def branch_2_mn(small):
m = []
n = []
while (len(n) == 0 or len(m) == 0):
r1 = random.random()
r2 = random.random()
r3 = random.random()
if (r1 >= r2 and r2 >= r3 and r3 > 0.0):
r = random.random()
if (r > 0.5):
m = [r1, r2, r3, 0, 0, 0]
else:
m = [r1, r1, r1, 0, 0, 0]
assert adptbx.is_positive_definite(m, small)
if (r1 >= r2 and r2 >= r3 and r3 > 0.0):
r = random.random()
if (r > 0.5):
n = [r1, r3, r2, 0, 0, 0]
else:
n = [r1, r1, r1, 0, 0, 0]
assert adptbx.is_positive_definite(n, small)
r = random.random()
if (r > 0.5):
m = adptbx.random_rotate_ellipsoid(u_cart=m)
n = adptbx.random_rotate_ellipsoid(u_cart=n)
return m, n
def run(pdb_file_name,
n_models,
log,
eps=1.e-7,
output_file_name="ensemble.pdb"):
pdb_inp = iotbx.pdb.input(file_name = pdb_file_name)
pdb_hierarchy = pdb_inp.construct_hierarchy()
xrs = pdb_hierarchy.extract_xray_structure(
crystal_symmetry=pdb_inp.crystal_symmetry_from_cryst1())
tls_extract = mmtbx.tls.tools.tls_from_pdb_inp(
remark_3_records = pdb_inp.extract_remark_iii_records(3),
pdb_hierarchy = pdb_hierarchy)
tlso = tls_extract.tls_params
if(len(tlso)!=1):
raise Sorry("Only one TLS group per PDB is currently supported.")
tlso = tlso[0] # XXX one group only
deg_to_rad_scale = math.pi/180
# Units: T[A], L[deg**2], S[A*deg]
T = matrix.sym(sym_mat3=tlso.t)
L = matrix.sym(sym_mat3=tlso.l)*(deg_to_rad_scale**2)
S = matrix.sqr(tlso.s)*deg_to_rad_scale
# sanity check
if(not adptbx.is_positive_definite(tlso.t, eps)):
raise Sorry("T matrix is not positive definite.")
if(not adptbx.is_positive_definite(tlso.l, eps)):
raise Sorry("L matrix is not positive definite.")
r = analysis.run(T=T, L=L, S=S, log=log)
ensemble_generator(
decompose_tls_object = r,
pdb_hierarchy = pdb_hierarchy,
xray_structure = xrs,
n_models = n_models,
log = log).write_pdb_file(file_name=output_file_name)
def branch_2_mn(small):
m=[]
n=[]
while (len(n)==0 or len(m)==0):
r1 = random.random()
r2 = random.random()
r3 = random.random()
if(r1 >= r2 and r2 >= r3 and r3> 0.0):
r = random.random()
if(r > 0.5):
m = [r1,r2,r3,0,0,0]
else:
m = [r1,r1,r1,0,0,0]
assert adptbx.is_positive_definite(m,small)
if(r1 >= r2 and r2 >= r3 and r3 > 0.0):
r = random.random()
if(r > 0.5):
n = [r1,r3,r2,0,0,0]
else:
n = [r1,r1,r1,0,0,0]
assert adptbx.is_positive_definite(n,small)
r = random.random()
if(r > 0.5):
m = adptbx.random_rotate_ellipsoid(u_cart = m)
n = adptbx.random_rotate_ellipsoid(u_cart = n)
return m,n
def branch_3_mn():
m = None
n = None
small = 1.e-15
for i in range(10000):
m2 = []
n2 = []
for i in range(4):
r1 = random.random()
r2 = random.random()
r3 = random.random()
if (r3 > 0.1):
r1 = r2
m2.append(r1)
n2.append(r2)
p1 = 0.5 * (m2[0] + m2[3] + math.sqrt(4 * m2[1] * m2[2] +
(m2[0] - m2[3])**2))
p2 = 0.5 * (m2[0] + m2[3] - math.sqrt(4 * m2[1] * m2[2] +
(m2[0] - m2[3])**2))
q1 = 0.5 * (n2[0] + m2[3] + math.sqrt(4 * n2[1] * n2[2] +
(n2[0] - n2[3])**2))
q2 = 0.5 * (n2[0] + m2[3] - math.sqrt(4 * n2[1] * n2[2] +
(n2[0] - n2[3])**2))
if (min(p1, p2) > 0.0 and min(q1, q2) > 0.0):
r = random.random()
if (r > 0.5):
r1 = r3
r2 = r2
m = [m2[0], m2[3], r1, m2[1], 0, 0]
n = [n2[0], n2[3], r2, n2[1], 0, 0]
if ([
adptbx.is_positive_definite(m),
adptbx.is_positive_definite(n)
].count(True) == 2):
esm = adptbx.eigensystem(m)
esn = adptbx.eigensystem(n)
vn = esn.values()
vm = esm.values()
mmin = flex.min(flex.double(vm))
nmin = flex.min(flex.double(vn))
if (abs(abs(mmin) - abs(nmin)) < small and mmin > 0.
and nmin > 0.):
for i, v in enumerate(vn):
if (abs(abs(nmin) - v) < small): break
for j, v in enumerate(vm):
if (abs(abs(mmin) - v) < small): break
vecn = flex.double(esn.vectors(i))
vecm = flex.double(esm.vectors(j))
if (flex.mean(vecm - vecn) < small): break
else:
m = None
n = None
assert [m, n] != [None, None]
assert [adptbx.is_positive_definite(m),
adptbx.is_positive_definite(n)].count(True) == 2
r = random.random()
if (r > 0.5):
m = adptbx.random_rotate_ellipsoid(u_cart=m)
n = adptbx.random_rotate_ellipsoid(u_cart=n)
return m, n
def branch_3_mn():
m = None
n = None
small = 1.e-15
for i in xrange(10000):
m2=[]
n2=[]
for i in xrange(4):
r1 = random.random()
r2 = random.random()
r3 = random.random()
if(r3 > 0.1):
r1 = r2
m2.append(r1)
n2.append(r2)
p1 = 0.5 * (m2[0]+m2[3] + math.sqrt(4*m2[1]*m2[2]+(m2[0]-m2[3])**2))
p2 = 0.5 * (m2[0]+m2[3] - math.sqrt(4*m2[1]*m2[2]+(m2[0]-m2[3])**2))
q1 = 0.5 * (n2[0]+m2[3] + math.sqrt(4*n2[1]*n2[2]+(n2[0]-n2[3])**2))
q2 = 0.5 * (n2[0]+m2[3] - math.sqrt(4*n2[1]*n2[2]+(n2[0]-n2[3])**2))
if(min(p1,p2) > 0.0 and min(q1,q2) > 0.0):
r = random.random()
if(r > 0.5):
r1 = r3
r2 = r2
m = [m2[0],m2[3],r1,m2[1],0,0]
n = [n2[0],n2[3],r2,n2[1],0,0]
if([adptbx.is_positive_definite(m),
adptbx.is_positive_definite(n)].count(True)==2):
esm = adptbx.eigensystem(m)
esn = adptbx.eigensystem(n)
vn = esn.values()
vm = esm.values()
mmin = flex.min(flex.double(vm))
nmin = flex.min(flex.double(vn))
if(abs(abs(mmin) - abs(nmin)) < small and mmin> 0. and nmin> 0.):
for i, v in enumerate(vn):
if(abs(abs(nmin) - v) < small): break
for j, v in enumerate(vm):
if(abs(abs(mmin) - v) < small): break
vecn = flex.double(esn.vectors(i))
vecm = flex.double(esm.vectors(j))
if(flex.mean(vecm-vecn) < small): break
else:
m = None
n = None
assert [m,n] != [None,None]
assert [adptbx.is_positive_definite(m),
adptbx.is_positive_definite(n)].count(True)==2
r = random.random()
if(r > 0.5):
m = adptbx.random_rotate_ellipsoid(u_cart = m)
n = adptbx.random_rotate_ellipsoid(u_cart = n)
return m,n
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():
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 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 run(pdb_file_name, n_models, log, output_file_name_prefix, eps=1.e-7):
pdb_inp = iotbx.pdb.input(file_name=pdb_file_name)
pdb_hierarchy = pdb_inp.construct_hierarchy()
asc = pdb_hierarchy.atom_selection_cache()
cs = pdb_inp.crystal_symmetry_from_cryst1()
tls_extract = mmtbx.tls.tools.tls_from_pdb_inp(
remark_3_records=pdb_inp.extract_remark_iii_records(3),
pdb_hierarchy=pdb_hierarchy)
for i_group, tls_params_one_group in enumerate(tls_extract.tls_params):
selection = asc.selection(tls_params_one_group.selection_string)
pdb_hierarchy_sel = pdb_hierarchy.select(selection)
xrs = pdb_hierarchy_sel.extract_xray_structure(crystal_symmetry=cs)
deg_to_rad_scale = math.pi / 180
# Units: T[A], L[deg**2], S[A*deg]
T = matrix.sym(sym_mat3=tls_params_one_group.t)
L = matrix.sym(sym_mat3=tls_params_one_group.l)
S = matrix.sqr(tls_params_one_group.s)
origin = tls_params_one_group.origin
tlso = tools.tlso(t=T.as_sym_mat3(),
l=L.as_sym_mat3(),
s=S,
origin=origin)
# sanity check
if (not adptbx.is_positive_definite(tls_params_one_group.t, eps)):
raise Sorry("T matrix is not positive definite.")
if (not adptbx.is_positive_definite(tls_params_one_group.l, eps)):
raise Sorry("L matrix is not positive definite.")
r = analysis.run(T=T,
L=L * (deg_to_rad_scale**2),
S=S * deg_to_rad_scale,
log=log).self_check()
ensemble_generator_obj = ensemble_generator(
tls_from_motions_object=r,
pdb_hierarchy=pdb_hierarchy_sel,
xray_structure=xrs,
n_models=n_models,
origin=origin,
log=log)
ensemble_generator_obj.write_pdb_file(
file_name=output_file_name_prefix +
"_ensemble_%s.pdb" % str(i_group))
# get U from TLS
u_from_tls = tools.uaniso_from_tls_one_group(
tlso=tlso, sites_cart=xrs.sites_cart(), zeroize_trace=False)
# get U from ensemble
pdb_hierarchy_from_tls = pdb_hierarchy_sel.deep_copy()
pdb_hierarchy_from_ens = pdb_hierarchy_sel.deep_copy()
u_from_ens = tools.u_cart_from_ensemble(
models=ensemble_generator_obj.states.root.models())
for i in xrange(xrs.sites_cart().size()):
print "atom %d:" % i
print " Ucart(from TLS):", ["%8.5f" % u for u in u_from_tls[i]]
print " Ucart(from ens):", ["%8.5f" % u for u in u_from_ens[i]]
#
u1, u2 = u_from_tls.as_double(), u_from_ens.as_double()
cc = flex.linear_correlation(x=u1, y=u2).coefficient()
r = flex.sum(flex.abs(u1-u2))/\
flex.sum(flex.abs(flex.abs(u1)+flex.abs(u2)))*2
print "%6.4f %6.4f" % (cc, r)
#
pdb_hierarchy_from_tls.atoms().set_uij(u_from_tls)
pdb_hierarchy_from_ens.atoms().set_uij(u_from_ens)
pdb_hierarchy_from_tls.write_pdb_file(
file_name=output_file_name_prefix +
"_u_from_tls_%s.pdb" % str(i_group),
crystal_symmetry=cs)
pdb_hierarchy_from_ens.write_pdb_file(
file_name=output_file_name_prefix +
"_u_from_ensemble_%s.pdb" % str(i_group),
crystal_symmetry=cs)
return ensemble_generator_obj
def exercise_branch_2_1(small=1.e-9):
m = [2, 1, 2, 0, 0, 0]
n = [2, 1, 1, 0, 0, 0]
counter = 0
trials = 100000
i = 0
branch_0 = 0
branch_1 = 0
branch_1_1 = 0
branch_1_2 = 0
branch_1_2_1 = 0
branch_1_2_2 = 0
branch_1_2_3 = 0
branch_1_2_3_1 = 0
branch_1_2_3_2 = 0
while i < trials:
i += 1
m = [2, 1, 2, 0, 0, 0]
n = [2, 1, 1, 0, 0, 0]
counter += 1
c = scitbx.math.euler_angles_as_matrix(
[random.uniform(0, 360) for j in range(3)], deg=True).elems
r = random.random()
if (r < 0.25):
m = adptbx.c_u_c_transpose(c, m)
n = adptbx.c_u_c_transpose(c, n)
elif (r >= 0.25 and r < 0.5):
m = adptbx.c_u_c_transpose(c, m)
elif (r >= 0.5 and r < 0.75):
n = adptbx.c_u_c_transpose(c, n)
else:
r = random.random()
run_away = 1000
while run_away > 0:
run_away -= 1
r = random.random()
if (r < 0.33):
m = adptbx.c_u_c_transpose(c, m)
n = adptbx.c_u_c_transpose(c, n)
elif (r >= 0.33 and r < 0.66):
m = adptbx.c_u_c_transpose(c, m)
else:
n = adptbx.c_u_c_transpose(c, n)
m = adptbx.c_u_c_transpose(c, m)
n = adptbx.c_u_c_transpose(c, n)
m = [
m[0], m[1], m[2], m[3] * random.choice((0, 1)),
m[4] * random.choice((0, 1)), m[5] * random.choice((0, 1))
]
n = [
n[0], n[1], n[2], n[3] * random.choice((0, 1)),
n[4] * random.choice((0, 1)), n[5] * random.choice((0, 1))
]
m = factor(list(m), i)
n = factor(list(n), i)
if (adptbx.is_positive_definite(m, small)
and adptbx.is_positive_definite(n, small)):
break
m_dc = copy.deepcopy(m)
n_dc = copy.deepcopy(n)
qq = tools.common(n, m, small)
#assert approx_equal(m,m_dc)
#assert approx_equal(n,n_dc)
if (qq.branch_0()): branch_0 += 1
if (qq.branch_1()): branch_1 += 1
if (qq.branch_1_1()): branch_1_1 += 1
if (qq.branch_1_2()): branch_1_2 += 1
if (qq.branch_1_2_1()): branch_1_2_1 += 1
if (qq.branch_1_2_2()): branch_1_2_2 += 1
if (qq.branch_1_2_3()): branch_1_2_3 += 1
if (qq.branch_1_2_3_1()): branch_1_2_3_1 += 1
if (qq.branch_1_2_3_2()): branch_1_2_3_2 += 1
if (counter >= 10000):
counter = 0
print("." * 30)
print("i= ", i, "out of ", trials)
print("branch_0 = ", branch_0)
print("branch_1 = ", branch_1)
print("branch_1_1 = ", branch_1_1)
print("branch_1_2 = ", branch_1_2)
print("branch_1_2_1 = ", branch_1_2_1)
print("branch_1_2_2 = ", branch_1_2_2)
print("branch_1_2_3 = ", branch_1_2_3)
print("branch_1_2_3_1 = ", branch_1_2_3_1)
print("branch_1_2_3_2 = ", branch_1_2_3_2)
sys.stdout.flush()
def tls_from_uanisos(xray_structure,
selections,
tlsos_initial,
number_of_macro_cycles = 3000,
max_iterations = 1000,
refine_T = True,
refine_L = True,
refine_S = True,
verbose = -1,
enforce_positive_definite_TL = True,
out = None):
global time_tls_from_uanisos
t1 = time.time()
if(out is None): out = sys.stdout
if(verbose > 0):
show_tls(tlsos = tlsos_initial,
text = "TLS from ADP: start TLS values", out = out)
u_cart=xray_structure.scatterers().extract_u_cart(xray_structure.unit_cell())
T_min = []
L_min = []
S_min = []
group_counter = 0
for tlso_initial, selection in zip(tlsos_initial, selections):
group_counter += 1
T_initial = tlso_initial.t
L_initial = tlso_initial.l
S_initial = tlso_initial.s
if(enforce_positive_definite_TL):
T_initial = adptbx.eigenvalue_filtering(T_initial)
L_initial = adptbx.eigenvalue_filtering(L_initial)
stop_flag = 0
target_stop = -1.0
sites_cart_selected = xray_structure.sites_cart().select(selection)
u_cart_selected = u_cart.select(selection)
for i in range(1, number_of_macro_cycles+1):
target_start = target_stop
minimized = tls_from_uaniso_minimizer(uaniso = u_cart_selected,
T_initial = T_initial,
L_initial = L_initial,
S_initial = S_initial,
refine_T = refine_T,
refine_L = refine_L,
refine_S = refine_S,
max_iterations = max_iterations,
origin = tlso_initial.origin,
sites = sites_cart_selected)
if(refine_T): T_initial = minimized.T_min
else: assert approx_equal(T_initial, minimized.T_min)
if(refine_L): L_initial = minimized.L_min
else: assert approx_equal(L_initial, minimized.L_min)
if(refine_S): S_initial = minimized.S_min
else: assert approx_equal(S_initial, minimized.S_min)
if(verbose > 0):
print >> out, "TLS group %d: minimized target = " %(group_counter),minimized.f
T_min_ = minimized.T_min
L_min_ = minimized.L_min
if(enforce_positive_definite_TL):
T_min_ = adptbx.eigenvalue_filtering(T_min_)
L_min_ = adptbx.eigenvalue_filtering(L_min_)
T_min.append(T_min_)
L_min.append(L_min_)
S_min.append(minimized.S_min)
if(enforce_positive_definite_TL):
assert adptbx.is_positive_definite(T_min_, 1.e-6)
assert adptbx.is_positive_definite(L_min_, 1.e-6)
tlsos_result = generate_tlsos(selections = selections,
xray_structure = xray_structure,
T = T_min,
L = L_min,
S = S_min)
if(verbose > 0):
show_tls(tlsos = tlsos_result,
text = "TLS from ADP: final TLS values", out = out)
t2 = time.time()
time_tls_from_uanisos += (t2 - t1)
return tlsos_result
def tls_from_u_cart(xray_structure,
tlsos_initial,
tls_selections,
number_of_macro_cycles = 100,
max_iterations = 100):
global time_tls_from_u_cart
timer = user_plus_sys_time()
uc = xray_structure.unit_cell()
xray_structure.tidy_us(u_min = 1.e-6)
ueq = xray_structure.extract_u_iso_or_u_equiv()
assert (ueq < 0.0).count(True) == 0
u_cart = xray_structure.scatterers().extract_u_cart(uc)
for tls_selection in tls_selections:
u_cart_selected = u_cart.select(tls_selection)
assert adptbx.is_positive_definite(u_cart_selected,1.e-6).count(False)==0
xray_structure.tidy_us(u_min = 1.e-6)
t = []
l = []
s = []
lim_l = 10.0
for tls_selection, tlso in zip(tls_selections, tlsos_initial):
t.append( tlso.t )
#if(abs(tlso.t[0]) < eps and abs(tlso.t[1]) < eps and abs(tlso.t[2]) < eps and
# abs(tlso.t[3]) < eps and abs(tlso.t[4]) < eps and abs(tlso.t[5]) < eps):
# t.append( t_from_u_cart(u_cart.select(tls_selection), 1.e-6) )
#else:
# t.append( tlso.t )
#l.append( [0,0,0,0,0,0] )
if abs(tlso.l[0])>lim_l: l1 = tlso.l[0]/5.
else: l1 = tlso.l[0]
if abs(tlso.l[1])>lim_l: l2 = tlso.l[1]/5.
else: l2 = tlso.l[1]
if abs(tlso.l[2])>lim_l: l3 = tlso.l[2]/5.
else: l3 = tlso.l[2]
if abs(tlso.l[3])>lim_l: l4 = tlso.l[3]/5.
else: l4 = tlso.l[3]
if abs(tlso.l[4])>lim_l: l5 = tlso.l[4]/5.
else: l5 = tlso.l[4]
if abs(tlso.l[5])>lim_l: l6 = tlso.l[5]/5.
else: l6 = tlso.l[5]
l.append( [l1,l2,l3,l4,l5,l6] )
s.append( tlso.s )
tlsos = generate_tlsos(selections = tls_selections,
xray_structure = xray_structure,
T = t, L = l, S = s)
#for rt,rl,rs in [[0,1,1],[1,0,0]]*3:
for rt,rl,rs in [[0,1,1],[1,0,0],[1,1,1]]:
tlsos_ = tls_from_uanisos(xray_structure = xray_structure,
selections = tls_selections,
tlsos_initial = tlsos,
number_of_macro_cycles = number_of_macro_cycles,
max_iterations = max_iterations,
refine_T = rt,
refine_L = rl,
refine_S = rs,
verbose = -1,
out = None)
tlsos = tlsos_
t = []
l = []
s = []
for tlso in tlsos:
t.append( tlso.t )
if abs(tlso.l[0])>lim_l: l1 = lim_l/5.
else: l1 = tlso.l[0]
if abs(tlso.l[1])>lim_l: l2 = lim_l/5.
else: l2 = tlso.l[1]
if abs(tlso.l[2])>lim_l: l3 = lim_l/5.
else: l3 = tlso.l[2]
if abs(tlso.l[3])>lim_l: l4 = lim_l/5.
else: l4 = tlso.l[3]
if abs(tlso.l[4])>lim_l: l5 = lim_l/5.
else: l5 = tlso.l[4]
if abs(tlso.l[5])>lim_l: l6 = lim_l/5.
else: l6 = tlso.l[5]
l.append( [l1,l2,l3,l4,l5,l6] )
s.append( tlso.s )
tlsos = generate_tlsos(selections = tls_selections,
xray_structure = xray_structure,
T = t, L = l, S = s)
time_tls_from_u_cart += timer.elapsed()
return tlsos
def tls_from_u_cart(xray_structure,
tlsos_initial,
tls_selections,
number_of_macro_cycles=100,
max_iterations=100):
global time_tls_from_u_cart
timer = user_plus_sys_time()
uc = xray_structure.unit_cell()
xray_structure.tidy_us(u_min=1.e-6)
ueq = xray_structure.extract_u_iso_or_u_equiv()
assert (ueq < 0.0).count(True) == 0
u_cart = xray_structure.scatterers().extract_u_cart(uc)
for tls_selection in tls_selections:
u_cart_selected = u_cart.select(tls_selection)
assert adptbx.is_positive_definite(u_cart_selected,
1.e-6).count(False) == 0
xray_structure.tidy_us(u_min=1.e-6)
t = []
l = []
s = []
lim_l = 10.0
for tls_selection, tlso in zip(tls_selections, tlsos_initial):
t.append(tlso.t)
#if(abs(tlso.t[0]) < eps and abs(tlso.t[1]) < eps and abs(tlso.t[2]) < eps and
# abs(tlso.t[3]) < eps and abs(tlso.t[4]) < eps and abs(tlso.t[5]) < eps):
# t.append( t_from_u_cart(u_cart.select(tls_selection), 1.e-6) )
#else:
# t.append( tlso.t )
#l.append( [0,0,0,0,0,0] )
if abs(tlso.l[0]) > lim_l: l1 = tlso.l[0] / 5.
else: l1 = tlso.l[0]
if abs(tlso.l[1]) > lim_l: l2 = tlso.l[1] / 5.
else: l2 = tlso.l[1]
if abs(tlso.l[2]) > lim_l: l3 = tlso.l[2] / 5.
else: l3 = tlso.l[2]
if abs(tlso.l[3]) > lim_l: l4 = tlso.l[3] / 5.
else: l4 = tlso.l[3]
if abs(tlso.l[4]) > lim_l: l5 = tlso.l[4] / 5.
else: l5 = tlso.l[4]
if abs(tlso.l[5]) > lim_l: l6 = tlso.l[5] / 5.
else: l6 = tlso.l[5]
l.append([l1, l2, l3, l4, l5, l6])
s.append(tlso.s)
tlsos = generate_tlsos(selections=tls_selections,
xray_structure=xray_structure,
T=t,
L=l,
S=s)
#for rt,rl,rs in [[0,1,1],[1,0,0]]*3:
for rt, rl, rs in [[0, 1, 1], [1, 0, 0], [1, 1, 1]]:
tlsos_ = tls_from_uanisos(
xray_structure=xray_structure,
selections=tls_selections,
tlsos_initial=tlsos,
number_of_macro_cycles=number_of_macro_cycles,
max_iterations=max_iterations,
refine_T=rt,
refine_L=rl,
refine_S=rs,
verbose=-1,
out=None)
tlsos = tlsos_
t = []
l = []
s = []
for tlso in tlsos:
t.append(tlso.t)
if abs(tlso.l[0]) > lim_l: l1 = lim_l / 5.
else: l1 = tlso.l[0]
if abs(tlso.l[1]) > lim_l: l2 = lim_l / 5.
else: l2 = tlso.l[1]
if abs(tlso.l[2]) > lim_l: l3 = lim_l / 5.
else: l3 = tlso.l[2]
if abs(tlso.l[3]) > lim_l: l4 = lim_l / 5.
else: l4 = tlso.l[3]
if abs(tlso.l[4]) > lim_l: l5 = lim_l / 5.
else: l5 = tlso.l[4]
if abs(tlso.l[5]) > lim_l: l6 = lim_l / 5.
else: l6 = tlso.l[5]
l.append([l1, l2, l3, l4, l5, l6])
s.append(tlso.s)
tlsos = generate_tlsos(selections=tls_selections,
xray_structure=xray_structure,
T=t,
L=l,
S=s)
time_tls_from_u_cart += timer.elapsed()
return tlsos
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 tls_from_uanisos(xray_structure,
selections,
tlsos_initial,
number_of_macro_cycles=3000,
max_iterations=1000,
refine_T=True,
refine_L=True,
refine_S=True,
verbose=-1,
enforce_positive_definite_TL=True,
out=None):
global time_tls_from_uanisos
t1 = time.time()
if (out is None): out = sys.stdout
if (verbose > 0):
show_tls(tlsos=tlsos_initial,
text="TLS from ADP: start TLS values",
out=out)
u_cart = xray_structure.scatterers().extract_u_cart(
xray_structure.unit_cell())
T_min = []
L_min = []
S_min = []
group_counter = 0
for tlso_initial, selection in zip(tlsos_initial, selections):
group_counter += 1
T_initial = tlso_initial.t
L_initial = tlso_initial.l
S_initial = tlso_initial.s
if (enforce_positive_definite_TL):
T_initial = adptbx.eigenvalue_filtering(T_initial)
L_initial = adptbx.eigenvalue_filtering(L_initial)
stop_flag = 0
target_stop = -1.0
sites_cart_selected = xray_structure.sites_cart().select(selection)
u_cart_selected = u_cart.select(selection)
for i in range(1, number_of_macro_cycles + 1):
target_start = target_stop
minimized = tls_from_uaniso_minimizer(
uaniso=u_cart_selected,
T_initial=T_initial,
L_initial=L_initial,
S_initial=S_initial,
refine_T=refine_T,
refine_L=refine_L,
refine_S=refine_S,
max_iterations=max_iterations,
origin=tlso_initial.origin,
sites=sites_cart_selected)
if (refine_T): T_initial = minimized.T_min
else: assert approx_equal(T_initial, minimized.T_min)
if (refine_L): L_initial = minimized.L_min
else: assert approx_equal(L_initial, minimized.L_min)
if (refine_S): S_initial = minimized.S_min
else: assert approx_equal(S_initial, minimized.S_min)
if (verbose > 0):
print >> out, "TLS group %d: minimized target = " % (
group_counter), minimized.f
T_min_ = minimized.T_min
L_min_ = minimized.L_min
if (enforce_positive_definite_TL):
T_min_ = adptbx.eigenvalue_filtering(T_min_)
L_min_ = adptbx.eigenvalue_filtering(L_min_)
T_min.append(T_min_)
L_min.append(L_min_)
S_min.append(minimized.S_min)
if (enforce_positive_definite_TL):
assert adptbx.is_positive_definite(T_min_, 1.e-6)
assert adptbx.is_positive_definite(L_min_, 1.e-6)
tlsos_result = generate_tlsos(selections=selections,
xray_structure=xray_structure,
T=T_min,
L=L_min,
S=S_min)
if (verbose > 0):
show_tls(tlsos=tlsos_result,
text="TLS from ADP: final TLS values",
out=out)
t2 = time.time()
time_tls_from_uanisos += (t2 - t1)
return tlsos_result
def exercise(small=1.e-9):
for symbol in ["P 1"]:
space_group_info = sgtbx.space_group_info(symbol=symbol)
random_xray_structure = random_structure.xray_structure(
space_group_info=space_group_info,
elements=["N"] * 10,
volume_per_atom=50.0,
random_u_iso=False,
u_iso=adptbx.b_as_u(20.0))
sg = random_xray_structure.space_group()
uc = random_xray_structure.unit_cell()
print(symbol, uc)
print()
sys.stdout.flush()
counter = 0
trials = 100000
i = 0
branch_0 = 0
branch_1 = 0
branch_1_1 = 0
branch_1_2 = 0
branch_1_2_1 = 0
branch_1_2_2 = 0
branch_1_2_3 = 0
branch_1_2_3_1 = 0
branch_1_2_3_2 = 0
while i < trials:
i += 1
counter += 1
r = random.random()
if (r < 0.333):
m = adptbx.random_u_cart(u_scale=20. * random.random(),
u_min=0)
n = adptbx.random_u_cart(u_scale=20. * random.random(),
u_min=0)
while 1:
for ind in range(6):
r = random.random()
m = flex.double(m)
if (r > 0.5):
m[ind] = n[ind]
m = list(m)
if (adptbx.is_positive_definite(m, 0)
and adptbx.is_positive_definite(n, 0)):
break
elif (r >= 0.333 and r < 0.66):
m, n = branch_3_mn()
else:
m, n = branch_2_mn(0)
m_dc = copy.deepcopy(m)
n_dc = copy.deepcopy(n)
m = factor(list(m), i)
n = factor(list(n), i)
qq = tools.common(n, m, small)
#assert approx_equal(m,m_dc)
#assert approx_equal(n,n_dc)
if (qq.branch_0()): branch_0 += 1
if (qq.branch_1()): branch_1 += 1
if (qq.branch_1_1()): branch_1_1 += 1
if (qq.branch_1_2()): branch_1_2 += 1
if (qq.branch_1_2_1()): branch_1_2_1 += 1
if (qq.branch_1_2_2()): branch_1_2_2 += 1
if (qq.branch_1_2_3()): branch_1_2_3 += 1
if (qq.branch_1_2_3_1()): branch_1_2_3_1 += 1
if (qq.branch_1_2_3_2()): branch_1_2_3_2 += 1
if (counter >= 10000):
counter = 0
print("." * 30, symbol)
print("i= ", i, "out of ", trials)
print("branch_0 = ", branch_0)
print("branch_1 = ", branch_1)
print("branch_1_1 = ", branch_1_1)
print("branch_1_2 = ", branch_1_2)
print("branch_1_2_1 = ", branch_1_2_1)
print("branch_1_2_2 = ", branch_1_2_2)
print("branch_1_2_3 = ", branch_1_2_3)
print("branch_1_2_3_1 = ", branch_1_2_3_1)
print("branch_1_2_3_2 = ", branch_1_2_3_2)
sys.stdout.flush()
def run(pdb_file_name,
n_models,
log,
output_file_name_prefix,
eps=1.e-7):
pdb_inp = iotbx.pdb.input(file_name = pdb_file_name)
pdb_hierarchy = pdb_inp.construct_hierarchy()
asc = pdb_hierarchy.atom_selection_cache()
cs = pdb_inp.crystal_symmetry_from_cryst1()
tls_extract = mmtbx.tls.tools.tls_from_pdb_inp(
remark_3_records = pdb_inp.extract_remark_iii_records(3),
pdb_hierarchy = pdb_hierarchy)
for i_group, tls_params_one_group in enumerate(tls_extract.tls_params):
selection = asc.selection(tls_params_one_group.selection_string)
pdb_hierarchy_sel = pdb_hierarchy.select(selection)
xrs = pdb_hierarchy_sel.extract_xray_structure(crystal_symmetry=cs)
deg_to_rad_scale = math.pi/180
# Units: T[A], L[deg**2], S[A*deg]
T = matrix.sym(sym_mat3=tls_params_one_group.t)
L = matrix.sym(sym_mat3=tls_params_one_group.l)
S = matrix.sqr(tls_params_one_group.s)
origin = tls_params_one_group.origin
tlso = tools.tlso(
t = T.as_sym_mat3(),
l = L.as_sym_mat3(),
s = S,
origin = origin)
# sanity check
if(not adptbx.is_positive_definite(tls_params_one_group.t, eps)):
raise Sorry("T matrix is not positive definite.")
if(not adptbx.is_positive_definite(tls_params_one_group.l, eps)):
raise Sorry("L matrix is not positive definite.")
r = analysis.run(T=T, L=L*(deg_to_rad_scale**2), S=S*deg_to_rad_scale,
log=log).self_check()
ensemble_generator_obj = ensemble_generator(
tls_from_motions_object = r,
pdb_hierarchy = pdb_hierarchy_sel,
xray_structure = xrs,
n_models = n_models,
origin = origin,
log = log)
ensemble_generator_obj.write_pdb_file(
file_name=output_file_name_prefix+"_ensemble_%s.pdb"%str(i_group))
# get U from TLS
u_from_tls = tools.uaniso_from_tls_one_group(
tlso = tlso,
sites_cart = xrs.sites_cart(),
zeroize_trace = False)
# get U from ensemble
pdb_hierarchy_from_tls = pdb_hierarchy_sel.deep_copy()
pdb_hierarchy_from_ens = pdb_hierarchy_sel.deep_copy()
u_from_ens = tools.u_cart_from_ensemble(
models = ensemble_generator_obj.states.root.models())
for i in xrange(xrs.sites_cart().size()):
print "atom %d:"%i
print " Ucart(from TLS):", ["%8.5f"%u for u in u_from_tls[i]]
print " Ucart(from ens):", ["%8.5f"%u for u in u_from_ens[i]]
#
u1, u2 = u_from_tls.as_double(), u_from_ens.as_double()
cc = flex.linear_correlation(x=u1, y=u2).coefficient()
r = flex.sum(flex.abs(u1-u2))/\
flex.sum(flex.abs(flex.abs(u1)+flex.abs(u2)))*2
print "%6.4f %6.4f"%(cc, r)
#
pdb_hierarchy_from_tls.atoms().set_uij(u_from_tls)
pdb_hierarchy_from_ens.atoms().set_uij(u_from_ens)
pdb_hierarchy_from_tls.write_pdb_file(
file_name = output_file_name_prefix+"_u_from_tls_%s.pdb"%str(i_group),
crystal_symmetry = cs)
pdb_hierarchy_from_ens.write_pdb_file(
file_name = output_file_name_prefix+"_u_from_ensemble_%s.pdb"%str(i_group),
crystal_symmetry = cs)
return ensemble_generator_obj
def exercise_branch_2_1(small = 1.e-9):
m = [2,1,2,0,0,0]
n = [2,1,1,0,0,0]
counter = 0
trials = 100000
i = 0
branch_0 = 0
branch_1 = 0
branch_1_1 = 0
branch_1_2 = 0
branch_1_2_1 = 0
branch_1_2_2 = 0
branch_1_2_3 = 0
branch_1_2_3_1 = 0
branch_1_2_3_2 = 0
while i < trials:
i += 1
m = [2,1,2,0,0,0]
n = [2,1,1,0,0,0]
counter += 1
c = scitbx.math.euler_angles_as_matrix(
[random.uniform(0,360) for j in xrange(3)], deg=True).elems
r = random.random()
if(r<0.25):
m = adptbx.c_u_c_transpose(c, m)
n = adptbx.c_u_c_transpose(c, n)
elif(r>=0.25 and r < 0.5):
m = adptbx.c_u_c_transpose(c, m)
elif(r>=0.5 and r < 0.75):
n = adptbx.c_u_c_transpose(c, n)
else:
r = random.random()
run_away = 1000
while run_away > 0:
run_away -= 1
r = random.random()
if(r<0.33):
m = adptbx.c_u_c_transpose(c, m)
n = adptbx.c_u_c_transpose(c, n)
elif(r>=0.33 and r < 0.66):
m = adptbx.c_u_c_transpose(c, m)
else:
n = adptbx.c_u_c_transpose(c, n)
m = adptbx.c_u_c_transpose(c, m)
n = adptbx.c_u_c_transpose(c, n)
m = [m[0],m[1],m[2],m[3]*random.choice((0,1)),m[4]*random.choice((0,1)),m[5]*random.choice((0,1))]
n = [n[0],n[1],n[2],n[3]*random.choice((0,1)),n[4]*random.choice((0,1)),n[5]*random.choice((0,1))]
m = factor(list(m), i)
n = factor(list(n), i)
if(adptbx.is_positive_definite(m,small) and
adptbx.is_positive_definite(n,small)): break
m_dc = copy.deepcopy(m)
n_dc = copy.deepcopy(n)
qq = tools.common(n,m,small)
#assert approx_equal(m,m_dc)
#assert approx_equal(n,n_dc)
if(qq.branch_0() ): branch_0 += 1
if(qq.branch_1() ): branch_1 += 1
if(qq.branch_1_1() ): branch_1_1 += 1
if(qq.branch_1_2() ): branch_1_2 += 1
if(qq.branch_1_2_1() ): branch_1_2_1 += 1
if(qq.branch_1_2_2() ): branch_1_2_2 += 1
if(qq.branch_1_2_3() ): branch_1_2_3 += 1
if(qq.branch_1_2_3_1()): branch_1_2_3_1 += 1
if(qq.branch_1_2_3_2()): branch_1_2_3_2 += 1
if (counter >= 10000):
counter = 0
print "."*30
print "i= ", i, "out of ", trials
print "branch_0 = ", branch_0
print "branch_1 = ", branch_1
print "branch_1_1 = ", branch_1_1
print "branch_1_2 = ", branch_1_2
print "branch_1_2_1 = ", branch_1_2_1
print "branch_1_2_2 = ", branch_1_2_2
print "branch_1_2_3 = ", branch_1_2_3
print "branch_1_2_3_1 = ", branch_1_2_3_1
print "branch_1_2_3_2 = ", branch_1_2_3_2
sys.stdout.flush()
def exercise(small = 1.e-9):
for symbol in ["P 1"]:
space_group_info = sgtbx.space_group_info(symbol = symbol)
random_xray_structure = random_structure.xray_structure(
space_group_info = space_group_info,
elements = ["N"]*10,
volume_per_atom = 50.0,
random_u_iso = False,
u_iso = adptbx.b_as_u(20.0))
sg = random_xray_structure.space_group()
uc = random_xray_structure.unit_cell()
print symbol, uc
print
sys.stdout.flush()
counter = 0
trials = 100000
i = 0
branch_0 = 0
branch_1 = 0
branch_1_1 = 0
branch_1_2 = 0
branch_1_2_1 = 0
branch_1_2_2 = 0
branch_1_2_3 = 0
branch_1_2_3_1 = 0
branch_1_2_3_2 = 0
while i < trials:
i += 1
counter += 1
r = random.random()
if(r < 0.333):
m = adptbx.random_u_cart(u_scale=20.*random.random(), u_min=0)
n = adptbx.random_u_cart(u_scale=20.*random.random(), u_min=0)
while 1:
for ind in xrange(6):
r = random.random()
m = flex.double(m)
if(r > 0.5):
m[ind] = n[ind]
m = list(m)
if(adptbx.is_positive_definite(m,0) and
adptbx.is_positive_definite(n,0)): break
elif(r>=0.333 and r<0.66):
m,n = branch_3_mn()
else:
m,n = branch_2_mn(0)
m_dc = copy.deepcopy(m)
n_dc = copy.deepcopy(n)
m = factor(list(m), i)
n = factor(list(n), i)
qq = tools.common(n,m,small)
#assert approx_equal(m,m_dc)
#assert approx_equal(n,n_dc)
if(qq.branch_0() ): branch_0 += 1
if(qq.branch_1() ): branch_1 += 1
if(qq.branch_1_1() ): branch_1_1 += 1
if(qq.branch_1_2() ): branch_1_2 += 1
if(qq.branch_1_2_1() ): branch_1_2_1 += 1
if(qq.branch_1_2_2() ): branch_1_2_2 += 1
if(qq.branch_1_2_3() ): branch_1_2_3 += 1
if(qq.branch_1_2_3_1()): branch_1_2_3_1 += 1
if(qq.branch_1_2_3_2()): branch_1_2_3_2 += 1
if (counter >= 10000):
counter = 0
print "."*30, symbol
print "i= ", i, "out of ", trials
print "branch_0 = ", branch_0
print "branch_1 = ", branch_1
print "branch_1_1 = ", branch_1_1
print "branch_1_2 = ", branch_1_2
print "branch_1_2_1 = ", branch_1_2_1
print "branch_1_2_2 = ", branch_1_2_2
print "branch_1_2_3 = ", branch_1_2_3
print "branch_1_2_3_1 = ", branch_1_2_3_1
print "branch_1_2_3_2 = ", branch_1_2_3_2
sys.stdout.flush()
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.")
