def refine_box_with_selected(self, selection=None):
if (selection is None):
selections = self.xray_structure.all_selection()
ph_box = self.pdb_hierarchy.select(selection)
ph_box.atoms().reset_i_seq()
box = mmtbx.utils.extract_box_around_model_and_map(
xray_structure=self.xray_structure.select(selection),
map_data=self.map,
box_cushion=self.atom_radius)
ph_box.adopt_xray_structure(box.xray_structure_box)
group_adp_sel = []
for rg in ph_box.residue_groups():
group_adp_sel.append(rg.atoms().extract_i_seq())
f_obs_box_complex = box.box_map_coefficients(d_min=self.d_min)
f_obs_box = abs(f_obs_box_complex)
#
xrs = box.xray_structure_box.deep_copy_scatterers().set_b_iso(value=0)
assert approx_equal(flex.mean(xrs.extract_u_iso_or_u_equiv()), 0.)
f_calc = f_obs_box.structure_factors_from_scatterers(
xray_structure=xrs).f_calc()
# Get overall B estimate
o = bulk_solvent.complex_f_kb_scaled(
f1=f_obs_box_complex.data(),
f2=f_calc.data(),
b_range=flex.double(range(5, 505, 5)),
ss=1. / flex.pow2(f_calc.d_spacings().data()) / 4.)
#
xrs = xrs.set_b_iso(value=o.b())
f_calc = f_obs_box.structure_factors_from_scatterers(
xray_structure=xrs).f_calc()
k_isotropic = flex.double(f_calc.data().size(), o.k())
fmodel = mmtbx.f_model.manager(f_obs=f_obs_box, xray_structure=xrs)
fmodel.update_core(k_isotropic=k_isotropic)
fmodel.update(target_name="ls_wunit_k1") # Risky?
#
fmodel.update_all_scales(update_f_part1=False,
apply_back_trace=True,
remove_outliers=False)
#
if (self.nproc > 1): log = None
else: log = self.log
group_b_manager = mmtbx.refinement.group.manager(
fmodel=fmodel,
selections=group_adp_sel,
convergence_test=False,
max_number_of_iterations=50,
number_of_macro_cycles=3,
run_finite_differences_test=False,
use_restraints=self.use_adp_restraints,
refine_adp=True,
log=log)
return fmodel.xray_structure.extract_u_iso_or_u_equiv(
) * adptbx.u_as_b(1.)
def map_and_model_to_fmodel(map_data,
xray_structure,
atom_radius,
d_min,
reset_adp=True):
box = mmtbx.utils.extract_box_around_model_and_map(
xray_structure=xray_structure,
map_data=map_data,
box_cushion=atom_radius)
box.apply_mask_inplace(atom_radius=atom_radius)
f_obs_complex = box.box_map_coefficients(d_min=d_min)
f_obs = abs(f_obs_complex)
if (flex.mean(f_obs.data()) < 1.e-6): return None
xrs = box.xray_structure_box.deep_copy_scatterers()
if (reset_adp):
vals_init = xrs.extract_u_iso_or_u_equiv()
xrs = xrs.set_b_iso(value=0)
assert approx_equal(flex.mean(xrs.extract_u_iso_or_u_equiv()), 0.)
f_calc = f_obs.structure_factors_from_scatterers(
xray_structure=xrs).f_calc()
sc = flex.sum(abs(f_obs).data()*abs(f_calc).data())/ \
flex.sum(abs(f_calc).data()*abs(f_calc).data())
f_calc = f_calc.array(data=f_calc.data() * sc)
o = bulk_solvent.complex_f_kb_scaled(
f1=f_obs_complex.data(),
f2=f_calc.data(),
b_range=flex.double(range(5, 505, 5)),
ss=1. / flex.pow2(f_calc.d_spacings().data()) / 4.)
xrs = xrs.set_b_iso(value=o.b())
k_isotropic = flex.double(f_calc.data().size(), o.k())
if (o.k() < 1.e-6):
k_isotropic = flex.double(f_calc.data().size(), 1)
xrs.set_u_iso(values=vals_init)
fmodel = mmtbx.f_model.manager(f_obs=f_obs, xray_structure=xrs)
if (reset_adp):
fmodel.update_core(k_isotropic=k_isotropic)
fmodel.update(target_name="ls_wunit_k1")
fmodel.update_all_scales(update_f_part1=False,
apply_back_trace=True,
remove_outliers=False)
return fmodel