def test_weights():
from scitbx import matrix
from dials.algorithms.profile_model.modeller import SingleSampler
scan_range = (2, 12)
nz = 2
sampler = SingleSampler(scan_range, nz)
# Check the weight at the coord in 1.0
eps = 1e-7
for i in range(len(sampler)):
coord = sampler.coord(i)
weight = sampler.weight(i, 0, coord)
assert abs(weight - 1.0) < eps
# Ensure we get the expected weight at the next grid point at half way
# between grid points
expected = math.exp(-4.0 * math.log(2.0))
for k in range(nz):
coord1 = matrix.col(sampler.coord(k))
if k > 0:
coord = matrix.col(sampler.coord(k - 1))
weight = sampler.weight(k, 0, coord)
assert abs(weight - expected) < eps
weight = sampler.weight(k, 0, (coord + coord1) / 2.0)
assert abs(weight - 0.5) < eps
if k < nz - 1:
coord = matrix.col(sampler.coord(k + 1))
weight = sampler.weight(k, 0, coord)
assert abs(weight - expected) < eps
weight = sampler.weight(k, 0, (coord + coord1) / 2.0)
assert abs(weight - 0.5) < eps
def test_self_consistent():
from dials.algorithms.profile_model.modeller import SingleSampler
scan_range = (2, 12)
nz = 2
sampler = SingleSampler(scan_range, nz)
for i in range(len(sampler)):
coord = sampler.coord(i)
index = sampler.nearest(0, coord)
assert index == i
def test_self_consistent():
from dials.algorithms.profile_model.modeller import SingleSampler
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nz = 2
sampler = SingleSampler(scan_range, nz)
for i in range(len(sampler)):
coord = sampler.coord(i)
index = sampler.nearest(0, coord)
assert (index == i)
def tst_weights(self):
from dials.algorithms.profile_model.modeller import SingleSampler
from scitbx import matrix
from math import log, exp
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nz = 2
sampler = SingleSampler(scan_range, nz)
# Check the weight at the coord in 1.0
eps = 1e-7
for i in range(len(sampler)):
coord = sampler.coord(i)
weight = sampler.weight(i, 0, coord)
assert abs(weight - 1.0) < eps
# Ensure we get the expected weight at the next grid point at half way
# between grid points
expected = exp(-4.0 * log(2.0))
for k in range(nz):
coord1 = matrix.col(sampler.coord(k))
if k > 0:
coord = matrix.col(sampler.coord(k - 1))
weight = sampler.weight(k, 0, coord)
assert abs(weight - expected) < eps
weight = sampler.weight(k, 0, (coord + coord1) / 2.0)
assert abs(weight - 0.5) < eps
if k < nz - 1:
coord = matrix.col(sampler.coord(k + 1))
weight = sampler.weight(k, 0, coord)
assert abs(weight - expected) < eps
weight = sampler.weight(k, 0, (coord + coord1) / 2.0)
assert abs(weight - 0.5) < eps
print "OK"
def tst_weights(self):
from dials.algorithms.profile_model.modeller import SingleSampler
from scitbx import matrix
from math import log, exp
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nz = 2
sampler = SingleSampler(scan_range, nz)
# Check the weight at the coord in 1.0
eps = 1e-7
for i in range(len(sampler)):
coord = sampler.coord(i)
weight = sampler.weight(i, 0, coord)
assert (abs(weight - 1.0) < eps)
# Ensure we get the expected weight at the next grid point at half way
# between grid points
expected = exp(-4.0 * log(2.0))
for k in range(nz):
coord1 = matrix.col(sampler.coord(k))
if k > 0:
coord = matrix.col(sampler.coord(k - 1))
weight = sampler.weight(k, 0, coord)
assert (abs(weight - expected) < eps)
weight = sampler.weight(k, 0, (coord + coord1) / 2.0)
assert (abs(weight - 0.5) < eps)
if k < nz - 1:
coord = matrix.col(sampler.coord(k + 1))
weight = sampler.weight(k, 0, coord)
assert (abs(weight - expected) < eps)
weight = sampler.weight(k, 0, (coord + coord1) / 2.0)
assert (abs(weight - 0.5) < eps)
print 'OK'
def tst_self_consistent(self):
from dials.algorithms.profile_model.modeller import SingleSampler
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nz = 2
sampler = SingleSampler(scan_range, nz)
for i in range(len(sampler)):
coord = sampler.coord(i)
index = sampler.nearest(coord)
assert(index == i)
print 'OK'
def test_indexing():
from dials.algorithms.profile_model.modeller import SingleSampler
width = 1000
height = 1000
scan_range = (2, 12)
nz = 2
sampler = SingleSampler(scan_range, nz)
zstep = sampler.step_size()
zind = list(range(nz))
xp = [width * 0.5 for k in range(nz)]
yp = [height * 0.5 for k in range(nz)]
zp = [(z + 0.5) * zstep + scan_range[0] for z in zind]
eps = 1e-10
for x0, y0, z0, i in zip(xp, yp, zp, range(len(sampler))):
x1, y1, z1 = sampler.coord(i)
assert abs(z0 - z1) <= eps
def tst_indexing(self):
from dials.algorithms.profile_model.modeller import SingleSampler
width = 1000
height = 1000
scan_range = (2, 12)
depth = scan_range[1] - scan_range[0]
nz = 2
sampler = SingleSampler(scan_range, nz)
zstep = sampler.step_size()
zind = [k for k in range(nz)]
xp = [width *0.5 for k in range(nz)]
yp = [height *0.5 for k in range(nz)]
zp = [(z + 0.5) * zstep + scan_range[0] for z in zind]
eps = 1e-10
for x0, y0, z0, i in zip(xp, yp, zp, range(len(sampler))):
x1, y1, z1 = sampler.coord(i)
assert(abs(z0 - z1) <= eps)
print 'OK'
