def regression_test():
"""Perform a regression test by comparing to indices generating
by the brute force method used in the Use Case."""
from rstbx.diffraction import rotation_angles
from rstbx.diffraction import full_sphere_indices
from cctbx.sgtbx import space_group, space_group_symbols
from cctbx.uctbx import unit_cell
# cubic, 50A cell, 1A radiation, 1 deg osciillation, everything ideal
a = 50.0
ub_beg = matrix.sqr(
(1.0 / a, 0.0, 0.0, 0.0, 1.0 / a, 0.0, 0.0, 0.0, 1.0 / a))
axis = matrix.col((0, 1, 0))
r_osc = matrix.sqr(
scitbx.math.r3_rotation_axis_and_angle_as_matrix(axis=axis,
angle=1.0,
deg=True))
ub_end = r_osc * ub_beg
uc = unit_cell((a, a, a, 90, 90, 90))
sg = space_group(space_group_symbols('P23').hall())
s0 = matrix.col((0, 0, 1))
wavelength = 1.0
dmin = 1.5
indices = full_sphere_indices(unit_cell=uc,
resolution_limit=dmin,
space_group=sg)
ra = rotation_angles(dmin, ub_beg, wavelength, axis)
obs_indices, obs_angles = ra.observed_indices_and_angles_from_angle_range(
phi_start_rad=0.0 * pi / 180.0,
phi_end_rad=1.0 * pi / 180.0,
indices=indices)
r = reeke_model(ub_beg, ub_end, axis, s0, dmin, 1.0)
reeke_indices = r.generate_indices()
#r.visualize_with_rgl()
for oi in obs_indices:
assert (tuple(map(int, oi)) in reeke_indices)
#TODO Tests for an oblique cell
print "OK"
def regression_test():
"""Perform a regression test by comparing to indices generating
by the brute force method used in the Use Case."""
from rstbx.diffraction import rotation_angles
from rstbx.diffraction import full_sphere_indices
from cctbx.sgtbx import space_group, space_group_symbols
from cctbx.uctbx import unit_cell
# cubic, 50A cell, 1A radiation, 1 deg osciillation, everything ideal
a = 50.0
ub_beg = matrix.sqr((1.0 / a, 0.0, 0.0, 0.0, 1.0 / a, 0.0, 0.0, 0.0, 1.0 / a))
axis = matrix.col((0, 1, 0))
r_osc = matrix.sqr(scitbx.math.r3_rotation_axis_and_angle_as_matrix(axis=axis, angle=1.0, deg=True))
ub_end = r_osc * ub_beg
uc = unit_cell((a, a, a, 90, 90, 90))
sg = space_group(space_group_symbols("P23").hall())
s0 = matrix.col((0, 0, 1))
wavelength = 1.0
dmin = 1.5
indices = full_sphere_indices(unit_cell=uc, resolution_limit=dmin, space_group=sg)
ra = rotation_angles(dmin, ub_beg, wavelength, axis)
obs_indices, obs_angles = ra.observed_indices_and_angles_from_angle_range(
phi_start_rad=0.0 * pi / 180.0, phi_end_rad=1.0 * pi / 180.0, indices=indices
)
r = reeke_model(ub_beg, ub_end, axis, s0, dmin, 1.0)
reeke_indices = r.generate_indices()
# r.visualize_with_rgl()
for oi in obs_indices:
assert tuple(map(int, oi)) in reeke_indices
# TODO Tests for an oblique cell
print "OK"
def test_versus_brute_force():
"""Perform a regression test by comparing to indices generated by the brute
force method"""
# cubic, 50A cell, 1A radiation, 1 deg osciillation, everything ideal
a = 50.0
ub_beg = matrix.sqr(
(1.0 / a, 0.0, 0.0, 0.0, 1.0 / a, 0.0, 0.0, 0.0, 1.0 / a))
axis = matrix.col((0, 1, 0))
r_osc = matrix.sqr(
r3_rotation_axis_and_angle_as_matrix(axis=axis, angle=1.0, deg=True))
ub_end = r_osc * ub_beg
uc = unit_cell((a, a, a, 90, 90, 90))
sg = space_group(space_group_symbols("P23").hall())
s0 = matrix.col((0, 0, 1))
wavelength = 1.0
dmin = 1.5
# get the full set of indices
indices = full_sphere_indices(unit_cell=uc,
resolution_limit=dmin,
space_group=sg)
# find the observed indices
ra = rotation_angles(dmin, ub_beg, wavelength, axis)
obs_indices, obs_angles = ra.observed_indices_and_angles_from_angle_range(
phi_start_rad=0.0 * math.pi / 180.0,
phi_end_rad=1.0 * math.pi / 180.0,
indices=indices,
)
# r = reeke_model(ub_beg, ub_end, axis, s0, dmin, 1.0)
# reeke_indices = r.generate_indices()
# now try the Reeke method to generate indices
r = ReekeIndexGenerator(ub_beg,
ub_end,
sg.type(),
axis,
s0,
dmin,
margin=1)
reeke_indices = r.to_array()
for oi in obs_indices:
assert tuple(map(int, oi)) in reeke_indices
def predict_observations(self):
'''Actually perform the prediction calculations.'''
d2r = math.pi / 180.0
cfc = coordinate_frame_converter(self._configuration_file)
self.img_start, self.osc_start, self.osc_range = parse_xds_xparm_scan_info(
self._configuration_file)
if self._dmin is None:
self._dmin = cfc.derive_detector_highest_resolution()
phi_start = ((self._img_range[0] - self.img_start) * self.osc_range + \
self.osc_start) * d2r
phi_end = ((self._img_range[1] - self.img_start + 1) * self.osc_range + \
self.osc_start) * d2r
self.phi_start_rad = phi_start
self.phi_end_rad = phi_end
# in principle this should come from the crystal model - should that
# crystal model record the cell parameters or derive them from the
# axis directions?
A = cfc.get_c('real_space_a')
B = cfc.get_c('real_space_b')
C = cfc.get_c('real_space_c')
cell = (A.length(), B.length(), C.length(), B.angle(C, deg = True),
C.angle(A, deg = True), A.angle(B, deg = True))
self.uc = unit_cell(cell)
# generate all of the possible indices, then pull out those which should
# be systematically absent
sg = cfc.get('space_group_number')
indices = full_sphere_indices(
unit_cell = self.uc,
resolution_limit = self._dmin,
space_group = space_group(space_group_symbols(sg).hall()))
# then get the UB matrix according to the Rossmann convention which
# is used within the Labelit code.
u, b = cfc.get_u_b(convention = cfc.ROSSMANN)
axis = cfc.get('rotation_axis', convention = cfc.ROSSMANN)
ub = u * b
wavelength = cfc.get('wavelength')
self.wavelength = wavelength
# work out which reflections should be observed (i.e. pass through the
# Ewald sphere)
ra = rotation_angles(self._dmin, ub, wavelength, axis)
obs_indices, obs_angles = ra.observed_indices_and_angles_from_angle_range(
phi_start_rad = phi_start,
phi_end_rad = phi_end,
indices = indices)
# convert all of these to full scattering vectors in a laboratory frame
# (for which I will use the CBF coordinate frame) and calculate which
# will intersect with the detector
u, b = cfc.get_u_b()
axis = cfc.get_c('rotation_axis')
# must guarantee that sample_to_source vector is normalized so that
# s0 has length of 1/wavelength.
sample_to_source_vec = cfc.get_c('sample_to_source').normalize()
s0 = (- 1.0 / wavelength) * sample_to_source_vec
ub = u * b
# need some detector properties for this as well... starting to
# abstract these to a detector model.
df = detector_factory_from_cfc(cfc)
d = df.build()
# the Use Case assumes the detector consists of a single sensor
sensor = d.sensors()[0]
self.pixel_size_fast, self.pixel_size_slow = d.px_size_fast(), \
d.px_size_slow()
# used for polarization correction
self.distance = sensor.distance
rp = reflection_prediction(axis, s0, ub, sensor)
if self._rocking_curve is not None:
assert self._rocking_curve != "none"
rp.set_rocking_curve(self._rocking_curve)
rp.set_mosaicity(self._mosaicity_deg, degrees = True)
return rp.predict(obs_indices, obs_angles)
def predict_observations(self):
'''Actually perform the prediction calculations.'''
d2r = math.pi / 180.0
cfc = coordinate_frame_converter(self._configuration_file)
self.img_start, self.osc_start, self.osc_range = parse_xds_xparm_scan_info(
self._configuration_file)
if self._dmin is None:
self._dmin = cfc.derive_detector_highest_resolution()
phi_start = ((self._img_range[0] - self.img_start) * self.osc_range + \
self.osc_start) * d2r
phi_end = ((self._img_range[1] - self.img_start + 1) * self.osc_range + \
self.osc_start) * d2r
self.phi_start_rad = phi_start
self.phi_end_rad = phi_end
# in principle this should come from the crystal model - should that
# crystal model record the cell parameters or derive them from the
# axis directions?
A = cfc.get_c('real_space_a')
B = cfc.get_c('real_space_b')
C = cfc.get_c('real_space_c')
cell = (A.length(), B.length(), C.length(), B.angle(C, deg = True),
C.angle(A, deg = True), A.angle(B, deg = True))
self.uc = unit_cell(cell)
# generate all of the possible indices, then pull out those which should
# be systematically absent
sg = cfc.get('space_group_number')
indices = full_sphere_indices(
unit_cell = self.uc,
resolution_limit = self._dmin,
space_group = space_group(space_group_symbols(sg).hall()))
# then get the UB matrix according to the Rossmann convention which
# is used within the Labelit code.
u, b = cfc.get_u_b(convention = cfc.ROSSMANN)
axis = cfc.get('rotation_axis', convention = cfc.ROSSMANN)
ub = u * b
wavelength = cfc.get('wavelength')
self.wavelength = wavelength
# work out which reflections should be observed (i.e. pass through the
# Ewald sphere)
ra = rotation_angles(self._dmin, ub, wavelength, axis)
obs_indices, obs_angles = ra.observed_indices_and_angles_from_angle_range(
phi_start_rad = phi_start,
phi_end_rad = phi_end,
indices = indices)
# convert all of these to full scattering vectors in a laboratory frame
# (for which I will use the CBF coordinate frame) and calculate which
# will intersect with the detector
u, b = cfc.get_u_b()
axis = cfc.get_c('rotation_axis')
# must guarantee that sample_to_source vector is normalized so that
# s0 has length of 1/wavelength.
sample_to_source_vec = cfc.get_c('sample_to_source').normalize()
s0 = (- 1.0 / wavelength) * sample_to_source_vec
ub = u * b
# need some detector properties for this as well... starting to
# abstract these to a detector model.
df = detector_factory_from_cfc(cfc)
d = df.build()
# the Use Case assumes the detector consists of a single sensor
sensor = d.sensors()[0]
self.pixel_size_fast, self.pixel_size_slow = d.px_size_fast(), \
d.px_size_slow()
# used for polarization correction
self.distance = sensor.distance
rp = reflection_prediction(axis, s0, ub, sensor)
if self._rocking_curve is not None:
assert self._rocking_curve != "none"
rp.set_rocking_curve(self._rocking_curve)
rp.set_mosaicity(self._mosaicity_deg, degrees = True)
return rp.predict(obs_indices, obs_angles)
def regenerate_predictions_brute(xds_integrate_hkl_file, phi_range):
from rstbx.cftbx.coordinate_frame_converter import coordinate_frame_converter
from rstbx.diffraction import rotation_angles
from rstbx.diffraction import full_sphere_indices
from cctbx.sgtbx import space_group, space_group_symbols
from cctbx.uctbx import unit_cell
import math
cfc = coordinate_frame_converter(xds_integrate_hkl_file)
d2r = math.pi / 180.0
dmin = cfc.derive_detector_highest_resolution()
A = cfc.get_c('real_space_a')
B = cfc.get_c('real_space_b')
C = cfc.get_c('real_space_c')
cell = (A.length(), B.length(), C.length(), B.angle(C, deg = True),
C.angle(A, deg = True), A.angle(B, deg = True))
uc = unit_cell(cell)
sg = cfc.get('space_group_number')
indices = full_sphere_indices(
unit_cell = uc,
resolution_limit = dmin,
space_group = space_group(space_group_symbols(sg).hall()))
u, b = cfc.get_u_b(convention = cfc.ROSSMANN)
axis = cfc.get('rotation_axis', convention = cfc.ROSSMANN)
ub = u * b
wavelength = cfc.get('wavelength')
ra = rotation_angles(dmin, ub, wavelength, axis)
obs_indices, obs_angles = ra.observed_indices_and_angles_from_angle_range(
phi_start_rad = phi_range[0] * d2r,
phi_end_rad = phi_range[1] * d2r,
indices = indices)
# in here work in internal (i.e. not Rossmann) coordinate frame
u, b = cfc.get_u_b()
axis = cfc.get_c('rotation_axis')
sample_to_source_vec = cfc.get_c('sample_to_source').normalize()
s0 = (- 1.0 / wavelength) * sample_to_source_vec
ub = u * b
detector_origin = cfc.get_c('detector_origin')
detector_fast = cfc.get_c('detector_fast')
detector_slow = cfc.get_c('detector_slow')
detector_normal = detector_fast.cross(detector_slow)
distance = detector_origin.dot(detector_normal.normalize())
nx, ny = cfc.get('detector_size_fast_slow')
px, py = cfc.get('detector_pixel_size_fast_slow')
limits = [0, nx * px, 0, ny * py]
xyz_to_hkl = { }
for hkl, angle in zip(obs_indices, obs_angles):
s = (ub * hkl).rotate(axis, angle)
q = (s + s0).normalize()
# check if diffracted ray parallel to detector face
q_dot_n = q.dot(detector_normal)
if q_dot_n == 0:
continue
r = (q * distance / q_dot_n) - detector_origin
x = r.dot(detector_fast)
y = r.dot(detector_slow)
if x < limits[0] or y < limits[2]:
continue
if x > limits[1] or y > limits[3]:
continue
xyz = (x, y, angle / d2r)
xyz_to_hkl[xyz] = map(int, hkl)
return xyz_to_hkl
mybeam = beam_factory.make_beam(direction, 1.5)
# make a random P1 crystal
a = random.uniform(10, 20) * random_direction_close_to(matrix.col((1, 0, 0)))
b = random.uniform(10, 20) * random_direction_close_to(matrix.col((0, 1, 0)))
c = random.uniform(10, 20) * random_direction_close_to(matrix.col((0, 0, 1)))
crystal_model(a, b, c, space_group_symbol="P 1")
# make a dumb goniometer that rotates around X
mygonio = goniometer_factory.known_axis((1, 0, 0))
# generate some indices
resolution = 2.0
indices = full_sphere_indices(
unit_cell=mycrystal.get_unit_cell(),
resolution_limit=resolution,
space_group=space_group(space_group_symbols(1).hall()),
)
# generate list of phi values
R_to_rossmann = align_reference_frame(
mybeam.get_unit_s0(), (0.0, 0.0, 1.0), mygonio.get_rotation_axis(), (0.0, 1.0, 0.0)
)
ra = rotation_angles(
resolution,
R_to_rossmann * mycrystal.get_U() * mycrystal.get_B(),
mybeam.get_wavelength(),
R_to_rossmann * matrix.col(mygonio.get_rotation_axis()),
)
direction = random_direction_close_to(matrix.col((0, 0, 1)))
mybeam = beam_factory.make_beam(direction, 1.5)
# make a random P1 crystal
a = random.uniform(10,20) * random_direction_close_to(matrix.col((1, 0, 0)))
b = random.uniform(10,20) * random_direction_close_to(matrix.col((0, 1, 0)))
c = random.uniform(10,20) * random_direction_close_to(matrix.col((0, 0, 1)))
crystal_model(a, b, c, space_group_symbol="P 1")
# make a dumb goniometer that rotates around X
mygonio = goniometer_factory.known_axis((1, 0, 0))
# generate some indices
resolution = 2.0
indices = full_sphere_indices(
unit_cell = mycrystal.get_unit_cell(),
resolution_limit = resolution,
space_group = space_group(space_group_symbols(1).hall()))
# generate list of phi values
R_to_rossmann = align_reference_frame(
mybeam.get_unit_s0(), (0.0, 0.0, 1.0),
mygonio.get_rotation_axis(), (0.0, 1.0, 0.0))
ra = rotation_angles(resolution,
R_to_rossmann * mycrystal.get_U() * mycrystal.get_B(),
mybeam.get_wavelength(),
R_to_rossmann * matrix.col(mygonio.get_rotation_axis()))
obs_indices_rstbx, obs_angles_rstbx = \
ra.observed_indices_and_angles_from_angle_range(
phi_start_rad = 0.0, phi_end_rad = math.pi, indices = indices)
