 141.7627292261777, 23.88853987130905, 59.8787129422614, 134.0875449831233, 18.797881626196098, 55.08478667538935, 8.349169179567953, 17.903774356217223, 24.321017746178363, 12.964329205367742, 88.20042582122193, 17.462202679124957, 74.34694267171434, 26.245355015556477, 10.597025127989438, 15.197629317910717, 5.0866923192359, 79.01310723591551, 21.7777775592789, 22.7124355594976, 5.739480550453841, 51.72768029403289, 21.736520009841623, 43.46649209076089, 17.488334125426924, 47.23500531972941, 17.124922815534052, 18.77943507298161, 38.72988709605471, 5.505892485155513, 96.92414108212532, 29.373118349474552, 27.421142555857045, 62.484608509586515, 51.06793851838555, 66.84441408815168, 9.82369840581642, 121.56859694812657, 94.83534926189193, 57.20725279651787, 11.386510726548597, 32.795349207110604, 60.86385496946233, 132.55970180294773, 55.27251971156275, 27.487703668485878, 44.3841140163689, 67.9353441390179, 13.26613260798115, 5.283617947031699, 14.261099925681885, 8.773099897850322, 7.138904137131235, 48.26771737713776, 9.184326218412648, 18.031983884871973, 58.67637069677416, 7.309034317070265, 63.04452212698274, 50.47252622546806, 11.87767446432115, 36.07627158340906, 32.62180082735984, 6.041732360990048, 72.93940436111896, 103.20369848658684, 13.852356056371846, 7.356065823819707, 6.268682736122418, 13.926844934051783, 6.3216493694567175, 131.01520279131137, 6.063605170791715, 21.106663286965265, 15.441607872663068, 6.453780814557448, 8.251531835450606, 20.56297840640216, 47.15452119087336, 48.746351642906745, 28.628031000330054, 46.43850584115996, 139.25435067074517, 25.855762054320667, 10.693536591201877, 44.67965768873514, 14.29439159774092, 112.18063942181507, 9.329959673034981, 5.431118742371678, 20.062822457203886, 26.467238206181257, 52.18548158686342, 11.550842906220447, 7.4250448975411985, 60.09825972436355, 23.383073776812076, 11.580768451447328, 37.44517113964605, 131.65274071060412, 11.121128834538037, 39.34981989407462, 22.795976748751862, 22.99275795399667, 7.7567962657411, 40.90041545042263, 6.853858704734758, 35.6159439231748, 12.373573761818978, 19.11024267778962, 40.17138125660608, 38.620760231990246, 10.020432026262377, 70.04872414016285, 47.795432583777476, 29.16690607712419, 95.2797024378645, 14.007024116291538, 18.866337393935865, 7.473233350402218, 75.09234486895286, 81.49571152337634, 41.07548919504284, 43.21255897354109, 5.9904875613036355, 51.27872565839702, 83.66215353994073, 10.477432381902213, 40.70634402087849, 14.543596768036203, 24.093924592540375, 118.50096131625212, 8.704383718115908, 151.72447286729405, 50.32766929956662, 64.25815480425807, 79.11434508471156, 15.274512740836187, 12.411095250067223, 5.194251572973013, 10.019056364288874, 66.88180333190526, 119.74900057802645, 13.631979059008046, 175.33203628362762, 97.18583543071918, 6.122992053221494, 33.03046038952149, 49.04379268952657, 9.305728072080216, 69.54885959730964, 6.203650121875686, 24.4567454889025, 75.24028101720305, 31.131817819790157, 30.457164676815623, 75.81363822331183, 168.35555377676857, 118.27648690719074, 24.856834095890562, 13.302038477660071, 33.4918171382622, 47.059704603913474, 6.590120228370517, 48.92639500396685, 24.745178634929157, 57.42046368969477, 47.46792429796537, 105.14996590973497, 150.69962575366375, 37.39283730357555, 52.93053365329729, 27.766445474589304, 44.93370267989489, 174.40327842202038, 130.8115171838662, 61.161849398209796, 61.102154109389005, 19.402123781125926, 75.20059182334782, 68.40785082198167, 21.849896735412695, 47.519793930983894, 27.585031150703596, 14.218740084708205, 35.98038493232221, 68.42222324449588, 10.137294702513909, 23.26044326647756, 13.367328338764922, 26.173660998131822, 21.67967902107657, 8.898342504681615, 23.028904889229988, 61.68743247564666, 11.515745541782621, 13.690792326113725, 7.1920741723734825, 12.115813765837034, 28.846294144190477, 61.802997522502025, 8.895645585469875, 5.523716096852602, 11.795726820414508, 18.91171787328809, 6.465595292339552, 133.2287312387199, 20.678484534479768, 14.172417098353025, 68.89017866166424, 15.085270606826018, 10.706184121385466, 112.88990345315804, 8.860777210155467, 26.879509728145106, 25.03296203774991, 6.791424688418236, 25.126568294064764, 29.641546022294882, 97.95746291443398, 90.72613521566451, 17.04850877170246, 6.21484397606306, 62.52404951507688, 28.49251847619064, 8.481036187808307, 33.04777725701324, 85.42463020167015, 21.78217388065877, 11.315140400253625, 11.225601267687834, 84.30187697363576, 64.58652630706584, 5.957758502982739, 41.48595986649536, 9.682318147713042, 67.43323594257063, 7.587362691574734, 189.4199164193481, 81.17015155969928, 109.72989704725052, 243.30815404194297, 51.29263855646026, 24.95921785434964, 40.17541491118661, 6.283568752293017, 23.987900281160435, 7.696628341618867, 29.054730278658784, 13.61063454117376, 90.21089487353063, 5.867187894983036, 34.68110941501987, 58.69369535922559, 49.604808406347786, 6.627826281459123, 27.45193300388448, 55.11784245853839, 13.174934120148272, 6.306574461049041, 36.61946553833724, 83.31295430787266, 69.97270122825319, 42.107689060078435, 57.81741133749967, 7.3072459168155985, 5.133111761437639, 9.89909415729619, 36.71366366529276, 106.55698921778801, 7.664620391703142, 8.651368583056623, 30.732499989915695, 65.87773029178572, 58.05719340664185, 8.326872297986053, 43.93295668489517, 38.543026369882455, 19.38423296509157, 9.52680513962959, 41.407839299976374, 5.3121436843432575, 18.281866776337537, 49.84337524315067, 82.49239228586936, 103.41488508910115, 68.76154979710168, 11.07689141821894, 30.51395935428612, 17.180895721610767, 6.5493714887870285, 11.118515342125876, 6.476660387020689, 55.111389493280775, 6.534753091999598, 6.6628522983334655, 37.1423713134512, 13.913009632640359, 5.854710749369217, 82.88808028145243, 52.00153220782791, 13.140029998848657, 43.39811719789272, 99.41341073846219, 29.401276111278364, 6.929983057762391, 35.6083354780639, 10.603165555297082, 5.311337001510328, 7.046857104927231, 13.421295159060861, 101.21819651104461, 95.29829672159202, 18.426453807364382, 62.379497255485944, 34.02951953997385, 155.89062394271355, 80.23306259036528, 14.66400511543279, 18.93026520652596, 8.147472097461108, 21.896732874645064, 25.87417013289277, 93.62694399051693, 71.43481736367471, 15.963839154094732, 19.057542832221113, 11.341041782655847, 15.883907800363316, 59.82828610435709, 52.27040700081681, 5.475164934331578, 79.42460037620332, 39.44131761293213, 17.44646364922434, 14.580889455761703, 8.60710652982532, 128.62438445228003, 26.50816610322368, 10.130389627301476, 124.26153389920873, 96.16557958863353, 7.179876008437176, 11.144477954574713, 21.817567701002666, 17.403878076529125, 11.124156101633352, 27.270100435160824, 15.999640949318628, 6.02099521435562, 19.470542231222495, 5.362110113773783, 69.01144070204055, 25.174335070987482, 73.76425003516471, 20.922382015476757, 8.09862639876091, 23.302629630134533, 19.369455656684487, 58.884834752553246, 128.68351597056846, 37.002041900829056, 31.201159563628735, 20.744297744299246, 16.02157421599065, 19.862975443353417, 8.74495449827254, 50.21313207810469, 59.90220068558396, 81.88274069083386, 47.72232344191744, 47.62886426797842, 22.69520991684965, 15.307777984666071, 8.843489717783205, 9.342761434747993, 7.970654973091953, 12.08391565090713, 87.14089921780425, 25.095823665868352, 56.454617909952184, 7.799495823793183, 10.363805094380789, 45.31368278626964, 5.146115024724633, 22.126319375142455, 78.58085217214263, 8.57175168984264, 14.104022558650648, 43.82002002328301, 13.080617879049052, 8.644052315028478, 30.37291755615399, 6.281110266524798, 64.34028431832064, 16.730128433920207, 18.109383723217974, 34.01743067824703, 135.28664512118155, 54.74114776712184, 35.20934463760325, 7.71662429425825, 25.56808405479451, 37.439461854657345, 78.29594671624795, 10.538864846864945, 28.88399557288474, 54.97125976199496, 19.28790729353595, 5.326841935349693, 20.58446185925691, 45.92817809831914, 87.70572947301706, 10.95465056408846, 8.576426258088048, 62.50993147666729, 54.19652128665192, 22.425340417347485, 6.446863269676537, 49.17918711575237, 9.908888302015963, 64.5055350270214, 70.64342646035611, 46.51206870997394, 90.14125842589259, 26.36845526226054, 30.150947086656192, 38.87689772727454, 77.64094035710049, 36.90326040343056, 9.263002624321302, 13.13810312488826, 28.390276360467663, 123.34390650163719, 70.84374036425042, 51.78188188436628, 93.27344605042461, 24.358697378553405, 5.359250714434578, 104.13758378079226, 11.90955991151781, 9.616512729816005, 6.536045460839909, 82.52626990182569, 50.67669249007889, 41.43996515169325, 65.39295812888714, 6.82824242964056, 25.89690864327352, 62.59757648652324, 17.638894256165244, 64.46205808763533, 40.727590295032854, 126.09492910391506, 6.413203577212886, 45.44997440123742, 238.33210744907836, 75.22884652654696, 56.39659500514344, 25.018410211335016, 83.75430832027182, 29.317395468219292, 11.669282316373227, 32.58603807423109, 11.854368624103945, 10.386607686374397, 28.57427443046975, 9.607696367980106, 13.584258357844492, 76.1553217746553, 41.55404300083511, 56.37574077278916, 17.567377681730072, 23.318002712846145, 43.726516842487264, 46.63844329454142, 80.5888804971529, 81.82961005659416, 101.87307357151236, 23.74291398367836, 110.73028713392385, 47.72530032726955, 94.05688916847882, 18.30182962070374, 14.540126545956674, 43.74765612201528, 68.840951774263, 60.478703551484045, 77.45421215789334, 59.960562276484275, 14.165390116822337, 32.39478699705094, 36.9584215167666, 47.06273597881825, 42.679135224237804, 29.267917879042212, 39.95225630356676, 26.683748202255597, 21.647426076466388, 58.61875069366071, 50.37639104876946, 49.757528459046796, 76.52609232638527, 22.108100612250684, 103.50263324263894, 19.119888893428982, 70.2811082198995, 64.83033938777804, 24.373261965528926, 17.18087825879846, 12.348734788615156, 25.612937422778817, 19.295341555962843, 31.622377432932726, 17.012264698016708, 109.89153560431691, 123.75358472542516, 14.135911584849637, 25.107826754179253, 19.995120993635492, 28.272239268943856, 21.360019796065888, 56.31318815362961, 82.66759572915375, 74.29756755029928, 46.383637181617544, 32.540596242644355, 89.03647247387218, 34.21661883330295, 25.526296926214798, 71.19084001932279, 6.333239657817041, 15.815287102212572, 8.746552230756777, 49.81906493683879, 11.88601787453043, 86.48049286453158, 17.65478095911994, 11.929779492212017, 13.65853696345586, 92.3526568857422, 67.07154837690501, 33.22972931038663, 6.284137255760298, 6.050231648975426, 58.57662032288643, 14.640677032268677, 52.294283818349136, 20.638308065886804, 11.549306995826164, 76.19439444966041, 11.565996435335645, 33.29707280058691, 62.39793174465364, 18.5743560304483, 18.005780698144513, 12.44653106323796, 21.473558276618594, 19.360236264327213, 56.92647446979024, 90.8014901532128, 38.99985001140813, 36.49470955996079, 58.17212423249003, 14.335698841543747, 79.51971110758672, 7.255071788215574, 6.289395001557266, 43.59396744884342, 51.94934377219752, 82.76980200655002, 28.317336416937643, 8.700072484951674, 16.83782777883354, 83.1282473591045, 5.527022794236763, 6.275503827428149, 30.94192933439457, 32.36843164397269, 7.116924352502695, 83.11497392490963, 20.799796591562796, 51.6258704106698, 19.15805966616899, 15.531571058063818, 42.514550744932194, 12.084926082312947, 23.788867420821003, 70.94524632067143, 22.54064803569959, 28.415896079419372, 6.767627270102004, 76.32088424640718, 79.64936348877406, 14.89024100934066, 30.35834279110535, 24.04369358750118, 116.78577264286893, 41.22573806321425, 72.0275389345606, 46.41877354144149, 51.577434151788346, 8.033145190317162, 141.37666988197344, 6.7716100508343775, 21.39474596353709, 15.221880843010696, 32.59885221698921, 38.890399477926756, 22.344069347210947, 40.434297138058824, 9.056778342166899, 5.33511289408887, 30.003538023374308, 11.934662087772587, 45.49987245934513, 18.38735274761357, 66.8330770433738, 93.93789990016089, 9.087062572194858, 17.456329150909173, 60.97977867283666, 24.016442811418102, 6.117303782784906, 102.30683801728514, 68.99594245342298, 61.42168335228429, 12.390326696780932, 15.094187092548925, ...])
Detected energies during the discharge + Energy spectrum
multiplot(icon_fig, T_int_first,E,xle,Etot)