def simSonoraSpc(tAl2O3, e0, det, wkDst=5, lt=100, pc=1, nTraj=1000, xtraParams={}):
"""simSonoraSpc(tAl2O3, e0, det, wkDst=5, lt=100, pc=1, nTraj=1000, xtraParams={})
Simulate a spectrum from tAl2O3 nm of Al2O3 on Al recoreed at
e0 kV using the DTSA detector det and a wkDst mm working distance for
lt sec with a probe current of pc nA. Compute nTraj trajectories."""
tAl = 100 # um
al2o3 = dt2.material("Al2O3",density=3.95)
al = dt2.material("Al", density=2.70)
lAl2O3 = [al2o3, tAl2O3*1.0e-9]
lAl = [al, tAl*1.0e-6]
lay = [lAl2O3, lAl]
sNam = "%g-nm-Al2O3-on-Al-%g-kV" % (tAl2O3, e0)
spc = dt2.wrap(mc3.multiFilm(lay, det, e0, True, nTraj, lt*pc, True, True, xtraParams))
props=spc.getProperties()
props.setTextProperty(epq.SpectrumProperties.SpectrumDisplayName, sNam)
props.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
props.setNumericProperty(epq.SpectrumProperties.FaradayBegin, pc)
props.setNumericProperty(epq.SpectrumProperties.BeamEnergy, e0)
props.setNumericProperty(epq.SpectrumProperties.WorkingDistance, wkDst)
return(spc)
def suggestTransitions(mat, e0=20.0):
"""suggestTransitions(mat, e0=20.0)
Suggest a list of transitions for the specified material."""
mat = dtsa2.material(mat)
xrts = ("%s K-L3", "%s K-M3", "%s L3-M5", "%s L2-N4", "%s M5-N7", "%s M4-N6")
res = []
for elm in mat.getElementSet():
for xrt in xrts:
tr = dtsa2.transition(xrt % elm.toAbbrev())
if tr.exists() and (tr.getEnergy() < 0.95 * epq.ToSI.keV(e0)) and (tr.getEnergy() > epq.ToSI.keV(0.2)):
res.append(tr)
return res
def simulate(mat, det, e0=20.0, dose=defaultDose, withPoisson=True, nTraj=defaultNumTraj, sf=defaultCharFluor, bf=defaultBremFluor, xtraParams=defaultXtraParams):
"""simulate(mat,det,[e0=20.0],[withPoisson=True],[nTraj=defaultNumTraj],[dose=defaultDose],[sf=defaultCharFluor],[bf=defaultBremFluor],[xtraParams=defaultXtraParams])
Simulate a bulk spectrum for the material mat on the detector det at beam energy e0 (in keV). If \
sf then simulate characteristic secondary fluorescence. If bf then simulate bremsstrahlung secondary \
fluorescence. nTraj specifies the number of electron trajectories. dose is in nA*sec."""
mat = dtsa2.material(mat)
if not isinstance(mat, epq.Material):
print u"Please provide a material with a density - %s" % mat
tmp = u"MC simulation of bulk %s at %0.1f keV%s%s" % (mat, e0, (" + CSF" if sf else ""), (" + BSF" if bf else ""))
print tmp
res = base(det, e0, withPoisson, nTraj, dose, sf, bf, tmp, buildBulk, { "Material" : mat }, xtraParams)
res.getProperties().setCompositionProperty(epq.SpectrumProperties.StandardComposition, mat)
return res
def simNiCuPetSpc(tNi, tCu, e0, det, wkDst=17, lt=100, pc=1, nTraj=1000):
"""simNiCuPetSpc(tNi, tCu, e0, det, wkDst=17, lt=100, pc=1, nTraj=1000)
Simulate a spectrum from tNi nm of Ni on tCu nm of Cu on PET recoreded at
e0 kV using the DTSA detector det and a wkDst mm working distance for
lt sec with a probe current of pc nA. Compute nTraj trajectories."""
tPET = 76 # um
pet = dt2.material("C10H8O4",density=1.37)
cu = dt2.material("Cu", density=8.96)
ni = dt2.material("Ni", density=8.90)
lNi = [ni, tNi*1.0e-9]
lCu = [cu, tCu*1.0e-9]
lPET = [pet, tPET*1.0e-6]
lay = [lNi, lCu, lPET]
sNam = "%g-nm-Ni-%g-nm-Cu-on-PET-%g-kV" % (tNi, tCu, e0)
spc = dt2.wrap(mc3.multiFilm(lay, det, e0, True, nTraj, lt*pc, True, True))
props=spc.getProperties()
props.setTextProperty(epq.SpectrumProperties.SpectrumDisplayName, sNam)
props.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
props.setNumericProperty(epq.SpectrumProperties.FaradayBegin, pc)
props.setNumericProperty(epq.SpectrumProperties.BeamEnergy, e0)
props.setNumericProperty(epq.SpectrumProperties.WorkingDistance, wkDst)
return(spc)
def addMeasurement(spec, mat):
"""addMeasurement(spec, mat)
Add a QC entry based on the specified spectrum collected from the named material. /
The spectrum must define the probe current and detector properties."""
comp = d2.material("__QC__[%s]" % mat)
if not comp:
comp = d2.material(mat)
if not comp:
raise "Please specify a known material."
comp.setName(mat)
det = spec.getProperties().getDetector()
if not det:
raise "Please specify a detector in the spectrum properties."
det = d2.Database.getEarliestCalibrated(det)
beamE = spec.getProperties().getNumericWithDefault(
epq.SpectrumProperties.BeamEnergy, 0.0)
if beamE == 0.0:
raise "Please specify the beam energy in the spectrum properties."
qcp = d2.Database.getQCProject(det, comp, beamE)
mode = d2.Datab
data = epq.SpectrumFitter7.performQC(det, comp, spec, None)
d2.Database.addQC(qcp, spec, data)
print "%s added to %s" % (spec, d2.Database.describeQCProject(qcp))
def ranges(comp, e0, over=1.5):
"""Example: ranges(createMaterial(),5.0,1.5)
Prints a list of edges, over voltages, and ionization ranges (in meters)
for the specified material at the specified beam energy in keV (5.0) and
required overvoltage (1.5)"""
print "Shell\tOver\tRange (m)"
comp = dtsa2.material(comp)
for elm in comp.getElementSet():
elm = dtsa2.element(elm)
sh = maxEdge(elm, e0, over)
if sh != None:
print "%s\t%g\t%e" % (
sh, e0 / epq.FromSI.keV(sh.getEdgeEnergy()),
epq.ElectronRange.KanayaAndOkayama1972.compute(
comp, sh, epq.ToSI.keV(e0)) / comp.getDensity())
else:
print "%s\tNone\tNone" % elm
def suggestTransitionSets(mat, e0=20.0):
"""suggestTransitions(mat, e0=20.0)
Suggest a list of XRayTransitionSet objects for the specified material."""
mat = dtsa2.material(mat)
fams = ("Ka", "Kb", "La", "Lb", "Ma", "Mb")
res = []
for elm in mat.getElementSet():
for fam in fams:
xrts = dtsa2.getTransitionSet(elm, fam)
removeMe = epq.XRayTransitionSet()
if (xrts.size() > 0):
for xrt in xrts:
ee = epq.FromSI.keV(xrt.getEnergy())
if (ee < 0.2) or (ee > 0.95 * e0):
removeMe.add(xrt)
if removeMe.size() > 0:
xrts.removeAll(removeMe)
if xrts.size() > 0:
res.append(xrts)
return res
def stemCell(h2oThickness,
objMat,
objDiameter,
objDepth,
e0,
beamOffset=0.0,
detectorDistance=0.008,
detectorRadius=0.02,
detRingCount=100,
nTraj=10000):
"""stemCell(h2oThickness, objMat, objDiameter, objDepth, e0, [beamOffset=0.0], [detectorDistance=0.008], [detectorRadius=0.02], [detRingCount=100], [nTraj=10000]):
Model scattering from a spherical object embedded in a suspended water film.
Example:
> import dtsa2.stemCell as sc
> sc.stemCell(1.0e-6, material("Au",10.0), 2.0e-7, 4.0e-7, 100.0,nTraj=1000)"""
monte = nm.MonteCarloSS()
monte.setBeamEnergy(epq.ToSI.keV(e0))
beam = nm.GaussianBeam(1.0e-10)
beam.setCenter((beamOffset, 0.0, -0.01))
monte.setElectronGun(beam)
h2o = d2.material("H2O", 1.0)
h2oThickness = max(h2oThickness, objDiameter)
objDepth = max(0.5 * objDiameter,
min(h2oThickness - 0.5 * objDiameter, objDepth))
h2oSr = monte.addSubRegion(
monte.getChamber(), h2o,
nm.MultiPlaneShape.createFilm((0.0, 0.0, -1.0), (0.0, 0.0, 0.0),
h2oThickness))
monte.addSubRegion(h2oSr, objMat,
nm.Sphere((0.0, 0.0, objDepth), 0.5 * objDiameter))
ann = nm.AnnularDetector(detectorRadius, detRingCount,
(0.0, 0.0, detectorDistance), (0.0, 0.0, -1.0))
monte.addActionListener(ann)
monte.runMultipleTrajectories(nTraj)
header = "Parameters:\nWater thickness\t%g nm\nSphere material\t%s\nSphere diameter\t%g nm\nSphere center depth\t%g nm\nBeam offset\t%g nm\nDetector distance\t%g mm\nDetector radius\t%g mm\nE0\t%g keV" % (
1.0e9 * h2oThickness, objMat.descriptiveString(False),
1.0e9 * objDiameter, 1.0e9 * objDepth, 1.0e9 * beamOffset,
1.0e3 * detectorDistance, 1.0e3 * detectorRadius, e0)
print header
return (header, ann)
def simCarbonCoatedStd(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0):
"""simCarbonCoatedStd(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0)
Use mc3 multilayer simulation to simulate a C-ctd standard specimen
Parameters
----------
mat - a dtsa material.
Note the material must have an associated density. It should have a useful name.
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated standard spectrum
Example
-------
import dtsa2.jmMC3 as jm3
det = findDetector("Si(Li)")
mgo = material("MgO", density=3.58)
a = jm3.simCarbonCoatedStd(mgo, det, 20.0, 100, 100, 1.0, 20.0)
a.display()
"""
dose = pc * lt # na-sec"
c = dt2.material("C", density=2.1)
layers = [[c, tc * 1.0e-9], [mat, 50.0e-6]]
xrts = []
trs = mc3.suggestTransitions(c, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(mat, e0)
for tr in trs:
xrts.append(tr)
xtraParams = {}
xtraParams.update(mc3.configureXRayAccumulators(xrts, True, True, True))
sim = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams=xtraParams)
sName = "%g-nm-C-on-%s-%g-kV-%g-Traj" % (tc, mat, e0, nTraj)
sim.rename(sName)
sim.setAsStandard(mat)
return sim
def simCtdOxOnSi(det, e0, nTraj, lt=100, pc=1.0, tox=10.0, tc=20.0):
"""
simCtdOxOnSi(det, e0, nTraj, lt=100, pc=1.0, tox = 10.0, tc=20.0)
Use mc3 multilayer simulation to simulate a C-ctd silicon specimen
with a native oxide layer.
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tox - float (10.0)
The thickness of the native oxide in nm
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated spectrum
Example
-------
import dtsa2.jmMC3 as jm3
det = findDetector("Si(Li)")
a = jm3.simCtdOxOnSi(det, 3.0, 100, 100, 1.0, 10.0, 20.0)
a.display()
"""
c = dt2.material("C", density=2.1)
si = dt2.material("Si", density=2.329)
sio2 = dt2.material("SiO2", density=2.65)
dose = pc * lt # na-sec"
layers = [[c, tc * 1.0e-9], [sio2, tox * 1.0e-9], [si, 50.0e-6]]
xrts = []
trs = mc3.suggestTransitions(c, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(sio2, e0)
for tr in trs:
xrts.append(tr)
xtraParams = {}
xtraParams.update(mc3.configureXRayAccumulators(xrts, True, True, True))
sim = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams=xtraParams)
sName = "%g-nm-C-on-%g-nm-SiO2-on-Si-%g-kV-%g-Traj" % (tc, tox, e0, nTraj)
sim.rename(sName)
return sim
def zaf(comp, det, e0, nTraj=defaultNumTraj, stds={}):
"""zaf(comp, det, e0, nTraj = 1000, stds=None)
Example: mc3.zaf(material("Al2O3",1),d2,10.0,stds={ "Al":"Al", "O":"MgO" })
The Monte Carlo equivalent of dtsa2.zaf(comp,det,e0,stds) in the base DTSA-II scripting package. \
Tabulates the ZAF corrections as computed from Monte Carlo simulations of the generated and emitted x-ray \
intensities normalized relative to the specified standards (or if no standards are specified relative to \
pure elements)"""
def doMonte(cc):
monte = nm.MonteCarloSS()
monte.setBeamEnergy(epq.ToSI.keV(e0))
monte.addSubRegion(chamber, cc, nm.MultiPlaneShape.createSubstrate([0.0, 0.0, -1.0], origin))
# Add event listeners to model characteristic radiation
chXR = nm3.CharacteristicXRayGeneration3.create(monte)
chTr = nm3.XRayTransport3.create(monte, det, chXR)
xrel = nm3.XRayAccumulator3(xrts, "Characteristic")
chTr.addXRayListener(xrel)
fxg3 = nm3.FluorescenceXRayGeneration3.create(monte, chXR)
chSFTr = nm3.XRayTransport3.create(monte, det, fxg3)
chSF = nm3.XRayAccumulator3(xrts, "Secondary")
chSFTr.addXRayListener(chSF)
det.reset()
monte.runMultipleTrajectories(nTraj)
return (xrel, chSF)
comp = dtsa2.material(comp, 1.0)
print u"Material\t%s" % comp.descriptiveString(0)
print u"Detector\t%s" % det
print u"Algorithm\t%s" % "Monte Carlo (Gen3)"
print u"MAC\t%s" % epq.AlgorithmUser.getDefaultMAC().getName()
print u"E0\t%0.1f keV" % e0
print u"Take-off\t%g%s" % (jl.Math.toDegrees(epq.SpectrumUtils.getTakeOffAngle(det.getProperties())), epq.SpectrumProperties.TakeOffAngle.getUnits())
elms = comp.getElementSet()
allStds = {}
for elm, std in stds.iteritems():
allStds[dtsa2.element(elm)] = dtsa2.material(std, 1.0)
for elm in elms:
if not allStds.has_key(elm):
allStds[elm] = dtsa2.material(elm.toAbbrev(), 1.0)
origin = epq.SpectrumUtils.getSamplePosition(det.getProperties())
xrts = dtsa2.majorTransitions(comp, e0, thresh=0.8)
xrel, chSF = {}, {}
for elm in elms:
xrel[elm], chSF[elm] = doMonte(allStds[elm])
# Run unknown
xrelu, chSFu = doMonte(dtsa2.material(comp, 1.0))
print u"\nIUPAC\tSeigbahn\tStandard\tEnergy\t ZAF\t Z\t A\t F\tk-ratio"
for elm in elms:
xrels = xrel[elm]
chSFs = chSF[elm]
cu = comp.weightFraction(elm, False)
cs = allStds[elm].weightFraction(elm, False)
for xrt in xrts:
if xrt.getElement().equals(elm) and (xrels.getEmitted(xrt) > 0.0) and (xrelu.getEmitted(xrt) > 0.0):
try:
# print "%g\t%g\t%g\t%g" % (xrelu.getGenerated(xrt), xrelu.getEmitted(xrt),xrels.getGenerated(xrt), xrels.getEmitted(xrt) )
a = (xrelu.getEmitted(xrt) * xrels.getGenerated(xrt)) / (xrelu.getGenerated(xrt) * xrels.getEmitted(xrt))
z = (cs * xrelu.getGenerated(xrt)) / (cu * xrels.getGenerated(xrt))
f = (1.0 + chSFu.getEmitted(xrt) / xrelu.getEmitted(xrt)) / (1.0 + chSFs.getEmitted(xrt) / xrels.getEmitted(xrt))
k = (xrelu.getEmitted(xrt) / xrels.getEmitted(xrt)) * f
eTr = epq.FromSI.keV(xrt.getEnergy())
print u"%s\t%s\t%s\t%2.4f\t%1.4f\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % (xrt, xrt.getSiegbahnName(), allStds[elm], eTr, z * a * f, z, a, f, k)
except:
print u"%s - %s" % (elm, xrt)
def createGas(comp, pascal):
"""createGas(comp, pascal)
Create a gas from a composition at the specified pressure in Pascal at 300 K.
Ex: createGas("H2O", 0.1)"""
return epq.Gas(dtsa2.material(comp), pascal, 300.0)
def backscatterCoefficient(mat, e0=20.0): """backscatterCoefficient(mat, e0=20.0) Computes eta, the backscatter coefficient, for the specified material (element) and beam energy keV.""" return epq.BackscatterCoefficient.Heinrich81.compute(dtsa2.material(mat),epq.ToSI.keV(e0))
def backscatterFraction(mat, e0=20.0): """backscatterFraction(mat) Computes the backscatter fraction for an element or composition""" mat=dtsa2.material(mat) return epq.BackscatterCoefficient.Heinrich81.compute(mat,epq.ToSI.keV(e0))
def simCarbonCoatedStd(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0):
"""simCarbonCoatedStd(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0)
Use mc3 multilayer simulation to simulate a C-ctd standard specimen
Parameters
----------
mat - a dtsa material.
Note the material must have an associated density. It should have a useful name.
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated standard spectrum
Example
-------
import dtsa2.jmMC3 as jm3
det = findDetector("Oxford p4 05eV 2K")
mgo = material("MgO", density=3.58)
a = jm3.simCarbonCoatedStd(mgo, det, 20.0, 100, 100, 1.0, 20.0)
a.display()
"""
dose = pc * lt # na-sec"
c = dt2.material("C", density=2.1)
layers = [ [ c, tc*1.0e-9],
[mat, 50.0e-6]
]
xrts = []
trs = mc3.suggestTransitions(c, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(mat, e0)
for tr in trs:
xrts.append(tr)
xtraParams={}
xtraParams.update(mc3.configureXRayAccumulators(xrts,True, True, True))
sim = mc3.multiFilm(layers, det, e0, withPoisson=True, nTraj=nTraj,
dose=dose, sf=True, bf=True, xtraParams=xtraParams)
sName = "%g-nm-C-on-%s-%g-kV-%g-Traj" % (tc, mat, e0, nTraj)
sim.rename(sName)
sim.setAsStandard(mat)
return sim
def simCtdOxOnSi(det, e0, nTraj, lt=100, pc=1.0, tox = 10.0, tc=20.0):
"""
simCtdOxOnSi(det, e0, nTraj, lt=100, pc=1.0, tox = 10.0, tc=20.0)
Use mc3 multilayer simulation to simulate a C-ctd silicon specimen
with a native oxide layer.
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tox - float (10.0)
The thickness of the native oxide in nm
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated spectrum
Example
-------
import dtsa2.jmMC3 as jm3
det = findDetector("Oxford p4 05eV 2K")
a = jm3.simCtdOxOnSi(det, 3.0, 100, 100, 1.0, 10.0, 20.0)
a.display()
"""
c = dt2.material("C", density=2.1)
si = dt2.material("Si", density=2.329)
sio2 = dt2.material("SiO2", density=2.65)
dose = pc * lt # na-sec"
layers = [ [ c, tc*1.0e-9],
[sio2, tox*1.0e-9],
[si, 50.0e-6] ]
xrts = []
trs = mc3.suggestTransitions(c, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(sio2, e0)
for tr in trs:
xrts.append(tr)
xtraParams={}
xtraParams.update(mc3.configureXRayAccumulators(xrts,True, True, True))
sim = mc3.multiFilm(layers, det, e0, withPoisson=True, nTraj=nTraj,
dose=dose, sf=True, bf=True, xtraParams=xtraParams)
sName = "%g-nm-C-on-%g-nm-SiO2-on-Si-%g-kV-%g-Traj" % (tc, tox, e0, nTraj)
sim.rename(sName)
return sim