def assignlabels(self):
self.resetlabels()
nr = self.nrows
pks_xyz = np.empty((nr, 3), float)
pks_xyz[:, 0] = self.colf.xl
pks_xyz[:, 1] = self.colf.yl
pks_xyz[:, 2] = self.colf.zl
#print(self.gvecs.shape, pks_xyz.shape)
for i, g in enumerate(self.grains):
if g.translation is None:
t = np.array((0, 0, 0), float)
else:
t = np.array(
(g.translation[0], g.translation[1], g.translation[2]),
float)
cImageD11.compute_gv(pks_xyz, self.colf.omega,
self.colf.parameters.get('omegasign'),
self.colf.parameters.get('wavelength'),
self.colf.parameters.get('wedge'),
self.colf.parameters.get('chi'), t,
self.gvecs)
cImageD11.score_and_assign(g.ubi, self.gvecs, self.tol, self.drlv2,
self.labels, i)
self.colf.labels[:] = self.labels
self.colf.drlv2[:] = self.drlv2
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()
ubis = (np.random.random(9*20).reshape((20,3,3))-0.5)*10
gvf= np.array( testvecs.T, order='F')
tim = time.time
for tol in [0.01, 0.1, 0.2, 0.5]:
int_tmpf = np.zeros( NPK, np.int32 )
drlv2f = np.zeros( NPK, np.float)
start = tim()
for i, gr in enumerate(ubis):
fImageD11.assign( gr, gvf , tol, drlv2f, int_tmpf, i )
end = tim()
fortrantime = end -start
int_tmpc = np.zeros( NPK, np.int32 )
drlv2c = np.zeros( NPK, np.float)
start = tim()
for i, gr in enumerate(ubis):
cImageD11.score_and_assign( gr, testvecs , tol, drlv2c, int_tmpc, i )
end = tim()
ctime = end - start
print "tol","fortrantime",fortrantime,"ctime",ctime
assert np.allclose( drlv2c, drlv2f )
assert (int_tmpc == int_tmpf).all()