def callback_after_step(self, minimizer):
if self.verbose > 0:
print "xray.minimization step: f,iter,nfun:",
print self.f, minimizer.iter(), minimizer.nfun()
if self.verbose > 1 and self.reference_structure is not None:
xray.meaningful_site_cart_differences(
self.xray_structure, self.reference_structure).show()
def check_refinement_stability(self):
if not self.shall_refine_thermal_displacements:
for sc in self.xray_structure.scatterers():
sc.flags.set_grad_site(True)
if sc.flags.use_u_aniso(): sc.flags.set_grad_u_aniso(False)
if sc.flags.use_u_iso(): sc.flags.set_grad_u_iso(False)
xs = self.xray_structure
xs0 = self.reference_xray_structure = xs.deep_copy_scatterers()
mi = xs0.build_miller_set(anomalous_flag=False, d_min=0.5)
fo_sq = mi.structure_factors_from_scatterers(
xs0, algorithm="direct").f_calc().norm()
fo_sq = fo_sq.customized_copy(sigmas=flex.double(fo_sq.size(), 1))
xs.shake_sites_in_place(rms_difference=0.1)
if self.shall_refine_thermal_displacements:
# a spread of 10 for u_iso's would be enormous for our low temperature
# test structures if those u_iso's were not constrained
xs.shake_adp(
spread=10, # absolute
aniso_spread=0.2) # relative
self.reparametrisation = constraints.reparametrisation(
xs,
self.constraints,
self.connectivity_table,
temperature=self.t_celsius)
obs = fo_sq.as_xray_observations()
ls = least_squares.crystallographic_ls(
obs,
self.reparametrisation,
weighting_scheme=least_squares.mainstream_shelx_weighting())
self.cycles = self.normal_eqns_solving_method(ls)
print("%i %s iterations to recover from shaking" %
(self.cycles.n_iterations, self.cycles))
if 0:
from crys3d.qttbx.xray_structure_viewer import display
display(xray_structure=xs)
diff = xray.meaningful_site_cart_differences(xs0, xs)
assert diff.max_absolute() < self.site_refinement_tolerance,\
self.__class__.__name__
if self.shall_refine_thermal_displacements:
delta_u = []
for sc, sc0 in itertools.izip(xs.scatterers(), xs0.scatterers()):
if not sc.flags.use_u_aniso() or not sc0.flags.use_u_aniso():
continue
delta_u.extend(matrix.col(sc.u_star) - matrix.col(sc0.u_star))
delta_u = flex.double(delta_u)
assert flex.max_absolute(delta_u) < self.u_star_refinement_tolerance,\
self.__class__.__name__
def check_refinement_stability(self):
if not self.shall_refine_thermal_displacements:
for sc in self.xray_structure.scatterers():
sc.flags.set_grad_site(True)
if sc.flags.use_u_aniso(): sc.flags.set_grad_u_aniso(False)
if sc.flags.use_u_iso(): sc.flags.set_grad_u_iso(False)
xs = self.xray_structure
xs0 = self.reference_xray_structure = xs.deep_copy_scatterers()
mi = xs0.build_miller_set(anomalous_flag=False, d_min=0.5)
fo_sq = mi.structure_factors_from_scatterers(
xs0, algorithm="direct").f_calc().norm()
fo_sq = fo_sq.customized_copy(sigmas=flex.double(fo_sq.size(), 1))
xs.shake_sites_in_place(rms_difference=0.1)
if self.shall_refine_thermal_displacements:
# a spread of 10 for u_iso's would be enormous for our low temperature
# test structures if those u_iso's were not constrained
xs.shake_adp(spread=10, # absolute
aniso_spread=0.2) # relative
self.reparametrisation = constraints.reparametrisation(
xs, self.constraints, self.connectivity_table,
temperature=self.t_celsius)
obs = fo_sq.as_xray_observations()
ls = least_squares.crystallographic_ls(
obs,
self.reparametrisation,
weighting_scheme=least_squares.mainstream_shelx_weighting())
self.cycles = self.normal_eqns_solving_method(ls)
print ("%i %s iterations to recover from shaking"
% (self.cycles.n_iterations,
self.cycles))
if 0:
from crys3d.qttbx.xray_structure_viewer import display
display(xray_structure=xs)
diff = xray.meaningful_site_cart_differences(xs0, xs)
assert diff.max_absolute() < self.site_refinement_tolerance,\
self.__class__.__name__
if self.shall_refine_thermal_displacements:
delta_u = []
for sc, sc0 in itertools.izip(xs.scatterers(), xs0.scatterers()):
if not sc.flags.use_u_aniso() or not sc0.flags.use_u_aniso(): continue
delta_u.extend(matrix.col(sc.u_star) - matrix.col(sc0.u_star))
delta_u = flex.double(delta_u)
assert flex.max_absolute(delta_u) < self.u_star_refinement_tolerance,\
self.__class__.__name__
def exercise_constrained_lbfgs(xray_structure,
constraints_list,
t_celsius,
d_min=0.5,
shake_sites_rmsd=0.5,
shake_u_iso_spread=0,
shake_u_aniso_spread=0,
grad_site=True,
grad_u_iso=True,
grad_u_aniso=False,
grad_occupancy=False,
grad_fp_fdp=False,
lbfgs_m=5,
lbfgs_max_iterations=1000,
verbose=0):
xs = xray_structure
xray.set_scatterer_grad_flags(scatterers=xs.scatterers(),
site=grad_site,
u_iso=grad_u_iso,
u_aniso=grad_u_aniso,
occupancy=grad_occupancy,
fp=grad_fp_fdp,
fdp=grad_fp_fdp,
tan_u_iso=False,
param=0)
xs0 = xs.deep_copy_scatterers()
mi = xs0.build_miller_set(anomalous_flag=False, d_min=d_min)
fo_sq = mi.structure_factors_from_scatterers(
xs0, algorithm="direct").f_calc().norm()
fo_sq = fo_sq.customized_copy(sigmas=flex.double(fo_sq.size(), 1))
fo_sq.set_observation_type_xray_intensity()
y_obs = fo_sq
#y_obs = fo_sq.f_sq_as_f()
if grad_site:
xs.shake_sites_in_place(rms_difference=shake_sites_rmsd)
if not grad_u_aniso: shake_u_aniso_spread = 0
if not grad_u_iso: shake_u_iso_spread = 0
if grad_u_aniso or grad_u_iso:
xs.shake_adp(spread=shake_u_iso_spread,
aniso_spread=shake_u_aniso_spread)
xs1 = xs.deep_copy_scatterers()
core_params = scitbx.lbfgs.core_parameters(m=lbfgs_m,
maxfev=100,
xtol=1e-5)
connectivity_table = smtbx.utils.connectivity_table(xs0)
if constraints_list is None:
from smtbx.development import generate_hydrogen_constraints
constraints_list = generate_hydrogen_constraints(
structure=xs0, connectivity_table=connectivity_table)
reparametrisation = constraints.reparametrisation(xs,
constraints_list,
connectivity_table,
temperature=t_celsius)
lbfgs_termination_params = scitbx.lbfgs.termination_parameters(
traditional_convergence_test=False,
drop_convergence_test_max_drop_eps=1.e-20,
drop_convergence_test_iteration_coefficient=1,
min_iterations=500,
max_iterations=lbfgs_max_iterations)
minimizer = lbfgs(
target_functor=xray.target_functors.unified_least_squares_residual(
y_obs),
xray_structure=xs,
reparametrisation=reparametrisation,
structure_factor_algorithm="direct",
lbfgs_termination_params=lbfgs_termination_params,
lbfgs_core_params=core_params,
reference_structure=xs0,
verbose=verbose)
if verbose > 0:
print "Total parameters: ", xs.n_parameters()
print "Independent parameters: ", reparametrisation.n_independents
print "Reference model: "
xs0.show_angles(distance_cutoff=1.5)
print
print "Starting model: "
xs1.show_angles(distance_cutoff=1.5)
print
print "Refined model: "
xs.show_angles(distance_cutoff=1.5)
print
print "n_iter, n_fun: ", minimizer.minimizer.iter(
), minimizer.minimizer.nfun()
h_selection = xs.element_selection('H')
diff = xray.meaningful_site_cart_differences(
xs0.select(h_selection, negate=True),
xs.select(h_selection, negate=True))
#diff = xray.meaningful_site_cart_differences(xs0, xs)
#assert diff.max_absolute() < 1e-3
if verbose > 0:
diff.show()
print
assert diff.max_absolute() < 2e-2, diff.max_absolute()
diff = xray.meaningful_site_cart_differences(xs0, xs)
if verbose > 0:
diff.show()
print
# XXX why does this tolerance have to be so high?
assert diff.max_absolute() < 0.5, diff.max_absolute()
def exercise_constrained_lbfgs(xray_structure,
constraints_list,
t_celsius,
d_min=0.5,
shake_sites_rmsd=0.5,
shake_u_iso_spread=0,
shake_u_aniso_spread=0,
grad_site=True,
grad_u_iso=True,
grad_u_aniso=False,
grad_occupancy=False,
grad_fp_fdp=False,
lbfgs_m=5,
lbfgs_max_iterations=1000,
verbose=0):
xs = xray_structure
xray.set_scatterer_grad_flags(scatterers=xs.scatterers(),
site=grad_site,
u_iso=grad_u_iso,
u_aniso=grad_u_aniso,
occupancy=grad_occupancy,
fp=grad_fp_fdp,
fdp=grad_fp_fdp,
tan_u_iso=False,
param=0)
xs0 = xs.deep_copy_scatterers()
mi = xs0.build_miller_set(anomalous_flag=False, d_min=d_min)
fo_sq = mi.structure_factors_from_scatterers(
xs0, algorithm="direct").f_calc().norm()
fo_sq = fo_sq.customized_copy(sigmas=flex.double(fo_sq.size(), 1))
fo_sq.set_observation_type_xray_intensity()
y_obs = fo_sq
#y_obs = fo_sq.f_sq_as_f()
if grad_site:
xs.shake_sites_in_place(rms_difference=shake_sites_rmsd)
if not grad_u_aniso: shake_u_aniso_spread = 0
if not grad_u_iso: shake_u_iso_spread = 0
if grad_u_aniso or grad_u_iso:
xs.shake_adp(spread=shake_u_iso_spread, aniso_spread=shake_u_aniso_spread)
xs1 = xs.deep_copy_scatterers()
core_params = scitbx.lbfgs.core_parameters(m=lbfgs_m, maxfev=100, xtol=1e-5)
connectivity_table = smtbx.utils.connectivity_table(xs0)
if constraints_list is None:
from smtbx.development import generate_hydrogen_constraints
constraints_list = generate_hydrogen_constraints(
structure=xs0, connectivity_table=connectivity_table)
reparametrisation = constraints.reparametrisation(
xs,
constraints_list,
connectivity_table,
temperature=t_celsius)
lbfgs_termination_params=scitbx.lbfgs.termination_parameters(
traditional_convergence_test=False,
drop_convergence_test_max_drop_eps=1.e-20,
drop_convergence_test_iteration_coefficient=1,
min_iterations=500,
max_iterations=lbfgs_max_iterations)
minimizer = lbfgs(
target_functor=xray.target_functors.unified_least_squares_residual(y_obs),
xray_structure=xs,
reparametrisation=reparametrisation,
structure_factor_algorithm="direct",
lbfgs_termination_params=lbfgs_termination_params,
lbfgs_core_params=core_params,
reference_structure=xs0,
verbose=verbose)
if verbose > 0:
print "Total parameters: ", xs.n_parameters()
print "Independent parameters: ", reparametrisation.n_independents
print "Reference model: "
xs0.show_angles(distance_cutoff=1.5)
print
print "Starting model: "
xs1.show_angles(distance_cutoff=1.5)
print
print "Refined model: "
xs.show_angles(distance_cutoff=1.5)
print
print "n_iter, n_fun: ", minimizer.minimizer.iter(), minimizer.minimizer.nfun()
h_selection = xs.element_selection('H')
diff = xray.meaningful_site_cart_differences(
xs0.select(h_selection, negate=True),
xs.select(h_selection, negate=True))
#diff = xray.meaningful_site_cart_differences(xs0, xs)
#assert diff.max_absolute() < 1e-3
if verbose > 0:
diff.show()
print
assert diff.max_absolute() < 2e-2, diff.max_absolute()
diff = xray.meaningful_site_cart_differences(xs0, xs)
if verbose > 0:
diff.show()
print
# XXX why does this tolerance have to be so high?
assert diff.max_absolute() < 0.5, diff.max_absolute()
def callback_after_step(self, minimizer):
if self.verbose > 0:
print "xray.minimization step: f,iter,nfun:",
print self.f,minimizer.iter(),minimizer.nfun()
if self.verbose > 1 and self.reference_structure is not None:
xray.meaningful_site_cart_differences(self.xray_structure, self.reference_structure).show()
