def tst_nearest_n(self):
from math import sqrt, atan2, pi, floor
from random import uniform
from dials.algorithms.profile_model.modeller import CircleSampler
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nz = 2
sampler = CircleSampler((width, height), scan_range, nz)
xc, yc = sampler.image_centre()
r1 = sampler.r1()
for i in range(1000):
x = uniform(0, 1000)
y = uniform(0, 1000)
z = uniform(scan_range[0], scan_range[1])
r = sqrt((x - xc)**2 + (y - yc)**2)
if r < r1:
index00 = 0
else:
t = atan2(y - yc, x - xc)
ai = int(floor(t * 8 / (2 * pi) + 0.5)) % 8
index00 = ai + 1
index01 = int((z-scan_range[0]) * nz / depth)
if index01 < 0:
index01 = 0
if index01 >= 2:
index01 = 1
index0 = index00 + index01 * 9
index1 = sampler.nearest_n(0, (x, y, z))
assert(index0 == index1[0])
if index0 % 9 == 0:
assert(len(index1) == 9)
assert(all(idx == index0 + i for i, idx in enumerate(index1)))
else:
assert(len(index1) == 4)
assert(index1[1] == (index0 // 9) * 9)
if (index0 % 9) == 1:
assert(index1[2] == index0 + 1)
assert(index1[3] == index0 + 7)
elif (index0 % 9) == 8:
assert(index1[2] == index0 - 7)
assert(index1[3] == index0 - 1)
else:
assert(index1[2] == index0 + 1)
assert(index1[3] == index0 - 1)
print 'OK'
def tst_nearest_n(self):
from math import sqrt, atan2, pi, floor
from random import uniform
from dials.algorithms.profile_model.modeller import CircleSampler
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nz = 2
sampler = CircleSampler((width, height), scan_range, nz)
xc, yc = sampler.image_centre()
r1 = sampler.r1()
for i in range(1000):
x = uniform(0, 1000)
y = uniform(0, 1000)
z = uniform(scan_range[0], scan_range[1])
r = sqrt((x - xc)**2 + (y - yc)**2)
if r < r1:
index00 = 0
else:
t = atan2(y - yc, x - xc)
ai = int(floor(t * 8 / (2 * pi) + 0.5)) % 8
index00 = ai + 1
index01 = int((z - scan_range[0]) * nz / depth)
if index01 < 0:
index01 = 0
if index01 >= 2:
index01 = 1
index0 = index00 + index01 * 9
index1 = sampler.nearest_n((x, y, z))
assert (index0 == index1[0])
if index0 % 9 == 0:
assert (len(index1) == 9)
assert (all(idx == index0 + i for i, idx in enumerate(index1)))
else:
assert (len(index1) == 4)
assert (index1[1] == (index0 // 9) * 9)
if (index0 % 9) == 1:
assert (index1[2] == index0 + 1)
assert (index1[3] == index0 + 7)
elif (index0 % 9) == 8:
assert (index1[2] == index0 - 7)
assert (index1[3] == index0 - 1)
else:
assert (index1[2] == index0 + 1)
assert (index1[3] == index0 - 1)
print 'OK'
def test_nearest_n():
from dials.algorithms.profile_model.modeller import CircleSampler
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nz = 2
sampler = CircleSampler((width, height), scan_range, nz)
xc, yc = sampler.image_centre()
r1 = sampler.r1()
for i in range(1000):
x = random.uniform(0, 1000)
y = random.uniform(0, 1000)
z = random.uniform(scan_range[0], scan_range[1])
r = math.sqrt((x - xc)**2 + (y - yc)**2)
if r < r1:
index00 = 0
else:
t = math.atan2(y - yc, x - xc)
ai = int(math.floor(t * 8 / (2 * math.pi) + 0.5)) % 8
index00 = ai + 1
index01 = int((z - scan_range[0]) * nz / depth)
if index01 < 0:
index01 = 0
if index01 >= 2:
index01 = 1
index0 = index00 + index01 * 9
index1 = sampler.nearest_n(0, (x, y, z))
assert index0 == index1[0]
if index0 % 9 == 0:
assert len(index1) == 9
assert all(idx == index0 + i for i, idx in enumerate(index1))
else:
assert len(index1) == 4
assert index1[1] == (index0 // 9) * 9
if (index0 % 9) == 1:
assert index1[2] == index0 + 1
assert index1[3] == index0 + 7
elif (index0 % 9) == 8:
assert index1[2] == index0 - 7
assert index1[3] == index0 - 1
else:
assert index1[2] == index0 + 1
assert index1[3] == index0 - 1
def compute_reference(experiments, reflections):
from dials.algorithms.profile_model.modeller import CircleSampler
from dials.array_family import flex
from dials.algorithms.profile_model.gaussian_rs.transform import TransformForward
from dials.algorithms.profile_model.gaussian_rs.transform import TransformSpec
from dials.algorithms.profile_model.gaussian_rs import CoordinateSystem
reflections = select_strong(reflections)
print("Selected %d strong spots" % len(reflections))
sampler = CircleSampler(
experiments[0].detector[0].get_image_size(),
experiments[0].scan.get_array_range(),
1,
)
n_sigma = 4.0
grid_size = 25
spec = TransformSpec(
experiments[0].beam,
experiments[0].detector,
experiments[0].goniometer,
experiments[0].scan,
experiments[0].profile.sigma_b(deg=False),
experiments[0].profile.sigma_m(deg=False),
n_sigma,
grid_size,
)
m2 = experiments[0].goniometer.get_rotation_axis()
s0 = experiments[0].beam.get_s0()
reference = [
flex.double(
flex.grid(1 + 2 * grid_size, 1 + 2 * grid_size, 1 + 2 * grid_size))
for i in range(len(sampler))
]
count = [0] * len(sampler)
for r in reflections:
s1 = r["s1"]
phi = r["xyzcal.mm"][2]
xyz = r["xyzcal.px"]
bbox = r["bbox"]
panel = r["panel"]
image = r["shoebox"].data.as_double()
mask = r["shoebox"].mask.as_1d() == 5
mask.reshape(image.accessor())
cs = CoordinateSystem(m2, s0, s1, phi)
try:
transform = TransformForward(spec, cs, bbox, panel, image, mask)
d = transform.profile()
d /= flex.sum(d)
index = sampler.nearest(0, xyz)
indices = sampler.nearest_n(0, xyz)
for i in indices:
w = sampler.weight(i, 0, xyz)
reference[i] += w * d
count[i] += 1
except Exception:
pass
for i in range(len(reference)):
r = reference[i]
if flex.sum(r) > 0:
print(flex.max(r))
g = r.accessor()
r = r.as_1d()
s = r > 0.02 * flex.max(r)
r.set_selected(~s, flex.double(len(r), 0))
r = r / flex.sum(r)
r.reshape(g)
reference[i] = r
for i in range(len(reference)):
from matplotlib import pylab
print(count[i])
r = reference[i]
d = r.as_numpy_array()[11, :, :]
pylab.imshow(d, interpolation="None")
pylab.show()
return reference
