def compute_target(self, compute_gradients):
target_and_grads = self.geometry_restraints.energies_sites(
sites_cart = self.xray_structure.sites_cart(),
compute_gradients = True)
self.f = target_and_grads.target
if(compute_gradients):
#self.g = target_and_grads.gradients.as_double()
self.grads = target_and_grads.gradients
# -----------------------------------------------------
# if use_riding hydrogen, modify the gradients
if self.use_riding:
modify_gradients.modify_gradients(
sites_cart = self.xray_structure.sites_cart(),
h_parameterization = self.h_parameterization,
grads = self.grads)
# -----------------------------------------------------
self.g = self.grads.as_double()
def exercise(pdb_str, eps):
mon_lib_srv = monomer_library.server.server()
ener_lib = monomer_library.server.ener_lib()
processed_pdb_file = monomer_library.pdb_interpretation.process(
mon_lib_srv = mon_lib_srv,
ener_lib = ener_lib,
raw_records = pdb_str,
force_symmetry = True)
pdb_hierarchy = processed_pdb_file.all_chain_proxies.pdb_hierarchy
xray_structure = processed_pdb_file.xray_structure()
sites_cart = xray_structure.sites_cart()
geometry = processed_pdb_file.geometry_restraints_manager(
show_energies = False,
plain_pairs_radius = 5.0)
es = geometry.energies_sites(
sites_cart = sites_cart,
compute_gradients = True)
g_analytical = es.gradients
#
riding_h_manager = riding.manager(
pdb_hierarchy = pdb_hierarchy,
geometry_restraints = geometry)
h_parameterization = riding_h_manager.h_parameterization
riding_h_manager.idealize_hydrogens_inplace(
pdb_hierarchy=pdb_hierarchy,
xray_structure=xray_structure)
#sites_cart = pdb_hierarchy.atoms().extract_xyz()
sites_cart = xray_structure.sites_cart()
#for i in g_analytical:
# print i
#print '----------'
g_analytical = geometry.energies_sites(
sites_cart = sites_cart, compute_gradients = True).gradients
modify_gradients.modify_gradients(
sites_cart = sites_cart,
h_parameterization = h_parameterization,
grads = g_analytical)
#
ex = [eps,0,0]
ey = [0,eps,0]
ez = [0,0,eps]
g_fd = flex.vec3_double()
for i_site in xrange(sites_cart.size()):
g_fd_i = []
for e in [ex,ey,ez]:
ts = []
for sign in [-1,1]:
sites_cart_ = sites_cart.deep_copy()
xray_structure_ = xray_structure.deep_copy_scatterers()
sites_cart_[i_site] = [
sites_cart_[i_site][j]+e[j]*sign for j in xrange(3)]
xray_structure_.set_sites_cart(sites_cart_)
# after shift, recalculate H position
riding_h_manager.idealize_hydrogens_inplace(
xray_structure=xray_structure_)
sites_cart_ = xray_structure_.sites_cart()
ts.append(geometry.energies_sites(
sites_cart = sites_cart_,
compute_gradients = False).target)
g_fd_i.append((ts[1]-ts[0])/(2*eps))
g_fd.append(g_fd_i)
for g1, g2 in zip(g_analytical, g_fd):
#print g1,g2
assert approx_equal(g1,g2, 1.e-4)