Prime prove correlazioni¶

In [1]:
import struct
import os
import sys

import numpy as np
from matplotlib import pyplot as plt
import matplotlib as mpl
import copy
In [2]:
my_cmap = copy.copy(mpl.cm.jet) # copy the default cmap
my_cmap.set_bad(my_cmap(0))
In [3]:
myEvent = np.dtype([
    ('timestamp', np.dtype('u8')),
    ('qshort', np.dtype('u2')),
    ('qlong', np.dtype('u2')),
    ('baseline', np.dtype('u2')),
    ('channel', np.dtype('u1')),
    ('PUR', np.dtype('u1')),
])

Prima presa dati¶

In [4]:
with open("abcd_data_2022-05-04T08%3A30%3A27+0000_events.ade", "rb") as f:
    myData = np.fromfile(f, dtype = myEvent)
    
ph = myData["qlong"]
tempi = myData["qshort"]
ch = myData["channel"]
In [5]:
for i,j in enumerate(ch):
    if (i)%2 != j:
        print("Mannaggia")
# Bene, sono alternati
In [6]:
ph1 = ph[ch==0]
ph2 = ph[ch==1]

tempi1 = tempi[ch==0]
tempi2 = tempi[ch==1]
In [7]:
sogliaPhAlpha = 1100
sogliaPhGamma = 920

fig, ax = plt.subplots(2,2)
fig.set_size_inches(16,8)
ax = ax.flatten()

fig.suptitle("Istogrammi semplici", fontsize = 16)

opts = {"color":"lime", "edgecolor":"darkgreen","histtype":"stepfilled"}

ax[0].hist(ph1, bins=100, label = "PH alpha", **opts)
ax[1].hist(ph2, bins=100, range=(0,2000), label = "PH gamma", **opts)
ax[2].hist(tempi1, bins=100, label = "Tempo alpha", **opts)
ax[3].hist(tempi2, bins=100, label = "Tempo gamma", **opts)

ax[0].axvline(x = sogliaPhAlpha, c = "k", ls = "--")
ax[1].axvline(x = sogliaPhGamma, c = "k", ls = "--")


for i in ax: 
    i.set_yscale("log")
    i.legend(fontsize = 16)
    i.set_ylabel("Entries", fontsize = 14)

plt.show()
In [8]:
fig, ax = plt.subplots()
hh = ax.hist2d(ph1, ph2, bins = 100, range = ((0,2000),(0,1000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Energia alpha [ADC]", fontsize = 14)
ax.set_ylabel("Energia gamma [ADC]", fontsize = 14)
ax.set_title("Correlazioni PH", fontsize = 16)

fig.colorbar(hh[3], ax = ax)

plt.show()
In [9]:
fig, ax = plt.subplots()
hh = ax.hist2d(tempi1, tempi2, bins = 100, range = ((0,2000),(0,1000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Energia alpha [ADC]", fontsize = 14)
ax.set_ylabel("Energia gamma [ADC]", fontsize = 14)
ax.set_title("Correlazioni tempi", fontsize = 16)

fig.colorbar(hh[3], ax = ax)

plt.show()

Implemento tagli¶

In [10]:
myLogic = (ph1 > sogliaPhAlpha) & (ph2 > sogliaPhGamma)
In [11]:
fig, ax = plt.subplots(2,2)
fig.set_size_inches(16,8)
ax = ax.flatten()
fig.suptitle("Istogrammi - selezione in PH", fontsize = 16)

opts = {"color":"lime", "edgecolor":"darkgreen","histtype":"stepfilled"}

ax[0].hist(ph1[myLogic], bins=100, label = "PH alpha", **opts)
ax[1].hist(ph2[myLogic], bins=100, range=(0,2000), label = "PH gamma", **opts)
ax[2].hist(tempi1[myLogic], bins=100, label = "Tempo alpha", **opts)
ax[3].hist(tempi2[myLogic], bins=100, label = "Tempo gamma", **opts)

for i in ax: 
    i.set_yscale("log")
    i.legend(fontsize = 16)
    i.set_ylabel("Entries", fontsize = 14)

plt.show()
In [12]:
fig, ax = plt.subplots()
hh = ax.hist2d(ph1[myLogic], ph2[myLogic], bins = 100, range = ((0,2000),(0,2000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Energia alpha [ADC]", fontsize = 14)
ax.set_ylabel("Energia gamma [ADC]", fontsize = 14)
ax.set_title("Correlazioni PH", fontsize = 16)

fig.colorbar(hh[3], ax = ax)

plt.show()

Allungando la finestra a 4096¶

In [13]:
with open("241Am_corr_nuova_window_events.ade", "rb") as f:
    myData = np.fromfile(f, dtype = myEvent)
    
ph = myData["qlong"]
tempi = myData["qshort"]
ch = myData["channel"]
In [14]:
for i,j in enumerate(ch):
    if (i)%2 != j:
        print("Mannaggia")
# Bene, sono alternati
In [15]:
ph1 = ph[ch==0]
ph2 = ph[ch==1]

tempi1 = tempi[ch==0]
tempi2 = tempi[ch==1]
In [16]:
sogliaPhAlpha = 1100
sogliaPhGamma = 750

fig, ax = plt.subplots(2,2)
fig.set_size_inches(16,8)
ax = ax.flatten()

fig.suptitle("Istogrammi semplici", fontsize = 16)

opts = {"color":"lime", "edgecolor":"darkgreen","histtype":"stepfilled"}

ax[0].hist(ph1, bins=100, label = "PH alpha", **opts)
ax[1].hist(ph2, bins=100, range=(0,2000), label = "PH gamma", **opts)
ax[2].hist(tempi1, bins=100, label = "Tempo alpha", **opts)
ax[3].hist(tempi2, bins=100, label = "Tempo gamma", **opts)

ax[0].axvline(x = sogliaPhAlpha, c = "k", ls = "--")
ax[1].axvline(x = sogliaPhGamma, c = "k", ls = "--")


for i in ax: 
    i.set_yscale("log")
    i.legend(fontsize = 16)
    i.set_ylabel("Entries", fontsize = 14)

plt.show()
In [17]:
fig, ax = plt.subplots()
hh = ax.hist2d(ph1, ph2, bins = 100, range = ((0,2000),(0,1000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Energia alpha [ADC]", fontsize = 14)
ax.set_ylabel("Energia gamma [ADC]", fontsize = 14)
ax.set_title("Correlazioni PH", fontsize = 16)

fig.colorbar(hh[3], ax = ax)

plt.show()
In [18]:
fig, ax = plt.subplots()
hh = ax.hist2d(tempi1, tempi2, bins = 100, range = ((0,2000),(0,1000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Energia alpha [ADC]", fontsize = 14)
ax.set_ylabel("Energia gamma [ADC]", fontsize = 14)
ax.set_title("Correlazioni tempi", fontsize = 16)

fig.colorbar(hh[3], ax = ax)

plt.show()

Implemento tagli¶

In [19]:
myLogic = (ph1 > sogliaPhAlpha) & (ph2 > sogliaPhGamma)
In [20]:
%matplotlib qt
%matplotlib inline

fig, ax = plt.subplots(3,2)
fig.set_size_inches(16,8)
ax = ax.flatten()
fig.suptitle("Istogrammi - selezione in PH", fontsize = 16)

opts = {"color":"lime", "edgecolor":"darkgreen","histtype":"stepfilled"}

ax[0].hist(ph1[myLogic], bins=100, label = "PH alpha", **opts)
ax[1].hist(ph2[myLogic], bins=100, range=(0,2000), label = "PH gamma", **opts)
ax[2].hist(tempi1[myLogic], bins=100, label = "Tempo alpha", **opts)
ax[3].hist(tempi2[myLogic], bins=100, label = "Tempo gamma", **opts)
ax[4].hist(tempi1[myLogic], bins=100, label = "Tempo alpha", range = (3140, 3200), **opts)
ax[5].hist(tempi2[myLogic], bins=100, label = "Tempo gamma", range = (3000, 3130), **opts)

for i in ax: 
    i.set_yscale("log")
    i.legend(fontsize = 16)
    i.set_ylabel("Entries", fontsize = 14)

plt.show()
In [21]:
fig, ax = plt.subplots()
hh = ax.hist2d(ph1[myLogic], ph2[myLogic], bins = 100, range = ((0,2000),(0,2000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Energia alpha [ADC]", fontsize = 14)
ax.set_ylabel("Energia gamma [ADC]", fontsize = 14)
ax.set_title("Correlazioni PH", fontsize = 16)

fig.colorbar(hh[3], ax = ax)

plt.show()
In [ ]:

Very long run¶

In [37]:
with open("241Am_corr_looong_events.ade", "rb") as f:
    myData = np.fromfile(f, dtype = myEvent)
    
ph = myData["qlong"]
tempi = myData["qshort"]
ch = myData["channel"]
In [38]:
ph1 = ph[ch==0]
ph2 = ph[ch==1]

tempi1 = tempi[ch==0]
tempi2 = tempi[ch==1]
In [39]:
sogliaPhAlpha = 1100
sogliaPhGamma = 750

fig, ax = plt.subplots(2,2)
fig.set_size_inches(16,8)
ax = ax.flatten()

fig.suptitle("Istogrammi semplici", fontsize = 16)

opts = {"color":"lime", "edgecolor":"darkgreen","histtype":"stepfilled"}

ax[0].hist(ph1, bins=100, label = "PH alpha", **opts)
ax[1].hist(ph2, bins=100, range=(0,2000), label = "PH gamma", **opts)
ax[2].hist(tempi1, bins=100, label = "Tempo alpha", **opts)
ax[3].hist(tempi2, bins=100, label = "Tempo gamma", **opts)

ax[0].axvline(x = sogliaPhAlpha, c = "k", ls = "--")
ax[1].axvline(x = sogliaPhGamma, c = "k", ls = "--")


for i in ax: 
    i.set_yscale("log")
    i.legend(fontsize = 16)
    i.set_ylabel("Entries", fontsize = 14)

plt.show()
In [40]:
fig, ax = plt.subplots()
hh = ax.hist2d(ph1, ph2, bins = 100, range = ((0,2000),(0,1000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Energia alpha [ADC]", fontsize = 14)
ax.set_ylabel("Energia gamma [ADC]", fontsize = 14)
ax.set_title("Correlazioni PH", fontsize = 16)

fig.colorbar(hh[3], ax = ax)

plt.show()
In [41]:
fig, ax = plt.subplots()
hh = ax.hist2d(tempi1, tempi2, bins = 100, range = ((0,2000),(0,1000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Energia alpha [ADC]", fontsize = 14)
ax.set_ylabel("Energia gamma [ADC]", fontsize = 14)
ax.set_title("Correlazioni tempi", fontsize = 16)

fig.colorbar(hh[3], ax = ax)

plt.show()

Implemento tagli¶

In [42]:
myLogic = (ph1 > sogliaPhAlpha) & (ph2 > sogliaPhGamma)
In [43]:
%matplotlib qt
%matplotlib inline

fig, ax = plt.subplots(3,2)
fig.set_size_inches(16,8)
ax = ax.flatten()
fig.suptitle("Istogrammi - selezione in PH", fontsize = 16)

opts = {"color":"lime", "edgecolor":"darkgreen","histtype":"stepfilled"}

ax[0].hist(ph1[myLogic], bins=100, label = "PH alpha", **opts)
ax[1].hist(ph2[myLogic], bins=100, range=(0,2000), label = "PH gamma", **opts)
ax[2].hist(tempi1[myLogic], bins=100, label = "Tempo alpha", **opts)
ax[3].hist(tempi2[myLogic], bins=100, label = "Tempo gamma", **opts)
ax[4].hist(tempi1[myLogic], bins=60, label = "Tempo alpha", range = (3140, 3200), **opts)
ax[5].hist(tempi2[myLogic], bins=65, label = "Tempo gamma", range = (3000, 3130), **opts)

for i in ax: 
    i.set_yscale("log")
    i.legend(fontsize = 16)
    i.set_ylabel("Entries", fontsize = 14)

plt.show()
In [44]:
fig, ax = plt.subplots()
hh = ax.hist2d(ph1[myLogic], ph2[myLogic], bins = 100, range = ((0,2000),(0,2000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Energia alpha [ADC]", fontsize = 14)
ax.set_ylabel("Energia gamma [ADC]", fontsize = 14)
ax.set_title("Correlazioni PH", fontsize = 16)

fig.colorbar(hh[3], ax = ax)

plt.show()

Per poster:¶

In [66]:
"""
myLogic = (ph1 > sogliaPhAlpha) & (ph2 > sogliaPhGamma)
"""
tMinAlpha = 3050
tMaxAlpha = 3200
tMinGamma = 3000
tMaxGamma = 3200


%matplotlib qt
%matplotlib inline

fig, ax = plt.subplots(2,2)
fig.set_size_inches(16,8)
ax = ax.flatten()
# fig.suptitle("Istogrammi - selezione in PH", fontsize = 16)

opts = {"color":"lime", "edgecolor":"darkgreen","histtype":"stepfilled"}

ax[0].hist(ph1[myLogic], bins=100, label = "PH alpha with cut", **opts)
ax[1].hist(ph2[myLogic], bins=100, range=(0,2000), label = "PH gamma with cut", **opts)
ax[2].hist(tempi1[myLogic], bins=100, label = "Time alpha", **opts)
ax[3].hist(tempi2[myLogic], bins=100, label = "Time gamma", **opts)
# ax[4].hist(tempi1[myLogic], bins=60, label = "Tempo alpha", range = (3140, 3200), **opts)
# ax[5].hist(tempi2[myLogic], bins=65, label = "Tempo gamma", range = (3000, 3130), **opts)

ax[2].axvline(x = tMinAlpha, c = "k", ls = "--")
ax[2].axvline(x = tMaxAlpha, c = "k", ls = "--")
ax[3].axvline(x = tMinGamma, c = "k", ls = "--")
ax[3].axvline(x = tMaxGamma, c = "k", ls = "--")


for i in ax: 
    i.set_yscale("log")
    i.set_ylabel("Entries", fontsize = 14)
    
ax[0].legend(fontsize = 14)
ax[1].legend(fontsize = 14, loc = 'upper left')
ax[2].legend(fontsize = 14, loc = 'upper left')
ax[3].legend(fontsize = 14, loc = 'upper left')


plt.show()


myLogicTime = myLogic & (tempi1 > tMinAlpha) & (tempi1 < tMaxAlpha) & (tempi2 > tMinGamma) & (tempi2 < tMaxGamma)
In [67]:
%matplotlib qt
%matplotlib inline

fig, ax = plt.subplots(2,2)
fig.set_size_inches(16,8)
ax = ax.flatten()
# fig.suptitle("Istogrammi - selezione in PH", fontsize = 16)

opts = {"color":"lime", "edgecolor":"darkgreen","histtype":"stepfilled"}

ax[0].hist(ph1[myLogicTime], bins=100, label = "PH alpha with cut", **opts)
ax[1].hist(ph2[myLogicTime], bins=100, range=(0,2000), label = "PH gamma with cut", **opts)
ax[2].hist(tempi1[myLogicTime], bins=100, label = "Time alpha", **opts)
ax[3].hist(tempi2[myLogicTime], bins=100, label = "Time gamma", **opts)
# ax[4].hist(tempi1[myLogic], bins=60, label = "Tempo alpha", range = (3140, 3200), **opts)
# ax[5].hist(tempi2[myLogic], bins=65, label = "Tempo gamma", range = (3000, 3130), **opts)

# ax[2].axvline(x = tMinAlpha, c = "k", ls = "--")
# ax[2].axvline(x = tMaxAlpha, c = "k", ls = "--")
# ax[3].axvline(x = tMinGamma, c = "k", ls = "--")
# ax[3].axvline(x = tMaxGamma, c = "k", ls = "--")


for i in ax: 
    i.set_yscale("log")
    i.set_ylabel("Entries", fontsize = 14)
    
ax[0].legend(fontsize = 14)
ax[1].legend(fontsize = 14, loc = 'upper left')
ax[2].legend(fontsize = 14, loc = 'upper left')
ax[3].legend(fontsize = 14, loc = 'upper left')


plt.show()
In [75]:
fig, ax = plt.subplots()
fig.set_size_inches(12,10)
hh = ax.hist2d(ph1[myLogicTime], ph2[myLogicTime], bins = 100, range = ((0,2000),(0,2000)),
         norm = mpl.colors.LogNorm(), cmap = my_cmap)

ax.set_xlabel("Alpha energy [ADC]", fontsize = 16)
ax.set_ylabel("Gamma energy [ADC]", fontsize = 16)
ax.set_title("Pulse height correlation plot", fontsize = 20)

fig.colorbar(hh[3], ax = ax)

plt.show()

Nuovo timestamp¶

In [30]:
with open("241Am_corr_timestampNuovi_events.ade", "rb") as f:
    myData = np.fromfile(f, dtype = myEvent)
    
ph = myData["qlong"]
tempi = myData["qshort"]
ch = myData["channel"]
In [31]:
ph1 = ph[ch==0]
ph2 = ph[ch==1]

tempi1 = tempi[ch==0]
tempi2 = tempi[ch==1]
In [32]:
for i in range(30):
    print(myData["timestamp"][i])

2913858729
2913858401
2914526093
2914527005
2914761325
2914761820
2918966169
2918963408
2919777624
2919776088
2920133986
2920133089
2924528053
2924526217
2925030162
2925028659
2927098443
2927098881
2928171368
2928168740
2930841845
2930839587
2931255191
2931254974
2932968979
2932966041
2935802486
2935801354
2937842331
2937839510
In [33]:
a = myData["timestamp"][3]
b = myData["timestamp"][2]
print(a,b)

2914527005 2914526093
In [34]:
for i in range(30):    
    aa = myData["qshort"][2*i]
    gg = myData["qshort"][2*i+1]

    print(aa-gg if aa>gg else gg-aa)

328
912
495
2761
1536
897
1836
1503
438
2628
2258
217
2938
1132
2821
448
1028
597
2188
394
1643
562
490
632
1433
1699
2827
285
1942
1970
In [35]:
for i in range(30):    
    aa = myData["timestamp"][2*i]
    gg = myData["timestamp"][2*i+1]

    print(aa-gg if aa>gg else gg-aa)

328
912
495
2761
1536
897
1836
1503
438
2628
2258
217
2938
1132
2821
448
1028
597
2188
394
1643
562
490
632
1433
1699
2827
285
1942
1970
In [36]:
for i,j in enumerate(ch):
    if (i)%2 != j:
        print("Mannaggia")
# Bene, sono alternati