def test_nearest():
from dials.algorithms.profile_model.modeller import GridSampler
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nx = 10
ny = 10
nz = 2
sampler = GridSampler((width, height), scan_range, (nx, ny, nz))
for i in range(1000):
x = random.uniform(0, 1000)
y = random.uniform(0, 1000)
z = random.uniform(*scan_range)
i = int(math.floor(x / (width / nx)))
j = int(math.floor(y / (height / ny)))
k = int(math.floor((z - scan_range[0]) / (depth / nz)))
if i >= nx:
i = nx - 1
if j >= ny:
j = ny - 1
if k >= nz:
k = nz - 1
index0 = i + j * nx + k * nx * ny
index1 = sampler.nearest(0, (x, y, z))
assert index0 == index1
def tst_nearest(self):
from random import uniform
from dials.algorithms.profile_model.modeller import GridSampler
from math import floor
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nx = 10
ny = 10
nz = 2
sampler = GridSampler((width, height), scan_range, (nx, ny, nz))
for i in range(1000):
x = uniform(0, 1000)
y = uniform(0, 1000)
z = uniform(*scan_range)
i = int(floor(x / (width / nx)))
j = int(floor(y / (height / ny)))
k = int(floor((z-scan_range[0]) / (depth / nz)))
if i >= nx:
i = nx - 1
if j >= ny:
j = ny - 1
if k >= nz:
k = nz - 1
index0 = i + j * nx + k * nx * ny
index1 = sampler.nearest((x, y, z))
assert(index0 == index1)
print 'OK'
def compute_profile(experiments, reflection, reference, N):
from dials.array_family import flex
from dials.algorithms.profile_model.gaussian_rs import CoordinateSystem
from dials.algorithms.profile_model.modeller import GridSampler
from dials_scratch.jmp.sim import compute_profile_internal
from random import uniform
sbox = reflection["shoebox"]
bbox = sbox.bbox
zs = sbox.zsize()
ys = sbox.ysize()
xs = sbox.xsize()
profile = flex.double(flex.grid(zs, ys, xs))
m2 = experiments[0].goniometer.get_rotation_axis_datum()
s0 = experiments[0].beam.get_s0()
s1 = reflection["s1"]
phi = reflection["xyzcal.mm"][2]
detector = experiments[0].detector
scan = experiments[0].scan
cs = CoordinateSystem(m2, s0, s1, phi)
scan_range = scan.get_array_range()
image_size = detector[0].get_image_size()
grid_size = (3, 3, 40)
assert grid_size[0] * grid_size[1] * grid_size[2] == len(reference[0])
sampler = GridSampler(image_size, scan_range, grid_size)
xyz = reflection["xyzcal.px"]
index = sampler.nearest(0, xyz)
for g in reference[0]:
assert abs(flex.sum(g) - 1.0) < 1e-7
grid = reference[0][index]
sigma_d = experiments[0].profile.sigma_b(deg=False)
sigma_m = experiments[0].profile.sigma_m(deg=False)
delta_d = 3.0 * sigma_d
delta_m = 3.0 * sigma_m
profile = compute_profile_internal(grid, bbox, zs, ys, xs, N, delta_d,
delta_m, detector, scan, cs)
# from dials_scratch.jmp.viewer import show_image_stack_multi_view
# show_image_stack_multi_view(profile.as_numpy_array(), vmax=max(profile))
sum_p = flex.sum(profile)
print("Partiality: %f" % sum_p)
try:
assert sum_p > 0, "sum_p == 0"
except Exception as e:
print(e)
return None
return profile
def test_self_consistent():
from dials.algorithms.profile_model.modeller import GridSampler
width = 1000
height = 1000
scan_range = (2, 12)
nx = 10
ny = 10
nz = 2
sampler = GridSampler((width, height), scan_range, (nx, ny, nz))
for i in range(len(sampler)):
coord = sampler.coord(i)
index = sampler.nearest(0, coord)
assert index == i
def tst_self_consistent(self):
from dials.algorithms.profile_model.modeller import GridSampler
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nx = 10
ny = 10
nz = 2
sampler = GridSampler((width, height), scan_range, (nx, ny, nz))
for i in range(len(sampler)):
coord = sampler.coord(i)
index = sampler.nearest(coord)
assert(index == i)
print 'OK'
