def get_tardy_model_no_density():
tardy_tree = scitbx.graph.tardy_tree.construct(
n_vertices=len(sites), edge_list=[])
tardy_tree.build_tree()
potential_obj = potential_object(
density_map=None,
geo_manager=geo_manager,
reduced_geo_manager=None,
prolsq_repulsion_function_changes=
params.prolsq_repulsion_function_changes,
real_space_gradients_delta=None,
real_space_target_weight=None,
ideal_sites_cart=None)
return scitbx.rigid_body.tardy_model(
labels=labels,
sites=sites,
masses=masses,
tardy_tree=tardy_tree,
potential_obj=potential_obj)
def run_test(params, pdb_files, other_files, callback=None, log=None):
if (log is None): log = sys.stdout
if (params.random_seed is not None):
random.seed(params.random_seed)
flex.set_random_seed(value=params.random_seed)
#
if (len(pdb_files) != 0):
print >> log, "PDB files:"
for file_name in pdb_files:
print >> log, " ", file_name
print >> log
if (len(other_files) != 0):
print >> log, "Other files:"
for file_name in other_files:
print >> log, " ", file_name
print >> log
#
assert len(pdb_files) in [1, 2]
#
pdb_interpretation_params = pdb_interpretation.master_params.extract()
pdb_interpretation_params.dihedral_function_type \
= params.dihedral_function_type
processed_pdb_files = pdb_interpretation.run(
args=pdb_files[-1:]+other_files,
params=pdb_interpretation_params,
strict_conflict_handling=False,
substitute_non_crystallographic_unit_cell_if_necessary=True,
return_all_processed_pdb_files=True,
log=log)
assert len(processed_pdb_files) == 1
print >> log
#
xs = processed_pdb_files[0].xray_structure()
geo_manager = processed_pdb_files[0].geometry_restraints_manager()
labels = [sc.label for sc in xs.scatterers()]
ideal_sites_cart = xs.sites_cart()
sites = ideal_sites_cart
masses = xs.atomic_weights()
tardy_tree_simple_connectivity = geo_manager.construct_tardy_tree(sites=sites)
rmsd_calculator = tardy_tree_simple_connectivity.rmsd_calculator()
#
if (params.tardy_displacements is not None):
def get_tardy_model_no_potential():
return scitbx.rigid_body.tardy_model(
labels=labels,
sites=sites,
masses=masses,
tardy_tree=tardy_tree_simple_connectivity,
potential_obj=None)
def get_tardy_model_no_density():
tardy_tree = scitbx.graph.tardy_tree.construct(
n_vertices=len(sites), edge_list=[])
tardy_tree.build_tree()
potential_obj = potential_object(
density_map=None,
geo_manager=geo_manager,
reduced_geo_manager=None,
prolsq_repulsion_function_changes=
params.prolsq_repulsion_function_changes,
real_space_gradients_delta=None,
real_space_target_weight=None,
ideal_sites_cart=None)
return scitbx.rigid_body.tardy_model(
labels=labels,
sites=sites,
masses=masses,
tardy_tree=tardy_tree,
potential_obj=potential_obj)
if (params.tardy_displacements is Auto):
auto_params = params.tardy_displacements_auto
target_rmsd = \
params.structure_factors_high_resolution \
* auto_params.rmsd_vs_high_resolution_factor
target_rmsd_tol = \
params.structure_factors_high_resolution \
* auto_params.rmsd_tolerance
assert target_rmsd > 0
assert target_rmsd_tol > 0
print >> log, "Random displacements (%s):" \
% params.tardy_displacements_auto.parameterization
print >> log, " high resolution: %.6g" \
% params.structure_factors_high_resolution
print >> log, " target rmsd: %.6g" % target_rmsd
print >> log, " target rmsd tolerance: %.6g" % target_rmsd_tol
log.flush()
def raise_max_steps_exceeded(var_name, rmsd_history):
msg = [
"tardy_displacements_auto.max_steps exceeded:",
" % -13s rmsd" % var_name]
for var_rmsd in rmsd_history:
msg.append(" %13.6e %13.6e" % var_rmsd)
raise Sorry("\n".join(msg))
if (params.tardy_displacements_auto.parameterization == "cartesian"):
multiplier = 1.5
rmsd_history = []
for i_step in xrange(auto_params.max_steps):
sites = cartesian_random_displacements(
sites_cart=ideal_sites_cart,
target_rmsd=target_rmsd*multiplier)
tardy_model = get_tardy_model_no_density()
tardy_model.minimization(max_iterations=20)
sites = tardy_model.sites_moved()
sites_moved = sites
rmsd = rmsd_calculator(sites_moved, ideal_sites_cart)
rmsd_history.append((multiplier, rmsd))
print >> log, " multiplier, rmsd: %13.6e, %13.6e" \
% rmsd_history[-1]
log.flush()
if (rmsd < target_rmsd - target_rmsd_tol):
if (rmsd != 0):
multiplier = min(
multiplier*2, max(
multiplier*1.2,
target_rmsd / rmsd))
else:
multiplier *= 2
else:
if (rmsd <= target_rmsd + target_rmsd_tol):
tardy_model.minimization(max_iterations=500)
sites = tardy_model.sites_moved()
sites_moved = sites
rmsd = rmsd_calculator(sites_moved, ideal_sites_cart)
rmsd_history.append((0, rmsd))
print >> log, " multiplier, rmsd: %13.6e, %13.6e" \
% rmsd_history[-1]
log.flush()
break
multiplier *= max(0.5, target_rmsd/rmsd)
else:
raise_max_steps_exceeded(
var_name="multiplier", rmsd_history=rmsd_history)
del rmsd_history
print >> log, " actual rmsd: %.6g" % rmsd
print >> log
elif (params.tardy_displacements_auto.parameterization == "constrained"):
tardy_model = get_tardy_model_no_potential()
tardy_model.assign_random_velocities()
delta_t = auto_params.first_delta_t
rmsd_history = []
assert auto_params.max_steps > 0
for i_step in xrange(auto_params.max_steps):
prev_q = tardy_model.pack_q()
prev_qd = tardy_model.pack_qd()
tardy_model.dynamics_step(delta_t=delta_t)
sites_moved = tardy_model.sites_moved()
rmsd = rmsd_calculator(sites_moved, ideal_sites_cart)
rmsd_history.append((delta_t, rmsd))
if (rmsd < target_rmsd - target_rmsd_tol):
delta_t *= 2 - rmsd / target_rmsd
else:
if (rmsd <= target_rmsd + target_rmsd_tol):
break
tardy_model.unpack_q(q_packed=prev_q)
tardy_model.unpack_qd(qd_packed=prev_qd)
delta_t *= 0.5
prev_q = None
prev_qd = None
else:
raise_max_steps_exceeded(
var_name="delta_t", rmsd_history=rmsd_history)
del rmsd_history
print >> log, " actual rmsd: %.6g" % rmsd
print >> log, " tardy_displacements=%s" % ",".join(
["%.6g" % v for v in tardy_model.pack_q()])
print >> log
sites = tardy_model.sites_moved()
else:
raise AssertionError
else:
tardy_model = get_tardy_model_no_potential()
q = tardy_model.pack_q()
if (len(params.tardy_displacements) != len(q)):
print >> log, "tardy_displacements:", params.tardy_displacements
hinge_edges = tardy_model.tardy_tree.cluster_manager.hinge_edges
assert len(hinge_edges) == tardy_model.bodies_size()
dofej = tardy_model.degrees_of_freedom_each_joint()
qsej = tardy_model.q_size_each_joint()
for ib,(i,j) in enumerate(hinge_edges):
if (i == -1): si = "root"
else: si = tardy_model.labels[i]
sj = tardy_model.labels[j]
print >> log, "%21s - %-21s: %d dof, %d q_size" % (
si, sj, dofej[ib], qsej[ib])
print >> log, "Zero displacements:"
print >> log, " tardy_displacements=%s" % ",".join(
[str(v) for v in q])
raise Sorry("Incompatible tardy_displacements.")
tardy_model.unpack_q(q_packed=flex.double(params.tardy_displacements))
sites = tardy_model.sites_moved()
#
if (params.emulate_cartesian):
tardy_tree = scitbx.graph.tardy_tree.construct(
n_vertices=len(sites), edge_list=[])
tardy_tree.build_tree()
else:
tardy_tree = tardy_tree_simple_connectivity
print >> log, "tardy_tree summary:"
tardy_tree.show_summary(vertex_labels=labels, out=log, prefix=" ")
print >> log
#
if (len(pdb_files) == 2):
ideal_pdb_inp = iotbx.pdb.input(file_name=pdb_files[0])
ideal_pdb_hierarchy = ideal_pdb_inp.construct_hierarchy()
assert ideal_pdb_hierarchy.is_similar_hierarchy(
processed_pdb_files[0].all_chain_proxies.pdb_hierarchy)
ideal_sites_cart = ideal_pdb_hierarchy.atoms().extract_xyz()
xs.set_sites_cart(sites_cart=ideal_sites_cart)
fft_map = xs.structure_factors(
d_min=params.structure_factors_high_resolution).f_calc().fft_map()
fft_map.apply_sigma_scaling()
#
assert not params.orca_experiments or not params.emulate_cartesian
if (params.orca_experiments):
from mmtbx.refinement import orca
x = orca.expand(
labels=labels,
sites_cart=sites,
masses=masses,
geo_manager=geo_manager)
labels = x.labels
sites = x.sites_cart
masses = x.masses
geo_manager = x.geo_manager
tardy_tree = x.tardy_tree
x_ideal_sites_cart = flex.vec3_double()
for i_orc,i_seq in x.indices:
x_ideal_sites_cart.append(ideal_sites_cart[i_seq])
ideal_sites_cart = x_ideal_sites_cart
rmsd_calculator = x.rmsd_calculator(
tardy_tree_rmsd_calculator=rmsd_calculator)
#
if (params.emulate_cartesian or params.keep_all_restraints):
reduced_geo_manager = None
else:
reduced_geo_manager = geo_manager.reduce_for_tardy(tardy_tree=tardy_tree)
real_space_gradients_delta = \
params.structure_factors_high_resolution \
* params.real_space_gradients_delta_resolution_factor
potential_obj = potential_object(
density_map=fft_map.real_map(),
geo_manager=geo_manager,
reduced_geo_manager=reduced_geo_manager,
prolsq_repulsion_function_changes=params.prolsq_repulsion_function_changes,
real_space_gradients_delta=real_space_gradients_delta,
real_space_target_weight=params.real_space_target_weight,
ideal_sites_cart=ideal_sites_cart,
site_labels=labels,
orca_experiments=params.orca_experiments)
tardy_model = scitbx.rigid_body.tardy_model(
labels=labels,
sites=sites,
masses=masses,
tardy_tree=tardy_tree,
potential_obj=potential_obj)
mmtbx.refinement.tardy.action(
tardy_model=tardy_model,
params=params,
rmsd_calculator=rmsd_calculator,
callback=callback,
log=log)
print >> log
