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 = 44529
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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5.889746723795036, 16.642400753730172, 15.18501496634751, 27.0943252053947, 19.076704642784655, 6.691163229226904, 57.66642499346492, 16.615214856301986, 5.323664037217394, 12.870639758178005, 13.47855306367875, 84.86008029315596, 15.024038021536226, 21.08832857150172, 20.502913106869094, 33.75538405899368, 6.733575600312667, 15.809364813691337, 7.201286681865446, 6.0816451145323285, 79.26252707616494, 13.726517039074029, 47.781471066476385, 22.24930516414614, 60.7518547946961, 31.221493428716915, 24.966690284075703, 14.347249701326785, 21.599194252546575, 38.3588353782252, 15.564421283043233, 13.597774954942903, 39.99628468780775, 22.88995648003838, 40.48202396444261, 35.67166497409103, 134.39385721480718, 5.300263663531363, 85.30866242084073, 69.29067386173162, 41.64134077449923, 43.43278645042357, 59.87782170498564, 55.78212196213634, 6.899441414885073, 14.38002948266162, 38.737229854579226, 19.287070746067666, 19.365617318460707, 7.858825854702455, 6.779570110032547, 8.623146387587262, 9.429939411889002, 5.3678137539094415, 16.7341984319211, 22.73427983825978, 11.966264598200269, 6.834493365791316, 5.379952966447907, 39.778012427051905, 26.206673266390045, 12.036368094820142, 37.99691192933244, 49.06396024947829, 146.17828993538492, 55.25260988315125, 37.1440217974349, 15.787236319903396, 16.647127300143982, 6.12673853908567, 5.659348981629775, 22.30105131438771, 16.729821211280854, 29.051625317992823, 10.811494287935094, 25.861532066629692, 34.97851508179406, 67.02990443086271, 24.414695995324138, 16.379813581841642, 23.11032814379475, 55.247479014106645, 61.38022337818151, 24.324547752369202, 22.241070093804975, 7.314593122274525, 80.20173111609554, 77.0908019147634, 102.9154672109412, 22.957495580830614, 33.765342634374036, 46.24134287797399, 69.1674379915813, 6.375937003992957, 8.713720782090602, 100.05871615653862, 28.610017911759115, 79.28598522153132, 16.865336857350403, 64.55196103296775, 9.53284924231757, 19.443259794927265, 5.033671761238463, 10.470431196475305, 25.097019873028934, 35.04574341438455, 27.402774751803868, 12.694683810796962, 8.340559177073482, 13.640831375927062, 54.81265703640567, 49.06493623588928, 5.62065897658044, 8.794972639428673, 87.87589858414329, 30.56781556105499, 47.260721922823905, 78.42667838875936, 48.34745105241726, 22.619691068853466, 68.67742711842382, 6.318123902707775, 5.5245489791167115, 5.7359263785661305, 52.12040622413002, 11.50279764375112, 57.866386987602226, 42.608079697869286, 85.535365369179, 10.253058998940517, 13.472752065084217, 42.71999881154682, 24.339973270093914, 6.913804574393271, 23.523027679021425, 79.90497877345776, 6.785036547183423, 30.94330828229974, 56.959207546751344, 104.11825331105041, 20.765798431667406, 6.6513033600003375, 47.76379734947511, 37.89704300608452, 8.56893262957653, 7.885937528121809, 26.27196888419597, 26.26207190317276, 51.051474998370665, 14.108970344869345, 6.773956792795996, 33.69043216476397, 92.38500111882406, 40.292837394265725, 35.630836819228385, 74.14495319564793, 23.83770323817886, 8.822136888904623, 13.207788281550927, 101.69144236874027, 50.83514608014728, 11.361083673417486, 105.45912645222798, 17.43275333135287, 10.799588486890835, 26.664916885708884, 30.04018034377117, 11.969509083779881, 26.214602777262158, 47.738302108751135, 26.654833699605224, 53.26300719531444, 36.57322617394971, 11.079982486593522, 19.746098796914005, 13.11481075609913, 6.431811899239111, 47.500103614519844, 28.433849245706867, 5.328613322419715, 11.888137753680944, 16.759864257868692, 9.6620400973615, 57.540275366133756, 18.81247992716082, 35.09621044822148, 7.865318277315491, 28.762790559811386, 33.41290685122884, 5.432056116735115, 10.007605498857345, 6.830449368245077, 37.41825647814323, 15.793492646300152, 7.9181812397333475, 60.219999080497615, 51.71645802030075, 12.279336418927917, 5.339399799810742, 11.160836850946943, 13.716416215455652, 51.61698277085947, 9.043224983718092, 88.66804603884162, 45.37083132518059, 21.57801995895946, 77.2429299500754, 62.76121402777798, 7.603611602313181, 35.33944535508393, 30.609880227178472, 12.177713182778449, 18.675053405733717, 7.654187800790934, 54.36381559419603, 27.994434279752134, 12.665632173913874, 45.660785740555816, 18.92654886503231, 32.17850497185195, 18.233160117141868, 40.79318550543543, 54.72864586884015, 32.364631241112306, 12.836469344741218, 18.740895444816292, 5.629464643133254, 12.523195639411641, 17.26606467230877, 22.11263852921472, 6.407171551870401, 49.31818741691774, 7.333911131171782, 81.60236692441008, 9.725901949970657, 11.261091657772775, 11.530471496658208, 6.702385151807667, 14.80563544414959, 29.65868461440448, 7.804736296517852, 11.551961936322066, 99.99260820493305, 24.514330279134825, 17.07862801704698, 42.52883438094541, 5.978605888754163, 75.74311853146145, 97.90859183660349, 56.948107276915316, 67.48149726836735, 33.42602915415409, 33.50280221714644, 21.360916216218968, 41.48654089270738, 5.896252938555228, 81.94242824717769, 77.20691742822233, 10.152184116461445, 13.017087975525696, 23.577173353366046, 109.27527899189722, 114.18203835613429, 50.30175731612823, 5.146128300237676, 12.865746802158746, 33.40661388393106, 69.20976579662678, 53.32857712598188, 81.99181316987061, 91.74674516924516, 141.83846404564252, 15.66922277029354, 41.07080556221892, 69.69847771686334])
Detected energies during the discharge + Energy spectrum
multiplot(icon_fig, T_int_first,E,xle,Etot)