def test_set_Ih_values_to_target(test_sg):
"""Test the setting of Ih values for targeted scaling."""
"""Generate input for testing joint_Ih_table."""
Ih_table = IhTable(
[generated_refl_for_splitting_1(),
generated_refl_for_splitting_2()],
test_sg,
nblocks=2,
)
Ih_table.calc_Ih()
# First check that values are set up correctly.
block_list = Ih_table.blocked_data_list
assert list(block_list[0].Ih_values) == pytest.approx(
[6.0, 17.0 / 3.0, 17.0 / 3.0, 6.0, 17.0 / 3.0])
assert list(block_list[1].Ih_values) == pytest.approx(
[16.0 / 3.0, 16.0 / 3.0, 7.0, 16.0 / 3.0, 7.0, 7.0])
# set some values in the target
# change the (2, 0, 0) reflections to (4, 0, 0) to test if they are removed
# from the blocks
t1 = generated_refl_for_splitting_1()
t2 = generated_refl_for_splitting_2()
t1["miller_index"][1] = (4, 0, 0)
t1["miller_index"][5] = (4, 0, 0)
t2["miller_index"][1] = (4, 0, 0)
target = IhTable([t1, t2], test_sg, nblocks=1)
target.blocked_data_list[0].Ih_table["Ih_values"] = np.array(
[0.1, 0.2, 0.2, 0.3, 0.3, 0.4, 0.1, 0.2, 0.3, 0.4, 0.4])
for block in block_list:
block.match_Ih_values_to_target(target)
assert list(block_list[0].Ih_values) == [0.1, 0.2, 0.2, 0.1, 0.2]
assert list(block_list[1].Ih_values) == [0.4, 0.4, 0.4]
def test_set_Ih_values_to_target(test_sg):
"""Test the setting of Ih values for targeted scaling."""
"""Generate input for testing joint_Ih_table."""
Ih_table = IhTable(
[generated_refl_for_splitting_1(),
generated_refl_for_splitting_2()],
test_sg,
nblocks=2,
)
Ih_table.calc_Ih()
# First check that values are set up correctly.
block_list = Ih_table.blocked_data_list
assert list(block_list[0].Ih_values) == [
6.0,
17.0 / 3.0,
17.0 / 3.0,
6.0,
17.0 / 3.0,
]
assert list(block_list[1].Ih_values) == [
16.0 / 3.0,
16.0 / 3.0,
7.0,
16.0 / 3.0,
7.0,
7.0,
]
target = IhTable(
[generated_refl_for_splitting_1(),
generated_refl_for_splitting_2()],
test_sg,
nblocks=1,
)
# set some values in the target
# change the (2, 0, 0) reflections to (4, 0, 0) to test if they are removed
# from the blocks
vals = target.blocked_data_list[0].asu_miller_index
vals[3] = (4, 0, 0)
vals[4] = (4, 0, 0)
vals[8] = (4, 0, 0)
target.blocked_data_list[0].Ih_table["Ih_values"] = flex.double(
[0.1, 0.2, 0.2, 0.3, 0.3, 0.4, 0.1, 0.2, 0.3, 0.4, 0.4])
for block in block_list:
block.match_Ih_values_to_target(target)
assert list(block_list[0].Ih_values) == [0.1, 0.2, 0.2, 0.1, 0.2]
assert list(block_list[1].Ih_values) == [0.4, 0.4, 0.4]
def test_IhTable_freework(large_reflection_table, small_reflection_table, test_sg):
sel1 = flex.bool(7, True)
sel1[6] = False
sel2 = flex.bool(4, True)
sel2[1] = False
Ih_table = IhTable(
reflection_tables=[
large_reflection_table.select(sel1),
small_reflection_table.select(sel2),
],
indices_lists=[sel1.iselection(), sel2.iselection()],
space_group=test_sg,
nblocks=2,
free_set_percentage=50.0,
)
assert len(Ih_table.blocked_data_list) == 3
assert Ih_table.n_datasets == 2
assert Ih_table.n_work_blocks == 2
block_list = Ih_table.Ih_table_blocks
# two standard blocks
assert block_list[0].h_index_matrix[0, 0] == 1
assert block_list[0].h_index_matrix.non_zeroes == 1
assert block_list[1].h_index_matrix[0, 0] == 1
assert block_list[1].h_index_matrix[1, 0] == 1
assert block_list[1].h_index_matrix[2, 0] == 1
assert block_list[1].h_index_matrix.non_zeroes == 3
# free set block
assert block_list[2].h_index_matrix[0, 0] == 1
assert block_list[2].h_index_matrix[1, 1] == 1
assert block_list[2].h_index_matrix[2, 2] == 1
assert block_list[2].h_index_matrix[3, 2] == 1
assert block_list[2].h_index_matrix[4, 3] == 1
assert block_list[2].h_index_matrix.non_zeroes == 5
assert list(block_list[0].block_selections[0]) == [5]
assert list(block_list[0].block_selections[1]) == []
assert list(block_list[1].block_selections[0]) == [0, 2]
assert list(block_list[1].block_selections[1]) == [0]
assert list(block_list[2].block_selections[0]) == [1, 3, 4]
assert list(block_list[2].block_selections[1]) == [3, 2]
# test get_block_selections_for_dataset
block_sels_0 = Ih_table.get_block_selections_for_dataset(0)
assert len(block_sels_0) == 3
assert list(block_sels_0[0]) == [5]
assert list(block_sels_0[1]) == [0, 2]
assert list(block_sels_0[2]) == [1, 3, 4]
block_sels_1 = Ih_table.get_block_selections_for_dataset(1)
assert len(block_sels_1) == 3
assert list(block_sels_1[0]) == []
assert list(block_sels_1[1]) == [0]
assert list(block_sels_1[2]) == [3, 2]
with pytest.raises(AssertionError):
_ = Ih_table.get_block_selections_for_dataset(2)
Ih_table.calc_Ih()
# test setting data
# set scale factors
new_s_block_2 = flex.double(range(1, 6))
Ih_table.set_inverse_scale_factors(new_s_block_2, 2)
assert list(Ih_table.Ih_table_blocks[2].inverse_scale_factors) == list(
new_s_block_2
)
# set derivatives
derivs = Mock()
Ih_table.set_derivatives(derivs, 0)
assert Ih_table.Ih_table_blocks[0].derivatives is derivs
def update_vars_side_effect(*args):
return flex.double([0.5] * len(args[0]))
# test setting an error model
em = Mock()
em.update_variances.side_effect = update_vars_side_effect
Ih_table.update_weights(em)
for block in Ih_table.Ih_table_blocks:
assert list(block.weights) == pytest.approx([2.0] * block.size)
Ih_table.calc_Ih(1)
# now test free set with offset
Ih_table = IhTable(
reflection_tables=[
large_reflection_table.select(sel1),
small_reflection_table.select(sel2),
],
indices_lists=[sel1.iselection(), sel2.iselection()],
space_group=test_sg,
nblocks=2,
free_set_percentage=50.0,
free_set_offset=1,
)
assert len(Ih_table.blocked_data_list) == 3
assert Ih_table.n_datasets == 2
assert Ih_table.n_work_blocks == 2
block_list = Ih_table.Ih_table_blocks
# two standard blocks
assert block_list[0].h_index_matrix[0, 0] == 1
assert block_list[0].h_index_matrix[1, 1] == 1
assert block_list[0].h_index_matrix.non_zeroes == 2
assert block_list[1].h_index_matrix[0, 0] == 1
assert block_list[1].h_index_matrix[1, 0] == 1
assert block_list[1].h_index_matrix[2, 1] == 1
assert block_list[1].h_index_matrix.non_zeroes == 3
# free set block
assert block_list[2].h_index_matrix[0, 0] == 1
assert block_list[2].h_index_matrix[1, 1] == 1
assert block_list[2].h_index_matrix[2, 1] == 1
assert block_list[2].h_index_matrix[3, 1] == 1
assert block_list[2].h_index_matrix.non_zeroes == 4
assert list(block_list[0].block_selections[0]) == [1, 3]
assert list(block_list[0].block_selections[1]) == []
assert list(block_list[1].block_selections[0]) == [4]
assert list(block_list[1].block_selections[1]) == [3, 2]
assert list(block_list[2].block_selections[0]) == [5, 0, 2]
assert list(block_list[2].block_selections[1]) == [0]
Ih_table.calc_Ih()
# Test the 'as_miller_array' method.
unit_cell = uctbx.unit_cell((1.0, 1.0, 1.0, 90.0, 90.0, 90.0))
arr = Ih_table.as_miller_array(unit_cell)
assert arr.size() == 5
assert list(arr.indices()) == [
(0, 0, 1),
(0, 2, 0),
(0, 4, 0),
(0, 4, 0),
(10, 0, 0),
]
assert list(arr.data()) == pytest.approx(
[x / 2.0 for x in [100.0, 60.0, 30.0, 30.0, 10.0]]
)
assert list(arr.sigmas()) == pytest.approx(
[(x / 4.0) ** 0.5 for x in [100.0, 60.0, 30.0, 30.0, 10.0]]
)
arr = Ih_table.as_miller_array(unit_cell, return_free_set_data=True)
assert arr.size() == 4
assert list(arr.indices()) == [(0, 0, 2), (1, 0, 0), (1, 0, 0), (1, 0, 0)]
assert list(arr.data()) == pytest.approx(
[x / 2.0 for x in [40.0, 100.0, 80.0, 60.0]]
)
assert list(arr.sigmas()) == pytest.approx(
[(x / 4.0) ** 0.5 for x in [50.0, 90.0, 90.0, 60.0]]
)