def rigid_bond_deviation(self):
if (self.n_rigid_bond_proxies is not None):
rigid_bond_deltas = adp_restraints.rigid_bond_deltas(
sites_cart=self.sites_cart,
u_cart=self.u_cart,
proxies=self.rigid_bond_proxies)
r_sq = rigid_bond_deltas * rigid_bond_deltas
r_ave = math.sqrt(flex.mean_default(r_sq, 0))
r_max = math.sqrt(flex.max_default(r_sq, 0))
r_min = math.sqrt(flex.min_default(r_sq, 0))
return r_min, r_max, r_ave
def rigid_bond_deviation(self):
if (self.n_rigid_bond_proxies is not None):
rigid_bond_deltas = adp_restraints.rigid_bond_deltas(
sites_cart=self.sites_cart,
u_cart=self.u_cart,
proxies=self.rigid_bond_proxies)
r_sq = rigid_bond_deltas * rigid_bond_deltas
r_ave = math.sqrt(flex.mean_default(r_sq, 0))
r_max = math.sqrt(flex.max_default(r_sq, 0))
r_min = math.sqrt(flex.min_default(r_sq, 0))
return r_min, r_max, r_ave
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)