def do_exercise(self, verbose=False):
xs = self.xs
indices = self.miller_indices(xs.space_group_info())
exp_i_2pi_functor = cctbx.math_module.cos_sin_table(1024)
custom_fc_sq = (structure_factors.f_calc_modulus_squared(
xs, exp_i_2pi_functor))
std_fc_sq = (structure_factors.f_calc_modulus_squared(xs))
deltas = flex.double()
for h in indices:
custom_fc_sq.linearise(h)
std_fc_sq.linearise(h)
deltas.append(
abs(custom_fc_sq.f_calc - std_fc_sq.f_calc) /
abs(std_fc_sq.f_calc))
stats = median_statistics(deltas)
if verbose:
if not self.has_printed_header:
print("f_calc and sin/cos: |tabulated - std|/|std|")
print("median & median absolute deviation")
self.has_printed_header = True
print("%s: %.12g +/- %.12g" %
(xs.space_group_info().type().hall_symbol(), stats.median,
stats.median_absolute_deviation))
assert stats.median < 0.01, (str(xs.space_group_info()), stats.median)
assert stats.median_absolute_deviation < 0.005, (str(
xs.space_group_info()), stats.median_absolute_deviation)
def exercise_trigonometric_ff():
from math import cos, sin, pi
sgi = sgtbx.space_group_info("P1")
cs = sgi.any_compatible_crystal_symmetry(volume=1000)
miller_set = miller.build_set(cs, anomalous_flag=False, d_min=1)
miller_set = miller_set.select(flex.random_double(miller_set.size()) < 0.2)
for i in range(5):
sites = flex.random_double(9)
x1, x2, x3 = (matrix.col(sites[:3]), matrix.col(sites[3:6]),
matrix.col(sites[6:]))
xs = xray.structure(crystal.special_position_settings(cs))
for x in (x1, x2, x3):
sc = xray.scatterer(site=x, scattering_type="const")
sc.flags.set_grad_site(True)
xs.add_scatterer(sc)
f_sq = structure_factors.f_calc_modulus_squared(xs)
for h in miller_set.indices():
h = matrix.col(h)
phi1, phi2, phi3 = 2 * pi * h.dot(x1), 2 * pi * h.dot(
x2), 2 * pi * h.dot(x3)
fc_mod_sq = 3 + 2 * (cos(phi1 - phi2) + cos(phi2 - phi3) +
cos(phi3 - phi1))
g = []
g.extend(-2 * (sin(phi1 - phi2) - sin(phi3 - phi1)) * 2 * pi * h)
g.extend(-2 * (sin(phi2 - phi3) - sin(phi1 - phi2)) * 2 * pi * h)
g.extend(-2 * (sin(phi3 - phi1) - sin(phi2 - phi3)) * 2 * pi * h)
grad_fc_mod_sq = g
f_sq.linearise(h)
assert approx_equal(f_sq.observable, fc_mod_sq)
assert approx_equal(f_sq.grad_observable, grad_fc_mod_sq)
def exercise_trigonometric_ff():
from math import cos, sin, pi
sgi = sgtbx.space_group_info("P1")
cs = sgi.any_compatible_crystal_symmetry(volume=1000)
miller_set = miller.build_set(cs, anomalous_flag=False, d_min=1)
miller_set = miller_set.select(flex.random_double(miller_set.size()) < 0.2)
for i in xrange(5):
sites = flex.random_double(9)
x1, x2, x3 = (matrix.col(sites[:3]), matrix.col(sites[3:6]), matrix.col(sites[6:]))
xs = xray.structure(crystal.special_position_settings(cs))
for x in (x1, x2, x3):
sc = xray.scatterer(site=x, scattering_type="const")
sc.flags.set_grad_site(True)
xs.add_scatterer(sc)
f_sq = structure_factors.f_calc_modulus_squared(xs)
for h in miller_set.indices():
h = matrix.col(h)
phi1, phi2, phi3 = 2 * pi * h.dot(x1), 2 * pi * h.dot(x2), 2 * pi * h.dot(x3)
fc_mod_sq = 3 + 2 * (cos(phi1 - phi2) + cos(phi2 - phi3) + cos(phi3 - phi1))
g = []
g.extend(-2 * (sin(phi1 - phi2) - sin(phi3 - phi1)) * 2 * pi * h)
g.extend(-2 * (sin(phi2 - phi3) - sin(phi1 - phi2)) * 2 * pi * h)
g.extend(-2 * (sin(phi3 - phi1) - sin(phi2 - phi3)) * 2 * pi * h)
grad_fc_mod_sq = g
f_sq.linearise(h)
assert approx_equal(f_sq.observable, fc_mod_sq)
assert approx_equal(f_sq.grad_observable, grad_fc_mod_sq)
def do_exercise(self, verbose=False):
xs = self.xs
sg = xs.space_group_info().group()
origin_centric_case = sg.is_origin_centric()
indices = self.miller_indices(xs.space_group_info())
f = structure_factors.f_calc_modulus_squared(xs)
f1 = structure_factors.f_calc_modulus_squared(xs)
for h in indices:
f.linearise(h)
fl = f.f_calc
f1.evaluate(h)
fe = f1.f_calc
assert f1.grad_f_calc is None
assert approx_equal_relatively(fe, fl,
relative_error=1e-12), (fe, fl)
if (xs.space_group().is_origin_centric()
and not self.inelastic_scattering):
for h in indices:
f.linearise(h)
assert f.f_calc.imag == 0
assert flex.imag(f.grad_f_calc).all_eq(0)
eta = 1e-8
xs_forward = xs.deep_copy_scatterers()
f_forward = structure_factors.f_calc_modulus_squared(xs_forward)
deltas = flex.double()
for direction in islice(self.structures_forward(xs, xs_forward, eta),
self.n_directions):
for h in indices:
f.linearise(h)
assert approx_equal(abs(f.f_calc)**2, f.observable)
f_forward.linearise(h)
diff_num = (f_forward.observable - f.observable) / eta
diff = f.grad_observable.dot(direction)
delta = abs(1 - diff / diff_num)
deltas.append(delta)
stats = median_statistics(deltas)
tol = 1e-5
assert stats.median < tol, (xs.space_group_info().symbol_and_number(),
stats.median)
assert stats.median_absolute_deviation < tol, (
xs.space_group_info().symbol_and_number(),
stats.median_absolute_deviation)
def do_exercise(self, verbose=False):
xs = self.xs
sg = xs.space_group_info().group()
origin_centric_case = sg.is_origin_centric()
indices = self.miller_indices(xs.space_group_info())
f = structure_factors.f_calc_modulus_squared(xs)
f1 = structure_factors.f_calc_modulus_squared(xs)
for h in indices:
f.linearise(h)
fl = f.f_calc
f1.evaluate(h)
fe = f1.f_calc
assert f1.grad_f_calc is None
assert approx_equal_relatively(fe, fl, relative_error=1e-12), (fe, fl)
if xs.space_group().is_origin_centric() and not self.inelastic_scattering:
for h in indices:
f.linearise(h)
assert f.f_calc.imag == 0
assert flex.imag(f.grad_f_calc).all_eq(0)
eta = 1e-8
xs_forward = xs.deep_copy_scatterers()
f_forward = structure_factors.f_calc_modulus_squared(xs_forward)
deltas = flex.double()
for direction in islice(self.structures_forward(xs, xs_forward, eta), self.n_directions):
for h in indices:
f.linearise(h)
assert approx_equal(abs(f.f_calc) ** 2, f.observable)
f_forward.linearise(h)
diff_num = (f_forward.observable - f.observable) / eta
diff = f.grad_observable.dot(direction)
delta = abs(1 - diff / diff_num)
deltas.append(delta)
stats = median_statistics(deltas)
tol = 1e-3
assert stats.median < tol, (str(space_group_info), stats.median)
assert stats.median_absolute_deviation < tol, (str(space_group_info), stats.median_absolute_deviation)
def do_exercise(self, verbose=False):
xs = self.xs
indices = self.miller_indices(xs.space_group_info())
f = structure_factors.f_calc_modulus(xs)
f_sq = structure_factors.f_calc_modulus_squared(xs)
for h in indices:
f.linearise(h)
f_sq.linearise(h)
assert approx_equal_relatively(f.observable ** 2, f_sq.observable, relative_error=1e-10)
grad_f_sq = f_sq.grad_observable
two_f_grad_f = 2 * f.observable * f.grad_observable
flex.compare_derivatives(two_f_grad_f, grad_f_sq, eps=1e-12)
def do_exercise(self, verbose=False):
xs = self.xs
indices = self.miller_indices(xs.space_group_info())
f = structure_factors.f_calc_modulus(xs)
f_sq = structure_factors.f_calc_modulus_squared(xs)
for h in indices:
f.linearise(h)
f_sq.linearise(h)
assert approx_equal_relatively(f.observable**2,
f_sq.observable,
relative_error=1e-10)
grad_f_sq = f_sq.grad_observable
two_f_grad_f = (2 * f.observable * f.grad_observable)
flex.compare_derivatives(two_f_grad_f, grad_f_sq, eps=1e-12)
def __init__(self, observations, reparametrisation, **kwds):
super(klass, self).__init__(reparametrisation.n_independents)
self.observations = observations
self.reparametrisation = reparametrisation
adopt_optional_init_args(self, kwds)
if self.f_mask is not None:
assert self.f_mask.size() == observations.fo_sq.size()
self.one_h_linearisation = direct.f_calc_modulus_squared(
self.xray_structure)
if self.weighting_scheme == "default":
self.weighting_scheme = self.default_weighting_scheme()
self.origin_fixing_restraint = self.origin_fixing_restraints_type(
self.xray_structure.space_group())
self.taken_step = None
self.restraints_normalisation_factor = None
def do_exercise(self, verbose=False):
xs = self.xs
indices = self.miller_indices(xs.space_group_info())
exp_i_2pi_functor = cctbx.math_module.cos_sin_table(1024)
custom_fc_sq = structure_factors.f_calc_modulus_squared(xs, exp_i_2pi_functor)
std_fc_sq = structure_factors.f_calc_modulus_squared(xs)
deltas = flex.double()
for h in indices:
custom_fc_sq.linearise(h)
std_fc_sq.linearise(h)
deltas.append(abs(custom_fc_sq.f_calc - std_fc_sq.f_calc) / abs(std_fc_sq.f_calc))
stats = median_statistics(deltas)
if verbose:
if not self.has_printed_header:
print "f_calc and sin/cos: |tabulated - std|/|std|"
print "median & median absolute deviation"
self.has_printed_header = True
print "%s: %.12g +/- %.12g" % (
xs.space_group_info().type().hall_symbol(),
stats.median,
stats.median_absolute_deviation,
)
assert stats.median < 0.01, (str(xs.space_group_info()), stats.median)
assert stats.median_absolute_deviation < 0.005, (str(xs.space_group_info()), stats.median_absolute_deviation)
def __init__(self, observations, reparametrisation,
**kwds):
super(crystallographic_ls, self).__init__(reparametrisation.n_independents)
self.observations = observations
self.reparametrisation = reparametrisation
adopt_optional_init_args(self, kwds)
if self.f_mask is not None:
assert self.f_mask.size() == observations.fo_sq.size()
self.one_h_linearisation = direct.f_calc_modulus_squared(
self.xray_structure)
if self.weighting_scheme == "default":
self.weighting_scheme = self.default_weighting_scheme()
self.origin_fixing_restraint = self.origin_fixing_restraints_type(
self.xray_structure.space_group())
self.taken_step = None
self.restraints_normalisation_factor = None
def do_exercise(self, verbose=False):
xs = self.xs
indices = self.miller_indices(xs.space_group_info())
cctbx_structure_factors = xray.structure_factors.from_scatterers_direct(
xray_structure=xs,
miller_set=miller.set(
crystal.symmetry(unit_cell=xs.unit_cell(),
space_group_info=xs.space_group_info()),
indices))
f = structure_factors.f_calc_modulus_squared(xs)
for h, fc in cctbx_structure_factors.f_calc():
f.linearise(h)
if fc == 0:
assert f.f_calc == 0
else:
delta = abs((f.f_calc - fc) / fc)
assert delta < 1e-6
def do_exercise(self, verbose=False):
xs = self.xs
indices = self.miller_indices(xs.space_group_info())
cctbx_structure_factors = xray.structure_factors.from_scatterers_direct(
xray_structure=xs,
miller_set=miller.set(
crystal.symmetry(unit_cell=xs.unit_cell(), space_group_info=xs.space_group_info()), indices
),
)
f = structure_factors.f_calc_modulus_squared(xs)
for h, fc in cctbx_structure_factors.f_calc():
f.linearise(h)
if fc == 0:
assert f.f_calc == 0
else:
delta = abs((f.f_calc - fc) / fc)
assert delta < 1e-6
