def __init__(self,
u_cart,
u_iso=None,
use_u_aniso=None,
sites_cart=None,
adp_similarity_proxies=None,
rigid_bond_proxies=None,
isotropic_adp_proxies=None,
compute_gradients=True,
gradients_aniso_cart=None,
gradients_iso=None,
disable_asu_cache=False,
normalization=False):
adopt_init_args(self, locals())
self.number_of_restraints = 0
self.residual_sum = 0
self.normalization_factor = None
if (adp_similarity_proxies is not None):
assert u_iso is not None and use_u_aniso is not None
if (rigid_bond_proxies is not None): assert sites_cart is not None
if (sites_cart is not None): assert sites_cart.size() == u_cart.size()
if (u_iso is not None): assert u_iso.size() == u_cart.size()
if (use_u_aniso is not None):
assert use_u_aniso.size() == u_cart.size()
if (compute_gradients):
if (self.gradients_aniso_cart is None):
self.gradients_aniso_cart = flex.sym_mat3_double(
sites_cart.size(), [0, 0, 0, 0, 0, 0])
else:
assert self.gradients_aniso_cart.size() == sites_cart.size()
if (u_iso is not None and self.gradients_iso is None):
self.gradients_iso = flex.double(sites_cart.size(), 0)
elif (u_iso is not None):
assert self.gradients_iso.size() == sites_cart.size()
if (adp_similarity_proxies is None):
self.n_adp_similarity_proxies = None
self.adp_similarity_residual_sum = 0
else:
self.n_adp_similarity_proxies = len(adp_similarity_proxies)
self.adp_similarity_residual_sum = adp_restraints.adp_similarity_residual_sum(
u_cart=u_cart,
u_iso=u_iso,
use_u_aniso=use_u_aniso,
proxies=adp_similarity_proxies,
gradients_aniso_cart=self.gradients_aniso_cart,
gradients_iso=self.gradients_iso)
self.number_of_restraints += 6 * self.n_adp_similarity_proxies
self.residual_sum += self.adp_similarity_residual_sum
if (rigid_bond_proxies is None):
self.n_rigid_bond_proxies = None
self.rigid_bond_residual_sum = 0
else:
self.n_rigid_bond_proxies = len(rigid_bond_proxies)
self.rigid_bond_residual_sum = adp_restraints.rigid_bond_residual_sum(
sites_cart=sites_cart,
u_cart=u_cart,
proxies=rigid_bond_proxies,
gradients_aniso_cart=self.gradients_aniso_cart)
self.number_of_restraints += self.n_rigid_bond_proxies
self.residual_sum += self.rigid_bond_residual_sum
if (isotropic_adp_proxies is None):
self.n_isotropic_adp_proxies = None
self.isotropic_adp_residual_sum = 0
else:
self.n_isotropic_adp_proxies = len(isotropic_adp_proxies)
self.isotropic_adp_residual_sum = adp_restraints.isotropic_adp_residual_sum(
u_cart=u_cart,
proxies=isotropic_adp_proxies,
gradients_aniso_cart=self.gradients_aniso_cart)
self.number_of_restraints += self.n_isotropic_adp_proxies
self.residual_sum += self.isotropic_adp_residual_sum
self.finalize_target_and_gradients()
def exercise_rigid_bond():
i_seqs = (1,2)
weight = 1
p = adp_restraints.rigid_bond_proxy(i_seqs=i_seqs,weight=weight)
assert p.i_seqs == i_seqs
assert p.weight == weight
sites = ((1,2,3),(2,3,4))
u_cart = ((1,2,3,4,5,6), (3,4,5,6,7,8))
expected_gradients = ((-4, -4, -4, -8, -8, -8), (4, 4, 4, 8, 8, 8))
r = adp_restraints.rigid_bond(sites=sites, u_cart=u_cart, weight=weight)
assert r.weight == weight
assert approx_equal(r.delta_z(), -6)
assert approx_equal(r.residual(), 36)
assert approx_equal(r.gradients(), expected_gradients)
sites_cart = flex.vec3_double(((1,2,3),(2,5,4),(3,4,5)))
u_cart = flex.sym_mat3_double(((1,2,3,4,5,6),
(2,3,3,5,7,7),
(3,4,5,3,7,8)))
r = adp_restraints.rigid_bond(
adp_restraint_params(sites_cart=sites_cart, u_cart=u_cart),
proxy=p)
assert approx_equal(r.weight, weight)
unit_cell = uctbx.unit_cell([15,25,30,90,90,90])
sites_frac = unit_cell.fractionalize(sites_cart=sites_cart)
u_star = flex.sym_mat3_double([
adptbx.u_cart_as_u_star(unit_cell, u_cart_i)
for u_cart_i in u_cart])
pair = adp_restraints.rigid_bond_pair(sites_frac[1],
sites_frac[2],
u_star[1],
u_star[2],
unit_cell)
assert approx_equal(pair.delta_z(), abs(r.delta_z()))
assert approx_equal(pair.z_12(), r.z_12())
assert approx_equal(pair.z_21(), r.z_21())
#
gradients_aniso_cart = flex.sym_mat3_double(sites_cart.size(), (0,0,0,0,0,0))
gradients_iso = flex.double(sites_cart.size(), 0)
proxies = adp_restraints.shared_rigid_bond_proxy([p,p])
params = adp_restraint_params(sites_cart=sites_cart, u_cart=u_cart)
residuals = adp_restraints.rigid_bond_residuals(params, proxies=proxies)
assert approx_equal(residuals, (r.residual(),r.residual()))
deltas = adp_restraints.rigid_bond_deltas(params, proxies=proxies)
assert approx_equal(deltas, (r.delta_z(),r.delta_z()))
residual_sum = adp_restraints.rigid_bond_residual_sum(
params=params,
proxies=proxies,
gradients_aniso_cart=gradients_aniso_cart)
assert approx_equal(residual_sum, 2 * r.residual())
for g,e in zip(gradients_aniso_cart[1:3], r.gradients()):
assert approx_equal(g, matrix.col(e)*2)
fd_grads_aniso, fd_grads_iso = finite_difference_gradients(
restraint_type=adp_restraints.rigid_bond,
proxy=p,
sites_cart=sites_cart,
u_cart=u_cart)
for g,e in zip(gradients_aniso_cart, fd_grads_aniso):
assert approx_equal(g, matrix.col(e)*2)
#
# check frame invariance of residual
#
u_cart_1 = matrix.sym(sym_mat3=(0.1,0.2,0.05,0.03,0.02,0.01))
u_cart_2 = matrix.sym(sym_mat3=(0.21,0.32,0.11,0.02,0.02,0.07))
u_cart = (u_cart_1.as_sym_mat3(),u_cart_2.as_sym_mat3())
site_cart_1 = matrix.col((1,2,3))
site_cart_2 = matrix.col((3,1,4.2))
sites = (tuple(site_cart_1),tuple(site_cart_2))
a = adp_restraints.rigid_bond(sites=sites, u_cart=u_cart, weight=1)
expected_residual = a.residual()
gen = flex.mersenne_twister()
for i in range(20):
R = matrix.rec(gen.random_double_r3_rotation_matrix(),(3,3))
u_cart_1_rot = R * u_cart_1 * R.transpose()
u_cart_2_rot = R * u_cart_2 * R.transpose()
u_cart = (u_cart_1_rot.as_sym_mat3(),u_cart_2_rot.as_sym_mat3())
site_cart_1_rot = R * site_cart_1
site_cart_2_rot = R * site_cart_2
sites = (tuple(site_cart_1_rot),tuple(site_cart_2_rot))
a = adp_restraints.rigid_bond(
sites=sites, u_cart=u_cart,
weight=1)
assert approx_equal(a.residual(), expected_residual)
def exercise_rigid_bond():
i_seqs = (1,2)
weight = 1
p = adp_restraints.rigid_bond_proxy(i_seqs=i_seqs,weight=weight)
assert p.i_seqs == i_seqs
assert p.weight == weight
sites = ((1,2,3),(2,3,4))
u_cart = ((1,2,3,4,5,6), (3,4,5,6,7,8))
expected_gradients = ((-4, -4, -4, -8, -8, -8), (4, 4, 4, 8, 8, 8))
r = adp_restraints.rigid_bond(sites=sites, u_cart=u_cart, weight=weight)
assert r.weight == weight
assert approx_equal(r.delta_z(), -6)
assert approx_equal(r.residual(), 36)
assert approx_equal(r.gradients(), expected_gradients)
sites_cart = flex.vec3_double(((1,2,3),(2,5,4),(3,4,5)))
u_cart = flex.sym_mat3_double(((1,2,3,4,5,6),
(2,3,3,5,7,7),
(3,4,5,3,7,8)))
r = adp_restraints.rigid_bond(
adp_restraint_params(sites_cart=sites_cart, u_cart=u_cart),
proxy=p)
assert approx_equal(r.weight, weight)
unit_cell = uctbx.unit_cell([15,25,30,90,90,90])
sites_frac = unit_cell.fractionalize(sites_cart=sites_cart)
u_star = flex.sym_mat3_double([
adptbx.u_cart_as_u_star(unit_cell, u_cart_i)
for u_cart_i in u_cart])
pair = adp_restraints.rigid_bond_pair(sites_frac[1],
sites_frac[2],
u_star[1],
u_star[2],
unit_cell)
assert approx_equal(pair.delta_z(), abs(r.delta_z()))
assert approx_equal(pair.z_12(), r.z_12())
assert approx_equal(pair.z_21(), r.z_21())
#
gradients_aniso_cart = flex.sym_mat3_double(sites_cart.size(), (0,0,0,0,0,0))
gradients_iso = flex.double(sites_cart.size(), 0)
proxies = adp_restraints.shared_rigid_bond_proxy([p,p])
params = adp_restraint_params(sites_cart=sites_cart, u_cart=u_cart)
residuals = adp_restraints.rigid_bond_residuals(params, proxies=proxies)
assert approx_equal(residuals, (r.residual(),r.residual()))
deltas = adp_restraints.rigid_bond_deltas(params, proxies=proxies)
assert approx_equal(deltas, (r.delta_z(),r.delta_z()))
residual_sum = adp_restraints.rigid_bond_residual_sum(
params=params,
proxies=proxies,
gradients_aniso_cart=gradients_aniso_cart)
assert approx_equal(residual_sum, 2 * r.residual())
for g,e in zip(gradients_aniso_cart[1:3], r.gradients()):
assert approx_equal(g, matrix.col(e)*2)
fd_grads_aniso, fd_grads_iso = finite_difference_gradients(
restraint_type=adp_restraints.rigid_bond,
proxy=p,
sites_cart=sites_cart,
u_cart=u_cart)
for g,e in zip(gradients_aniso_cart, fd_grads_aniso):
assert approx_equal(g, matrix.col(e)*2)
#
# check frame invariance of residual
#
u_cart_1 = matrix.sym(sym_mat3=(0.1,0.2,0.05,0.03,0.02,0.01))
u_cart_2 = matrix.sym(sym_mat3=(0.21,0.32,0.11,0.02,0.02,0.07))
u_cart = (u_cart_1.as_sym_mat3(),u_cart_2.as_sym_mat3())
site_cart_1 = matrix.col((1,2,3))
site_cart_2 = matrix.col((3,1,4.2))
sites = (tuple(site_cart_1),tuple(site_cart_2))
a = adp_restraints.rigid_bond(sites=sites, u_cart=u_cart, weight=1)
expected_residual = a.residual()
gen = flex.mersenne_twister()
for i in range(20):
R = matrix.rec(gen.random_double_r3_rotation_matrix(),(3,3))
u_cart_1_rot = R * u_cart_1 * R.transpose()
u_cart_2_rot = R * u_cart_2 * R.transpose()
u_cart = (u_cart_1_rot.as_sym_mat3(),u_cart_2_rot.as_sym_mat3())
site_cart_1_rot = R * site_cart_1
site_cart_2_rot = R * site_cart_2
sites = (tuple(site_cart_1_rot),tuple(site_cart_2_rot))
a = adp_restraints.rigid_bond(
sites=sites, u_cart=u_cart,
weight=1)
assert approx_equal(a.residual(), expected_residual)
def __init__(self, u_cart,
u_iso=None,
use_u_aniso=None,
sites_cart=None,
adp_similarity_proxies=None,
rigid_bond_proxies=None,
isotropic_adp_proxies=None,
compute_gradients=True,
gradients_aniso_cart=None,
gradients_iso=None,
disable_asu_cache=False,
normalization=False):
adopt_init_args(self, locals())
self.number_of_restraints = 0
self.residual_sum = 0
self.normalization_factor = None
if (adp_similarity_proxies is not None):
assert u_iso is not None and use_u_aniso is not None
if (rigid_bond_proxies is not None): assert sites_cart is not None
if (sites_cart is not None): assert sites_cart.size() == u_cart.size()
if (u_iso is not None): assert u_iso.size() == u_cart.size()
if (use_u_aniso is not None): assert use_u_aniso.size() == u_cart.size()
if (compute_gradients):
if (self.gradients_aniso_cart is None):
self.gradients_aniso_cart = flex.sym_mat3_double(
sites_cart.size(), [0,0,0,0,0,0])
else:
assert self.gradients_aniso_cart.size() == sites_cart.size()
if (u_iso is not None and self.gradients_iso is None):
self.gradients_iso = flex.double(sites_cart.size(), 0)
elif (u_iso is not None):
assert self.gradients_iso.size() == sites_cart.size()
if (adp_similarity_proxies is None):
self.n_adp_similarity_proxies = None
self.adp_similarity_residual_sum = 0
else:
self.n_adp_similarity_proxies = len(adp_similarity_proxies)
self.adp_similarity_residual_sum = adp_restraints.adp_similarity_residual_sum(
u_cart=u_cart,
u_iso=u_iso,
use_u_aniso=use_u_aniso,
proxies=adp_similarity_proxies,
gradients_aniso_cart=self.gradients_aniso_cart,
gradients_iso=self.gradients_iso)
self.number_of_restraints += 6 * self.n_adp_similarity_proxies
self.residual_sum += self.adp_similarity_residual_sum
if (rigid_bond_proxies is None):
self.n_rigid_bond_proxies = None
self.rigid_bond_residual_sum = 0
else:
self.n_rigid_bond_proxies = len(rigid_bond_proxies)
self.rigid_bond_residual_sum = adp_restraints.rigid_bond_residual_sum(
sites_cart=sites_cart,
u_cart=u_cart,
proxies=rigid_bond_proxies,
gradients_aniso_cart=self.gradients_aniso_cart)
self.number_of_restraints += self.n_rigid_bond_proxies
self.residual_sum += self.rigid_bond_residual_sum
if (isotropic_adp_proxies is None):
self.n_isotropic_adp_proxies = None
self.isotropic_adp_residual_sum = 0
else:
self.n_isotropic_adp_proxies = len(isotropic_adp_proxies)
self.isotropic_adp_residual_sum = adp_restraints.isotropic_adp_residual_sum(
u_cart=u_cart,
proxies=isotropic_adp_proxies,
gradients_aniso_cart=self.gradients_aniso_cart)
self.number_of_restraints += self.n_isotropic_adp_proxies
self.residual_sum += self.isotropic_adp_residual_sum
self.finalize_target_and_gradients()
