def MakeSiggenWaveform(samp, r, z, ene, t0, smooth=1, phi=np.pi / 8):
""" Use pysiggen to generate a waveform w/ arb. ADC amplitude. Thanks Ben. """
wf_length = samp # in tens of ns. This sets how long a wf you will simulate
# r ranges from 0 to detector.detector_radius
# phi ranges from 0 to np.pi/4 (Clint: Limit is the pcrad, set below)
# z ranges from 0 to detector.detector_length (Clint: Limit is the pclen, set below)
# energy sets the waveform amplitude
# t0 sets the start point of the waveform
# smooth is a gaussian smoothing parameter
# default: r, phi, z, energy, t0, smooth = (15, np.pi/8, 15, 80, 10,15)
# Probably don't mess around with anything in this block
fitSamples = 1000 # ask me if you think you need to change this (you almost definitely don't)
timeStepSize = 1 # don't change this, you'll break everything
# Create a detector model (don't change any of this)
detName = "../data/conf/P42574A_grad%0.2f_pcrad%0.2f_pclen%0.2f.conf" % (
0.05, 2.5, 1.65)
detector = Detector(detName,
timeStep=timeStepSize,
numSteps=fitSamples * 10. / timeStepSize,
maxWfOutputLength=5000)
detector.LoadFieldsGrad("../data/fields_impgrad.npz", pcLen=1.6, pcRad=2.5)
# Sets the impurity gradient. Don't bother changing this
detector.SetFieldsGradIdx(0)
# First 3 params control the preamp shaping.
# The 4th param is the RC decay, you can change that if you want.
# params 5 and 6 are set not to do anything (theyre for the 2 rc constant decay model)
rc_decay = 72.6 #us
detector.SetTransferFunction(50, -0.814072377576, 0.82162729751, rc_decay,
1, 1)
wf_notrap = np.copy(
detector.MakeSimWaveform(r,
phi,
z,
ene,
t0,
wf_length,
h_smoothing=smooth))
timesteps = np.arange(0, wf_length) * 10 # makes it so your plot is in ns
# Add charge trapping
# trap_constants = [8, 28,288] # these are in microseconds
# trap_constant_colors = ["red", "blue", "purple"]
# for (idx, trap_rc) in enumerate(trap_constants):
# detector.trapping_rc = trap_rc
# wf = np.copy(detector.MakeSimWaveform(r, phi, z, ene, t0, wf_length, h_smoothing=smooth))
# ax0.plot(timesteps, wf, color = trap_constant_colors[idx], label = "%0.1f us trapping" % trap_rc )
# ax1.plot(timesteps, wf_notrap - wf, color = trap_constant_colors[idx])
# print "amplitude diff: %f" % ( (np.amax(wf_notrap) - np.amax(wf)) / np.amax(wf_notrap) )
return wf_notrap, timesteps
exit()
siggen_wf_length = (max_sample_idx - np.amin(baselineLengths) + 10) * 10
output_wf_length = np.amax(wfLengths) + 1
#Create a detector model
timeStepSize = 1 #ns
detName = "conf/P42574A_grad%0.2f_pcrad%0.2f_pclen%0.2f.conf" % (0.05, 2.5,
1.65)
det = Detector(detName,
timeStep=timeStepSize,
numSteps=siggen_wf_length,
maxWfOutputLength=output_wf_length,
t0_padding=100)
det.LoadFieldsGrad(fieldFileName)
det.SetFieldsGradIdx(10)
def fit(directory):
initializeDetectorAndWaveforms(
det,
wfs,
)
initMultiThreading(numThreads)
# Create a model object and a sampler
model = Model()
sampler = dnest4.DNest4Sampler(model,
backend=dnest4.backends.CSVBackend(
basedir="./" + directory, sep=" "))
def plot_waveforms():
wf_length = 200 #in tens of ns. This sets how long a wf you will simulate
#Probably don't mess around with anything in this block
fitSamples = 1000 #ask me if you think you need to change this (you almost definitely don't)
timeStepSize = 1 #don't change this, you'll break everything
#Create a detector model (don't change any of this)
detName = "conf/P42574A_grad%0.2f_pcrad%0.2f_pclen%0.2f.conf" % (0.05, 2.5,
1.65)
detector = Detector(detName,
timeStep=timeStepSize,
numSteps=fitSamples * 10. / timeStepSize,
maxWfOutputLength=5000)
detector.LoadFieldsGrad("fields_impgrad.npz", pcLen=1.6, pcRad=2.5)
#sets the impurity gradient. Don't bother changing this
detector.SetFieldsGradIdx(0)
#First 3 params control the preamp shaping.
#The 4th param is the RC decay, you can change that if you want.
#params 5 and 6 are set not to do anything (theyre for the 2 rc constant decay model)
rc_decay = 72.6 #us
detector.SetTransferFunction(50, -0.814072377576, 0.82162729751, rc_decay,
1, 1)
#r ranges from 0 to detector.detector_radius
#phi ranges from 0 to np.pi/4
#z ranges from 0 to detector.detector_length
#energy sets the waveform amplitude
#t0 sets the start point of the waveform
#smooth is a gaussian smoothing parameter
r, phi, z, energy, t0, smooth = (15, np.pi / 8, 15, 80, 10, 15)
trap_constants = [8, 28, 288] #these are in microseconds
trap_constant_colors = ["red", "blue", "purple"]
# fig1 = plt.figure(0, figsize=(20,10))
fig1 = plt.figure(0, figsize=(9, 7))
gs = gridspec.GridSpec(2, 1, height_ratios=[4, 1])
ax0 = plt.subplot(gs[0])
ax1 = plt.subplot(gs[1], sharex=ax0)
ax1.set_xlabel("Digitizer Time [ns]")
ax0.set_ylabel("Voltage [A.U.]")
ax1.set_ylabel("Residual [A.U]")
timesteps = np.arange(0, wf_length) * 10 #makes it so your plot is in ns
wf_notrap = np.copy(
detector.MakeSimWaveform(r,
phi,
z,
energy,
t0,
wf_length,
h_smoothing=smooth))
ax0.plot(timesteps, wf_notrap, color="green", label="No trapping")
for (idx, trap_rc) in enumerate(trap_constants):
detector.trapping_rc = trap_rc
wf = np.copy(
detector.MakeSimWaveform(r,
phi,
z,
energy,
t0,
wf_length,
h_smoothing=smooth))
ax0.plot(timesteps,
wf,
color=trap_constant_colors[idx],
label="%0.1f us trapping" % trap_rc)
ax1.plot(timesteps, wf_notrap - wf, color=trap_constant_colors[idx])
print "amplitude diff: %f" % (
(np.amax(wf_notrap) - np.amax(wf)) / np.amax(wf_notrap))
ax0.legend(loc=4)
plt.show()
plt.savefig("wf.pdf")
max_sample_idx = 150
#Prepare detector
timeStepSize = 1
fitSamples = 200
detName = "conf/P42574A_grad%0.2f_pcrad%0.2f_pclen%0.2f.conf" % (0.05, 2.5,
1.65)
detector = Detector(detName,
timeStep=timeStepSize,
numSteps=fitSamples * 10. / timeStepSize,
maxWfOutputLength=fitSamples + max_sample_idx + 2)
fieldFileName = "P42574A_fields_impgrad_0.00000-0.00100.npz"
#sets the impurity gradient. Don't bother changing this
detector.LoadFieldsGrad(fieldFileName)
detector.SetFieldsGradIdx(33)
b = 169.722312
c = -0.805889
d = 0.813206
rc1 = 72.904982
rc2 = 23.900887
rcfrac = 0.996435
fallPercentage = 0.99
detector.SetTransferFunction(b, c, d, rc1, rc2, rcfrac)
h_100_mu0, h_100_beta, h_100_e0 = 337372.980584, 0.545879, 30.952525,
h_111_mu0, h_111_beta, h_111_e0 = 452053.925755, 0.430484, 23.900887
detector.siggenInst.set_hole_params(h_100_mu0, h_100_beta, h_100_e0, h_111_mu0,
def main(argv):
wfFileName = "P42574A_24_spread.npz"
if os.path.isfile(wfFileName):
data = np.load(wfFileName)
wfs = data['wfs']
else:
print "No saved waveforms available."
exit(0)
global wf
wf = wfs[20]
max_sample_idx = 150
fallPercentage = 0.97
wf.WindowWaveformAroundMax(fallPercentage=fallPercentage,
rmsMult=2,
earlySamples=max_sample_idx)
baseline_length = wf.t0Guess
print "wf length %d (entry %d from run %d)" % (
wf.wfLength, wf.entry_number, wf.runNumber)
wf_length = wf.wfLength
wf_max = np.argmax(wf.windowedWf)
baseline_origin_idx = baseline_length - 30
if baseline_origin_idx < 0:
print "not enough baseline!!"
exit(0)
initT0Padding(max_sample_idx, baseline_origin_idx)
siggen_wf_length = (max_sample_idx - baseline_length + 10) * 10
global output_wf_length
output_wf_length = wf_length + 1
#setup .ector
timeStepSize = 1
fitSamples = 200
detName = "conf/P42574A_ben.conf"
det = Detector(
detName,
timeStep=timeStepSize,
numSteps=siggen_wf_length,
maxWfOutputLength=output_wf_length,
)
fieldFileName = "P42574A_fields_impgrad_0.00000-0.00100.npz"
#sets the impurity gradient. Don't bother changing this
det.LoadFieldsGrad(fieldFileName)
det.SetFieldsGradIdx(np.int(imp_grad))
det.siggenInst.set_hole_params(h_100_mu0, h_100_beta, h_100_e0, h_111_mu0,
h_111_beta, h_111_e0)
det.trapping_rc = trapping_rc
det.SetTransferFunction(
tf_b,
tf_c,
tf_d,
rc1,
rc2,
rcfrac,
)
global detector
detector = det
directory = ""
if len(argv) == 0:
fit(directory)
elif argv[0] == "plot":
if len(argv) > 1: directory = argv[1]
plot("sample.txt", directory)
elif argv[0] == "plotpost":
if len(argv) > 1: directory = argv[1]
plot("posterior_sample.txt", directory)
else:
fit(argv[0])