def test_crystal_with_scan_points(example_crystal):
c1 = Crystal(**example_crystal)
A = c1.get_A()
c1.set_A_at_scan_points([A for i in range(5)])
# Set the B covariance. The values are nonsense, just ensure they are
# all different
cov_B = flex.double(range(9 * 9)) * 1e-5
c1.set_B_covariance(cov_B)
cov_B.reshape(flex.grid(1, 9, 9))
cov_B_array = flex.double(flex.grid(5, 9, 9))
for i in range(5):
cov_B_array[i:(i + 1), :, :] = cov_B
c1.set_B_covariance_at_scan_points(cov_B_array)
cov_B = c1.get_B_covariance()
d = c1.to_dict()
c2 = CrystalFactory.from_dict(d)
eps = 1e-9
for Acomp in d["A_at_scan_points"]:
for e1, e2 in zip(A, Acomp):
assert abs(e1 - e2) <= eps
for covBcomp in d["B_covariance_at_scan_points"]:
for e1, e2 in zip(cov_B, covBcomp):
assert abs(e1 - e2) <= eps
assert c1 == c2
def from_dict(d):
''' Convert the dictionary to a crystal model
Params:
d The dictionary of parameters
Returns:
The crystal model
'''
from dxtbx.model import Crystal
# If None, return None
if d is None:
return None
# Check the version and id
if str(d['__id__']) != "crystal":
raise ValueError("\"__id__\" does not equal \"crystal\"")
# Extract from the dictionary
real_space_a = d['real_space_a']
real_space_b = d['real_space_b']
real_space_c = d['real_space_c']
# str required to force unicode to ascii conversion
space_group = str("Hall:" + d['space_group_hall_symbol'])
xl = Crystal(real_space_a,
real_space_b,
real_space_c,
space_group_symbol=space_group)
# Isoforms used for stills
try:
xl.identified_isoform = d['identified_isoform']
except KeyError:
pass
# Extract scan point setting matrices, if present
try:
A_at_scan_points = d['A_at_scan_points']
xl.set_A_at_scan_points(A_at_scan_points)
except KeyError:
pass
# Extract covariance of B, if present
try:
cov_B = d['B_covariance']
xl.set_B_covariance(cov_B)
except KeyError:
pass
# Extract covariance of B at scan points, if present
cov_B_at_scan_points = d.get('B_covariance_at_scan_points')
if cov_B_at_scan_points is not None:
from scitbx.array_family import flex
cov_B_at_scan_points = flex.double(cov_B_at_scan_points).as_1d()
cov_B_at_scan_points.reshape(flex.grid(xl.num_scan_points, 9, 9))
xl.set_B_covariance_at_scan_points(cov_B_at_scan_points)
return xl
def test_crystal_with_scan_points():
from dxtbx.model import Crystal, CrystalFactory
from scitbx import matrix
real_space_a = matrix.col((35.2402102454, -7.60002142787, 22.080026774))
real_space_b = matrix.col((22.659572494, 1.47163505925, -35.6586361881))
real_space_c = matrix.col((5.29417246554, 38.9981792999, 4.97368666613))
c1 = Crystal(
real_space_a=real_space_a,
real_space_b=real_space_b,
real_space_c=real_space_c,
space_group_symbol="P 1 2/m 1",
)
A = c1.get_A()
c1.set_A_at_scan_points([A for i in range(5)])
# Set the B covariance. The values are nonsense, just ensure they are
# all different
from scitbx.array_family import flex
cov_B = flex.double(range((9 * 9))) * 1e-5
c1.set_B_covariance(cov_B)
cov_B.reshape(flex.grid(1, 9, 9))
cov_B_array = flex.double(flex.grid(5, 9, 9))
for i in range(5):
cov_B_array[i : (i + 1), :, :] = cov_B
c1.set_B_covariance_at_scan_points(cov_B_array)
cov_B = c1.get_B_covariance()
d = c1.to_dict()
c2 = CrystalFactory.from_dict(d)
eps = 1e-9
for Acomp in d["A_at_scan_points"]:
for e1, e2 in zip(A, Acomp):
assert abs(e1 - e2) <= eps
for covBcomp in d["B_covariance_at_scan_points"]:
for e1, e2 in zip(cov_B, covBcomp):
assert abs(e1 - e2) <= eps
assert c1 == c2
def test_check_old_vs_new():
from dxtbx.tests.model.crystal_model_old import crystal_model_old
model_1 = Crystal(
real_space_a=(10, 0, 0),
real_space_b=(0, 11, 0),
real_space_c=(0, 0, 12),
space_group_symbol="P 1",
)
model_2 = crystal_model_old(
real_space_a=(10, 0, 0),
real_space_b=(0, 11, 0),
real_space_c=(0, 0, 12),
space_group_symbol="P 1",
)
cov_B = matrix.sqr([1] * (9 * 9))
model_1.set_B_covariance(cov_B)
model_2.set_B_covariance(cov_B)
A_list = [model_1.get_A() for i in range(20)]
model_1.set_A_at_scan_points(A_list)
model_2.set_A_at_scan_points(A_list)
A1 = model_1.get_A()
A2 = model_2.get_A()
U1 = model_1.get_U()
U2 = model_2.get_U()
B1 = model_1.get_B()
B2 = model_2.get_B()
UC1 = model_1.get_unit_cell()
UC2 = model_2.get_unit_cell()
RSV1 = model_1.get_real_space_vectors()
RSV2 = model_2.get_real_space_vectors()
SG1 = model_1.get_space_group()
SG2 = model_2.get_space_group()
assert model_1.num_scan_points == model_2.num_scan_points
A_list_1 = [
model_1.get_A_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
A_list_2 = [
model_2.get_A_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
B_list_1 = [
model_1.get_B_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
B_list_2 = [
model_2.get_B_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
U_list_1 = [
model_1.get_U_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
U_list_2 = [
model_2.get_U_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
assert approx_equal(A1, A2)
assert approx_equal(B1, B2)
assert approx_equal(U1, U2)
assert approx_equal(UC1.parameters(), UC2.parameters())
assert approx_equal(RSV1[0], RSV2[0])
assert approx_equal(RSV1[1], RSV2[1])
assert approx_equal(RSV1[2], RSV2[2])
assert str(SG1.info()) == str(SG2.info())
for i in range(model_1.get_num_scan_points()):
assert approx_equal(A_list_1[i], A_list_2[i])
assert approx_equal(B_list_1[i], B_list_2[i])
assert approx_equal(U_list_1[i], U_list_2[i])
cell_sd_1 = model_1.get_cell_parameter_sd()
cell_sd_2 = model_2.get_cell_parameter_sd()
cell_volume_sd_1 = model_1.get_cell_volume_sd()
cell_volume_sd_2 = model_2.get_cell_volume_sd()
covB1 = model_1.get_B_covariance()
covB2 = model_1.get_B_covariance()
assert approx_equal(covB1, covB2)
assert approx_equal(cell_volume_sd_1, cell_volume_sd_2)
assert approx_equal(cell_sd_1, cell_sd_2)
def from_dict(d):
''' Convert the dictionary to a crystal model
Params:
d The dictionary of parameters
Returns:
The crystal model
'''
from dxtbx.model import Crystal
# If None, return None
if d is None:
return None
# Check the version and id
if str(d['__id__']) != "crystal":
raise ValueError("\"__id__\" does not equal \"crystal\"")
# Extract from the dictionary
real_space_a = d['real_space_a']
real_space_b = d['real_space_b']
real_space_c = d['real_space_c']
# str required to force unicode to ascii conversion
space_group = str("Hall:" + d['space_group_hall_symbol'])
xl = Crystal(real_space_a,
real_space_b,
real_space_c,
space_group_symbol=space_group)
# New parameters for maximum likelihood values
try:
xl._ML_half_mosaicity_deg = d['ML_half_mosaicity_deg']
except KeyError:
pass
try:
xl._ML_domain_size_ang = d['ML_domain_size_ang']
except KeyError:
pass
# Isoforms used for stills
try:
xl.identified_isoform = d['identified_isoform']
except KeyError:
pass
# Extract scan point setting matrices, if present
try:
A_at_scan_points = d['A_at_scan_points']
xl.set_A_at_scan_points(A_at_scan_points)
except KeyError:
pass
# Extract covariance of B, if present
try:
cov_B = d['B_covariance']
xl.set_B_covariance(cov_B)
except KeyError:
pass
# Extract mosaicity, if present
try:
mosaicity = d['mosaicity']
xl.set_mosaicity(mosaicity)
except KeyError:
pass
return xl
