def __init__(self, crystal, Patt, refls, data_image, szx=30, szy=30):
"""
Some tools for jittering the indexing solution
to try and come up with a better solution
THis uses simtbx wrapped into the Patt object
:param crystal: dxtbx crystal
:param Patt: an instance of PatternFactory that has been
primed (Patt.primer has been run)
Note, primer sets the Amatrix, Fcalcs, energy, and flux
:param refls: strong spots, we will simulate there vicinity
and use the simultion overlap as a proxy for indexing
solution quality
:param data_image: the raw data image that is used to compute
overlap
"""
detector = Patt.detector[Patt.panel_id]
self.FS = detector.get_fast_axis()
self.SS = detector.get_slow_axis()
self.A = sqr(crystal.get_A())
self.U = sqr(crystal.get_U())
self.B = sqr(crystal.get_B())
self.s0 = Patt.beam.get_s0()
self.ucell_abc = list(crystal.unit_cell().parameters())[:3]
self.crystal = crystal
self.Patt = Patt
self.data = data_image
self.rois = spot_utils.get_spot_roi(
refls,
dxtbx_image_size=detector.get_image_size(),
szx=szx,
szy=szy)
self.spotX, self.spotY, _ = spot_utils.xyz_from_refl(refls)
self.spot_mask = spot_utils.strong_spot_mask(refls, self.data.shape)
self.counts = spot_utils.count_roi_overlap(self.rois,
img_size=self.data.shape)
if np.any(self.counts > 0):
self.should_norm = True
else:
self.should_norm = False
for p in pts:
path = plt.mpl.path.Path(p)
patch = plt.mpl.patches.PathPatch(path, fc=fc, ec=ec, lw=lw)
patches.append(patch)
return patches
Malls = {}
for pid, img in izip(pids, pan_imgs):
panel = detector[pid]
rois = spot_utils.get_spot_roi(reflsPP[pid],
dxtbx_image_size=panel.get_image_size(),
szx=szx,
szy=szy)
counts = spot_utils.count_roi_overlap(rois, img_size=img.shape)
roi_pp.append(rois)
counts_pp.append(counts)
spot_masks = spot_utils.strong_spot_mask(reflsPP[pid],
img_sh,
as_composite=False)
# composite mask
Mall = np.any(spot_masks, axis=0)
yall, xall = np.where(Mall) # use comp mask to determine the boundary
xlims[pid] = (xall.min() - szx, xall.max() + szx)
ylims[pid] = (yall.max() + szy, yall.min() - szy)