def anaMcNiCuKa(spc, det, stdBase, maxCh=1200):
props=spc.getProperties()
e0 = props.getNumericProperty(epq.SpectrumProperties.BeamEnergy)
lt = props.getNumericProperty(epq.SpectrumProperties.LiveTime)
pc = props.getNumericProperty(epq.SpectrumProperties.FaradayBegin)
wkDst = props.getNumericProperty(epq.SpectrumProperties.WorkingDistance)
spc = jmg.cropSpec(spc, end=maxCh)
unSpc = jmg.updateCommonSpecProps(spc, det, liveTime=lt, probeCur=pc, e0=e0, wrkDist=wkDst)
dt2.display(unSpc)
# define the transitions I want to measure
tsNiKa = epq.XRayTransitionSet(epq.Element.Ni, epq.XRayTransitionSet.K_FAMILY)
tsCuKa = epq.XRayTransitionSet(epq.Element.Cu, epq.XRayTransitionSet.K_FAMILY)
trs = [tsNiKa, tsCuKa]
relStd = "/%gkV/" % (e0)
stdDir = stdBase + relStd
niFile = stdDir + "Ni-sim.msa"
cuFile = stdDir + "Cu-sim.msa"
spc = dt2.wrap(ept.SpectrumFile.open(niFile)[0])
props=spc.getProperties()
e0 = props.getNumericProperty(epq.SpectrumProperties.BeamEnergy)
lt = props.getNumericProperty(epq.SpectrumProperties.LiveTime)
pc = props.getNumericProperty(epq.SpectrumProperties.FaradayBegin)
wkDst = props.getNumericWithDefault(epq.SpectrumProperties.WorkingDistance, wkDst)
spc = jmg.cropSpec(spc, end=maxCh)
niSpc = jmg.updateCommonSpecProps(spc, det, liveTime=lt, probeCur=pc, e0=e0, wrkDist=wkDst)
dt2.display(niSpc)
spc = dt2.wrap(ept.SpectrumFile.open(cuFile)[0])
props=spc.getProperties()
e0 = props.getNumericProperty(epq.SpectrumProperties.BeamEnergy)
lt = props.getNumericProperty(epq.SpectrumProperties.LiveTime)
pc = props.getNumericProperty(epq.SpectrumProperties.FaradayBegin)
wkDst = props.getNumericWithDefault(epq.SpectrumProperties.WorkingDistance, wkDst)
spc = jmg.cropSpec(spc, end=maxCh)
cuSpc = jmg.updateCommonSpecProps(spc, det, liveTime=lt, probeCur=pc, e0=e0, wrkDist=wkDst)
dt2.display(cuSpc)
niStd = {"El":dt2.element("Ni"), "Spc":niSpc}
cuStd = {"El":dt2.element("Cu"), "Spc":cuSpc}
stds = [niStd, cuStd]
theKR = jmg.compKRs(unSpc, stds, trs, det, e0)
krNiCalc = theKR[0]
krCuCalc = theKR[1]
return [krNiCalc, krCuCalc]
def quantify(rpl,
stds,
refs={},
preferred=(),
elmByDiff=None,
elmByStoic=None,
assumedStoic={},
mask=None,
step=1,
visualize=False,
zaf=None,
withUnc=False):
"""quantify(rpl,stds,[refs={}],[preferred=()],[elmByDiff=None],[elmByStoic=None],[assumedStoic={}], [mask=None],[zaf=None], [withUnc=False])
Quantify a ripple/raw spectrum object based on the standards, references and other parameters specified. /
The arguments are the same as dtsa2.multiQuant. An additional 'mask' argument allows uninteresting pixels /
to be ignored (not quantified.) The mask should be an object like a BufferedImage with a getRGB(x,y) method. /
The pixel is ignored if mask.getRGB(x,y)==0. The result is written to a RPL/RAW file in FLOAT format.
> import javax.imageio.ImageIO as io
> mask = io.read(jio.File("c:/image.png"))
> zaf = epq.CorrectionAlgorithm.NullCorrection for k-ratios"""
oldSt = None
try:
if (zaf != None) and isinstance(zaf, epq.CorrectionAlgorithm):
oldSt = epq.AlgorithmUser.getGlobalStrategy()
newSt = epq.AlgorithmUser.getGlobalStrategy()
newSt.addAlgorithm(epq.CorrectionAlgorithm, zaf)
epq.AlgorithmUser.applyGlobalOverride(newSt)
det = rpl.getProperties().getDetector()
e0 = rpl.getProperties().getNumericProperty(
epq.SpectrumProperties.BeamEnergy)
mq = dt2.multiQuant(det, e0, stds, refs, preferred, elmByDiff,
elmByStoic, assumedStoic)
base = rpl.getProperties().getTextProperty(
epq.SpectrumProperties.SourceFile)
compRpl = base.replace(".rpl", "_comp.rpl")
compRaw = base.replace(".rpl", "_comp.raw")
compTxt = base.replace(".rpl", "_comp.txt")
status = file(compTxt, "wt")
status.write("File:\t%s\n" % base)
status.write("Results:\t%s\n" % compRpl)
status.write("Detector:\t%s\n" % det)
status.write("Beam energy\t%g keV\n" % e0)
status.write("Standards\n")
i = 0
elms = [] # Ensures the plane order is correct
if det.getChannelCount() != rpl.getChannelCount():
print "ERROR: The number of channels in %s (%d) doesn't match the number of channels in the RPL file (%d)." % (
det, det.getChannelCount(), rpl.getChannelCount())
return
for elm, std in stds.iteritems():
if std.getChannelCount() != rpl.getChannelCount():
print "ERROR: The number of channels in %s (%d) doesn't match the number of channels in the RPL file (%d)." % (
std, std.getChannelCount(), rpl.getChannelCount())
return
status.write("\t%d\t%s\t%s\n" % (i, elm, std))
elms.append(dt2.element(elm))
i = i + 1
if len(refs) > 0:
status.write("References\n")
for xrt, ref in refs.iteritems():
if ref.getChannelCount() != rpl.getChannelCount():
print "ERROR: The number of channels in %s (%d) doesn't match the number of channels in the RPL file (%d)." % (
ref, ref.getChannelCount(), rpl.getChannelCount())
status.write("\t%s\t%s\n" % (xrt, ref))
if len(preferred) > 0:
status.write("Preferred transitions\n")
for xrt in preferred:
status.write("\t%s for %s\n" % (xrt, xrt.getElement()))
if elmByDiff:
status.write("Element by difference: %s\n" % elmByDiff)
if elmByStoic:
status.write("Element by Stoiciometry: %s\n" % elmByStoic)
status.write("Element\tValence\n")
for elm, stoic in assumedStoic.iteritems():
status.write("\t%s\t%g\n" % (elm, stoic))
comps = ept.RippleFile((rpl.getColumns() + step - 1) / step,
(rpl.getRows() + step - 1) / step,
len(stds) + 1, ept.RippleFile.FLOAT, 8,
ept.RippleFile.DONT_CARE_ENDIAN, compRpl,
compRaw)
uncert = None
if withUnc:
uncRaw = base.replace(".rpl", "_unc.raw")
uncRpl = base.replace(".rpl", "_unc.rpl")
uncert = ept.RippleFile((rpl.getColumns() + step - 1) / step,
(rpl.getRows() + step - 1) / step,
len(stds) + 1, ept.RippleFile.FLOAT, 8,
ept.RippleFile.DONT_CARE_ENDIAN, uncRpl,
uncRaw)
dumpIt = False
if dumpIt:
dumpRpl = base.replace(".rpl", "_dump.rpl")
dumpRaw = base.replace(".rpl", "_dump.raw")
dump = ept.RippleFile((rpl.getColumns() + step - 1) / step,
(rpl.getRows() + step - 1) / step,
rpl.getChannelCount(),
ept.RippleFile.UNSIGNED, 4,
ept.RippleFile.DONT_CARE_ENDIAN, dumpRpl,
dumpRaw)
rpl.setSpan(step, step)
for r in xrange(0, rpl.getRows(), step):
if dt2.isTerminated():
break
dt2.StdOut.append(".")
dt2.StdOut.flush()
for c in xrange(0, rpl.getColumns(), step):
if dt2.isTerminated():
break
if visualize:
dt2.clearSpectra()
dt2.display(rpl)
comps.setPosition(c / step, r / step)
if (mask == None) or ((mask.getRGB(c, r) & 0xFFFFFF) > 0):
try:
rpl.setPosition(c, r)
rs = epq.SpectrumUtils.copy(rpl)
if dumpIt:
# print "%d\t%d\t%d\t%d" % (c, r, c / step, r / step)
dump.setPosition(c / step, r / step)
dump.write(epq.SpectrumUtils.toIntArray(rs))
res = mq.compute(rs)
comp = res.getComposition()
if visualize:
rpl.getProperties().setCompositionProperty(
epq.SpectrumProperties.
MicroanalyticalComposition, comp)
dt2.annotComposition()
tmp, unc = [], []
sU = 0.0
for elm in elms:
tmp.append(comp.weightFraction(elm, True))
u = comp.weightFractionU(elm, True).uncertainty()
unc.append(u)
sU = sU + u * u
tmp.append(comp.sumWeightFraction())
unc.append(jl.Math.sqrt(sU))
if dumpIt:
print tmp
comps.write(tmp)
if uncert:
uncert.write(unc)
except (epq.EPQException, Exception, jl.Exception), e:
msg = "row = %d, col = %d failed: %s" % (r, c, e)
print msg
status.write(msg + "\n")
for elm, std in stds.iteritems():
comps.write(0.0)
if uncert:
uncert.write(unc)
if visualize:
dt2.setAnnotation("row = %d, col = %d failed." %
(r, c))
else:
for elm, std in stds.iteritems():
comps.write(0.0)
if uncert:
uncert.write(unc)
comps.write(1.0)
if uncert:
uncert.write(1.0)
comps.close()
if uncert:
uncert.close()
if dumpIt:
dump.close()
status.close()
def simLineInMatrix(lin,
linMat,
blk,
blkMat,
nmLinWid,
umBlock,
nPts,
trs,
outDir,
hdr,
det,
e0,
lt,
pc,
withPoisson=True,
nTraj=100,
sf=True,
bf=True,
iDigits=5,
bVerbose=False,
xtraParams={}):
"""simLineInMatrix(lin, linMat, blk, blkMat, nmLinWid, umBlock, nPts,
trs, outDir, hdr, det, e0, lt, pc, withPoisson=True, nTraj=nTraj,
sf=True, bf=True, iDigits=5, bVerbose=False, xtraParams={})
Simulate a line of width `nmLinWid' nm at the center of a block of
`umBlock' microns. The line is of material `lin' with a name `linMat'.
The block is of material `blk' with a name `blkMat'.
We analyze an list `trs' of transitions, writing the K-ratios to a
.csv file with a header `hdr'. We use the detector `det', voltage `e0'
(kV) and live time `lt' sec and probe current `pc' nA. This will
compute the standard spectra, compute the spectra for nPts+1 from
-nPts/2 ... 0 ...nPts/2 times the block size. It will then compute the
K-ratios for each spectrum and write them to a file `name' in outDir
with a header `hdr' that matches the transition order.
"""
# order is order of trs..
sc = 1.0e-6 # scale from microns to meters for positions
lX = [] # an array for postions
lKlin = [] # an array for the K-ratio of the line
lKblk = [
] # an array for the K-ratio of the block. Title correspond to hdr string
# start clean
dt2.DataManager.clearSpectrumList()
# create the standards
linStd = simulateBulkStandard(lin,
linMat,
det,
e0,
lt,
pc,
withPoisson=True,
nTraj=nTraj,
sf=True,
bf=True,
xtraParams={})
dt2.display(linStd)
blkStd = simulateBulkStandard(blk,
blkMat,
det,
e0,
lt,
pc,
withPoisson=True,
nTraj=nTraj,
sf=True,
bf=True,
xtraParams={})
dt2.display(blkStd)
lStd = {"El": dt2.element(linMat), "Spc": linStd}
bStd = {"El": dt2.element(blkMat), "Spc": blkStd}
stds = [lStd, bStd] # note: put the transitions in this order
iCount = 0
for x in range(-nPts / 2, (nPts / 2) + 1, 1):
xv = sc * x * umBlock / nPts
lX.append(round(x * umBlock / nPts, iDigits))
monte = nm.MonteCarloSS()
monte.setBeamEnergy(epq.ToSI.keV(e0))
# use a 1 nm probe
beam = nm.GaussianBeam(1.0e-9)
monte.setElectronGun(beam)
beam.setCenter([xv, 0.0, -0.05])
# createBlock(double[] dims, double[] point, double phi, double theta, double psi)
# createBlock - Create a block of:
# dimensions specified in dims,
# centered at point,
# then rotated by the euler angles phi, theta, psi.
block = nm.MultiPlaneShape.createBlock(
[umBlock * 1.0e-6, umBlock * 1.0e-6, umBlock * 1.0e-6],
[0.0, 0.0, 0.5 * umBlock * 1.0e-6], 0.0, 0.0, 0.0)
matrix = monte.addSubRegion(monte.getChamber(), blk, block)
monte.addSubRegion(
matrix, lin,
nm.MultiPlaneShape.createBlock(
[1.0e-9 * nmLinWid, umBlock * 1.0e-6, umBlock * 1.0e-6],
[0.0, 0.0, 0.5 * umBlock * 1.0e-6], 0.0, 0.0, 0.0))
det.reset()
# Add event listeners to model characteristic radiation
chXR = nm3.CharacteristicXRayGeneration3.create(monte)
xrel = nm3.XRayTransport3.create(monte, det, chXR)
brXR = nm3.BremsstrahlungXRayGeneration3.create(monte)
brem = nm3.XRayTransport3.create(monte, det, brXR)
fxg3 = nm3.FluorescenceXRayGeneration3.create(monte, chXR)
chSF = nm3.XRayTransport3.create(monte, det, fxg3)
brSF = nm3.XRayTransport3.create(
monte, det, nm3.FluorescenceXRayGeneration3.create(monte, brXR))
# here is where we run the simulation
monte.runMultipleTrajectories(nTraj)
spec = det.getSpectrum((lt * pc * 1.0e-9) /
(nTraj * epq.PhysicalConstants.ElectronCharge))
props = spec.getProperties()
props.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
props.setNumericProperty(epq.SpectrumProperties.FaradayBegin, pc)
props.setNumericProperty(epq.SpectrumProperties.FaradayEnd, pc)
props.setNumericProperty(epq.SpectrumProperties.BeamEnergy, e0)
spcName = "x = %.3f um" % x
epq.SpectrumUtils.rename(spec, spcName)
spec = epq.SpectrumUtils.addNoiseToSpectrum(spec, 1.0)
# display(spec)
a = jmg.compKRs(spec, stds, trs, det, e0)
iCount += 1
print(iCount)
lKlin.append(round(a[0], iDigits))
lKblk.append(round(a[1], iDigits))
basFile = "%gnm-%s-in-%gum-%s-%gkV-%g-Traj.csv" % (
nmLinWid, linMat, umBlock, blkMat, e0, nTraj)
strOutFile = outDir + "/" + basFile
f = open(strOutFile, 'w')
strLine = hdr + '\n'
f.write(strLine)
for i in range(iCount):
strLine = "%.5f" % lX[i] + ","
strLine = strLine + "%.5f" % lKlin[i] + ","
strLine = strLine + "%.5f" % lKblk[i] + "\n"
f.write(strLine)
f.close()
def simLineInMatrixLimScan(lin,
linMat,
blk,
blkMat,
nmLinWid,
umBlock,
nmScan,
nPts,
trs,
outDir,
hdr,
det,
e0,
lt,
pc,
withPoisson=True,
nTraj=100,
sf=True,
bf=True,
iDigits=5,
bVerbose=False,
xtraParams={}):
"""simLineInMatrixLimScan(lin, linMat, blk, blkMat, nmLinWid, umBlock,
nmScan, nPts, trs, outDir, hdr, det, e0, lt, pc, withPoisson=True,
nTraj=nTraj, sf=True, bf=True, iDigits=5, bVerbose=False,
xtraParams={})
Simulate a line of width `nmLinWid' nm at the center of a block of
`umBlock' microns. The line is of material `lin' with a name `linMat'.
The block is of material `blk' with a name `blkMat'. We step a total
distance of nmScan across the center of the line.
We analyze an list `trs' of transitions, writing the K-ratios to a
.csv file with a header `hdr'. We use the detector `det', voltage `e0'
(kV) and live time `lt' sec and probe current `pc' nA. This will
compute the standard spectra, compute the spectra the scanned
region. It will then compute the K-ratios for each spectrum and write
them to a file `name' in outDir with a header `hdr' that matches the
transition order.
"""
# order is order of trs..
sc = 1.0e-6 # scale from microns to meters for positions
dose = lt * pc
lX = [] # an array for postions
lKlin = [] # an array for the K-ratio of the line
lKblk = [
] # an array for the K-ratio of the block. Title correspond to hdr string
umLine = nmLinWid * 1.0e-3
# start clean
dt2.DataManager.clearSpectrumList()
# create the standards
linStd = simulateBulkStandard(lin,
linMat,
det,
e0,
lt,
pc,
withPoisson=withPoisson,
nTraj=nTraj,
sf=sf,
bf=bf,
xtraParams={})
dt2.display(linStd)
blkStd = simulateBulkStandard(blk,
blkMat,
det,
e0,
lt,
pc,
withPoisson=withPoisson,
nTraj=nTraj,
sf=sf,
bf=sf,
xtraParams={})
dt2.display(blkStd)
lStd = {"El": dt2.element(linMat), "Spc": linStd}
bStd = {"El": dt2.element(blkMat), "Spc": blkStd}
stds = [lStd, bStd] # note: put the transitions in this order
iCount = 0
for x in range(-nPts / 2, (nPts / 2) + 1, 1):
xPosNm = x * nmScan / nPts
lX.append(round(xPosNm, iDigits))
xtraParams = {}
xtraParams.update(
mc3.configureXRayAccumulators(trs,
charAccum=sf,
charFluorAccum=sf,
bremFluorAccum=bf))
xtraParams.update(mc3.configureOutput(outDir))
xtraParams.update(mc3.configureBeam(xPosNm * 1.0e-09, 0, -0.099, 1.0))
spec = mc3.embeddedRectangle(lin,
[umLine * sc, umBlock * sc, umBlock * sc],
blk,
0,
det,
e0,
withPoisson=withPoisson,
nTraj=nTraj,
dose=dose,
sf=sf,
bf=bf,
xtraParams=xtraParams)
props = spec.getProperties()
props.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
props.setNumericProperty(epq.SpectrumProperties.FaradayBegin, pc)
props.setNumericProperty(epq.SpectrumProperties.FaradayEnd, pc)
props.setNumericProperty(epq.SpectrumProperties.BeamEnergy, e0)
spcName = "x = %.3f um" % x
epq.SpectrumUtils.rename(spec, spcName)
spec = epq.SpectrumUtils.addNoiseToSpectrum(spec, 1.0)
# display(spec)
a = jmg.compKRs(spec, stds, trs, det, e0)
iCount += 1
print(iCount, xPosNm)
lKlin.append(round(a[0], iDigits))
lKblk.append(round(a[1], iDigits))
basFile = "%gnm-%s-in-%gum-%s-%gkV-%g-Traj.csv" % (
nmLinWid, linMat, umBlock, blkMat, e0, nTraj)
strOutFile = outDir + "/" + basFile
f = open(strOutFile, 'w')
strLine = hdr + '\n'
f.write(strLine)
for i in range(iCount):
strLine = "%.3f" % lX[i] + ","
strLine = strLine + "%.5f" % lKlin[i] + ","
strLine = strLine + "%.5f" % lKblk[i] + "\n"
f.write(strLine)
f.close()
pyrDir = datDir + "/testRplProcCuAl Results"
rplFil = datDir + "/CuAl.rpl"
e0 = 20.0
pc = 1.0
lt = 30.0
det = findDetector("Oxford p4 05eV 2K")
# Let's start clean...
DataManager.clearSpectrumList()
rs = ht.openRipple(rplFil, e0, pc, lt, det)
rs.setPosition(32, 32) # go to a position
dt2.display(rs)
ary = wrap(rs).toDouble()
print("Print the min and max")
print(min(ary))
print(max(ary))
dir(rs)
print(dir(rs))
print("Computing maximum pixel spectrum")
mps = wrap(ht.maxPixel(rs))
mps.rename("CuAl max px")
dt2.display(mps)
def quantify(rpl, stds, refs={}, preferred=(), elmByDiff=None, elmByStoic=None, assumedStoic={}, mask=None, step=1, visualize=False, zaf=None, withUnc=False):
"""quantify(rpl,stds,[refs={}],[preferred=()],[elmByDiff=None],[elmByStoic=None],[assumedStoic={}], [mask=None],[zaf=None], [withUnc=False])
Quantify a ripple/raw spectrum object based on the standards, references and other parameters specified. /
The arguments are the same as dtsa2.multiQuant. An additional 'mask' argument allows uninteresting pixels /
to be ignored (not quantified.) The mask should be an object like a BufferedImage with a getRGB(x,y) method. /
The pixel is ignored if mask.getRGB(x,y)==0. The result is written to a RPL/RAW file in FLOAT format.
> import javax.imageio.ImageIO as io
> mask = io.read(jio.File("c:/image.png"))
> zaf = epq.CorrectionAlgorithm.NullCorrection for k-ratios"""
oldSt = None
try:
if (zaf != None) and isinstance(zaf, epq.CorrectionAlgorithm):
oldSt = epq.AlgorithmUser.getGlobalStrategy()
newSt = epq.AlgorithmUser.getGlobalStrategy()
newSt.addAlgorithm(epq.CorrectionAlgorithm, zaf)
epq.AlgorithmUser.applyGlobalOverride(newSt)
det = rpl.getProperties().getDetector()
e0 = rpl.getProperties().getNumericProperty(epq.SpectrumProperties.BeamEnergy)
mq = dt2.multiQuant(det, e0, stds, refs, preferred, elmByDiff, elmByStoic, assumedStoic)
base = rpl.getProperties().getTextProperty(epq.SpectrumProperties.SourceFile)
compRpl = base.replace(".rpl", "_comp.rpl")
compRaw = base.replace(".rpl", "_comp.raw")
compTxt = base.replace(".rpl", "_comp.txt")
status = file(compTxt, "wt")
status.write("File:\t%s\n" % base)
status.write("Results:\t%s\n" % compRpl)
status.write("Detector:\t%s\n" % det)
status.write("Beam energy\t%g keV\n" % e0)
status.write("Standards\n")
i = 0;
elms = [] # Ensures the plane order is correct
if det.getChannelCount() != rpl.getChannelCount():
print "ERROR: The number of channels in %s (%d) doesn't match the number of channels in the RPL file (%d)." % (det, det.getChannelCount(), rpl.getChannelCount())
return
for elm, std in stds.iteritems():
if std.getChannelCount() != rpl.getChannelCount():
print "ERROR: The number of channels in %s (%d) doesn't match the number of channels in the RPL file (%d)." % (std, std.getChannelCount(), rpl.getChannelCount())
return
status.write("\t%d\t%s\t%s\n" % (i, elm, std))
elms.append(dt2.element(elm))
i = i + 1
if len(refs) > 0:
status.write("References\n")
for xrt, ref in refs.iteritems():
if ref.getChannelCount() != rpl.getChannelCount():
print "ERROR: The number of channels in %s (%d) doesn't match the number of channels in the RPL file (%d)." % (ref, ref.getChannelCount(), rpl.getChannelCount())
status.write("\t%s\t%s\n" % (xrt, ref))
if len(preferred) > 0:
status.write("Preferred transitions\n")
for xrt in preferred:
status.write("\t%s for %s\n" % (xrt, xrt.getElement()))
if elmByDiff:
status.write("Element by difference: %s\n" % elmByDiff)
if elmByStoic:
status.write("Element by Stoiciometry: %s\n" % elmByStoic)
status.write("Element\tValence\n")
for elm, stoic in assumedStoic.iteritems():
status.write("\t%s\t%g\n" % (elm, stoic))
comps = ept.RippleFile((rpl.getColumns() + step - 1) / step, (rpl.getRows() + step - 1) / step, len(stds) + 1, ept.RippleFile.FLOAT, 8, ept.RippleFile.DONT_CARE_ENDIAN, compRpl, compRaw)
uncert = None
if withUnc:
uncRaw = base.replace(".rpl", "_unc.raw")
uncRpl = base.replace(".rpl", "_unc.rpl")
uncert = ept.RippleFile((rpl.getColumns() + step - 1) / step, (rpl.getRows() + step - 1) / step, len(stds) + 1, ept.RippleFile.FLOAT, 8, ept.RippleFile.DONT_CARE_ENDIAN, uncRpl, uncRaw)
dumpIt = False
if dumpIt:
dumpRpl = base.replace(".rpl", "_dump.rpl")
dumpRaw = base.replace(".rpl", "_dump.raw")
dump = ept.RippleFile((rpl.getColumns() + step - 1) / step, (rpl.getRows() + step - 1) / step, rpl.getChannelCount(), ept.RippleFile.UNSIGNED, 4, ept.RippleFile.DONT_CARE_ENDIAN, dumpRpl, dumpRaw)
rpl.setSpan(step, step)
for r in xrange(0, rpl.getRows(), step):
if dt2.isTerminated():
break
dt2.StdOut.append(".")
dt2.StdOut.flush()
for c in xrange(0, rpl.getColumns(), step):
if dt2.isTerminated():
break
if visualize:
dt2.clearSpectra()
dt2.display(rpl)
comps.setPosition(c / step, r / step)
if (mask == None) or ((mask.getRGB(c, r) & 0xFFFFFF) > 0):
try:
rpl.setPosition(c, r)
rs = epq.SpectrumUtils.copy(rpl)
if dumpIt:
# print "%d\t%d\t%d\t%d" % (c, r, c / step, r / step)
dump.setPosition(c / step, r / step)
dump.write(epq.SpectrumUtils.toIntArray(rs))
res = mq.compute(rs)
comp = res.getComposition()
if visualize:
rpl.getProperties().setCompositionProperty(epq.SpectrumProperties.MicroanalyticalComposition, comp)
dt2.annotComposition()
tmp, unc = [], []
sU = 0.0
for elm in elms:
tmp.append(comp.weightFraction(elm, True))
u = comp.weightFractionU(elm, True).uncertainty()
unc.append(u)
sU = sU + u*u
tmp.append(comp.sumWeightFraction())
unc.append(jl.Math.sqrt(sU))
if dumpIt:
print tmp
comps.write(tmp)
if uncert:
uncert.write(unc)
except (epq.EPQException, Exception, jl.Exception), e:
msg = "row = %d, col = %d failed: %s" % (r, c, e)
print msg
status.write(msg + "\n")
for elm, std in stds.iteritems():
comps.write(0.0)
if uncert:
uncert.write(unc)
if visualize:
dt2.setAnnotation("row = %d, col = %d failed." % (r, c))
else:
for elm, std in stds.iteritems():
comps.write(0.0)
if uncert:
uncert.write(unc)
comps.write(1.0)
if uncert:
uncert.write(1.0)
comps.close()
if uncert:
uncert.close()
if dumpIt:
dump.close()
status.close()
pc = 1.0
lt = 30.0
det = findDetector("Oxford-Paint")
if (det.toString()[0:4] != 'Oxfo'):
print(
"You need to add the Oxford-Paint detector. It is using the default..."
)
# Let's start clean...
DataManager.clearSpectrumList()
rs = ht.openRipple(rplFil, e0, pc, lt, det)
rs.setPosition(111, 35) # go to a position
dt2.display(rs)
ary = wrap(rs).toDouble()
print("Print the min and max")
print(min(ary))
print(max(ary))
dir(rs)
print(dir(rs))
print("Computing maximum pixel spectrum")
mps = wrap(ht.maxPixel(rs))
mps.rename("Paint maximum px")
dt2.display(mps)
# clean up cruft
def simLineInMatrixLimScan(lin, linMat, blk, blkMat, nmLinWid, umBlock,nmScan, nPts, trs, outDir, hdr, det, e0, lt, pc, withPoisson=True, nTraj=100, sf=True, bf=True, iDigits=5, bVerbose=False, xtraParams={}):
"""simLineInMatrixLimScan(lin, linMat, blk, blkMat, nmLinWid, umBlock,
nmScan, nPts, trs, outDir, hdr, det, e0, lt, pc, withPoisson=True,
nTraj=nTraj, sf=True, bf=True, iDigits=5, bVerbose=False,
xtraParams={})
Simulate a line of width `nmLinWid' nm at the center of a block of
`umBlock' microns. The line is of material `lin' with a name `linMat'.
The block is of material `blk' with a name `blkMat'. We step a total
distance of nmScan across the center of the line.
We analyze an list `trs' of transitions, writing the K-ratios to a
.csv file with a header `hdr'. We use the detector `det', voltage `e0'
(kV) and live time `lt' sec and probe current `pc' nA. This will
compute the standard spectra, compute the spectra the scanned
region. It will then compute the K-ratios for each spectrum and write
them to a file `name' in outDir with a header `hdr' that matches the
transition order.
"""
# order is order of trs..
sc = 1.0e-6 # scale from microns to meters for positions
dose = lt*pc
lX = [] # an array for postions
lKlin = [] # an array for the K-ratio of the line
lKblk = [] # an array for the K-ratio of the block. Title correspond to hdr string
umLine = nmLinWid * 1.0e-3
# start clean
dt2.DataManager.clearSpectrumList()
# create the standards
linStd = simulateBulkStandard(lin, linMat, det, e0, lt, pc, withPoisson=withPoisson, nTraj=nTraj, sf=sf, bf=bf, xtraParams={})
dt2.display(linStd)
blkStd = simulateBulkStandard(blk, blkMat, det, e0, lt, pc, withPoisson=withPoisson, nTraj=nTraj, sf=sf, bf=sf, xtraParams={})
dt2.display(blkStd)
lStd = {"El":dt2.element(linMat), "Spc":linStd}
bStd = {"El":dt2.element(blkMat), "Spc":blkStd}
stds = [lStd, bStd] # note: put the transitions in this order
iCount = 0
for x in range(-nPts/2, (nPts/2)+1, 1):
xPosNm = x * nmScan / nPts
lX.append(round(xPosNm, iDigits))
xtraParams={}
xtraParams.update(mc3.configureXRayAccumulators(trs, charAccum=sf, charFluorAccum=sf, bremFluorAccum=bf))
xtraParams.update(mc3.configureOutput(outDir))
xtraParams.update(mc3.configureBeam(xPosNm*1.0e-09, 0, -0.099, 1.0))
spec = mc3.embeddedRectangle(lin, [umLine*sc, umBlock*sc, umBlock*sc], blk, 0, det, e0, withPoisson=withPoisson, nTraj=nTraj, dose=dose, sf=sf, bf=bf, xtraParams=xtraParams)
props = spec.getProperties()
props.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
props.setNumericProperty(epq.SpectrumProperties.FaradayBegin, pc)
props.setNumericProperty(epq.SpectrumProperties.FaradayEnd, pc)
props.setNumericProperty(epq.SpectrumProperties.BeamEnergy, e0)
spcName = "x = %.3f um" % x
epq.SpectrumUtils.rename(spec, spcName)
spec = epq.SpectrumUtils.addNoiseToSpectrum(spec, 1.0)
# display(spec)
a = jmg.compKRs(spec, stds, trs, det, e0)
iCount += 1
print(iCount, xPosNm)
lKlin.append(round(a[0], iDigits))
lKblk.append(round(a[1], iDigits))
basFile ="%gnm-%s-in-%gum-%s-%gkV-%g-Traj.csv" % (nmLinWid, linMat, umBlock, blkMat, e0, nTraj)
strOutFile = outDir + "/" + basFile
f=open(strOutFile, 'w')
strLine = hdr + '\n'
f.write(strLine)
for i in range(iCount):
strLine = "%.3f" % lX[i] + ","
strLine = strLine + "%.5f" % lKlin[i] + ","
strLine = strLine + "%.5f" % lKblk[i] + "\n"
f.write(strLine)
f.close()
def simLineInMatrix(lin, linMat, blk, blkMat, nmLinWid, umBlock, nPts, trs, outDir, hdr, det, e0, lt, pc, withPoisson=True, nTraj=100, sf=True, bf=True, iDigits=5, bVerbose=False, xtraParams={}):
"""simLineInMatrix(lin, linMat, blk, blkMat, nmLinWid, umBlock, nPts,
trs, outDir, hdr, det, e0, lt, pc, withPoisson=True, nTraj=nTraj,
sf=True, bf=True, iDigits=5, bVerbose=False, xtraParams={})
Simulate a line of width `nmLinWid' nm at the center of a block of
`umBlock' microns. The line is of material `lin' with a name `linMat'.
The block is of material `blk' with a name `blkMat'.
We analyze an list `trs' of transitions, writing the K-ratios to a
.csv file with a header `hdr'. We use the detector `det', voltage `e0'
(kV) and live time `lt' sec and probe current `pc' nA. This will
compute the standard spectra, compute the spectra for nPts+1 from
-nPts/2 ... 0 ...nPts/2 times the block size. It will then compute the
K-ratios for each spectrum and write them to a file `name' in outDir
with a header `hdr' that matches the transition order.
"""
# order is order of trs..
sc = 1.0e-6 # scale from microns to meters for positions
lX = [] # an array for postions
lKlin = [] # an array for the K-ratio of the line
lKblk = [] # an array for the K-ratio of the block. Title correspond to hdr string
# start clean
dt2.DataManager.clearSpectrumList()
# create the standards
linStd = simulateBulkStandard(lin, linMat, det, e0, lt, pc, withPoisson=True, nTraj=nTraj, sf=True, bf=True, xtraParams={})
dt2.display(linStd)
blkStd = simulateBulkStandard(blk, blkMat, det, e0, lt, pc, withPoisson=True, nTraj=nTraj, sf=True, bf=True, xtraParams={})
dt2.display(blkStd)
lStd = {"El":dt2.element(linMat), "Spc":linStd}
bStd = {"El":dt2.element(blkMat), "Spc":blkStd}
stds = [lStd, bStd] # note: put the transitions in this order
iCount = 0
for x in range(-nPts/2, (nPts/2)+1, 1):
xv = sc*x*umBlock/nPts
lX.append(round(x*umBlock/nPts, iDigits))
monte=nm.MonteCarloSS()
monte.setBeamEnergy(epq.ToSI.keV(e0))
# use a 1 nm probe
beam=nm.GaussianBeam(1.0e-9)
monte.setElectronGun(beam)
beam.setCenter([xv, 0.0,-0.05])
# createBlock(double[] dims, double[] point, double phi, double theta, double psi)
# createBlock - Create a block of:
# dimensions specified in dims,
# centered at point,
# then rotated by the euler angles phi, theta, psi.
block = nm.MultiPlaneShape.createBlock([umBlock*1.0e-6, umBlock*1.0e-6, umBlock*1.0e-6],[0.0,0.0, 0.5*umBlock*1.0e-6],0.0,0.0,0.0)
matrix = monte.addSubRegion(monte.getChamber(), blk, block)
monte.addSubRegion(matrix, lin, nm.MultiPlaneShape.createBlock([1.0e-9*nmLinWid, umBlock*1.0e-6, umBlock*1.0e-6],[0.0, 0.0, 0.5*umBlock*1.0e-6],0.0,0.0,0.0))
det.reset()
# Add event listeners to model characteristic radiation
chXR = nm3.CharacteristicXRayGeneration3.create(monte)
xrel = nm3.XRayTransport3.create(monte, det, chXR)
brXR = nm3.BremsstrahlungXRayGeneration3.create(monte)
brem = nm3.XRayTransport3.create(monte, det, brXR)
fxg3 = nm3.FluorescenceXRayGeneration3.create(monte, chXR)
chSF = nm3.XRayTransport3.create(monte, det, fxg3)
brSF = nm3.XRayTransport3.create(monte, det, nm3.FluorescenceXRayGeneration3.create(monte, brXR))
# here is where we run the simulation
monte.runMultipleTrajectories(nTraj)
spec = det.getSpectrum((lt*pc*1.0e-9) / (nTraj * epq.PhysicalConstants.ElectronCharge))
props = spec.getProperties()
props.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
props.setNumericProperty(epq.SpectrumProperties.FaradayBegin, pc)
props.setNumericProperty(epq.SpectrumProperties.FaradayEnd, pc)
props.setNumericProperty(epq.SpectrumProperties.BeamEnergy, e0)
spcName = "x = %.3f um" % x
epq.SpectrumUtils.rename(spec, spcName)
spec = epq.SpectrumUtils.addNoiseToSpectrum(spec, 1.0)
# display(spec)
a = jmg.compKRs(spec, stds, trs, det, e0)
iCount += 1
print(iCount)
lKlin.append(round(a[0], iDigits))
lKblk.append(round(a[1], iDigits))
basFile ="%gnm-%s-in-%gum-%s-%gkV-%g-Traj.csv" % (nmLinWid, linMat, umBlock, blkMat, e0, nTraj)
strOutFile = outDir + "/" + basFile
f=open(strOutFile, 'w')
strLine = hdr + '\n'
f.write(strLine)
for i in range(iCount):
strLine = "%.5f" % lX[i] + ","
strLine = strLine + "%.5f" % lKlin[i] + ","
strLine = strLine + "%.5f" % lKblk[i] + "\n"
f.write(strLine)
f.close()
