def tst_with_flat_background(self):
from dials.algorithms.integration.fit import fit_profile
from scitbx.array_family import flex
from tst_profile_helpers import gaussian
# Create profile
p = gaussian((9, 9, 9), 1, (4, 4, 4), (2, 2, 2))
s = flex.sum(p)
p = p / s
# Copy profile
c0 = gaussian((9, 9, 9), 1, (4, 4, 4), (2, 2, 2))
b = flex.double(flex.grid(9, 9, 9), 5)
m = flex.bool(flex.grid(9,9,9), True)
c = c0 + b
# Fit
fit = fit_profile(p, m, c, b)
I = fit.intensity()
V = fit.variance()
# Test intensity is the same
eps = 1e-7
assert(abs(I - flex.sum(c0)) < eps)
assert(abs(V - (flex.sum(c0) + flex.sum(b))) < eps)
print 'OK'
def tst_with_flat_background_partial(self):
from dials.algorithms.integration.fit import fit_profile
from scitbx.array_family import flex
from tst_profile_helpers import gaussian
# Create profile
p = gaussian((9, 9, 9), 1, (4, 4, 4), (2, 2, 2))
s = flex.sum(p)
p = p / s
# Copy profile
c0 = gaussian((9, 9, 9), 1, (4, 4, 4), (2, 2, 2))
b = flex.double(flex.grid(9, 9, 9), 5)
m = flex.bool(flex.grid(9,9,9), True)
c = c0 + b
# Get the partial profiles
pp = p[0:5,:,:]
mp = m[0:5,:,:]
cp = c[0:5,:,:]
bp = b[0:5,:,:]
c0p = c0[0:5,:,:]
# Fit
fit = fit_profile(pp, mp, cp, bp)
I = fit.intensity()
V = fit.variance()
# Test intensity is the same
eps = 1e-7
assert(abs(I - flex.sum(c0)) < eps)
assert(abs(V - (flex.sum(c0p) + flex.sum(bp))) < eps)
print 'OK'
def tst_identical(self):
from dials.algorithms.integration.fit import fit_profile
from scitbx.array_family import flex
from tst_profile_helpers import gaussian
# Create profile
p = gaussian((9, 9, 9), 1, (4, 4, 4), (2, 2, 2))
s = flex.sum(p)
p = p / s
# Copy profile
c = p.deep_copy()
b = flex.double(flex.grid(9, 9, 9), 0)
m = flex.bool(flex.grid(9,9,9), True)
# Fit
fit = fit_profile(p, m, c, b)
I = fit.intensity()
V = fit.variance()
# Test intensity is the same
eps = 1e-7
assert(abs(I - flex.sum(p)) < eps)
assert(abs(V - I) < eps)
print 'OK'
def generate_single_central_non_negative_profiles(self):
from dials.array_family import flex
from tst_profile_helpers import gaussian
rlist = flex.reflection_table(1)
profile = gaussian(self.grid_size, 1000, (4, 4, 4), (1.5, 1.5, 1.5))
x = 500
y = 500
z = 5
xyz = flex.vec3_double(1)
xyz[0] = (x, y, z)
profiles = [ profile.deep_copy() ]
rlist['xyzcal.px'] = xyz
return rlist, profiles, profile
def generate_single_central_non_negative_profiles(self):
from dials.array_family import flex
from tst_profile_helpers import gaussian
rlist = flex.reflection_table(1)
profile = gaussian(self.grid_size, 1000, (4, 4, 4), (1.5, 1.5, 1.5))
x = 500
y = 500
z = 5
xyz = flex.vec3_double(1)
xyz[0] = (x, y, z)
profiles = [profile.deep_copy()]
rlist["xyzcal.px"] = xyz
return rlist, profiles, profile
def generate_identical_non_negative_profiles(self):
from dials.array_family import flex
from random import uniform
from tst_profile_helpers import gaussian
rlist = flex.reflection_table(1000)
profile = gaussian(self.grid_size, 1000, (4, 4, 4), (1.5, 1.5, 1.5))
xyz = flex.vec3_double(1000)
profiles = []
for i in range(1000):
x = uniform(0, 1000)
y = uniform(0, 1000)
z = uniform(0, 10)
xyz[i] = (x, y, z)
profiles.append(profile.deep_copy())
rlist['xyzcal.px'] = xyz
return rlist, profiles, profile
def generate_identical_non_negative_profiles(self):
from dials.array_family import flex
from random import uniform
from tst_profile_helpers import gaussian
rlist = flex.reflection_table(1000)
profile = gaussian(self.grid_size, 1000, (4, 4, 4), (1.5, 1.5, 1.5))
xyz = flex.vec3_double(1000)
profiles = []
for i in range(1000):
x = uniform(0, 1000)
y = uniform(0, 1000)
z = uniform(0, 10)
xyz[i] = (x, y, z)
profiles.append(profile.deep_copy())
rlist["xyzcal.px"] = xyz
return rlist, profiles, profile
def generate_systematically_offset_profiles(self):
from dials.array_family import flex
from random import uniform
from tst_profile_helpers import gaussian
rlist = flex.reflection_table(1000)
xyz = flex.vec3_double(1000)
profiles = []
for i in range(1000):
x = uniform(0, 1000)
y = uniform(0, 1000)
z = uniform(0, 10)
offset = -4.5 + 9 * x / 1000.0
profile = gaussian(self.grid_size, 1000, (4 + offset, 4, 4), (1.5, 1.5, 1.5))
xyz[i] = (x, y, z)
profiles.append(profile)
rlist["xyzcal.px"] = xyz
return rlist, profiles
def generate_systematically_offset_profiles(self):
from dials.array_family import flex
from random import uniform
from tst_profile_helpers import gaussian
rlist = flex.reflection_table(1000)
xyz = flex.vec3_double(1000)
profiles = []
for i in range(1000):
x = uniform(0, 1000)
y = uniform(0, 1000)
z = uniform(0, 10)
offset = -4.5 + 9 * x / 1000.0
profile = gaussian(self.grid_size, 1000,
(4 + offset, 4, 4), (1.5, 1.5, 1.5))
xyz[i] = (x, y, z)
profiles.append(profile)
rlist['xyzcal.px'] = xyz
return rlist, profiles
