From 2a069b322c96dd50e0a244e1e29a37a2e2c5a7ad Mon Sep 17 00:00:00 2001
From: "Antonello, Dr. Massimiliano" <massimiliano.antonello@uni-hamburg.de>
Date: Fri, 21 Jun 2024 14:38:02 +0200
Subject: [PATCH] Patch for new versions of numpy 2.0.0 (with Python 3.12). Now
added Main_example.py with the ability to plot transients interactively.
---
AdditionalPDFs.py | 5 +-
LightSimtastic.py | 27 ++++------
Main_example.py | 130 ++++++++++++++++++++++++++++++++++++++++++++++
3 files changed, 143 insertions(+), 19 deletions(-)
create mode 100644 Main_example.py
diff --git a/AdditionalPDFs.py b/AdditionalPDFs.py
index 2934d4c..1c3885b 100644
--- a/AdditionalPDFs.py
+++ b/AdditionalPDFs.py
@@ -1,11 +1,10 @@
import numpy as np
-from scipy.stats import rv_discrete, rv_continuous, uniform
+from scipy.stats import rv_discrete, uniform
import scipy.special as sc
-import matplotlib.pyplot as plt
from scipy.stats._distn_infrastructure import (
- rv_discrete, _ncx2_pdf, _ncx2_cdf, get_distribution_names)
+ rv_discrete, get_distribution_names)
class gpd_gen(rv_discrete):
diff --git a/LightSimtastic.py b/LightSimtastic.py
index c09d042..a4c72ca 100644
--- a/LightSimtastic.py
+++ b/LightSimtastic.py
@@ -1,29 +1,24 @@
import time
-import os
-import glob
import numpy as np
import pandas as pd
-import matplotlib
-import matplotlib.pyplot as plt
import scipy
import scipy.stats as stats
import scipy.signal as signal
from tqdm.auto import tqdm
-from itertools import repeat, chain, product, zip_longest
+from itertools import chain, product, zip_longest
from operator import add
from types import SimpleNamespace
from AdditionalPDFs import borel
-import json
-import re
import codecs
-import random
-from copy import deepcopy
np.set_printoptions(suppress=True)
# evil but works: just suppress the numpy nested ragged array warning
import warnings
-warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning)
+if hasattr(np, 'VisibleDeprecationWarning'):
+ warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning)
+else:
+ warnings.filterwarnings("ignore", category=DeprecationWarning)
class SiPMSimulation:
@@ -447,7 +442,7 @@ class SiPMSimulation:
Ap_d = []
Ap_t = []
-
+
for list_apg_d, list_apg_t in zip(apg_d, apg_t):
_Apd_list = []
_Apt_list = []
@@ -486,9 +481,9 @@ class SiPMSimulation:
Ap_d.append(_Apd_list)
Ap_t.append(_Apt_list)
-
- Ap_d = np.array(Ap_d)
- Ap_t = np.array(Ap_t)
+
+ Ap_d = np.array(Ap_d, dtype="object")
+ Ap_t = np.array(Ap_t, dtype="object")
@@ -505,8 +500,8 @@ class SiPMSimulation:
for list_pg_t, list_pXT_t, list_dXT_t, list_Ap_t, in zip(pg_t, pXT_t, dXT_t, Ap_t)
]
- ns.ag_d = ag_d
- ns.ag_t = ag_t
+ ns.ag_d = np.asarray(ag_d, dtype="object")
+ ns.ag_t = np.asarray(ag_t, dtype="object")
pbar.update(1)
pbar.set_description("{0}".format(self.pb_ag_text[6]))
diff --git a/Main_example.py b/Main_example.py
new file mode 100644
index 0000000..d6b940c
--- /dev/null
+++ b/Main_example.py
@@ -0,0 +1,130 @@
+from LightSimtastic import SiPMSimulation
+import matplotlib.pyplot as plt
+import numpy as np
+
+#################################
+# THE SIMULATION TOOL TAKES A DICTIONARY AS AN INPUT, WITH EACH OF THE VARIABLES AS KEYS.
+# FOR EACH ELEMENT YOU ADD TO THE LISTS, ANOTHER SIMULATION WILL BE PERFORMED.
+# THIS ALLOWS SCANS THROUGH PARAMETERS.
+#################################
+
+variables={
+"Name_Sim":[0], #THIS CAN BE ANYTHING YOU LIKE
+"mu":[7], # MEAN NUMBER OF GEIGER DISCHARGES
+"ppXT":[0.0], # PROBABILITY OF PROMPT CROSS-TALK
+"pdXT":[0.2], #PROBABILITY OF DELAYED CROSS-TALK
+"taudXT":[25], #TIME CONSTANT FOR DELAYED CROSS-TALK (NS)
+"rdXT":[0.5], #FRACTION OF DELAYED CROSS-TALK FROM ADJACENT CELLS
+"pAp":[0.15], #PROBABILITY OF AFTERPULSE
+"tauAp":[7.5], #TIME CONSTANT OF AFTERPULSE
+"taur":[20], # SIPM RECOVERY TIME CONSTANT
+"Sig0":[0.075], #WIDTH OF PEDESTAL [NORMALISED ADC]
+"Sig1":[0.02], # INCREASE IN PEAK WIDTH PER ADDITIONAL DISCHARGE [NORMALISED ADC]
+"DCR":[0.0], # DARK COUNT RATE [GHZ]
+"Sigt":[0.02], # ELECTRONICS NOISE FOR CURRENT TRANSIENT (FOR TRANSIENT)
+"GSig":[0.75], # WIDTH OF ELECTRONICS NOISE TRANSFER FUNCTION (FOR TRANSIENT)
+"tslow":[20], # TIME CONSTANT FOR SLOW PART OF PULSE
+"tfast":[1.5], # TIME CONSTANT FOR FAST PART OF PULSE
+"rfast":[0.2], # PROPORTION OF SLOW/FAST
+"start_tgate":[-5], # GATE START TIME [NS]
+"len_tgate":[150], # LENGTH OF GATE
+"t0":[100,], # STARTING POINT OF GATE
+"tl0":[0], #GAUSSIAN MEAN OF PRIMARY GEIGER DICHARGE TIME DISTRIBUTION
+"tl1":[0.1], #GAUSSIAN WIDTH OF PRIMARY GEIGER DICHARGE TIME DISTRIBUTION
+"tl2":[0], #FREE PARAMETER
+"Gen_mu":["Poisson"], # NUMBER PRIMARY GEIGER DISCHARGE PDF
+"Gen_tmu":["Gauss"], # TIME OF PRIMARY GEIGER DISCHARGE PDF
+"Gen_gain":["Gauss"], # GAIN PDF (FOR TRANSIENT)
+"Gen_npXT":["Binomial"], #NUMBER PROMPT X-TALK DISCHARGE DISTRIBUTION
+"Gen_ndXT":["Binomial"], #NUMBER PROMPT X-TALK DISCHARGE DISTRIBUTION
+"Gen_tdXT":["Exp"], #TIME DELAYED X-TALK DISTRIBUTION
+"Gen_nAP":["Binom"], #NUMBER AFTER DISTRIBUTION
+"Gen_tAP":["Exp"], #AFTERPULSE TIME DISTRIBUTION
+"Gen_noise":["Gauss"] #ELECTRONIC NOISE DISTRIBUTION (FOR TRANSIENT)
+}
+
+#################################
+# CREATE A SIPM SIMULATION CLASS OBJECT
+#################################
+
+s = SiPMSimulation()
+
+#################################
+# ADD VARIABLES
+#################################
+
+s.AddVariables(variables)
+
+n_events = int(1e2)
+iterplot=10
+
+#################################
+# SIMULATE
+#################################
+
+#s.Simulate(n_events, transients=False)
+s.Simulate(n_events, transients=True, n_transients=n_events)
+
+#################################
+# EXTRACT SIMULATION DATAFRAME
+#################################
+
+df = s.pars
+
+#################################
+# TRANSIENT
+#################################
+I = df.iloc[0]["Transients"]['I']
+t = df.iloc[0]["Transients"]['t']
+
+if iterplot>0:
+ # Iterative plot
+ wave_sum = np.sum(I, axis=0)
+ wave_avg = wave_sum / len(I)
+ x_min = t.min(); x_max = t.max()
+ y_min = -0.2; y_max = np.max(I)+1
+
+ fig, ax = plt.subplots(figsize=(15.5,10.5))
+ plt.rc('font', size=20)
+ plt.ion()
+ plt.show()
+
+ for index in range(iterplot):
+ ax.clear()
+ ax.plot(t, I[index], color='blue', label='Transient '+str(index))
+ ax.plot(t, wave_avg, color='red', label='Average transient')
+
+ ax.grid(True, which='both', linestyle=':', linewidth=0.5, color='lightgrey')
+ ax.set_xlim([x_min, x_max])
+ ax.set_ylim([y_min, y_max])
+ ax.set_xlabel('Time [ns]',loc='right')
+ ax.set_ylabel('Intensity [a.u.]',loc='top')
+ ax.set_title('Transients')
+ ax.legend()
+ plt.draw()
+ plt.pause(0.01)
+ input(" ")
+ plt.ioff()
+ plt.close()
+
+#################################
+# EXTRACT CHARGE SPECTRUM
+#################################
+
+Qs = df.iloc[0]["ChargeSpectrum"]
+
+#################################
+# PLOT
+#################################
+
+plt.figure(figsize=(15.5,10.5))
+H, edges = np.histogram(Qs, bins=1000)
+edges = edges[:-1]+(edges[1]-edges[0])
+plt.plot(edges, H)
+plt.title("Simulated Charge Spectrum")
+plt.yscale("log")
+plt.xticks(fontsize=25)
+plt.yticks(fontsize=25)
+plt.xlabel("# GD", fontsize=25),
+plt.savefig("./Example.png")
+
--
GitLab