def geometric_carrier_trapping(eventIDs):
filename = r"C:\Users\alexp\Documents\UW\Research\Selenium\aSe0vBB\particle\selenium-build\output\122_keV_testTuple.root"
emfilename = r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_5um_spacing_fullsize.txt"
configfilename = r"./config.txt"
settings = sc.readConfigFile(configfilename)
newCollection = pd.gEventCollection(filename)
newCollection.printInfo()
bmap = brewer2mpl.get_map("Set2", "Qualitative", max(len(eventIDs) + 1,
3)).mpl_colors
fig, ax = plt.subplots()
for colorj, j in enumerate(eventIDs):
settings["CARRIER_LIFETIME_GEOMETRIC"] = 1
event = newCollection.collection[j]
# Iterate over many scenarios to watch fluctuations
N = 30
qtot = 0
for i in range(N):
print(i)
t, q = pd.computeChargeSignal(event, emfilename, **settings)
ax.plot(t, -q / 1.6e-19 * 0.05, color=bmap[colorj], alpha=0.3)
qtot += q
ax.plot(
t,
-qtot / N / 1.6e-19 * 0.05,
color=bmap[colorj],
linewidth=2,
label="Noise, Event ID %i" % event.GetEventID(),
)
ax.set_xlabel(r"Time ($\mu$s)", fontsize=14)
ax.set_ylabel(r"Induced Charge (keV)", fontsize=14)
ax.set_title(
"Q(t), expressed as energy, on a Coplanar Detector (5 $\mu m$ thickness kapton, 280 V bias) \n with Carrier Trapping Fluctuation. Scaling",
fontsize=16,
)
settings["CARRIER_LIFETIME_GEOMETRIC"] = 0
t, q = pd.computeChargeSignal(event, emfilename, **settings)
ax.plot(t,
-q / 1.6e-19 * 0.05,
color="black",
linewidth=1,
label="No Noise")
ax.legend()
return fig, ax
def noise_histogram_parallel():
configfilename = "/home/apiers/aSe0vBB/carrierproduction/config.txt"
# configfilename = "/home/apiers/mnt/rocks/aSe0vBB/carrierproduction/localconfig.txt"
settings = sc.readConfigFile(configfilename)
filename = settings["PARTICLE_FILENAME"]
emfilename = settings["EM_FILENAME"]
# nEvents = pd.numberOfEvents(filename)
nEvents = 10000.0
simObj = pd.CarrierSimulation(emfilename=emfilename,
configfile=configfilename)
filesize = settings["NEVENTS_PER_FILE"]
outdir = settings["OUTPUT_DIR"]
outfilename = settings["OUTPUT_FILE"]
# Chunk event collection into smaller pieces if needed
for j in range(int(np.ceil(nEvents / filesize))):
indx = []
# Create new event collect with the smaller chunck size
newEventCollection = pd.gEventCollection(
filename, eventCounterRange=[j * filesize, (j + 1) * filesize - 1])
simObj.newEventCollection(newEventCollection)
for i in range(len(newEventCollection.collection)):
event = newEventCollection.collection[i]
zmin = min(event.z)
ymin = np.min(np.abs(event.y))
xmin = np.min(np.abs(event.x))
eevent = np.sum(event.energy)
# if xmin < 1.9 and ymin < 1.9 and zmin > -0.1:
if (xmin < settings["X_MAX"] and ymin < settings["Y_MAX"]
and zmin > settings["Z_MIN"]):
indx.append(i)
simOutput = simObj.processMultipleEvents(indx,
processes=int(
settings["NPROCESSORS"]))
simOutput.setGitInfo(settings["GIT_DIR"])
simObj.outputfile = outfilename % j
simObj.outputdir = outdir
simObj.savedata(simOutput)
signal = 0
def __init__(self, emfilename=None, eventCollection=None, configfile=None):
"""
Initialize the class
"""
self.emfilname = emfilename
self.configfile = configfile
# Default work function of 0.05 keV/ehp
self.symbolTable = cexprtk.Symbol_Table({"E": 10}, add_constants=True)
self.wehpExpression = cexprtk.Expression("0.05", self.symbolTable)
# Read and store settings
print("Read config")
if configfile:
self.settings = sc.readConfigFile(configfile)
else:
self.settings = None
warnings.warn(
"No Settings File Read. Please read (or create) class settings and run applySettings()."
)
return
# Read and store particle data
print("Read Geant4 Simulation Data")
if type(eventCollection) is str:
self.eventCollection = gEventCollection(eventCollection)
else:
self.eventCollection = eventCollection
# Read and store emdata
print("Read Comsol EM Data")
if emfilename:
self.newEmFile(emfilename)
else:
self.x = self.y = self.z = self.data = []
self.applySettings()
if self.settings["SCALE_WEIGHTED_PHI"]:
self.computeScaleFactor()
else:
self.scale = 1
def signalAnalysis():
filename = r"C:\Users\alexp\Documents\UW\Research\Selenium\aSe0vBB\particle\selenium-build\output\122_keV_testTuple.root"
emfilename = [
r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_1um_spacing_fullsize.txt",
r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_3um_spacing_fullsize.txt",
r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_5um_spacing_fullsize.txt",
r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_8um_spacing_fullsize.txt",
]
configfilename = r"./config.txt"
print ("Read settings")
settings = sc.readConfigFile(configfilename)
print ("Read Geant4 Particle data")
newCollection = pd.gEventCollection(filename)
event = newCollection.collection[140]
creatorProc = event.GetHits()[1]["creatorProcess"].split("\x00")[0]
print ("Calculating induced charge signal")
for file in emfilename:
biasVoltIndex = [0, 1, 2, 3, 4]
plt.rc("font", family="serif")
fig, ax = plt.subplots()
bmap = brewer2mpl.get_map("Set1", "Qualitative", 5).mpl_colors
biasString = ["120 V", "160 V", "200 V", "240 V", "280 V"]
for indx in biasVoltIndex:
print (indx)
settings["VOLTAGE_SWEEP_INDEX"] = indx
time, q = pd.computeChargeSignal(event, file, **settings)
ax.plot(time, -q, linewidth=2, color=bmap[indx], label=biasString[indx])
ax.set_xlabel(r"Time ($\mu s$)", fontsize=14)
ax.set_ylabel(r"Induced Charge (C)", fontsize=14)
ax.set_title(
"Induced Charge Signal at Amplifier for %s Kapton layer"
% file.split("\\")[-1].split("_")[3]
)
ax.legend()
return fig, ax
def testScaleFactor():
filename = r"C:\Users\alexp\Documents\UW\Research\Selenium\aSe0vBB\particle\selenium-build\output\122_keV_testTuple.root"
emfilename = r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_5um_spacing_fullsize.txt"
gCollection = pd.gEventCollection(filename)
event = gCollection.collection[146]
configfilename = r"./config.txt"
allhits = event.GetHits()
etot = 0
for i in allhits:
etot += i["energy"]
print (etot)
print (allhits[1]["y"])
event.plotH2()
settings = sc.readConfigFile(configfilename)
settings["SCALE_WEIGHTED_PHI"] = 1
t, q = pd.computeChargeSignal(event, emfilename, **settings)
settings["SCALE_WEIGHTED_PHI"] = 0
tt, qq = pd.computeChargeSignal(event, emfilename, **settings)
# fig, ax = plt.subplots()
# ax.plot(t, -q, 'k', linewidth=3)
# ax.plot(tt, -qq, '-b', linewidth=3)
# ax.set_xlabel(r'Time ($\mu s$)', fontsize=14)
# ax.set_ylabel(r'Induced Charge (C)', fontsize=14)
# ax.legend(['Scaled', 'Not Scaled'])
# return fig, ax
return etot
def main(argv):
""" Main program that acts as an entry point to the simulation """
# Set default values
configfile = "./carrierproduction/config.txt"
nEvents = 0
parser = argparse.ArgumentParser(
description="Process command line arguments for Selena simulation"
)
# Add arguments to the parsers
parser.add_argument(
"-c", "--configfile", nargs="?", default="./carrierproduction/config.txt"
)
parser.add_argument("-n", "--number", nargs="?", default=0, type=int)
parser.add_argument("-v", "--configvar")
parser.add_argument("configvarValue", nargs="*", default=["None"])
commandArgs = parser.parse_args()
# Assign command line variables
configfile = commandArgs.configfile
nEvents = commandArgs.number
# Setup and run the simulation
settings = sc.readConfigFile(configfile)
particlefilename = settings["PARTICLE_FILENAME"]
emfilename = settings["EM_FILENAME"]
if nEvents <= 0:
nEvents = pd.numberOfEvents(particlefilename)
# Print simulation information
print ("Config file is %s" % configfile)
print ("Number of events is %i\n" % nEvents)
simObj = pd.CarrierSimulation(emfilename=emfilename, configfile=configfile)
# Iterate over the values passed to the config var value
for val in commandArgs.configvarValue:
filesize = settings["NEVENTS_PER_FILE"]
outdir = settings["OUTPUT_DIR"]
outfilename = settings["OUTPUT_FILE"]
if val != "None":
print ("\nConfig variable: " + commandArgs.configvar + " = " + val)
outfilename = (
settings["OUTPUT_FILE"].split(".")[0]
+ "_"
+ commandArgs.configvar
+ "_"
+ val
+ "."
+ settings["OUTPUT_FILE"].split(".")[1]
)
# Try to parse config value into double if that is the form of the command line arguments
try:
val = float(val)
except ValueError:
pass
except Exception as e:
print (str(e))
return
# Change the configvar in the settings and apply
simObj.settings[commandArgs.configvar] = val
simObj.settings["OUTPUT_FILE"] = outfilename
simObj.applySettings()
# Chunk event collection into smaller pieces if needed
for j in range(int(np.ceil(float(nEvents) / filesize))):
indx = []
# Create new event collect with the smaller chunck size
newEventCollection = pd.gEventCollection(
particlefilename,
eventCounterRange=[j * filesize, (j + 1) * filesize - 1],
zoffset=settings["Z_OFFSET"],
)
simObj.newEventCollection(newEventCollection)
for i in range(len(newEventCollection.collection)):
event = newEventCollection.collection[i]
zr = np.max(np.abs(event.z))
yr = np.max(np.abs(event.y))
xr = np.max(np.abs(event.x))
eevent = np.sum(event.energy)
zmean = np.sum(np.array(event.z) * np.array(event.energy)) / np.sum(
event.energy
)
if (
xr < settings["X_MAX"]
and yr < settings["Y_MAX"]
and zr < settings["Z_MAX"]
# and zmean < 0.06
# and zmean > 0.01
# and eevent > 115
):
indx.append(i)
simOutput = simObj.processMultipleEvents(
indx, processes=int(settings["NPROCESSORS"])
)
# simOutput = simObj.processMultipleEvents(
# [indx[50]], processes=int(settings["NPROCESSORS"])
# )
simOutput.setGitInfo(settings["GIT_DIR"])
simObj.outputfile = outfilename % j
simObj.outputdir = outdir
simObj.savedata(simOutput)
return
def noise_histogram():
filename = r"C:\Users\alexp\Documents\UW\Research\Selenium\aSe0vBB\particle\selenium-build\output\122_keV_testTupleLarge.root"
emfilename = r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_5um_spacing_fullsize.txt"
configfilename = r"./config.txt"
settings = sc.readConfigFile(configfilename)
# For planar detector
settings["CHARGE_DIFFERENCE"] = 1
settings["VOLTAGE_SWEEP_INDEX"] = 4
settings["SCALE_WEIGHTED_PHI"] = 1
# color scheme
bmap = brewer2mpl.get_map("Dark2", "Qualitative", 5).mpl_colors
# Read event data
collection = pd.gEventCollection(filename)
event = collection.collection[125]
N = 50
wehp = 0.05 # keV
e = 1.6e-19
energy = []
charge = []
charge1usNoTrapping = []
charge20usNoTrapping = []
charge1usTrapping = []
charge20usTrapping = []
allfig = []
allax = []
for i in range(N):
print(i)
energy.append(sum(event.energy))
# nehp, nehpFluctuations, _, _ = event.createCarriers(**settings)
# totalCharge = np.sum((nehp + nehpFluctuations) * wehp)
# charge.append(totalCharge)
# No Trapping
settings["CARRIER_LIFETIME_GEOMETRIC"] = 0
t, qNo = pd.computeChargeSignal(event, emfilename, **settings)
indx1us = np.where(t > 1)[0][0]
indx20us = np.where(t > 20)[0][0]
charge1usNoTrapping.append(-qNo[indx1us] / e * wehp)
charge20usNoTrapping.append(-qNo[indx20us] / e * wehp)
# Trapping
settings["CARRIER_LIFETIME_GEOMETRIC"] = 1
t, qTrap = pd.computeChargeSignal(event, emfilename, **settings)
indx1us = np.where(t > 0.5)[0][0]
indx20us = np.where(t > 22)[0][0]
charge1usTrapping.append(-qTrap[indx1us] / e * wehp)
charge20usTrapping.append(-qTrap[indx20us] / e * wehp)
fig, ax = plt.subplots()
ax.plot(t, -qTrap)
# Energy histogram
fig, ax = plt.subplots()
ax.hist(energy,
bins=100,
range=(100, 140),
histtype="step",
linewidth=2,
color=bmap[0])
ax.set_title("Energy Deposited in Event %i" % event.GetEventID(),
fontsize=16)
ax.set_xlabel("Energy (keV)", fontsize=14)
allfig.append(fig), allax.append(ax)
# Charge creation histogram
# fig, ax = plt.subplots()
# ax.hist(charge, bins=100, range=(100,140), histtype='step', linewidth=2, color=bmap[0])
# ax.set_title('Charge Created with Poisson Fluctuations in Event %i' % event.GetEventID(), fontsize=16)
# ax.set_xlabel('Energy (keV)', fontsize=14)
# Induced charge, trapping
fig, ax = plt.subplots()
ax.hist(
charge1usTrapping,
bins=122,
range=(0, 122),
histtype="step",
linewidth=2,
color=bmap[0],
label="1 $\mu s$",
)
ax.hist(
charge20usTrapping,
bins=122,
range=(0, 122),
histtype="step",
linewidth=2,
color=bmap[1],
label="20 $\mu s$",
)
ax.set_title(
"Charge Induced at Planar Detector (Poisson and Trapping Fluctuations) in Event %i"
% event.GetEventID(),
fontsize=16,
)
ax.set_xlabel("Energy (keV)", fontsize=14)
ax.legend()
allfig.append(fig), allax.append(ax)
# Induced charge, no trapping
fig, ax = plt.subplots()
ax.hist(
charge1usNoTrapping,
bins=122,
range=(0, 122),
histtype="step",
linewidth=2,
color=bmap[0],
label="1 $\mu s$",
)
ax.hist(
charge20usNoTrapping,
bins=122,
range=(0, 122),
histtype="step",
linewidth=2,
color=bmap[1],
label="20 $\mu s$",
)
ax.set_title(
"Charge Induced at Planar Detector (Poisson and No Trapping Fluctuations) in Event %i"
% event.GetEventID(),
fontsize=16,
)
ax.set_xlabel("Energy (keV)", fontsize=14)
ax.legend()
allfig.append(fig), allax.append(ax)
return allfig, allax
def noise_histogram_multiple_events():
filename = r"C:\Users\alexp\Documents\UW\Research\Selenium\aSe0vBB\particle\selenium-build\output\122_keV_testTuple.root"
emfilename = r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_5um_spacing_fullsize.txt"
configfilename = r"./config.txt"
settings = sc.readConfigFile(configfilename)
# manipulate settings
eventCollection = pd.gEventCollection(filename)
eventCollection.printInfo()
wehp = 0.05 # keV
e = 1.6e-19
bmap = brewer2mpl.get_map("Dark2", "Qualitative", 5).mpl_colors
# data storage
allfig = []
allax = []
# info for iterating over 3 cases
emfilename = [
r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_5um_spacing_fullsize_fine.txt",
r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\kapton_layer_analysis_5um_spacing_fullsize_fine.txt",
r"C:\Users\alexp\Documents\UW\Research\Selenium\Coplanar Detector\sim_data\real_electrode.txt",
]
plotTitle = [
"Coplanar Detector No Scaling",
"Coplanar Detector Scaling",
"Planar Detector",
]
chargediff = [1, 1, 0]
voltageIndx = [4, 4, 0]
scaleWeight = [0, 1, 0]
neg = [-1, -1, 1]
# iterate over each event. Pick 122 keV and do simulation on them
for j in range(len(plotTitle)):
charge1usNoTrapping = []
charge20usNoTrapping = []
charge1usTrapping = []
charge20usTrapping = []
settings["CHARGE_DIFFERENCE"] = chargediff[j]
settings["VOLTAGE_SWEEP_INDEX"] = voltageIndx[j]
settings["SCALE_WEIGHTED_PHI"] = scaleWeight[j]
for i, event in enumerate(eventCollection.collection):
etot = sum(event.energy)
zmin = min(event.z)
# if energy is 122 kev, we do the analysis
if round(etot) == 122:
if np.max(np.abs(event.y)) < 0.5 and zmin > -0.05:
# No trapping
settings["CARRIER_LIFETIME_GEOMETRIC"] = 0
# t, qNo = pd.computeChargeSignal(event, emfilename[j], **settings)
# indx1us = np.where(t > 1)[0][0]
# indx20us = t.size - 1
q1, q20 = charge_compute_wrapper(event, emfilename[j], e,
wehp, neg[j], **settings)
charge1usNoTrapping.append(q1)
charge20usNoTrapping.append(q20)
print("1 us. Event ID %i: %f" % (event.GetEventID(), q1))
print("20 us. Event ID %i: %f" % (event.GetEventID(), q20))
# Trapping
# settings['CARRIER_LIFETIME_GEOMETRIC'] = 0
# t, qTrap = pd.computeChargeSignal(event, emfilename[j], **settings)
# indx1us = np.where(t >1)[0][0]
# indx20us = t.size - 1
# charge1usTrapping.append(neg[j]*qTrap[indx1us]/e * wehp)
# charge20usTrapping.append(neg[j]*qTrap[indx20us]/e * wehp)
# Induced charge, trapping
# fig, ax = plt.subplots()
# ax.hist(charge1usTrapping, bins=130, range=(0,130), histtype='step', linewidth=2, color=bmap[0], label='1 $\mu s$, mean=%.2f, rms=%.2f' %(np.mean(charge1usTrapping), np.std(charge1usTrapping)))
# ax.hist(charge20usTrapping, bins=130, range=(0,130), histtype='step', linewidth=2, color=bmap[1], label='20 $\mu s$, mean=%.2f, rms=%.2f' %(np.mean(charge20usTrapping), np.std(charge20usTrapping)))
# ax.set_title('Charge Induced at %s for Different 122 keV Events'%plotTitle[j], fontsize=16)
# ax.set_xlabel('Energy (keV)', fontsize=14)
# ax.legend(loc=2)
# allfig.append(fig), allax.append(ax)
# Induced charge, no trapping
fig, ax = plt.subplots()
ax.hist(
charge1usNoTrapping,
bins=130,
range=(0, 130),
histtype="step",
linewidth=2,
color=bmap[0],
label="1.5 $\mu s$, mean=%.2f, rms=%.2f" %
(np.mean(charge1usNoTrapping), np.std(charge1usNoTrapping)),
)
ax.hist(
charge20usNoTrapping,
bins=130,
range=(0, 130),
histtype="step",
linewidth=2,
color=bmap[1],
label="20 $\mu s$, mean=%.2f, rms=%.2f" %
(np.mean(charge20usNoTrapping), np.std(charge20usNoTrapping)),
)
ax.set_title(
"Charge Induced at %s for Different 122 keV Events" %
plotTitle[j],
fontsize=16,
)
ax.set_xlabel("Energy (keV)", fontsize=14)
ax.legend(loc=2)
allfig.append(fig), allax.append(ax)
return allfig, allax
def newSettings(self, configfile):
self.settings = sc.readConfigFile(configfile)
# Testing the operation of these objects
import seleniumconfig as sc
import particledata as pd
# Create the data for the simulated pulse objects
Load test particle data
eventCol = pd.gEventCollection(
"/home/apiers/mnt/rocks/selena/data/particle/pixel_sio2_122kev_12degBeam_100k.root",
eventCounterRange=[0, 5],
)
# Load config file
config = sc.readConfigFile(
"/home/apiers/mnt/rocks/aSe0vBB/carrierproduction/config.txt"
)
# Create fake data
n = 100
t = np.linspace(0, 10, n)
s1 = t[0 : int(np.random.uniform(1, n))] * np.random.uniform(0, 1)
s2 = t[0 : int(np.random.uniform(1, n))] * np.random.uniform(0, 1)
signal = np.concatenate((s1, s1[-1] * np.ones(n - s1.size))) + np.concatenate(
(s2, s2[-1] * np.ones(n - s2.size))
)
x, y, z = [1, 1, 1], [1, 2, 3], [5, 7, 7]
energy = np.array([12, 10, 100])
wehp = np.array([0.04, 0.041, 0.042])
nehp = energy / wehp
nehpf = np.random.poisson(nehp)
