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 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())
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)
