1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
|
"""Tests for ΔCC½ algorithms."""
from __future__ import annotations
from unittest import mock
from dxtbx.model import Crystal, Experiment, ExperimentList, Scan
from dials.algorithms.statistics.cc_half_algorithm import CCHalfFromDials
from dials.array_family import flex
from dials.command_line.compute_delta_cchalf import phil_scope
def generated_exp(n=1):
"""Generate an experiment list with two experiments."""
experiments = ExperimentList()
exp_dict = {
"__id__": "crystal",
"real_space_a": [1.0, 0.0, 0.0],
"real_space_b": [0.0, 1.0, 0.0],
"real_space_c": [0.0, 0.0, 2.0],
"space_group_hall_symbol": " C 2y",
}
for i in range(n):
experiments.append(
Experiment(
scan=Scan(image_range=[1, 25], oscillation=[0.0, 1.0]),
crystal=Crystal.from_dict(exp_dict),
identifier=str(i),
)
)
return experiments
def generated_refl():
"""Generate test data."""
refls = flex.reflection_table()
refls["intensity.scale.value"] = flex.double(range(50))
refls["intensity.scale.variance"] = flex.double(range(50))
refls["inverse_scale_factor"] = flex.double(50, 1.0)
refls["id"] = flex.int([0] * 25 + [1] * 25)
refls["xyzobs.px.value"] = flex.vec3_double(
[(0, 0, i + 0.5) for i in range(25)] * 2
)
vals = [0, 1, 2, 3, 48, 49]
# set first two of first sweep, and last two of last sweep as outliers
outliers = flex.bool(50, False)
for v in vals:
outliers[v] = True
refls.set_flags(outliers, refls.flags.outlier_in_scaling)
refls.experiment_identifiers()[0] = "0"
refls.experiment_identifiers()[1] = "1"
return refls
def test_setup_of_CCHalfFromDials():
"""Test the correct setup in image group mode.
Test for the case of outliers at the end of images, and image ranges not
equaling a multiple of the grouping."""
params = phil_scope.extract()
params.mode = "image_group"
expts = generated_exp(n=2)
refls = generated_refl()
# Expected behaviour is that the outliers will not be included in the
# image range, and that all groups will have at least 10 images in.
script = CCHalfFromDials(params, expts, refls)
assert script.group_to_datasetid_and_range == {
0: ("0", (5, 14)),
1: ("0", (15, 25)),
2: ("1", (1, 10)),
3: ("1", (11, 23)),
}
assert script.datasetid_to_groups == {"0": [0, 1], "1": [2, 3]}
def test_exclusion_in_CCHalfFromDials():
"""Test the exclusion of image groups."""
# Same input as above, but mock DeltaCCHalf algorithm to just test
# interpretation of results and setting of excluded regions. With the
# input, test that outlier edges are correctly removed.
params = phil_scope.extract()
params.mode = "image_group"
expts = generated_exp(n=2)
refls = generated_refl()
def mock_algorithm(*_):
"""Mock a result from DeltaCCHalf"""
algo = mock.Mock()
algo.run.return_value = None
algo.results_summary = {
"per_dataset_delta_cc_half_values": {
"delta_cc_half_values": [-5.0, -2.0, 4.0, -5.0],
"datasets": [0, 1, 2, 3],
},
"dataset_removal": {"cutoff_value": -1.0},
}
algo.cchalf_i = {0: 80.0, 1: 85.0, 2: 78.0, 3: 79.0}
algo.delta_cchalf_i = {0: 0.0, 1: 5.0, 2: -2.0, 3: -1.0}
return algo
with mock.patch(
"dials.algorithms.statistics.cc_half_algorithm.DeltaCCHalf",
side_effect=mock_algorithm,
):
script = CCHalfFromDials(params, expts, refls)
script.run()
table = script.get_table(True)
assert table
assert script.datasetid_to_groups == {"0": [], "1": [2]} # all but 3 removed
expts = script.experiments
assert list(expts.identifiers()) == ["1"]
assert expts[0].scan.get_valid_image_ranges(expts.identifiers()[0]) == [(1, 10)]
assert script.results_summary["dataset_removal"][
"experiment_ids_fully_removed"
] == [0]
assert script.results_summary["dataset_removal"][
"experiments_fully_removed"
] == ["0"]
|
