def ImageCalibrate(self, data):
'Needs a doc string'
import copy
import ImageCalibrants as calFile
print 'Image calibration:'
time0 = time.time()
ring = data['ring']
pixelSize = data['pixelSize']
scalex = 1000. / pixelSize[0]
scaley = 1000. / pixelSize[1]
pixLimit = data['pixLimit']
cutoff = data['cutoff']
varyDict = data['varyList']
if varyDict['dist'] and varyDict['wave']:
print 'ERROR - you can not simultaneously calibrate distance and wavelength'
return False
if len(ring) < 5:
print 'ERROR - not enough inner ring points for ellipse'
return False
#fit start points on inner ring
data['ellipses'] = []
data['rings'] = []
outE = FitEllipse(ring)
fmt = '%s X: %.3f, Y: %.3f, phi: %.3f, R1: %.3f, R2: %.3f'
fmt2 = '%s X: %.3f, Y: %.3f, phi: %.3f, R1: %.3f, R2: %.3f, chi**2: %.3f, Np: %d'
if outE:
print fmt % ('start ellipse: ', outE[0][0], outE[0][1], outE[1],
outE[2][0], outE[2][1])
ellipse = outE
else:
return False
#setup 360 points on that ring for "good" fit
data['ellipses'].append(ellipse[:] + ('g', ))
Ring = makeRing(1.0, ellipse, pixLimit, cutoff, scalex, scaley,
self.ImageZ)
if Ring:
ellipse = FitEllipse(Ring)
Ring = makeRing(1.0, ellipse, pixLimit, cutoff, scalex, scaley,
self.ImageZ) #do again
ellipse = FitEllipse(Ring)
else:
print '1st ring not sufficiently complete to proceed'
return False
if debug:
print fmt2 % ('inner ring: ', ellipse[0][0], ellipse[0][1],
ellipse[1], ellipse[2][0], ellipse[2][1], 0., len(Ring)
) #cent,phi,radii
data['ellipses'].append(ellipse[:] + ('r', ))
data['rings'].append(np.array(Ring))
G2plt.PlotImage(self, newImage=True)
#setup for calibration
data['rings'] = []
if not data['calibrant']:
print 'no calibration material selected'
return True
skip = data['calibskip']
dmin = data['calibdmin']
#generate reflection set
Bravais, SGs, Cells = calFile.Calibrants[data['calibrant']][:3]
HKL = []
for bravais, sg, cell in zip(Bravais, SGs, Cells):
A = G2lat.cell2A(cell)
if sg:
SGData = G2spc.SpcGroup(sg)[1]
hkl = G2pwd.getHKLpeak(dmin, SGData, A)
HKL += hkl
else:
hkl = G2lat.GenHBravais(dmin, bravais, A)
HKL += hkl
HKL = G2lat.sortHKLd(HKL, True, False)[skip:]
#set up 1st ring
elcent, phi, radii = ellipse #from fit of 1st ring
dsp = HKL[0][3]
print '1st ring: try %.4f' % (dsp)
if varyDict['dist']:
wave = data['wavelength']
tth = 2.0 * asind(wave / (2. * dsp))
else: #varyDict['wave']!
dist = data['distance']
tth = npatan2d(radii[0], dist)
data['wavelength'] = wave = 2.0 * dsp * sind(tth / 2.0)
Ring0 = makeRing(dsp, ellipse, 3, cutoff, scalex, scaley, self.ImageZ)
ttth = nptand(tth)
stth = npsind(tth)
ctth = npcosd(tth)
#1st estimate of tilt; assume ellipse - don't know sign though
if varyDict['tilt']:
tilt = npasind(np.sqrt(max(0., 1. - (radii[0] / radii[1])**2)) * ctth)
if not tilt:
print 'WARNING - selected ring was fitted as a circle'
print ' - if detector was tilted we suggest you skip this ring - WARNING'
else:
tilt = data['tilt']
#1st estimate of dist: sample to detector normal to plane
if varyDict['dist']:
data['distance'] = dist = radii[0]**2 / (ttth * radii[1])
else:
dist = data['distance']
if varyDict['tilt']:
#ellipse to cone axis (x-ray beam); 2 choices depending on sign of tilt
zdisp = radii[1] * ttth * tand(tilt)
zdism = radii[1] * ttth * tand(-tilt)
#cone axis position; 2 choices. Which is right?
#NB: zdisp is || to major axis & phi is rotation of minor axis
#thus shift from beam to ellipse center is [Z*sin(phi),-Z*cos(phi)]
centp = [elcent[0] + zdisp * sind(phi), elcent[1] - zdisp * cosd(phi)]
centm = [elcent[0] + zdism * sind(phi), elcent[1] - zdism * cosd(phi)]
#check get same ellipse parms either way
#now do next ring; estimate either way & do a FitDetector each way; best fit is correct one
fail = True
i2 = 1
while fail:
dsp = HKL[i2][3]
print '2nd ring: try %.4f' % (dsp)
tth = 2.0 * asind(wave / (2. * dsp))
ellipsep = GetEllipse2(tth, 0., dist, centp, tilt, phi)
print fmt % ('plus ellipse :', ellipsep[0][0], ellipsep[0][1],
ellipsep[1], ellipsep[2][0], ellipsep[2][1])
Ringp = makeRing(dsp, ellipsep, 3, cutoff, scalex, scaley,
self.ImageZ)
parmDict = {
'dist': dist,
'det-X': centp[0],
'det-Y': centp[1],
'tilt': tilt,
'phi': phi,
'wave': wave,
'dep': 0.0
}
varyList = [item for item in varyDict if varyDict[item]]
if len(Ringp) > 10:
chip = FitDetector(np.array(Ring0 + Ringp), varyList, parmDict,
True)
tiltp = parmDict['tilt']
phip = parmDict['phi']
centp = [parmDict['det-X'], parmDict['det-Y']]
fail = False
else:
chip = 1e6
ellipsem = GetEllipse2(tth, 0., dist, centm, -tilt, phi)
print fmt % ('minus ellipse:', ellipsem[0][0], ellipsem[0][1],
ellipsem[1], ellipsem[2][0], ellipsem[2][1])
Ringm = makeRing(dsp, ellipsem, 3, cutoff, scalex, scaley,
self.ImageZ)
if len(Ringm) > 10:
parmDict['tilt'] *= -1
chim = FitDetector(np.array(Ring0 + Ringm), varyList, parmDict,
True)
tiltm = parmDict['tilt']
phim = parmDict['phi']
centm = [parmDict['det-X'], parmDict['det-Y']]
fail = False
else:
chim = 1e6
if fail:
i2 += 1
if chip < chim:
data['tilt'] = tiltp
data['center'] = centp
data['rotation'] = phip
else:
data['tilt'] = tiltm
data['center'] = centm
data['rotation'] = phim
data['ellipses'].append(ellipsep[:] + ('b', ))
data['rings'].append(np.array(Ringp))
data['ellipses'].append(ellipsem[:] + ('r', ))
data['rings'].append(np.array(Ringm))
G2plt.PlotImage(self, newImage=True)
parmDict = {
'dist': data['distance'],
'det-X': data['center'][0],
'det-Y': data['center'][1],
'tilt': data['tilt'],
'phi': data['rotation'],
'wave': data['wavelength'],
'dep': data['DetDepth']
}
varyList = [item for item in varyDict if varyDict[item]]
data['rings'] = []
data['ellipses'] = []
for i, H in enumerate(HKL):
dsp = H[3]
tth = 2.0 * asind(wave / (2. * dsp))
if tth + abs(data['tilt']) > 90.:
print 'next line is a hyperbola - search stopped'
break
if debug: print 'HKLD:', H[:4], '2-theta: %.4f' % (tth)
elcent, phi, radii = ellipse = GetEllipse(dsp, data)
data['ellipses'].append(copy.deepcopy(ellipse + ('g', )))
if debug:
print fmt % ('predicted ellipse:', elcent[0], elcent[1], phi,
radii[0], radii[1])
Ring = makeRing(dsp, ellipse, pixLimit, cutoff, scalex, scaley,
self.ImageZ)
if Ring:
data['rings'].append(np.array(Ring))
rings = np.concatenate((data['rings']), axis=0)
if i:
chisq = FitDetector(rings, varyList, parmDict, False)
data['distance'] = parmDict['dist']
data['center'] = [parmDict['det-X'], parmDict['det-Y']]
data['rotation'] = parmDict['phi']
data['tilt'] = parmDict['tilt']
data['DetDepth'] = parmDict['dep']
data['chisq'] = chisq
elcent, phi, radii = ellipse = GetEllipse(dsp, data)
if debug:
print fmt2 % ('fitted ellipse: ', elcent[0], elcent[1],
phi, radii[0], radii[1], chisq, len(rings))
data['ellipses'].append(copy.deepcopy(ellipse + ('r', )))
# G2plt.PlotImage(self,newImage=True)
else:
if debug:
print 'insufficient number of points in this ellipse to fit'
# break
G2plt.PlotImage(self, newImage=True)
fullSize = len(self.ImageZ) / scalex
if 2 * radii[1] < .9 * fullSize:
print 'Are all usable rings (>25% visible) used? Try reducing Min ring I/Ib'
N = len(data['ellipses'])
if N > 2:
FitDetector(rings, varyList, parmDict)
data['wavelength'] = parmDict['wave']
data['distance'] = parmDict['dist']
data['center'] = [parmDict['det-X'], parmDict['det-Y']]
data['rotation'] = parmDict['phi']
data['tilt'] = parmDict['tilt']
data['DetDepth'] = parmDict['dep']
for H in HKL[:N]:
ellipse = GetEllipse(H[3], data)
data['ellipses'].append(copy.deepcopy(ellipse + ('b', )))
print 'calibration time = ', time.time() - time0
G2plt.PlotImage(self, newImage=True)
return True
def ImageCalibrate(self,data):
'Needs a doc string'
import copy
import ImageCalibrants as calFile
print 'Image calibration:'
time0 = time.time()
ring = data['ring']
pixelSize = data['pixelSize']
scalex = 1000./pixelSize[0]
scaley = 1000./pixelSize[1]
pixLimit = data['pixLimit']
cutoff = data['cutoff']
varyDict = data['varyList']
if varyDict['dist'] and varyDict['wave']:
print 'ERROR - you can not simultaneously calibrate distance and wavelength'
return False
if len(ring) < 5:
print 'ERROR - not enough inner ring points for ellipse'
return False
#fit start points on inner ring
data['ellipses'] = []
data['rings'] = []
outE = FitEllipse(ring)
fmt = '%s X: %.3f, Y: %.3f, phi: %.3f, R1: %.3f, R2: %.3f'
fmt2 = '%s X: %.3f, Y: %.3f, phi: %.3f, R1: %.3f, R2: %.3f, chi**2: %.3f, Np: %d'
if outE:
print fmt%('start ellipse: ',outE[0][0],outE[0][1],outE[1],outE[2][0],outE[2][1])
ellipse = outE
else:
return False
#setup 360 points on that ring for "good" fit
data['ellipses'].append(ellipse[:]+('g',))
Ring = makeRing(1.0,ellipse,pixLimit,cutoff,scalex,scaley,self.ImageZ)
if Ring:
ellipse = FitEllipse(Ring)
Ring = makeRing(1.0,ellipse,pixLimit,cutoff,scalex,scaley,self.ImageZ) #do again
ellipse = FitEllipse(Ring)
else:
print '1st ring not sufficiently complete to proceed'
return False
if debug:
print fmt2%('inner ring: ',ellipse[0][0],ellipse[0][1],ellipse[1],
ellipse[2][0],ellipse[2][1],0.,len(Ring)) #cent,phi,radii
data['ellipses'].append(ellipse[:]+('r',))
data['rings'].append(np.array(Ring))
G2plt.PlotImage(self,newImage=True)
#setup for calibration
data['rings'] = []
if not data['calibrant']:
print 'no calibration material selected'
return True
skip = data['calibskip']
dmin = data['calibdmin']
#generate reflection set
Bravais,SGs,Cells = calFile.Calibrants[data['calibrant']][:3]
HKL = []
for bravais,sg,cell in zip(Bravais,SGs,Cells):
A = G2lat.cell2A(cell)
if sg:
SGData = G2spc.SpcGroup(sg)[1]
hkl = G2pwd.getHKLpeak(dmin,SGData,A)
HKL += hkl
else:
hkl = G2lat.GenHBravais(dmin,bravais,A)
HKL += hkl
HKL = G2lat.sortHKLd(HKL,True,False)[skip:]
#set up 1st ring
elcent,phi,radii = ellipse #from fit of 1st ring
dsp = HKL[0][3]
print '1st ring: try %.4f'%(dsp)
if varyDict['dist']:
wave = data['wavelength']
tth = 2.0*asind(wave/(2.*dsp))
else: #varyDict['wave']!
dist = data['distance']
tth = npatan2d(radii[0],dist)
data['wavelength'] = wave = 2.0*dsp*sind(tth/2.0)
Ring0 = makeRing(dsp,ellipse,3,cutoff,scalex,scaley,self.ImageZ)
ttth = nptand(tth)
stth = npsind(tth)
ctth = npcosd(tth)
#1st estimate of tilt; assume ellipse - don't know sign though
if varyDict['tilt']:
tilt = npasind(np.sqrt(max(0.,1.-(radii[0]/radii[1])**2))*ctth)
if not tilt:
print 'WARNING - selected ring was fitted as a circle'
print ' - if detector was tilted we suggest you skip this ring - WARNING'
else:
tilt = data['tilt']
#1st estimate of dist: sample to detector normal to plane
if varyDict['dist']:
data['distance'] = dist = radii[0]**2/(ttth*radii[1])
else:
dist = data['distance']
if varyDict['tilt']:
#ellipse to cone axis (x-ray beam); 2 choices depending on sign of tilt
zdisp = radii[1]*ttth*tand(tilt)
zdism = radii[1]*ttth*tand(-tilt)
#cone axis position; 2 choices. Which is right?
#NB: zdisp is || to major axis & phi is rotation of minor axis
#thus shift from beam to ellipse center is [Z*sin(phi),-Z*cos(phi)]
centp = [elcent[0]+zdisp*sind(phi),elcent[1]-zdisp*cosd(phi)]
centm = [elcent[0]+zdism*sind(phi),elcent[1]-zdism*cosd(phi)]
#check get same ellipse parms either way
#now do next ring; estimate either way & do a FitDetector each way; best fit is correct one
fail = True
i2 = 1
while fail:
dsp = HKL[i2][3]
print '2nd ring: try %.4f'%(dsp)
tth = 2.0*asind(wave/(2.*dsp))
ellipsep = GetEllipse2(tth,0.,dist,centp,tilt,phi)
print fmt%('plus ellipse :',ellipsep[0][0],ellipsep[0][1],ellipsep[1],ellipsep[2][0],ellipsep[2][1])
Ringp = makeRing(dsp,ellipsep,3,cutoff,scalex,scaley,self.ImageZ)
parmDict = {'dist':dist,'det-X':centp[0],'det-Y':centp[1],
'tilt':tilt,'phi':phi,'wave':wave,'dep':0.0}
varyList = [item for item in varyDict if varyDict[item]]
if len(Ringp) > 10:
chip = FitDetector(np.array(Ring0+Ringp),varyList,parmDict,True)
tiltp = parmDict['tilt']
phip = parmDict['phi']
centp = [parmDict['det-X'],parmDict['det-Y']]
fail = False
else:
chip = 1e6
ellipsem = GetEllipse2(tth,0.,dist,centm,-tilt,phi)
print fmt%('minus ellipse:',ellipsem[0][0],ellipsem[0][1],ellipsem[1],ellipsem[2][0],ellipsem[2][1])
Ringm = makeRing(dsp,ellipsem,3,cutoff,scalex,scaley,self.ImageZ)
if len(Ringm) > 10:
parmDict['tilt'] *= -1
chim = FitDetector(np.array(Ring0+Ringm),varyList,parmDict,True)
tiltm = parmDict['tilt']
phim = parmDict['phi']
centm = [parmDict['det-X'],parmDict['det-Y']]
fail = False
else:
chim = 1e6
if fail:
i2 += 1
if chip < chim:
data['tilt'] = tiltp
data['center'] = centp
data['rotation'] = phip
else:
data['tilt'] = tiltm
data['center'] = centm
data['rotation'] = phim
data['ellipses'].append(ellipsep[:]+('b',))
data['rings'].append(np.array(Ringp))
data['ellipses'].append(ellipsem[:]+('r',))
data['rings'].append(np.array(Ringm))
G2plt.PlotImage(self,newImage=True)
parmDict = {'dist':data['distance'],'det-X':data['center'][0],'det-Y':data['center'][1],
'tilt':data['tilt'],'phi':data['rotation'],'wave':data['wavelength'],'dep':data['DetDepth']}
varyList = [item for item in varyDict if varyDict[item]]
data['rings'] = []
data['ellipses'] = []
for i,H in enumerate(HKL):
dsp = H[3]
tth = 2.0*asind(wave/(2.*dsp))
if tth+abs(data['tilt']) > 90.:
print 'next line is a hyperbola - search stopped'
break
if debug: print 'HKLD:',H[:4],'2-theta: %.4f'%(tth)
elcent,phi,radii = ellipse = GetEllipse(dsp,data)
data['ellipses'].append(copy.deepcopy(ellipse+('g',)))
if debug: print fmt%('predicted ellipse:',elcent[0],elcent[1],phi,radii[0],radii[1])
Ring = makeRing(dsp,ellipse,pixLimit,cutoff,scalex,scaley,self.ImageZ)
if Ring:
data['rings'].append(np.array(Ring))
rings = np.concatenate((data['rings']),axis=0)
if i:
chisq = FitDetector(rings,varyList,parmDict,False)
data['distance'] = parmDict['dist']
data['center'] = [parmDict['det-X'],parmDict['det-Y']]
data['rotation'] = parmDict['phi']
data['tilt'] = parmDict['tilt']
data['DetDepth'] = parmDict['dep']
data['chisq'] = chisq
elcent,phi,radii = ellipse = GetEllipse(dsp,data)
if debug: print fmt2%('fitted ellipse: ',elcent[0],elcent[1],phi,radii[0],radii[1],chisq,len(rings))
data['ellipses'].append(copy.deepcopy(ellipse+('r',)))
# G2plt.PlotImage(self,newImage=True)
else:
if debug: print 'insufficient number of points in this ellipse to fit'
# break
G2plt.PlotImage(self,newImage=True)
fullSize = len(self.ImageZ)/scalex
if 2*radii[1] < .9*fullSize:
print 'Are all usable rings (>25% visible) used? Try reducing Min ring I/Ib'
N = len(data['ellipses'])
if N > 2:
FitDetector(rings,varyList,parmDict)
data['wavelength'] = parmDict['wave']
data['distance'] = parmDict['dist']
data['center'] = [parmDict['det-X'],parmDict['det-Y']]
data['rotation'] = parmDict['phi']
data['tilt'] = parmDict['tilt']
data['DetDepth'] = parmDict['dep']
for H in HKL[:N]:
ellipse = GetEllipse(H[3],data)
data['ellipses'].append(copy.deepcopy(ellipse+('b',)))
print 'calibration time = ',time.time()-time0
G2plt.PlotImage(self,newImage=True)
return True
def ImageRecalibrate(self, data, masks):
'Needs a doc string'
import ImageCalibrants as calFile
print 'Image recalibration:'
time0 = time.time()
pixelSize = data['pixelSize']
scalex = 1000. / pixelSize[0]
scaley = 1000. / pixelSize[1]
pixLimit = data['pixLimit']
cutoff = data['cutoff']
data['rings'] = []
data['ellipses'] = []
if not data['calibrant']:
print 'no calibration material selected'
return True
skip = data['calibskip']
dmin = data['calibdmin']
Bravais, SGs, Cells = calFile.Calibrants[data['calibrant']][:3]
HKL = []
for bravais, sg, cell in zip(Bravais, SGs, Cells):
A = G2lat.cell2A(cell)
if sg:
SGData = G2spc.SpcGroup(sg)[1]
hkl = G2pwd.getHKLpeak(dmin, SGData, A)
HKL += hkl
else:
hkl = G2lat.GenHBravais(dmin, bravais, A)
HKL += hkl
HKL = G2lat.sortHKLd(HKL, True, False)
varyList = [item for item in data['varyList'] if data['varyList'][item]]
parmDict = {
'dist': data['distance'],
'det-X': data['center'][0],
'det-Y': data['center'][1],
'tilt': data['tilt'],
'phi': data['rotation'],
'wave': data['wavelength'],
'dep': data['DetDepth']
}
Found = False
wave = data['wavelength']
frame = masks['Frames']
tam = ma.make_mask_none(self.ImageZ.shape)
if frame:
tam = ma.mask_or(tam, MakeFrameMask(data, frame))
for iH, H in enumerate(HKL):
if debug: print H
dsp = H[3]
tth = 2.0 * asind(wave / (2. * dsp))
if tth + abs(data['tilt']) > 90.:
print 'next line is a hyperbola - search stopped'
break
ellipse = GetEllipse(dsp, data)
Ring = makeRing(dsp, ellipse, pixLimit, cutoff, scalex, scaley,
ma.array(self.ImageZ, mask=tam))
if Ring:
if iH >= skip:
data['rings'].append(np.array(Ring))
data['ellipses'].append(copy.deepcopy(ellipse + ('r', )))
Found = True
elif not Found: #skipping inner rings, keep looking until ring found
continue
else: #no more rings beyond edge of detector
data['ellipses'].append([])
continue
# break
rings = np.concatenate((data['rings']), axis=0)
chisq = FitDetector(rings, varyList, parmDict)
data['wavelength'] = parmDict['wave']
data['distance'] = parmDict['dist']
data['center'] = [parmDict['det-X'], parmDict['det-Y']]
data['rotation'] = np.mod(parmDict['phi'], 360.0)
data['tilt'] = parmDict['tilt']
data['DetDepth'] = parmDict['dep']
data['chisq'] = chisq
N = len(data['ellipses'])
data['ellipses'] = [] #clear away individual ellipse fits
for H in HKL[:N]:
ellipse = GetEllipse(H[3], data)
data['ellipses'].append(copy.deepcopy(ellipse + ('b', )))
print 'calibration time = ', time.time() - time0
G2plt.PlotImage(self, newImage=True)
return True
def ImageRecalibrate(self,data,masks):
'Needs a doc string'
import ImageCalibrants as calFile
print 'Image recalibration:'
time0 = time.time()
pixelSize = data['pixelSize']
scalex = 1000./pixelSize[0]
scaley = 1000./pixelSize[1]
pixLimit = data['pixLimit']
cutoff = data['cutoff']
data['rings'] = []
data['ellipses'] = []
if not data['calibrant']:
print 'no calibration material selected'
return True
skip = data['calibskip']
dmin = data['calibdmin']
Bravais,SGs,Cells = calFile.Calibrants[data['calibrant']][:3]
HKL = []
for bravais,sg,cell in zip(Bravais,SGs,Cells):
A = G2lat.cell2A(cell)
if sg:
SGData = G2spc.SpcGroup(sg)[1]
hkl = G2pwd.getHKLpeak(dmin,SGData,A)
HKL += hkl
else:
hkl = G2lat.GenHBravais(dmin,bravais,A)
HKL += hkl
HKL = G2lat.sortHKLd(HKL,True,False)
varyList = [item for item in data['varyList'] if data['varyList'][item]]
parmDict = {'dist':data['distance'],'det-X':data['center'][0],'det-Y':data['center'][1],
'tilt':data['tilt'],'phi':data['rotation'],'wave':data['wavelength'],'dep':data['DetDepth']}
Found = False
wave = data['wavelength']
frame = masks['Frames']
tam = ma.make_mask_none(self.ImageZ.shape)
if frame:
tam = ma.mask_or(tam,MakeFrameMask(data,frame))
for iH,H in enumerate(HKL):
if debug: print H
dsp = H[3]
tth = 2.0*asind(wave/(2.*dsp))
if tth+abs(data['tilt']) > 90.:
print 'next line is a hyperbola - search stopped'
break
ellipse = GetEllipse(dsp,data)
Ring = makeRing(dsp,ellipse,pixLimit,cutoff,scalex,scaley,ma.array(self.ImageZ,mask=tam))
if Ring:
if iH >= skip:
data['rings'].append(np.array(Ring))
data['ellipses'].append(copy.deepcopy(ellipse+('r',)))
Found = True
elif not Found: #skipping inner rings, keep looking until ring found
continue
else: #no more rings beyond edge of detector
data['ellipses'].append([])
continue
# break
rings = np.concatenate((data['rings']),axis=0)
chisq = FitDetector(rings,varyList,parmDict)
data['wavelength'] = parmDict['wave']
data['distance'] = parmDict['dist']
data['center'] = [parmDict['det-X'],parmDict['det-Y']]
data['rotation'] = np.mod(parmDict['phi'],360.0)
data['tilt'] = parmDict['tilt']
data['DetDepth'] = parmDict['dep']
data['chisq'] = chisq
N = len(data['ellipses'])
data['ellipses'] = [] #clear away individual ellipse fits
for H in HKL[:N]:
ellipse = GetEllipse(H[3],data)
data['ellipses'].append(copy.deepcopy(ellipse+('b',)))
print 'calibration time = ',time.time()-time0
G2plt.PlotImage(self,newImage=True)
return True