def updatecolfile(self):
if "xl" not in self.cf.titles:
if "sc" in self.cf.titles:
pks = self.cf.sc, self.cf.fc
elif "xc" in self.cf.titles:
pks = self.cf.xc, self.cf.yc
else:
raise Exception("peaks file misses xc or sc")
xl,yl,zl = transform.compute_xyz_lab( pks,
**self.transformpars.parameters)
self.cf.addcolumn(xl,"xl")
self.cf.addcolumn(yl,"yl")
self.cf.addcolumn(zl,"zl")
peaks_xyz = np.array((self.cf.xl,self.cf.yl,self.cf.zl))
om = self.cf.omega
sign = self.transformpars.get("omegasign")
tth, eta = transform.compute_tth_eta_from_xyz(
peaks_xyz, om*sign,
**self.transformpars.parameters)
self.cf.addcolumn( tth, "tth", )
self.cf.addcolumn( eta, "eta", )
gx, gy, gz = transform.compute_g_vectors(
tth, eta, om*sign,
wvln = self.transformpars.get("wavelength"),
wedge = self.transformpars.get("wedge"),
chi = self.transformpars.get("chi") )
self.cf.addcolumn(gx, "gx")
self.cf.addcolumn(gy, "gy")
self.cf.addcolumn(gz, "gz")
self.cf.addcolumn( np.sqrt( gx * gx +
gy * gy +
gz * gz ),
"modg")
def test_xyz_from_yaml(self):
for p in parfiles:
parfile = os.path.join(TEST, p)
fltfile = os.path.join(TEST, "test.flt")
ymlfile = os.path.join(
os.path.split(general_geometry.__file__)[0], "data",
"fable.yml")
pars = parameters.read_par_file(parfile).parameters
colf = columnfile.columnfile(fltfile)
sc = colf.sc[:4]
fc = colf.fc[:4]
geometry = general_geometry.from_yml(
pars,
ymlfile,
path=["Positioners", "Fable_detector"],
noisy=False)
# test old
xyz1 = transform.compute_xyz_lab((sc, fc), **pars)
# test new
v = np.zeros((3, len(sc)))
v[1] = fc
v[2] = sc
xyz2 = geometry((np.zeros(len(fc)), fc, sc))
if not np.allclose(xyz1, xyz2):
print("Geometry", geometry)
print("Parfile:", p)
for i in range(len(fc)):
print(xyz1[:, i])
print(xyz2[:, i])
print()
assert np.allclose(xyz1, xyz2)
def update_det_pars( peakdata, pars ):
"""
Update the xl, yl, zl columns
peakdata = columnfile
pars = ImageD11 parameters object
"""
print("Update xl, yl, zl for current parameters")
for label in ["xl","yl","zl"]:
if label not in peakdata.titles:
peakdata.titles.append(label)
peakdata.xl,peakdata.yl,peakdata.zl = transform.compute_xyz_lab(
[peakdata.sc, peakdata.fc],
**pars.get_parameters() )
# Imagine sample translates along +x. Detector is at x=+distance
# To get the difference vector right we add samtx to xl for omega=0
# Same for samty, yl and samtz, zl
# when omega rotates to + 90 degrees (right handed)
# samtx is along +yl
# samty is along -xl
rad = float(pars.parameters['omegasign'])*numpy.pi/180.0
peakdata.sinomega = numpy.sin(peakdata.omega * rad) # == 0 at omega = 0
peakdata.cosomega = numpy.cos(peakdata.omega * rad) # == 1 at omega = 0
peakdata.xl += peakdata.samtx * peakdata.cosomega - \
peakdata.samty * peakdata.sinomega
peakdata.yl += peakdata.samtx * peakdata.sinomega + \
peakdata.samty * peakdata.cosomega
peakdata.zl += peakdata.samtz
print("lab x shape",peakdata.xl.shape)
return peakdata
def compute_XLYLZL(self):
self.peaks_xyz = transform.compute_xyz_lab(
[self.colfile.sc, self.colfile.fc], **self.pars.parameters)
# These are the peak positions in the laboratory frame
#
# Now get the beam and peaks in the crystal frame
wedge = float(self.pars.get('wedge'))
chi = float(self.pars.get('chi'))
omega = self.colfile.omega
beam = np.zeros((3, len(omega)))
beam[0, :] = 1
self.XB = k_to_g(beam, omega, wedge, chi)
self.XS = k_to_g(self.peaks_xyz, omega, wedge, chi)
def getCxyz(colf, pars):
"""
Find spot positions in crystal frame
colf = columnfile (or other object) holding .sc, .fc, .omega
pars = parameters for ImageD11 transform module
"""
wedge = pars.get("wedge")
chi = pars.get("chi")
peaks_xyz = transform.compute_xyz_lab([colf.sc, colf.fc],
**pars.parameters)
fun = transform.compute_g_from_k
peaks_Cxyz = fun(peaks_xyz, colf.omega, wedge=wedge, chi=chi)
b = np.zeros(peaks_Cxyz.shape)
b[0, :] = 1.0 / pars.get("wavelength")
beam_Cxyz = fun(b, colf.omega, wedge=wedge, chi=chi)
return peaks_Cxyz, beam_Cxyz
def gridgrains(
ul,
flt,
pars,
minx=-750,
maxx=750,
stepx=25,
miny=-750,
maxy=750,
stepy=25,
tol=0.05,
):
trn = transformer.transformer()
trn.loadfiltered(flt)
trn.parameterobj = parameters.parameters(**pars)
peaks = [trn.getcolumn(trn.xname), trn.getcolumn(trn.yname)]
peaks_xyz = transform.compute_xyz_lab(peaks,
**trn.parameterobj.get_parameters())
omega = trn.getcolumn(trn.omeganame)
trn.updateparameters()
tx = minx - stepx
n = 0
sys.stderr.write("Using tol = %f\n" % (tol))
while tx <= maxx:
tx = tx + stepx
ty = miny - stepy
while ty <= maxy:
ty = ty + stepy
trn.parameterobj.set_parameters({'t_x': tx, 't_y': ty})
pars = trn.parameterobj.get_parameters()
tth, eta = transform.compute_tth_eta_from_xyz(
peaks_xyz, omega, **pars)
if 'omegasign' in pars:
om_sgn = float(pars["omegasign"])
else:
om_sgn = 1.0
gv = transform.compute_g_vectors(tth, eta, omega * om_sgn, **pars)
print(tx, ty, end=' ')
for ubi in ul:
ns = score(ubi, gv.T, tol)
print(ns, end=' ')
n += ns
print()
return n
def compute_XLYLZL(self):
self.peaks_xyz = transform.compute_xyz_lab(
[self.colfile.sc, self.colfile.fc],
**self.colfile.parameters.parameters)
# These are the peak positions in the laboratory frame
#
# Now get the beam and peaks in the crystal frame
wedge = float(self.colfile.parameters.get('wedge'))
chi = float(self.colfile.parameters.get('chi'))
self.chiwedge = gv_general.chiwedge(chi, wedge)
omega = np.radians(self.colfile.omega)
cosomega = np.cos(omega)
sinomega = np.sin(omega)
beam = np.zeros((3, len(omega)), float)
beam[0, :] = 1.
self.XB = k_to_g(beam, cosomega, sinomega, self.chiwedge)
self.XS = k_to_g(self.peaks_xyz, cosomega, sinomega, self.chiwedge)
def compute_tth_eta(self):
""" Compute the twotheta and eta for peaks previous read in """
if None in [self.xname, self.yname]:
raise Exception("No peaks loaded")
peaks = [self.getcolumn(self.xname), self.getcolumn(self.yname)]
peaks_xyz = transform.compute_xyz_lab(
peaks, **self.parameterobj.get_parameters())
# Store these in the columnfile
self.addcolumn(peaks_xyz[0], "xl")
self.addcolumn(peaks_xyz[1], "yl")
self.addcolumn(peaks_xyz[2], "zl")
# Get the Omega name?
omega = self.getcolumn(self.omeganame)
tth, eta = transform.compute_tth_eta_from_xyz(
peaks_xyz, omega, **self.parameterobj.get_parameters())
self.addcolumn(tth, "tth")
self.addcolumn(eta, "eta")
return tth, eta
def gof(self,args):
"""
<drlv> for all of the grains in all of the scans
"""
self.applyargs(args)
diffs = 0.
contribs = 0.
# defaulting to fitting all grains
for key in self.grains_to_refine:
g = self.grains[key]
### rotdex.fitagrain( gr, self.parameterobj )
grainname = key[0]
scanname = key[1]
# Compute gv using current parameters
# Keep labels fixed
if self.recompute_xlylzl:
g.peaks_xyz = transform.compute_xyz_lab([ g.sc,
g.fc ],
**self.parameterobj.parameters).T
self.compute_gv( g )
#print self.gv.shape
#print self.gv[0:10,i:]
# For stability, always start refining the read in one
g.set_ubi( self.refine( self.ubisread[grainname] ) )
#print self.npks,self.avg_drlv2 # number of peaks it got
#print self.gv.shape
diffs += self.npks*self.avg_drlv2
contribs+= self.npks
if contribs > 0:
return 1e6*diffs/contribs
else:
print("No contribs???", self.grains_to_refine)
return 1e6
def updateGeometry(self, pars=None):
"""
changing or not the parameters it (re)-computes:
xl,yl,zl = ImageD11.transform.compute_xyz_lab
tth, eta = ImageD11.transform.compute_tth_eta
gx,gy,gz = ImageD11.transform.compute_g_vectors
"""
if pars is not None:
self.setparameters(pars)
pars = self.parameters
if "sc" in self.titles and "fc" in self.titles:
pks = self.sc, self.fc
elif "xc" in self.titles and "yc" in self.titles:
pks = self.xc, self.yc
else:
raise Exception("columnfile file misses xc/yc or sc/fc")
xl, yl, zl = transform.compute_xyz_lab(pks, **pars.parameters)
peaks_xyz = np.array((xl, yl, zl))
assert "omega" in self.titles, "No omega column"
om = self.omega * float(pars.get("omegasign"))
tth, eta = transform.compute_tth_eta_from_xyz(peaks_xyz, om,
**pars.parameters)
gx, gy, gz = transform.compute_g_vectors(tth,
eta,
om,
wvln=pars.get("wavelength"),
wedge=pars.get("wedge"),
chi=pars.get("chi"))
modg = np.sqrt(gx * gx + gy * gy + gz * gz)
self.addcolumn(xl, "xl")
self.addcolumn(yl, "yl")
self.addcolumn(zl, "zl")
self.addcolumn(
tth,
"tth",
)
self.addcolumn(
eta,
"eta",
)
self.addcolumn(gx, "gx")
self.addcolumn(gy, "gy")
self.addcolumn(gz, "gz")
self.addcolumn(modg, "ds") # dstar
def test1(self):
pks = self.sc, self.fc
p = self.pars
testtilts = [-0.5, 0., 0.24]
tilts = [(x, y, z) for x in testtilts for y in testtilts
for z in testtilts]
pars = np.array((p.get("z_center"), p.get("y_center"), p.get("z_size"),
p.get("y_size")))
dist = np.array((p.get("distance"), 0., 0.))
ok = 0
for o11, o12, o21, o22 in [[1, 0, 0, 1], [-1, 0, 0, 1], [-1, 0, 0, -1],
[1, 0, 0, -1], [0, 1, 1, 0], [0, -1, 1, 0],
[0, -1, -1, 0], [0, 1, -1, 0]]:
for tx, ty, tz in tilts:
p.parameters['tilt_x'] = tx
p.parameters['tilt_y'] = ty
p.parameters['tilt_z'] = tz
p.parameters['o11'] = o11
p.parameters['o12'] = o12
p.parameters['o21'] = o21
p.parameters['o22'] = o22
xlylzl = transform.compute_xyz_lab(pks, **p.parameters)
dmat = transform.detector_rotation_matrix(
p.get('tilt_x'), p.get('tilt_y'), p.get('tilt_z'))
fmat = np.array([[1, 0, 0], [0, p.get('o22'),
p.get('o21')],
[0, p.get('o12'),
p.get('o11')]])
r = np.dot(dmat, fmat)
outxyz = np.zeros((len(self.sc), 3), np.float)
cImageD11.compute_xlylzl(self.sc, self.fc, pars, r.ravel(),
dist, outxyz)
error = np.abs(outxyz - xlylzl.T)
self.assertTrue(error.max() < 1e-6)
ok += 1
print("tested xlylzl %d times" % (ok))
def compute_XLYLZL(self):
self.peaks_xyz = transform.compute_xyz_lab( [self.colfile.sc,
self.colfile.fc],
**self.pars.parameters)
self.colfile.addcolumn( self.peaks_xyz[0], 'XL')
self.colfile.addcolumn( self.peaks_xyz[1], 'YL')
self.colfile.addcolumn( self.peaks_xyz[2], 'ZL')
# These are the peak positions in the laboratory frame
#
# Now get the beam and peaks in the crystal frame
wedge = float(self.pars.get('wedge'))
chi = float(self.pars.get('chi'))
omega = self.colfile.omega
beam = np.zeros( (3,len(omega)))
beam[0,:] = 1
self.XB = k_to_g( beam, omega, wedge, chi)
#print "XB",XB
self.colfile.addcolumn( self.XB[0], 'XB')
self.colfile.addcolumn( self.XB[1], 'YB')
self.colfile.addcolumn( self.XB[2], 'ZB')
self.XS = k_to_g( self.peaks_xyz, omega, wedge, chi )
self.colfile.addcolumn( self.XS[0], 'XS')
self.colfile.addcolumn( self.XS[1], 'YS')
self.colfile.addcolumn( self.XS[2], 'ZS')
def test_xyz(self):
for p in parfiles:
parfile = os.path.join(TEST, p)
fltfile = os.path.join(TEST, "test.flt")
pars = parameters.read_par_file(parfile).parameters
colf = columnfile.columnfile(fltfile)
sc = colf.sc
fc = colf.fc
geometry = general_geometry.fable_detector(pars, noisy=False)
# test old
xyz1 = transform.compute_xyz_lab((sc, fc), **pars)
# test new
v = np.zeros((3, len(sc)))
v[1] = fc
v[2] = sc
xyz2 = geometry((np.zeros(len(fc)), fc, sc))
if not np.allclose(xyz1, xyz2):
print("Geometry", geometry)
print("Parfile:", p)
for i in range(len(fc)):
print(xyz1[:, i])
print(xyz2[:, i])
print()
assert np.allclose(xyz1, xyz2)
mm = float(sys.argv[4])
except:
pixv = 2048.
pixh = 2048.
mm = 1
v = (pixv - 1) / 2.
h = (pixh - 1) / 2.
print("Getting parameters from", parfile)
p = parameters.parameters()
p.loadparameters(parfile)
pars = p.get_parameters()
xyz = np.transpose(transform.compute_xyz_lab([[v], [h]], **pars))
ks = list(pars.keys())
ks.sort()
for k in ks:
print(k, pars[k])
print()
print("central pixel position")
print("detector vertical", v, "horizontal", h)
print("real space x, y, z = ", xyz)
print("\n")
print("detector %i %i %0.4f %0.4f %0.4f %0.4f %0.4f %0.4f %0.4f %0.4f stem format %i %i %i %i" % \
(pixv,
pixh,
mm*pars['y_size'],
def setscfc(self, sc, fc):
self.sc = sc
self.fc = fc
self.XL = transform.compute_xyz_lab( [sc, fc],
**self.pars.parameters ).T.copy()
def assignlabels(self, quiet=False):
"""
Fill out the appropriate labels for the spots
"""
if not quiet:
print("Assigning labels with XLYLZL")
import time
start = time.time()
for s in self.scannames:
self.scandata[s].labels = self.scandata[s].labels * 0 - 2 # == -1
drlv2 = numpy.zeros(len(self.scandata[s].drlv2), numpy.float) + 1
nr = self.scandata[s].nrows
sc = self.scandata[s].sc
fc = self.scandata[s].fc
om = self.scandata[s].omega
# Looks like this in one dataset only
ng = len(self.grainnames)
int_tmp = numpy.zeros(nr, numpy.int32) - 1
tmp = transform.compute_xyz_lab(
[self.scandata[s].sc, self.scandata[s].fc],
**self.parameterobj.parameters)
peaks_xyz = tmp.T.copy()
if not quiet:
print("Start first grain loop", time.time() - start)
start = time.time()
gv = numpy.zeros((nr, 3), numpy.float)
wedge = self.parameterobj.parameters['wedge']
omegasign = self.parameterobj.parameters['omegasign']
chi = self.parameterobj.parameters['chi']
wvln = self.parameterobj.parameters['wavelength']
first_loop = time.time()
drlv2 = (self.scandata[s].drlv2 * 0 + 1).astype(float) # == 1
int_tmp = numpy.zeros(nr, numpy.int32) - 1
for ig, g in enumerate(self.grainnames):
gr = self.grains[(g, s)]
self.set_translation(g, s)
cImageD11.compute_gv(peaks_xyz, self.scandata[s].omega,
omegasign, wvln, wedge, chi,
gr.translation, gv)
cImageD11.score_and_assign(gr.ubi, gv, self.tolerance, drlv2,
int_tmp, int(g))
if not quiet:
print(time.time() - first_loop, "First loop")
self.gv = gv.copy()
# Second loop after checking all grains
if not quiet:
print("End first grain loop", time.time() - start)
start = time.time()
if not quiet:
print(self.scandata[s].labels.shape, \
numpy.minimum.reduce(self.scandata[s].labels),\
numpy.maximum.reduce(self.scandata[s].labels))
self.scandata[s].addcolumn(int_tmp, "labels")
self.scandata[s].addcolumn(drlv2, "drlv2")
if not quiet:
print(self.scandata[s].labels.shape, \
numpy.minimum.reduce(self.scandata[s].labels),\
numpy.maximum.reduce(self.scandata[s].labels))
tth = numpy.zeros(nr, numpy.float32) - 1
eta = numpy.zeros(nr, numpy.float32)
self.scandata[s].addcolumn(tth, "tth_per_grain")
self.scandata[s].addcolumn(eta, "eta_per_grain")
self.scandata[s].addcolumn(om * 0, "omegacalc_per_grain")
self.scandata[s].addcolumn(self.gv[:, 0], "gx")
self.scandata[s].addcolumn(self.gv[:, 1], "gy")
self.scandata[s].addcolumn(self.gv[:, 2], "gz")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "hr")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "kr")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "lr")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "h")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "k")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "l")
if not quiet:
print("Start second grain loop", time.time() - start)
start = time.time()
# We have the labels set in self.scandata!!!
for g in self.grainnames:
gr = self.grains[(g, s)]
ind = numpy.compress(int_tmp == g, numpy.arange(nr))
#print 'x',gr.x[:10]
#print 'ind',ind[:10]
gr.ind = ind # use this to push back h,k,l later
gr.peaks_xyz = numpy.take(peaks_xyz, ind, axis=0)
gr.sc = numpy.take(sc, ind)
gr.fc = numpy.take(fc, ind)
gr.om = numpy.take(self.scandata[s].omega, ind)
gr.omega_calc = gr.om.copy()
gr.npks = len(gr.ind)
self.set_translation(g, s)
try:
sign = self.parameterobj.parameters['omegasign']
except:
sign = 1.0
tth, eta = transform.compute_tth_eta_from_xyz(
gr.peaks_xyz.T,
omega=gr.om * sign,
**self.parameterobj.parameters)
self.scandata[s].tth_per_grain[ind] = tth
self.scandata[s].eta_per_grain[ind] = eta
# self.scandata[s].omegacalc_per_grain[ind] = gr.omega_calc
self.grains[(g, s)] = gr
if not quiet:
print("Grain", g, "Scan", s, "npks=", len(ind))
#print 'x',gr.x[:10]
# Compute the total integrated intensity if we have enough
# information available
compute_lp_factor(self.scandata[s])
for g in self.grainnames:
gr = self.grains[(g, s)]
gr.intensity_info = compute_total_intensity(
self.scandata[s],
gr.ind,
self.intensity_tth_range,
quiet=quiet)
if not quiet:
print("End second grain loop", time.time() - start)
print()
start = time.time()
parfile = sys.argv[3]
pars = parameters()
pars.loadparameters(parfile)
wedge = np.radians(float(pars.get("wedge")))
chi = np.radians(float(pars.get("chi")))
wvln = float(pars.get("wavelength"))
c = columnfile(colfile)
c.nrows = 2
c.bigarray = c.bigarray[:, :2]
print c.bigarray.shape
c.set_attributes()
XL = flatfloat(compute_xyz_lab([c.sc, c.fc], **pars.parameters).T)
om = flatfloat(np.radians(c.omega))
# XL[0,:]=[41,42,43]
grains = read_grain_file(grainfile)
UBIs = flatfloat([g.ubi for g in grains], shape=(len(grains), 3, 3))
UBs = flatfloat([np.linalg.inv(g.ubi) for g in grains],
shape=(len(grains), 3, 3))
Ts = flatfloat([g.translation for g in grains], shape=(len(grains), 3))
labels = np.zeros(c.nrows, np.int32)
hkls = np.zeros((c.nrows, 3), NPREAL)
print XL.shape
print om.shape
(p.get("z_center"), p.get("y_center"), p.get("z_size"), p.get("y_size")))
dist = np.array((p.get("distance"), 0., 0.))
for o11, o12, o21, o22 in [[1, 0, 0, 1], [-1, 0, 0, 1], [-1, 0, 0, -1],
[1, 0, 0, -1], [0, 1, 1, 0], [0, -1, 1, 0],
[0, -1, -1, 0], [0, 1, -1, 0]]:
for tx, ty, tz in tilts:
p.parameters['tilt_x'] = tx
p.parameters['tilt_y'] = ty
p.parameters['tilt_z'] = tz
p.parameters['o11'] = o11
p.parameters['o12'] = o12
p.parameters['o21'] = o21
p.parameters['o22'] = o22
xlylzl = compute_xyz_lab(pks, **p.parameters)
dmat = detector_rotation_matrix(p.get('tilt_x'), p.get('tilt_y'),
p.get('tilt_z'))
fmat = np.array([[1, 0, 0], [0, p.get('o22'),
p.get('o21')],
[0, p.get('o12'), p.get('o11')]])
r = np.dot(dmat, fmat)
outxyz = np.zeros((c.nrows, 3), np.float32)
cImageD11_wrap.compute_xlylzl_wrap(
c.sc.astype(np.float32).copy(),
c.fc.astype(np.float32).copy(), pars, r.ravel(), dist, outxyz)
error = np.abs(outxyz - xlylzl.T) / np.abs(outxyz + 1)
if error.mean() > 1e-5:
print tx, ty, ty
def assignlabels(self, quiet=False):
"""
Fill out the appropriate labels for the spots
"""
if not quiet:
print "Assigning labels with XLYLZL"
import time
start = time.time()
for s in self.scannames:
self.scandata[s].labels = self.scandata[s].labels * 0 - 2 # == -1
drlv2 = numpy.zeros(len(self.scandata[s].drlv2), numpy.float) + 1
nr = self.scandata[s].nrows
sc = self.scandata[s].sc
fc = self.scandata[s].fc
# Looks like this in one dataset only
ng = len(self.grainnames)
int_tmp = numpy.zeros(nr, numpy.int32) - 1
if 0: # this is pretty slow
tth_tmp = numpy.zeros((ng, nr), numpy.float32) - 1
eta_tmp = numpy.zeros((ng, nr), numpy.float32)
peaks_xyz = transform.compute_xyz_lab(
[self.scandata[s].sc, self.scandata[s].fc],
**self.parameterobj.parameters)
if not quiet:
print "Start first grain loop", time.time() - start
start = time.time()
gv = numpy.zeros(peaks_xyz.shape, numpy.float, order='F')
wedge = self.parameterobj.parameters['wedge']
omegasign = self.parameterobj.parameters['omegasign']
chi = self.parameterobj.parameters['chi']
wvln = self.parameterobj.parameters['wavelength']
first_loop = time.time()
import fImageD11
drlv2_2 = self.scandata[s].drlv2 * 0 + 1 # == 1
int_tmp_2 = numpy.zeros(nr, numpy.int32) - 1
for g, ig in zip(self.grainnames, range(ng)):
assert g == ig, "sorry - a bug in program"
gr = self.grains[(g, s)]
self.set_translation(g, s)
gr.peaks_xyz = peaks_xyz
gr.om = self.scandata[s].omega
# self.compute_gv( gr )
# print peaks_xyz.shape, self.scandata[s].omega.shape, gv.shape
fImageD11.compute_gv(peaks_xyz, self.scandata[s].omega,
omegasign, wvln, wedge, chi,
gr.translation, gv)
fImageD11.assign(gr.ubi, gv, self.tolerance, drlv2, int_tmp,
int(g))
# closest.score_and_assign( gr.ubi,
# gv.T,
# self.tolerance,
# drlv2_2,
# int_tmp_2,
# int(g))
if not quiet:
print time.time() - first_loop, "First loop"
# print "assigned"
self.gv = gv.T.astype(numpy.float32).copy()
# Second loop after checking all grains
if not quiet:
print "End first grain loop", time.time() - start
start = time.time()
if not quiet:
print self.scandata[s].labels.shape, \
numpy.minimum.reduce(self.scandata[s].labels),\
numpy.maximum.reduce(self.scandata[s].labels)
self.scandata[s].addcolumn(int_tmp, "labels")
self.scandata[s].addcolumn(drlv2, "drlv2")
if not quiet:
print self.scandata[s].labels.shape, \
numpy.minimum.reduce(self.scandata[s].labels),\
numpy.maximum.reduce(self.scandata[s].labels)
tth = numpy.zeros(nr, numpy.float32) - 1
eta = numpy.zeros(nr, numpy.float32)
self.scandata[s].addcolumn(tth, "tth_per_grain")
self.scandata[s].addcolumn(eta, "eta_per_grain")
self.scandata[s].addcolumn(self.gv[:, 0], "gx")
self.scandata[s].addcolumn(self.gv[:, 1], "gy")
self.scandata[s].addcolumn(self.gv[:, 2], "gz")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "hr")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "kr")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "lr")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "h")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "k")
self.scandata[s].addcolumn(numpy.zeros(nr, numpy.float32), "l")
if not quiet:
print "Start second grain loop", time.time() - start
start = time.time()
# We have the labels set in self.scandata!!!
for g in self.grainnames:
gr = self.grains[(g, s)]
ind = numpy.compress(int_tmp == g, range(nr))
#print 'x',gr.x[:10]
#print 'ind',ind[:10]
gr.ind = ind # use this to push back h,k,l later
gr.peaks_xyz = numpy.take(peaks_xyz, ind, axis=1)
gr.sc = numpy.take(sc, ind)
gr.fc = numpy.take(fc, ind)
gr.om = numpy.take(self.scandata[s].omega, ind)
gr.npks = len(gr.ind)
self.set_translation(g, s)
try:
sign = self.parameterobj.parameters['omegasign']
except:
sign = 1.0
tth, eta = transform.compute_tth_eta_from_xyz(
gr.peaks_xyz,
omega=gr.om * sign,
**self.parameterobj.parameters)
self.scandata[s].tth_per_grain[ind] = tth
self.scandata[s].eta_per_grain[ind] = eta
self.grains[(g, s)] = gr
if not quiet:
print "Grain", g, "Scan", s, "npks=", len(ind)
#print 'x',gr.x[:10]
# Compute the total integrated intensity if we have enough
# information available
compute_lp_factor(self.scandata[s])
for g in self.grainnames:
gr = self.grains[(g, s)]
gr.intensity_info = compute_total_intensity(
self.scandata[s],
gr.ind,
self.intensity_tth_range,
quiet=quiet)
if not quiet:
print "End second grain loop", time.time() - start
print
start = time.time()
wedge = np.radians(float(pars.get("wedge")))
chi = np.radians(float(pars.get("chi")))
wvln = float(pars.get("wavelength"))
c = columnfile( colfile )
try:
sf = c.sc,c.fc
except:
sf = c.xc,c.yc
# c.nrows = 2
# c.bigarray = c.bigarray[:,:2]
print (c.bigarray.shape)
c.set_attributes()
XL = flatfloat( compute_xyz_lab( sf , **pars.parameters ).T )
om = flatfloat( np.radians(c.omega ))
# XL[0,:]=[41,42,43]
grains = read_grain_file( grainfile )
UBIs = flatfloat( [ g.ubi for g in grains ], shape=(len(grains),3,3) )
UBs = flatfloat( [ np.linalg.inv(g.ubi) for g in grains ], shape=(len(grains),3,3) )
Ts = flatfloat( [ g.translation for g in grains ], shape=(len(grains),3))
labels = np.zeros( c.nrows, np.int32 )
hkls = np.zeros( ( c.nrows, 3 ), NPREAL )
print( XL.shape)
except:
pixv=2048.
pixh=2048.
mm=1
v = (pixv-1)/2.
h = (pixh-1)/2.
print("Getting parameters from",parfile)
p = parameters.parameters()
p.loadparameters(parfile)
pars = p.get_parameters()
xyz = np.transpose(
transform.compute_xyz_lab([[v],[h]],
**pars))
ks = list(pars.keys())
ks.sort()
for k in ks:
print(k,pars[k])
print()
print("central pixel position")
print("detector vertical",v,"horizontal",h)
print("real space x, y, z = ", xyz)
print("\n")
print("detector %i %i %0.4f %0.4f %0.4f %0.4f %0.4f %0.4f %0.4f %0.4f stem format %i %i %i %i" % \
(pixv,
pixh,
mm*pars['y_size'],
