def compute(self, reflections):
print("Computing bbox for %d reflections" % len(reflections))
# Compute quantile
quantile = chisq_quantile(2, 0.997)
D = sqrt(quantile) * 2
bbox = flex.int6()
print("ML: %f" % D)
for i in range(len(reflections)):
s1 = matrix.col(reflections[i]["s1"])
s2 = matrix.col(reflections[i]["s2"])
s0 = matrix.col(self.experiment.beam.get_s0())
# Ensure our values are ok
assert s1.length() > 0
sigma = MosaicityParameterisation(self.parameters).sigma()
R = compute_change_of_basis_operation(s0, s2)
S = R * sigma * R.transpose()
mu = R * s2
assert abs(1 - mu.normalize().dot(matrix.col((0, 0, 1)))) < 1e-7
S11 = matrix.sqr((S[0], S[1], S[3], S[4]))
S12 = matrix.col((S[2], S[5]))
S21 = matrix.col((S[6], S[7])).transpose()
S22 = S[8]
mu1 = matrix.col((mu[0], mu[1]))
mu2 = mu[2]
mubar = mu1 + S12 * (1 / S22) * (s0.length() - mu2)
Sbar = S11 - S12 * (1 / S22) * S21
eigen_decomposition = eigensystem.real_symmetric(
Sbar.as_flex_double_matrix())
Q = matrix.sqr(eigen_decomposition.vectors())
L = matrix.diag(eigen_decomposition.values())
max_L = max(L)
delta = sqrt(max_L) * D
p1 = mubar + matrix.col((-delta, -delta))
p2 = mubar + matrix.col((-delta, +delta))
p3 = mubar + matrix.col((+delta, -delta))
p4 = mubar + matrix.col((+delta, +delta))
p1 = matrix.col((p1[0], p1[1], s0.length())).normalize()
p2 = matrix.col((p2[0], p2[1], s0.length())).normalize()
p3 = matrix.col((p3[0], p3[1], s0.length())).normalize()
p4 = matrix.col((p4[0], p4[1], s0.length())).normalize()
x1 = R.transpose() * p1
x2 = R.transpose() * p2
x3 = R.transpose() * p3
x4 = R.transpose() * p4
xy1 = self.experiment.detector[0].get_ray_intersection_px(x1)
xy2 = self.experiment.detector[0].get_ray_intersection_px(x2)
xy3 = self.experiment.detector[0].get_ray_intersection_px(x3)
xy4 = self.experiment.detector[0].get_ray_intersection_px(x4)
xx = (xy1[0], xy2[0], xy3[0], xy4[0])
yy = (xy1[1], xy2[1], xy3[1], xy4[1])
x0, x1 = int(floor(min(xx))) - 1, int(ceil(max(xx))) + 1
y0, y1 = int(floor(min(yy))) - 1, int(ceil(max(yy))) + 1
assert x1 > x0
assert y1 > y0
bbox.append((x0, x1, y0, y1, 0, 1))
reflections["bbox"] = bbox
x0, x1, y0, y1, _, _ = bbox.parts()
xsize, ysize = self.experiment.detector[0].get_image_size()
selection = (x1 > 0) & (y1 > 0) & (x0 < xsize) & (y0 < ysize)
reflections = reflections.select(selection)
print("Filtered reflecions with bbox outside image range")
print("Kept %d reflections" % len(reflections))
return reflections
def compute_sigma22(b1, b2, b3, b4, b5, b6):
model = MosaicityParameterisation((b1, b2, b3, b4, b5, b6))
sigma = model.sigma()
sigmap = R * sigma * R.transpose()
sigma22 = sigmap[8]
return sigma22