class Test(TestForOverlaps):
def __init__(self):
from dials.util.options import Importer, flatten_experiments, flatten_reflections
import libtbx.load_env
try:
dials_regression = libtbx.env.dist_path('dials_regression')
except KeyError, e:
print 'SKIP: dials_regression not configured'
exit(0)
# test data
import os
refl_path = os.path.join(dials_regression, 'integration_test_data',
'stills_PSII',
'idx-20161021225550223_integrated.pickle')
expt_path = os.path.join(
dials_regression, 'integration_test_data', 'stills_PSII',
'idx-20161021225550223_refined_experiments.json')
importer = Importer([refl_path, refl_path, expt_path, expt_path],
read_experiments=True,
read_reflections=True,
check_format=False)
self.reflections = flatten_reflections(importer.reflections)
self.experiments = flatten_experiments(importer.experiments)
from dials.algorithms.integration.overlaps_filter import OverlapsFilterMultiExpt
overlaps_filter = OverlapsFilterMultiExpt(self.reflections[0],
self.experiments)
overlaps_filter.remove_foreground_foreground_overlaps()
overlaps_filter.remove_foreground_background_overlaps()
self.reflections = [overlaps_filter.refl]
def __call__(self):
overlaps_scope = self.params.integration.overlaps_filter
if True in [
overlaps_scope.foreground_foreground.enable,
overlaps_scope.foreground_background.enable,
]:
from dials.algorithms.integration.overlaps_filter import OverlapsFilterMultiExpt
overlaps_filter = OverlapsFilterMultiExpt(self.reflections,
self.experiments)
if overlaps_scope.foreground_foreground.enable:
overlaps_filter.remove_foreground_foreground_overlaps()
if overlaps_scope.foreground_background.enable:
overlaps_filter.remove_foreground_background_overlaps()
self.reflections = overlaps_filter.refl
def test_for_overlaps(dials_regression):
from cctbx.array_family import flex
from dials.algorithms.shoebox import MaskCode
code_fgd = MaskCode.Foreground | MaskCode.Valid
def is_fgd(code):
return (code & code_fgd) == code_fgd
code_bgd = MaskCode.Background | MaskCode.Valid
code_overlap = code_fgd | code_bgd
def is_overlap(code):
return (code & code_overlap) == code_overlap
from dials.util.options import Importer, flatten_experiments, flatten_reflections
# test data
refl_path = os.path.join(
dials_regression,
"integration_test_data",
"stills_PSII",
"idx-20161021225550223_integrated.pickle",
)
expt_path = os.path.join(
dials_regression,
"integration_test_data",
"stills_PSII",
"idx-20161021225550223_refined_experiments.json",
)
importer = Importer(
[refl_path, refl_path, expt_path, expt_path],
read_experiments=True,
read_reflections=True,
check_format=False,
)
reflections = flatten_reflections(importer.reflections)
experiments = flatten_experiments(importer.experiments)
from dials.algorithms.integration.overlaps_filter import OverlapsFilterMultiExpt
overlaps_filter = OverlapsFilterMultiExpt(reflections[0], experiments)
overlaps_filter.remove_foreground_foreground_overlaps()
overlaps_filter.remove_foreground_background_overlaps()
reflections = [overlaps_filter.refl]
for expt, refl in zip(experiments, reflections):
det = expt.detector
size_fast, size_slow = det[0].get_image_size()
mask_array = flex.size_t(size_fast * size_slow)
for obs in refl.rows():
shoebox = obs["shoebox"]
fast_coords = range(shoebox.xsize())
slow_coords = range(shoebox.ysize())
for f, s in zip(fast_coords, slow_coords):
f_abs = f + shoebox.bbox[0] # relative to detector
s_abs = s + shoebox.bbox[2] # relative to detector
posn = f_abs + s_abs * size_fast # position in mask_array
posn_in_shoebox = f + shoebox.xsize() * s # position in shoebox
assert not (
is_fgd(shoebox.mask[posn_in_shoebox])
and is_fgd(mask_array[posn])
), "Overlapping foreground found at indexed position (%d, %d), " % (
f_abs,
s_abs,
) + "observed centroid (%d, %d)" % (
obs["xyzcal.px"][0],
obs["xyzcal.px"][1],
)
try:
mask_array[posn] |= shoebox.mask[posn_in_shoebox]
except IndexError:
continue
for i, this_code in enumerate(mask_array):
assert not is_overlap(
this_code
), "Overlapping foreground and background found at (%d, %d)" % (
i % shoebox.xsize(),
i // shoebox.xsize(),
)