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 math
#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
t3pa2cls_XII - upravena fce energy(a, b, c, t, ToT, pocet_udalosti, RowNo, ClmNo) - nyni je se pocita i s pripadem "nan"
#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 = 44421
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):
pom=0
for i in range (0,len(ToT)):
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 math.isnan(e1):
e1=-1
if math.isnan(e2):
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))
if e1>=0 and e2==e1:
E.append(float(e1))
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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7.595131503419844, 5.262199059003333, 24.866516448072957, 57.846950386569695, 9.019960443676265, 11.591898655469569, 10.307122385393525, 8.381703445896443, 67.8630340849099, 7.5825649721422534, 23.836498439600355, 55.43267375919316, 28.171881240375292, 12.75617284648456, 43.97959719524967, 62.38884238767176, 44.02657682697092, 105.09570602702863, 14.269416342110299, 7.103521913477984, 32.46166852886451, 87.981202619976, 50.75855929370821, 6.7665814914708315, 16.184425196136647, 28.688816906598475, 21.345943303170326, 6.978848856274674, 14.515567983078618, 8.756411494947175, 36.86263607554434, 94.25697763535989, 38.61184790298786, 8.108589282538901, 29.519928223022866, 117.27916433159419, 30.07465129601577, 18.63105129517274, 93.67497625603873, 13.315633900634305, 12.652956040927736, 93.71276190953951, 29.317856489790763, 69.63891463416543, 19.898159657396388, 99.89374731093696, 12.03024171577962, 17.023258255970898, 50.67024288591484, 74.15117852856463, 100.27676264504207, 11.204117938595223, 48.85606681885727, 6.993787834917334, 91.01020229146654, 5.639618255226283, 25.673262390008166, 19.346784924950985, 7.236687995015059, 91.4277347840887, 353.1642279122236, 36.37287678975886, 46.55271824924424, 16.86401961732574, 119.00600501534062, 75.94277799720652, 67.54686160699924, 88.30576952473456, 79.55813907928605, 66.74668299853168, 121.40232566783122, 23.44354103353839, 37.80460217860864, 12.384182490644733, 25.308507741668198, 27.607836948025213, 8.993256446090609, 27.9037377771452, 57.13423535019656, 5.046396631140663, 44.086834791025915, 66.74971372287686, 27.738200159144114, 45.51973119322126, 51.66270325861968, 26.905048141459385, 26.311302575497017, 88.97825950052192, 13.808702050999035, 10.678434775540868, 73.90502937067505, 58.69590505379435, 105.89717699179204, 5.294855607703159, 101.69384297403197, 16.733896093663517, 87.00536751550376, 6.609254277026594, 9.65155975370857, 6.48612241898818, 40.30145682903612, 123.34882989333039, 68.0145437945947, 87.02470088046825, 93.81206059618643, 71.44698902926505, 58.30983422581389, 32.15203355561178, 5.916423642540554, 30.9130988942316, 6.249555021580535, 15.90630246329604, 6.28562401913752, 86.87241428142532, 54.351079022778784, 7.134341224991766, 17.096136255457374, 19.92868909812231, 34.336713266000196, 53.465675762668006, 7.383110831375479, 8.986872387970328, 25.180692068348698, 10.176058189247042, 8.765782124566964, 17.847395748501654, 5.390925106252046, 47.55967210845544, 77.22695733514392, 36.44198645335268, 10.509639699678628, 82.59798664832478, 17.966640429215992, 109.0400648102591, 88.84383647211538, 7.445812112406171, 25.22927028504059, 56.82189678005951, 35.29181108215458, 153.74291114516728, 29.16891237544511, 37.05516832637224, 8.063931334465185, 42.393506080608745, 8.951517343460209, 27.154606858544536, 12.440906097797285, 10.645248996858651, 20.657251567188904, 46.32437871064998, 13.79056245563096, 95.53644761602403, 5.642109104883516, 48.517876090168485, 71.36910977583898, 130.99796371486062, 266.3784372121979, 31.150834118164383, 23.640593019362363, 10.02856161573571, 55.01232295236313, 11.3243521823825, 20.421420456842146, 96.13504347282307, 44.733874727408, 5.314447388638433, 13.62390469488518, 48.359362282963225, 44.0283121981236, 7.44669337483592, 87.54480576545299, 39.49446947092157, 28.723013332423672, 5.347849955446591, 20.825280953577774, 17.622381532927115, 18.79132640856253, 82.33032146185803, 10.804286074145534, 51.29500426326619, 19.231125511639117, 20.809941750687315, 34.89520891523152, 24.929271644911097, 62.34204517554886, 59.80433150566743, 6.369125638555162, 13.53213615199345, 19.237423834168705, 81.55434988780229, 25.51474924984454, 39.961602829740784, 39.34906597304134, 29.601813498941535, 74.24570562880896, 12.443043106945156, 53.557109991300834, 25.237239085321065, 29.1143985322006, 59.778810203157214, 10.928939327289383, 99.82586749029521, 104.62288014114074, 9.636269598592841, 17.92983266303791, 42.71791829403579, 8.042905458541775, 59.43273924126808, 8.343303263102385, 9.550128467242548, 42.10264359512639, 29.49996674416728, 55.221125910082776, 25.34003603628621, 36.98195009867382, 9.576709926379376, 45.564432447761575, 48.8841558321223, 32.166816172471314, 63.45550384850628, 17.14636262308654, 46.3717311397301, 108.72719365228559, 9.308173721447426, 6.719568089073929, 60.14783108199132, 106.7345021685679, 114.65347446007313, 5.633961251372531, 34.70530159162008, 100.75740221525918, 47.276323665899724, 24.85545016299038, 67.76359356604408, 8.472723072290394, 80.88754997643593, 50.60425957738179, 62.20249289855061, 43.44018703069503, 8.857002308821771, 58.22565537096524, 15.564948172568315, 19.711650968229968, 44.61382870826216, 20.14649782290358, 10.055421070780172, 11.099897374328416, 26.445780340948648, 26.437255741632256, 7.9282467661832365, 65.24103557895515, 11.921007144002212, 30.0117374302872, 17.724164161189375, 12.038120756347773, 7.951074920277806, 68.10033788425696, 6.269389541954936, 8.072040429106723, 42.319592687157275, 18.210050327455065, 15.184742490935275, 20.520273403277418, 14.846213438072816, 111.00032855394824, 33.04133317558031, 23.97726433537025, 7.382010248781146, 197.45605549154098, 78.27808616261915, 29.253035980973785, 54.29200405215825, 16.49120169203737, 62.08548909419051, 14.570381489503943, 46.13538956857648, 12.930045592337276, 49.612746817511, 87.20058882061497, 192.81648358851922, 9.184625389748808, 5.36589311629812, 78.018781971986, 25.096645781713402, 14.355886686795778, 28.22848967836162, 11.766941001520966, 25.133002042488705, 5.040427443716263, 50.93368440761357, 14.127440566727369, 27.534648988171917, 90.65285683155685, 82.9133661897764, 13.63127413979858, 78.11627354295965, 11.988859299963206, 35.45729913098581, 140.70900701905535, 18.21578779218758, 21.24865585331601, 15.513826669434305, 42.69029408236171, 11.708097289580206, 9.703837389920766, 25.020001001873798, 26.55435936485997, 178.71031185973337, 28.499750288543495, 17.060559437983173, 9.725154956642417, 36.976255802483365, 25.48015430100551, 49.68583595379305, 94.17137364888862, 8.831332428666398, 42.892442869343974, 110.89121157547117, 39.16660294268549, 12.28268569752506, 19.932347319064377, 85.90759082868561, 30.20271064343336, 82.9317226375739, 90.32934303506532, 65.10447645401857, 40.146147008693944, 20.61662467497051, 31.66361887731261, 70.62800355781759, 70.89222321201929, 62.7985752632341, 10.43970733173884, 88.87487386981574, 58.73206694708578, 20.17503558150766, 48.05025390372097, 56.16643068990413, 24.62148481579287, 9.542029161981208, 17.550997561687197, 12.586012749901304, 9.908003683153384, 12.432497283838774, 53.27127954013546, 153.66814125521628, 12.949747237083626, 135.2584519260495, 10.994238864707107, 25.412272358579006, 15.100623085032536, 82.0343399277512, 6.438733284446497, 27.64732966830599, 82.57092054467921, 5.792411784230142, 5.962903281041188, 20.293438294090777, 13.523710676907264, 65.32852873365141, 14.903400340523557, 26.09989796425735, 13.583893511033459, 24.323453194495062, 26.31080908526332, 11.085416078948324, 35.814715315969664, 122.28073213827521, 224.25393843642073, 8.3446558244015, 61.31399284067861, 40.45997103084111, 21.196830834527777, 6.138514765845778, 9.826398019451755, 18.121123525948775, 58.52273355577291, 60.52714092773089, 34.19651865162656, 7.811793422787866, 80.06503019013093, 32.639821224373776, 212.83506066546738, 20.513631815986155, 28.635602371116054, 105.0038729524283, 21.50068987673967, 66.91896440610766, 32.007902600621094, 123.56829035988608, 36.48391338061768, 50.90852541112962, 184.12327395211761, 20.153877909748278, 363.33281798029674, 157.6722349980858, 184.31580405398876, 45.319900620454916, 54.75029249731975, 81.26647244263113, 39.51991731768729, 23.463264248663688, 72.74632521970332, 102.5145856574575, 29.338116643878244, 31.704457771215765, 36.105185112257544, 8.840000319077078, 44.592269466119575, 68.04642970584788, 28.650340985117243])
Detected energies during the discharge + Energy spectrum
multiplot(icon_fig, T_int_first,E,xle,Etot)