def run():
symmetry = crystal.symmetry(unit_cell=(10.67, 10.67, 4.68, 90, 90, 120),
space_group_symbol="P 3")
special_position_settings = crystal.special_position_settings(
crystal_symmetry=symmetry, min_distance_sym_equiv=0.5)
site = (0, 0, 0.236)
u_cif = ((0.17, 0.17, 0.19, 0.09, 0, 0))
site_symmetry = special_position_settings.site_symmetry(site)
print "Input Ucif:", u_cif
u_star = adptbx.u_cif_as_u_star(symmetry.unit_cell(), u_cif)
if (not site_symmetry.is_compatible_u_star(u_star)):
print "Warning: ADP tensor is incompatible with site symmetry."
u_star = site_symmetry.average_u_star(u_star)
u_cif = adptbx.u_star_as_u_cif(symmetry.unit_cell(), u_star)
print "Averaged Ucif:", u_cif
u_cart = adptbx.u_star_as_u_cart(symmetry.unit_cell(), u_star)
eigenvalues = adptbx.eigenvalues(u_cart)
if (not adptbx.is_positive_definite(eigenvalues)):
print "ADP tensor is not positive definite."
print "Eigenvectors and values:"
eigensystem = adptbx.eigensystem(u_cart)
for i in xrange(3):
print " v=(%.5f %.5f %.5f) " % eigensystem.vectors(i),
print "lambda=%.4f" % (eigensystem.values()[i], )
def run(args):
for file_name in args:
print "File name:", file_name
try:
pdb_inp = iotbx.pdb.input(file_name=file_name)
except KeyboardInterrupt:
raise
except Exception:
libtbx.utils.format_exception()
isotropic_b_factors = flex.double()
all_eigenvalues = flex.double()
for atom in pdb_inp.atoms():
if (atom.uij == (-1, -1, -1, -1, -1, -1)):
isotropic_b_factors.append(atom.b)
else:
all_eigenvalues.extend(
flex.double(adptbx.eigenvalues(atom.uij)))
all_eigenvalues *= adptbx.u_as_b(1)
print "Number of isotropic atoms: ", isotropic_b_factors.size()
print "Number of anisotropic atoms:", all_eigenvalues.size() // 3
if (isotropic_b_factors.size() != 0):
print "Histogram of isotropic B-factors:"
flex.histogram(data=isotropic_b_factors,
n_slots=10).show(prefix=" ",
format_cutoffs="%7.2f")
if (all_eigenvalues.size() != 0):
print "Histogram of eigenvalues of anisotropic B-factors:"
flex.histogram(data=all_eigenvalues,
n_slots=10).show(prefix=" ",
format_cutoffs="%7.2f")
print
def run():
symmetry = crystal.symmetry(
unit_cell=(10.67, 10.67, 4.68, 90, 90, 120),
space_group_symbol="P 3")
special_position_settings = crystal.special_position_settings(
crystal_symmetry=symmetry,
min_distance_sym_equiv=0.5)
site = (0, 0, 0.236)
u_cif = ((0.17, 0.17, 0.19, 0.09, 0, 0))
site_symmetry = special_position_settings.site_symmetry(site)
print "Input Ucif:", u_cif
u_star = adptbx.u_cif_as_u_star(symmetry.unit_cell(), u_cif)
if (not site_symmetry.is_compatible_u_star(u_star)):
print "Warning: ADP tensor is incompatible with site symmetry."
u_star = site_symmetry.average_u_star(u_star)
u_cif = adptbx.u_star_as_u_cif(symmetry.unit_cell(), u_star)
print "Averaged Ucif:", u_cif
u_cart = adptbx.u_star_as_u_cart(symmetry.unit_cell(), u_star)
eigenvalues = adptbx.eigenvalues(u_cart)
if (not adptbx.is_positive_definite(eigenvalues)):
print "ADP tensor is not positive definite."
print "Eigenvectors and values:"
eigensystem = adptbx.eigensystem(u_cart)
for i in xrange(3):
print " v=(%.5f %.5f %.5f) " % eigensystem.vectors(i),
print "lambda=%.4f" % (eigensystem.values()[i],)
def run(args):
for file_name in args:
print "File name:", file_name
try:
pdb_inp = iotbx.pdb.input(file_name=file_name)
except KeyboardInterrupt: raise
except Exception:
libtbx.utils.format_exception()
isotropic_b_factors = flex.double()
all_eigenvalues = flex.double()
for atom in pdb_inp.atoms():
if (atom.uij == (-1,-1,-1,-1,-1,-1)):
isotropic_b_factors.append(atom.b)
else:
all_eigenvalues.extend(flex.double(adptbx.eigenvalues(atom.uij)))
all_eigenvalues *= adptbx.u_as_b(1)
print "Number of isotropic atoms: ", isotropic_b_factors.size()
print "Number of anisotropic atoms:", all_eigenvalues.size() // 3
if (isotropic_b_factors.size() != 0):
print "Histogram of isotropic B-factors:"
flex.histogram(data=isotropic_b_factors, n_slots=10).show(
prefix=" ", format_cutoffs="%7.2f")
if (all_eigenvalues.size() != 0):
print "Histogram of eigenvalues of anisotropic B-factors:"
flex.histogram(data=all_eigenvalues, n_slots=10).show(
prefix=" ", format_cutoffs="%7.2f")
print
def exercise_eigen_core(diag):
u = adptbx.random_rotate_ellipsoid(diag + [0., 0., 0.])
ev = list(adptbx.eigenvalues(u))
diag.sort()
ev.sort()
for i in xrange(3):
check_eigenvalue(u, ev[i])
for i in xrange(3):
assert abs(diag[i] - ev[i]) < 1.e-4
if (adptbx.is_positive_definite(ev)):
es = adptbx.eigensystem(u)
ev = list(es.values())
ev.sort()
for i in xrange(3):
check_eigenvalue(u, ev[i])
for i in xrange(3):
assert abs(diag[i] - ev[i]) < 1.e-4
evec = []
for i in xrange(3):
check_eigenvector(u, es.values()[i], es.vectors(i))
evec.extend(es.vectors(i))
return # XXX following tests disabled for the moment
# sometimes fail if eigenvalues are very similar but not identical
sqrt_eval = matrix.diag(flex.sqrt(flex.double(es.values())))
evec = matrix.sqr(evec).transpose()
sqrt_u = evec * sqrt_eval * evec.transpose()
u_full = matrix.sym(sym_mat3=u).elems
assert approx_equal(u_full, (sqrt_u.transpose() * sqrt_u).elems,
eps=1.e-3)
assert approx_equal(u_full, (sqrt_u * sqrt_u.transpose()).elems,
eps=1.e-3)
assert approx_equal(u_full, (sqrt_u * sqrt_u).elems, eps=1.e-3)
sqrt_u_plus_shifts = matrix.sym(sym_mat3=[
x + 10 * (random.random() - .5) for x in sqrt_u.as_sym_mat3()
])
sts = (sqrt_u_plus_shifts.transpose() *
sqrt_u_plus_shifts).as_sym_mat3()
ev = adptbx.eigenvalues(sts)
assert min(ev) >= 0
sts = (sqrt_u_plus_shifts *
sqrt_u_plus_shifts.transpose()).as_sym_mat3()
ev = adptbx.eigenvalues(sts)
assert min(ev) >= 0
sts = (sqrt_u_plus_shifts * sqrt_u_plus_shifts).as_sym_mat3()
ev = adptbx.eigenvalues(sts)
assert min(ev) >= 0
def exercise_eigen_core(diag):
u = adptbx.random_rotate_ellipsoid(diag + [0.0, 0.0, 0.0])
ev = list(adptbx.eigenvalues(u))
diag.sort()
ev.sort()
for i in xrange(3):
check_eigenvalue(u, ev[i])
for i in xrange(3):
assert abs(diag[i] - ev[i]) < 1.0e-4
if adptbx.is_positive_definite(ev):
es = adptbx.eigensystem(u)
ev = list(es.values())
ev.sort()
for i in xrange(3):
check_eigenvalue(u, ev[i])
for i in xrange(3):
assert abs(diag[i] - ev[i]) < 1.0e-4
evec = []
for i in xrange(3):
check_eigenvector(u, es.values()[i], es.vectors(i))
evec.extend(es.vectors(i))
return # XXX following tests disabled for the moment
# sometimes fail if eigenvalues are very similar but not identical
sqrt_eval = matrix.diag(flex.sqrt(flex.double(es.values())))
evec = matrix.sqr(evec).transpose()
sqrt_u = evec * sqrt_eval * evec.transpose()
u_full = matrix.sym(sym_mat3=u).elems
assert approx_equal(u_full, (sqrt_u.transpose() * sqrt_u).elems, eps=1.0e-3)
assert approx_equal(u_full, (sqrt_u * sqrt_u.transpose()).elems, eps=1.0e-3)
assert approx_equal(u_full, (sqrt_u * sqrt_u).elems, eps=1.0e-3)
sqrt_u_plus_shifts = matrix.sym(sym_mat3=[x + 10 * (random.random() - 0.5) for x in sqrt_u.as_sym_mat3()])
sts = (sqrt_u_plus_shifts.transpose() * sqrt_u_plus_shifts).as_sym_mat3()
ev = adptbx.eigenvalues(sts)
assert min(ev) >= 0
sts = (sqrt_u_plus_shifts * sqrt_u_plus_shifts.transpose()).as_sym_mat3()
ev = adptbx.eigenvalues(sts)
assert min(ev) >= 0
sts = (sqrt_u_plus_shifts * sqrt_u_plus_shifts).as_sym_mat3()
ev = adptbx.eigenvalues(sts)
assert min(ev) >= 0
def check_u_cart(axis, u_cart):
ev = adptbx.eigenvalues(u_cart)
assert ev[0] > 0
assert approx_equal(ev[1:], [0, 0])
es = adptbx.eigensystem(u_cart)
evs = es.vectors(0), es.vectors(1), es.vectors(2)
a1 = math.acos((axis[0]*evs[0][0]+axis[1]*evs[0][1]+axis[2]*evs[0][2])/ \
(evs[0][0]**2+evs[0][1]**2+evs[0][2]**2)) *180/math.pi
a2 = math.acos((axis[0]*evs[1][0]+axis[1]*evs[1][1]+axis[2]*evs[1][2])/ \
(evs[1][0]**2+evs[1][1]**2+evs[1][2]**2)) *180/math.pi
a3 = math.acos((axis[0]*evs[2][0]+axis[1]*evs[2][1]+axis[2]*evs[2][2])/ \
(evs[2][0]**2+evs[2][1]**2+evs[2][2]**2)) *180/math.pi
assert approx_equal(a1, 90.)
def check_u_cart(axis, u_cart):
ev = adptbx.eigenvalues(u_cart)
assert ev[0] > 0
assert approx_equal(ev[1:],[0,0])
es = adptbx.eigensystem(u_cart)
evs = es.vectors(0),es.vectors(1),es.vectors(2)
a1 = math.acos((axis[0]*evs[0][0]+axis[1]*evs[0][1]+axis[2]*evs[0][2])/ \
(evs[0][0]**2+evs[0][1]**2+evs[0][2]**2)) *180/math.pi
a2 = math.acos((axis[0]*evs[1][0]+axis[1]*evs[1][1]+axis[2]*evs[1][2])/ \
(evs[1][0]**2+evs[1][1]**2+evs[1][2]**2)) *180/math.pi
a3 = math.acos((axis[0]*evs[2][0]+axis[1]*evs[2][1]+axis[2]*evs[2][2])/ \
(evs[2][0]**2+evs[2][1]**2+evs[2][2]**2)) *180/math.pi
assert approx_equal(a1, 90.)
def random_modify_u_star(self, u_star, gauss_sigma,
max_relative_difference=1./3,
max_trials=100):
for trial in xrange(max_trials):
modified_u_star = []
for i in xrange(len(u_star)):
u = u_star[i]
max_diff = u * max_relative_difference
modified_u = random.gauss(u, gauss_sigma)
if (modified_u - u > u + max_diff):
modified_u = u + max_diff
elif (u - modified_u > u + max_diff):
modified_u = u - max_diff
modified_u_star.append(modified_u)
u_cart = adptbx.u_star_as_u_cart(self.unit_cell(), modified_u_star)
eigenvalues = adptbx.eigenvalues(u_cart)
if (min(eigenvalues) > 0.001):
return modified_u_star
raise RuntimeError, "Cannot find suitable u_star."
def random_modify_u_star(self,
u_star,
gauss_sigma,
max_relative_difference=1. / 3,
max_trials=100):
for trial in xrange(max_trials):
modified_u_star = []
for i in xrange(len(u_star)):
u = u_star[i]
max_diff = u * max_relative_difference
modified_u = random.gauss(u, gauss_sigma)
if (modified_u - u > u + max_diff):
modified_u = u + max_diff
elif (u - modified_u > u + max_diff):
modified_u = u - max_diff
modified_u_star.append(modified_u)
u_cart = adptbx.u_star_as_u_cart(self.unit_cell(), modified_u_star)
eigenvalues = adptbx.eigenvalues(u_cart)
if (min(eigenvalues) > 0.001):
return modified_u_star
raise RuntimeError, "Cannot find suitable u_star."
def exercise_negative_parameters(verbose=0):
structure_default = xray.structure(
crystal_symmetry=crystal.symmetry(unit_cell=((10, 13, 17, 75, 80, 85)),
space_group_symbol="P 1"),
scatterers=flex.xray_scatterer(
[xray.scatterer(label="C", site=(0, 0, 0), u=0.25)]))
negative_gaussian = eltbx.xray_scattering.gaussian((1, 2), (2, 3), -4)
for i_trial in range(7):
structure = structure_default.deep_copy_scatterers()
scatterer = structure.scatterers()[0]
if (i_trial == 1):
scatterer.occupancy *= -1
elif (i_trial == 2):
structure.scattering_type_registry(
custom_dict={"C": negative_gaussian})
elif (i_trial == 3):
scatterer.u_iso *= -1
elif (i_trial == 4):
u_cart = adptbx.random_u_cart(u_scale=1, u_min=-1.1)
assert max(adptbx.eigenvalues(u_cart)) < 0
u_star = adptbx.u_cart_as_u_star(structure.unit_cell(), u_cart)
scatterer.u_star = u_star
scatterer.flags.set_use_u_aniso_only()
elif (i_trial == 5):
scatterer.fp = -10
elif (i_trial == 6):
scatterer.fp = -3
f_direct = structure.structure_factors(d_min=1,
algorithm="direct",
cos_sin_table=False).f_calc()
f_fft = structure.structure_factors(d_min=1,
algorithm="fft",
quality_factor=1.e8,
wing_cutoff=1.e-10).f_calc()
if (i_trial == 2):
assert negative_gaussian.at_d_star_sq(
f_fft.d_star_sq().data()).all_lt(0)
if (i_trial in [5, 6]):
f = structure.scattering_type_registry().gaussian_not_optional(
scattering_type="C").at_d_star_sq(f_fft.d_star_sq().data())
if (i_trial == 5):
assert flex.max(f) + scatterer.fp < 0
else:
assert flex.max(f) + scatterer.fp > 0
assert flex.min(f) + scatterer.fp < 0
cc = flex.linear_correlation(abs(f_direct).data(),
abs(f_fft).data()).coefficient()
if (cc < 0.999):
raise AssertionError("i_trial=%d, correlation=%.6g" %
(i_trial, cc))
elif (0 or verbose):
print("correlation=%.6g" % cc)
#
# very simple test of gradient calculations with negative parameters
structure_factor_gradients = \
cctbx.xray.structure_factors.gradients(
miller_set=f_direct,
cos_sin_table=False)
target_functor = xray.target_functors.intensity_correlation(
f_obs=abs(f_direct))
target_result = target_functor(f_fft, True)
xray.set_scatterer_grad_flags(scatterers=structure.scatterers(),
site=True,
u_iso=True,
u_aniso=True,
occupancy=True,
fp=True,
fdp=True)
for algorithm in ["direct", "fft"]:
grads = structure_factor_gradients(
xray_structure=structure,
u_iso_refinable_params=None,
miller_set=f_direct,
d_target_d_f_calc=target_result.derivatives(),
n_parameters=structure.n_parameters(),
algorithm=algorithm).packed()
def exercise_interface():
episq = 8*(math.pi**2)
assert approx_equal(adptbx.u_as_b(2.3), 2.3*episq)
assert approx_equal(adptbx.b_as_u(adptbx.u_as_b(2.3)), 2.3)
u = (3,4,9, 2,1,7)
assert approx_equal(adptbx.u_as_b(u), [x*episq for x in u])
assert approx_equal(adptbx.b_as_u(adptbx.u_as_b(u)), u)
uc = uctbx.unit_cell((5,4,7,80,110,100))
for fw,bw in ((adptbx.u_cif_as_u_star, adptbx.u_star_as_u_cif),
(adptbx.u_cart_as_u_star, adptbx.u_star_as_u_cart),
(adptbx.u_cart_as_u_cif, adptbx.u_cif_as_u_cart),
(adptbx.u_cart_as_beta, adptbx.beta_as_u_cart),
(adptbx.u_cif_as_beta, adptbx.beta_as_u_cif)):
assert approx_equal(bw(uc, fw(uc, u)), u)
assert approx_equal(adptbx.beta_as_u_star(adptbx.u_star_as_beta(u)), u)
assert approx_equal(adptbx.u_cart_as_u_iso(adptbx.u_iso_as_u_cart(2.3)), 2.3)
for fw,bw in ((adptbx.u_iso_as_u_star, adptbx.u_star_as_u_iso),
(adptbx.u_iso_as_u_cif, adptbx.u_cif_as_u_iso),
(adptbx.u_iso_as_beta, adptbx.beta_as_u_iso)):
assert approx_equal(bw(uc, fw(uc, 2.3)), 2.3)
fc = adptbx.factor_u_cart_u_iso(u_cart=u)
assert approx_equal(fc.u_iso, adptbx.u_cart_as_u_iso(u))
assert approx_equal(
fc.u_cart_minus_u_iso,
[uii-fc.u_iso for uii in u[:3]]+list(u[3:]))
f = adptbx.factor_u_star_u_iso(
unit_cell=uc, u_star=adptbx.u_cart_as_u_star(uc, u))
assert approx_equal(f.u_iso, fc.u_iso)
assert approx_equal(
f.u_star_minus_u_iso,
adptbx.u_cart_as_u_star(uc, fc.u_cart_minus_u_iso))
f = adptbx.factor_u_cif_u_iso(
unit_cell=uc, u_cif=adptbx.u_cart_as_u_cif(uc, u))
assert approx_equal(f.u_iso, fc.u_iso)
assert approx_equal(
f.u_cif_minus_u_iso,
adptbx.u_cart_as_u_cif(uc, fc.u_cart_minus_u_iso))
f = adptbx.factor_beta_u_iso(
unit_cell=uc, beta=adptbx.u_cart_as_beta(uc, u))
assert approx_equal(f.u_iso, fc.u_iso)
assert approx_equal(
f.beta_minus_u_iso,
adptbx.u_cart_as_beta(uc, fc.u_cart_minus_u_iso))
assert approx_equal(adptbx.debye_waller_factor_b_iso(0.25,2.3),
math.exp(-2.3*0.25))
assert approx_equal(adptbx.debye_waller_factor_u_iso(0.25,2.3),
math.exp(-2.3*episq*0.25))
assert approx_equal(adptbx.debye_waller_factor_b_iso(uc, (1,2,3), 2.3),
adptbx.debye_waller_factor_u_iso(uc, (1,2,3), 2.3/episq))
u_star = adptbx.u_cart_as_u_star(uc, u)
dw = adptbx.debye_waller_factor_u_star((1,2,3), u_star)
assert approx_equal(dw, adptbx.debye_waller_factor_beta((1,2,3),
adptbx.u_star_as_beta(u_star)))
assert approx_equal(dw, adptbx.debye_waller_factor_u_cif(uc, (1,2,3),
adptbx.u_star_as_u_cif(uc, u_star)))
assert approx_equal(dw, adptbx.debye_waller_factor_u_cart(uc, (1,2,3),
adptbx.u_star_as_u_cart(uc, u_star)))
for e in adptbx.eigenvalues(u):
check_eigenvalue(u, e)
assert not adptbx.is_positive_definite(adptbx.eigenvalues(u))
assert not adptbx.is_positive_definite(adptbx.eigenvalues(u), 0)
assert adptbx.is_positive_definite(adptbx.eigenvalues(u), 1.22)
assert not adptbx.is_positive_definite(u)
assert not adptbx.is_positive_definite(u, 0)
assert adptbx.is_positive_definite(u, 1.22)
up = (0.534, 0.812, 0.613, 0.0166, 0.134, -0.0124)
s = adptbx.eigensystem(up)
assert approx_equal(s.values(), (0.813132, 0.713201, 0.432668))
for i in xrange(3):
check_eigenvector(up, s.values()[i], s.vectors(i))
c = (1,2,3, 3,-4,5, 4,5,6)
v = (198,18,1020,116,447,269)
assert approx_equal(adptbx.c_u_c_transpose(c, u), v)
assert approx_equal(adptbx.eigensystem(u).values(),
(14.279201519086316, 2.9369143826320214, -1.2161159017183376))
s = adptbx.eigensystem(up)
try: s.vectors(4)
except RuntimeError, e: assert str(e).endswith("Index out of range.")
else: raise Exception_expected
uf = adptbx.eigenvalue_filtering(u_cart=u, u_min=0)
assert approx_equal(uf, (3.0810418, 4.7950710, 9.3400030,
1.7461615, 1.1659954, 6.4800706))
uf = adptbx.eigenvalue_filtering(u_cart=u, u_min=0, u_max=3)
assert approx_equal(uf, (2.7430890, 1.0378360, 2.1559895,
0.6193215, -0.3921632, 1.2846854))
uf = adptbx.eigenvalue_filtering(u_cart=u, u_min=0, u_max=3)
assert approx_equal(scitbx.linalg.eigensystem.real_symmetric(u).values(),
(14.2792015, 2.9369144, -1.2161159))
assert approx_equal(scitbx.linalg.eigensystem.real_symmetric(uf).values(),
(3, 2.9369144, 0))
uf = adptbx.eigenvalue_filtering(up)
assert approx_equal(uf, up)
def exercise_negative_parameters(verbose=0):
structure_default = xray.structure(
crystal_symmetry = crystal.symmetry(
unit_cell=((10,13,17,75,80,85)),
space_group_symbol="P 1"),
scatterers=flex.xray_scatterer([
xray.scatterer(label="C", site=(0,0,0), u=0.25)]))
negative_gaussian = eltbx.xray_scattering.gaussian((1,2), (2,3), -4)
for i_trial in xrange(7):
structure = structure_default.deep_copy_scatterers()
scatterer = structure.scatterers()[0]
if (i_trial == 1):
scatterer.occupancy *= -1
elif (i_trial == 2):
structure.scattering_type_registry(custom_dict={"C": negative_gaussian})
elif (i_trial == 3):
scatterer.u_iso *= -1
elif (i_trial == 4):
u_cart = adptbx.random_u_cart(u_scale=1, u_min=-1.1)
assert max(adptbx.eigenvalues(u_cart)) < 0
u_star = adptbx.u_cart_as_u_star(structure.unit_cell(), u_cart)
scatterer.u_star = u_star
scatterer.flags.set_use_u_aniso_only()
elif (i_trial == 5):
scatterer.fp = -10
elif (i_trial == 6):
scatterer.fp = -3
f_direct = structure.structure_factors(
d_min=1, algorithm="direct", cos_sin_table=False).f_calc()
f_fft = structure.structure_factors(
d_min=1, algorithm="fft",
quality_factor=1.e8, wing_cutoff=1.e-10).f_calc()
if (i_trial == 2):
assert negative_gaussian.at_d_star_sq(f_fft.d_star_sq().data()).all_lt(0)
if (i_trial in [5,6]):
f = structure.scattering_type_registry().gaussian_not_optional(
scattering_type="C").at_d_star_sq(f_fft.d_star_sq().data())
if (i_trial == 5):
assert flex.max(f) + scatterer.fp < 0
else:
assert flex.max(f) + scatterer.fp > 0
assert flex.min(f) + scatterer.fp < 0
cc = flex.linear_correlation(
abs(f_direct).data(),
abs(f_fft).data()).coefficient()
if (cc < 0.999):
raise AssertionError("i_trial=%d, correlation=%.6g" % (i_trial, cc))
elif (0 or verbose):
print "correlation=%.6g" % cc
#
# very simple test of gradient calculations with negative parameters
structure_factor_gradients = \
cctbx.xray.structure_factors.gradients(
miller_set=f_direct,
cos_sin_table=False)
target_functor = xray.target_functors.intensity_correlation(
f_obs=abs(f_direct))
target_result = target_functor(f_fft, True)
xray.set_scatterer_grad_flags(scatterers = structure.scatterers(),
site = True,
u_iso = True,
u_aniso = True,
occupancy = True,
fp = True,
fdp = True)
for algorithm in ["direct", "fft"]:
grads = structure_factor_gradients(
xray_structure=structure,
u_iso_refinable_params=None,
miller_set=f_direct,
d_target_d_f_calc=target_result.derivatives(),
n_parameters = structure.n_parameters(),
algorithm=algorithm).packed()
def exercise_interface():
episq = 8 * (math.pi ** 2)
assert approx_equal(adptbx.u_as_b(2.3), 2.3 * episq)
assert approx_equal(adptbx.b_as_u(adptbx.u_as_b(2.3)), 2.3)
u = (3, 4, 9, 2, 1, 7)
assert approx_equal(adptbx.u_as_b(u), [x * episq for x in u])
assert approx_equal(adptbx.b_as_u(adptbx.u_as_b(u)), u)
uc = uctbx.unit_cell((5, 4, 7, 80, 110, 100))
for fw, bw in (
(adptbx.u_cif_as_u_star, adptbx.u_star_as_u_cif),
(adptbx.u_cart_as_u_star, adptbx.u_star_as_u_cart),
(adptbx.u_cart_as_u_cif, adptbx.u_cif_as_u_cart),
(adptbx.u_cart_as_beta, adptbx.beta_as_u_cart),
(adptbx.u_cif_as_beta, adptbx.beta_as_u_cif),
):
assert approx_equal(bw(uc, fw(uc, u)), u)
assert approx_equal(adptbx.beta_as_u_star(adptbx.u_star_as_beta(u)), u)
assert approx_equal(adptbx.u_cart_as_u_iso(adptbx.u_iso_as_u_cart(2.3)), 2.3)
for fw, bw in (
(adptbx.u_iso_as_u_star, adptbx.u_star_as_u_iso),
(adptbx.u_iso_as_u_cif, adptbx.u_cif_as_u_iso),
(adptbx.u_iso_as_beta, adptbx.beta_as_u_iso),
):
assert approx_equal(bw(uc, fw(uc, 2.3)), 2.3)
fc = adptbx.factor_u_cart_u_iso(u_cart=u)
assert approx_equal(fc.u_iso, adptbx.u_cart_as_u_iso(u))
assert approx_equal(fc.u_cart_minus_u_iso, [uii - fc.u_iso for uii in u[:3]] + list(u[3:]))
f = adptbx.factor_u_star_u_iso(unit_cell=uc, u_star=adptbx.u_cart_as_u_star(uc, u))
assert approx_equal(f.u_iso, fc.u_iso)
assert approx_equal(f.u_star_minus_u_iso, adptbx.u_cart_as_u_star(uc, fc.u_cart_minus_u_iso))
f = adptbx.factor_u_cif_u_iso(unit_cell=uc, u_cif=adptbx.u_cart_as_u_cif(uc, u))
assert approx_equal(f.u_iso, fc.u_iso)
assert approx_equal(f.u_cif_minus_u_iso, adptbx.u_cart_as_u_cif(uc, fc.u_cart_minus_u_iso))
f = adptbx.factor_beta_u_iso(unit_cell=uc, beta=adptbx.u_cart_as_beta(uc, u))
assert approx_equal(f.u_iso, fc.u_iso)
assert approx_equal(f.beta_minus_u_iso, adptbx.u_cart_as_beta(uc, fc.u_cart_minus_u_iso))
assert approx_equal(adptbx.debye_waller_factor_b_iso(0.25, 2.3), math.exp(-2.3 * 0.25))
assert approx_equal(adptbx.debye_waller_factor_u_iso(0.25, 2.3), math.exp(-2.3 * episq * 0.25))
assert approx_equal(
adptbx.debye_waller_factor_b_iso(uc, (1, 2, 3), 2.3),
adptbx.debye_waller_factor_u_iso(uc, (1, 2, 3), 2.3 / episq),
)
u_star = adptbx.u_cart_as_u_star(uc, u)
dw = adptbx.debye_waller_factor_u_star((1, 2, 3), u_star)
assert approx_equal(dw, adptbx.debye_waller_factor_beta((1, 2, 3), adptbx.u_star_as_beta(u_star)))
assert approx_equal(dw, adptbx.debye_waller_factor_u_cif(uc, (1, 2, 3), adptbx.u_star_as_u_cif(uc, u_star)))
assert approx_equal(dw, adptbx.debye_waller_factor_u_cart(uc, (1, 2, 3), adptbx.u_star_as_u_cart(uc, u_star)))
for e in adptbx.eigenvalues(u):
check_eigenvalue(u, e)
assert not adptbx.is_positive_definite(adptbx.eigenvalues(u))
assert not adptbx.is_positive_definite(adptbx.eigenvalues(u), 0)
assert adptbx.is_positive_definite(adptbx.eigenvalues(u), 1.22)
assert not adptbx.is_positive_definite(u)
assert not adptbx.is_positive_definite(u, 0)
assert adptbx.is_positive_definite(u, 1.22)
up = (0.534, 0.812, 0.613, 0.0166, 0.134, -0.0124)
s = adptbx.eigensystem(up)
assert approx_equal(s.values(), (0.813132, 0.713201, 0.432668))
for i in xrange(3):
check_eigenvector(up, s.values()[i], s.vectors(i))
c = (1, 2, 3, 3, -4, 5, 4, 5, 6)
v = (198, 18, 1020, 116, 447, 269)
assert approx_equal(adptbx.c_u_c_transpose(c, u), v)
assert approx_equal(adptbx.eigensystem(u).values(), (14.279201519086316, 2.9369143826320214, -1.2161159017183376))
s = adptbx.eigensystem(up)
try:
s.vectors(4)
except RuntimeError, e:
assert str(e).endswith("Index out of range.")
def exercise_interface():
episq = 8 * (math.pi**2)
assert approx_equal(adptbx.u_as_b(2.3), 2.3 * episq)
assert approx_equal(adptbx.b_as_u(adptbx.u_as_b(2.3)), 2.3)
u = (3, 4, 9, 2, 1, 7)
assert approx_equal(adptbx.u_as_b(u), [x * episq for x in u])
assert approx_equal(adptbx.b_as_u(adptbx.u_as_b(u)), u)
uc = uctbx.unit_cell((5, 4, 7, 80, 110, 100))
for fw, bw in ((adptbx.u_cif_as_u_star, adptbx.u_star_as_u_cif),
(adptbx.u_cart_as_u_star, adptbx.u_star_as_u_cart),
(adptbx.u_cart_as_u_cif, adptbx.u_cif_as_u_cart),
(adptbx.u_cart_as_beta, adptbx.beta_as_u_cart),
(adptbx.u_cif_as_beta, adptbx.beta_as_u_cif)):
assert approx_equal(bw(uc, fw(uc, u)), u)
assert approx_equal(adptbx.beta_as_u_star(adptbx.u_star_as_beta(u)), u)
assert approx_equal(adptbx.u_cart_as_u_iso(adptbx.u_iso_as_u_cart(2.3)),
2.3)
for fw, bw in ((adptbx.u_iso_as_u_star, adptbx.u_star_as_u_iso),
(adptbx.u_iso_as_u_cif, adptbx.u_cif_as_u_iso),
(adptbx.u_iso_as_beta, adptbx.beta_as_u_iso)):
assert approx_equal(bw(uc, fw(uc, 2.3)), 2.3)
fc = adptbx.factor_u_cart_u_iso(u_cart=u)
assert approx_equal(fc.u_iso, adptbx.u_cart_as_u_iso(u))
assert approx_equal(fc.u_cart_minus_u_iso,
[uii - fc.u_iso for uii in u[:3]] + list(u[3:]))
f = adptbx.factor_u_star_u_iso(unit_cell=uc,
u_star=adptbx.u_cart_as_u_star(uc, u))
assert approx_equal(f.u_iso, fc.u_iso)
assert approx_equal(f.u_star_minus_u_iso,
adptbx.u_cart_as_u_star(uc, fc.u_cart_minus_u_iso))
f = adptbx.factor_u_cif_u_iso(unit_cell=uc,
u_cif=adptbx.u_cart_as_u_cif(uc, u))
assert approx_equal(f.u_iso, fc.u_iso)
assert approx_equal(f.u_cif_minus_u_iso,
adptbx.u_cart_as_u_cif(uc, fc.u_cart_minus_u_iso))
f = adptbx.factor_beta_u_iso(unit_cell=uc,
beta=adptbx.u_cart_as_beta(uc, u))
assert approx_equal(f.u_iso, fc.u_iso)
assert approx_equal(f.beta_minus_u_iso,
adptbx.u_cart_as_beta(uc, fc.u_cart_minus_u_iso))
assert approx_equal(adptbx.debye_waller_factor_b_iso(0.25, 2.3),
math.exp(-2.3 * 0.25))
assert approx_equal(adptbx.debye_waller_factor_u_iso(0.25, 2.3),
math.exp(-2.3 * episq * 0.25))
assert approx_equal(
adptbx.debye_waller_factor_b_iso(uc, (1, 2, 3), 2.3),
adptbx.debye_waller_factor_u_iso(uc, (1, 2, 3), 2.3 / episq))
u_star = adptbx.u_cart_as_u_star(uc, u)
dw = adptbx.debye_waller_factor_u_star((1, 2, 3), u_star)
assert approx_equal(
dw,
adptbx.debye_waller_factor_beta((1, 2, 3),
adptbx.u_star_as_beta(u_star)))
assert approx_equal(
dw,
adptbx.debye_waller_factor_u_cif(uc, (1, 2, 3),
adptbx.u_star_as_u_cif(uc, u_star)))
assert approx_equal(
dw,
adptbx.debye_waller_factor_u_cart(uc, (1, 2, 3),
adptbx.u_star_as_u_cart(uc, u_star)))
for e in adptbx.eigenvalues(u):
check_eigenvalue(u, e)
assert not adptbx.is_positive_definite(adptbx.eigenvalues(u))
assert not adptbx.is_positive_definite(adptbx.eigenvalues(u), 0)
assert adptbx.is_positive_definite(adptbx.eigenvalues(u), 1.22)
assert not adptbx.is_positive_definite(u)
assert not adptbx.is_positive_definite(u, 0)
assert adptbx.is_positive_definite(u, 1.22)
up = (0.534, 0.812, 0.613, 0.0166, 0.134, -0.0124)
s = adptbx.eigensystem(up)
assert approx_equal(s.values(), (0.813132, 0.713201, 0.432668))
for i in xrange(3):
check_eigenvector(up, s.values()[i], s.vectors(i))
c = (1, 2, 3, 3, -4, 5, 4, 5, 6)
v = (198, 18, 1020, 116, 447, 269)
assert approx_equal(adptbx.c_u_c_transpose(c, u), v)
assert approx_equal(
adptbx.eigensystem(u).values(),
(14.279201519086316, 2.9369143826320214, -1.2161159017183376))
s = adptbx.eigensystem(up)
try:
s.vectors(4)
except RuntimeError, e:
assert str(e).endswith("Index out of range.")
def build_scatterers(self,
elements,
sites_frac=None,
grid=None,
t_centre_of_inversion=None):
existing_sites = [scatterer.site for scatterer in self.scatterers()]
if (sites_frac is None):
all_sites = random_sites(
special_position_settings=self,
existing_sites=existing_sites,
n_new=len(elements),
min_hetero_distance=self.min_distance,
general_positions_only=self.general_positions_only,
grid=grid,
t_centre_of_inversion=t_centre_of_inversion)
else:
assert len(sites_frac) == len(elements)
all_sites = existing_sites + list(sites_frac)
assert len(all_sites) <= self.n_scatterers
sf_dict = {}
for element in elements:
if (not sf_dict.has_key(element)):
sf_dict[element] = eltbx.xray_scattering.best_approximation(
element)
fp = 0
fdp = 0
n_existing = self.scatterers().size()
i_label = n_existing
for element, site in zip(elements, all_sites[n_existing:]):
i_label += 1
scatterer = xray.scatterer(label=element + str(i_label),
scattering_type=element,
site=site)
site_symmetry = scatterer.apply_symmetry(
self.unit_cell(), self.space_group(),
self.min_distance_sym_equiv())
if (self.random_f_prime_d_min):
f0 = sf_dict[element].at_d_star_sq(
1. / self.random_f_prime_d_min**2)
assert f0 > 0
fp = -f0 * random.random() * self.random_f_prime_scale
if (self.random_f_double_prime):
f0 = sf_dict[element].at_d_star_sq(0)
fdp = f0 * random.random() * self.random_f_double_prime_scale
scatterer.fp = fp
scatterer.fdp = fdp
if (self.use_u_iso_):
scatterer.flags.set_use_u_iso_only()
u_iso = self.u_iso
if (not u_iso and self.random_u_iso):
u_iso = random.random() * self.random_u_iso_scale \
+ self.random_u_iso_min
scatterer.u_iso = u_iso
if (self.use_u_aniso):
scatterer.flags.set_use_u_aniso_only()
run_away_counter = 0
while 1:
run_away_counter += 1
assert run_away_counter < 100
u_cart = adptbx.random_u_cart(
u_scale=self.random_u_cart_scale)
scatterer.u_star = site_symmetry.average_u_star(
adptbx.u_cart_as_u_star(self.unit_cell(), u_cart))
u_cart = adptbx.u_star_as_u_cart(self.unit_cell(),
scatterer.u_star)
eigenvalues = adptbx.eigenvalues(u_cart)
if (min(eigenvalues) > 0.001):
break
if (self.random_occupancy):
scatterer.occupancy = self.random_occupancy_min \
+ (1-self.random_occupancy_min)*random.random()
self.add_scatterer(scatterer)
def build_scatterers(self,
elements,
sites_frac=None,
grid=None,
t_centre_of_inversion=None):
existing_sites = [scatterer.site for scatterer in self.scatterers()]
if (sites_frac is None):
all_sites = random_sites(
special_position_settings=self,
existing_sites=existing_sites,
n_new=len(elements),
min_hetero_distance=self.min_distance,
general_positions_only=self.general_positions_only,
grid=grid,
t_centre_of_inversion=t_centre_of_inversion)
else:
assert len(sites_frac) == len(elements)
all_sites = existing_sites + list(sites_frac)
assert len(all_sites) <= self.n_scatterers
sf_dict = {}
for element in elements:
if (not sf_dict.has_key(element)):
sf_dict[element] = eltbx.xray_scattering.best_approximation(element)
fp = 0
fdp = 0
n_existing = self.scatterers().size()
i_label = n_existing
for element,site in zip(elements, all_sites[n_existing:]):
i_label += 1
scatterer = xray.scatterer(
label=element + str(i_label),
scattering_type=element,
site=site)
site_symmetry = scatterer.apply_symmetry(
self.unit_cell(),
self.space_group(),
self.min_distance_sym_equiv())
if (self.random_f_prime_d_min):
f0 = sf_dict[element].at_d_star_sq(1./self.random_f_prime_d_min**2)
assert f0 > 0
fp = -f0 * random.random() * self.random_f_prime_scale
if (self.random_f_double_prime):
f0 = sf_dict[element].at_d_star_sq(0)
fdp = f0 * random.random() * self.random_f_double_prime_scale
scatterer.fp = fp
scatterer.fdp = fdp
if (self.use_u_iso_):
scatterer.flags.set_use_u_iso_only()
u_iso = self.u_iso
if (not u_iso and self.random_u_iso):
u_iso = random.random() * self.random_u_iso_scale \
+ self.random_u_iso_min
scatterer.u_iso = u_iso
if (self.use_u_aniso):
scatterer.flags.set_use_u_aniso_only()
run_away_counter = 0
while 1:
run_away_counter += 1
assert run_away_counter < 100
u_cart = adptbx.random_u_cart(u_scale=self.random_u_cart_scale)
scatterer.u_star = site_symmetry.average_u_star(
adptbx.u_cart_as_u_star(
self.unit_cell(), u_cart))
u_cart = adptbx.u_star_as_u_cart(self.unit_cell(), scatterer.u_star)
eigenvalues = adptbx.eigenvalues(u_cart)
if (min(eigenvalues) > 0.001):
break
if (self.random_occupancy):
scatterer.occupancy = self.random_occupancy_min \
+ (1-self.random_occupancy_min)*random.random()
self.add_scatterer(scatterer)
