def test_cspad_cbf_in_memory(dials_regression, tmpdir):
tmpdir.chdir()
# Check the data files for this test exist
image_path = os.path.join(dials_regression, "image_examples",
"LCLS_cspad_nexus", 'idx-20130301060858801.cbf')
assert os.path.isfile(image_path)
with open("process_lcls.phil", 'w') as f:
f.write("""
dispatch.squash_errors = False
spotfinder {
filter.min_spot_size=2
threshold.dispersion.gain=25
threshold.dispersion.global_threshold=100
}
indexing {
known_symmetry {
space_group = P6122
unit_cell = 92.9 92.9 130.4 90 90 120
}
refinement_protocol.d_min_start=1.7
stills.refine_candidates_with_known_symmetry=True
}
""")
params = phil_scope.fetch(parse(file_name="process_lcls.phil")).extract()
params.output.datablock_filename = None
processor = Processor(params)
mem_img = dxtbx.load(image_path)
raw_data = mem_img.get_raw_data(
) # cache the raw data to prevent swig errors
mem_img = FormatCBFCspadInMemory(mem_img._cbf_handle)
mem_img._raw_data = raw_data
mem_img._cbf_handle = None # drop the file handle to prevent swig errors
imgset = ImageSet(ImageSetData(MemReader([mem_img]), MemMasker([mem_img])))
imgset.set_beam(mem_img.get_beam())
imgset.set_detector(mem_img.get_detector())
datablock = DataBlockFactory.from_imageset(imgset)[0]
processor.process_datablock("20130301060858801",
datablock) # index/integrate the image
result = "idx-20130301060858801_integrated.pickle"
n_refls = range(
140, 152) # large ranges to handle platform-specific differences
with open(result, 'rb') as f:
table = pickle.load(f)
assert len(table) in n_refls, len(table)
assert 'id' in table
assert (table['id'] == 0).count(False) == 0
def do_work(i, item_list):
processor = Processor(copy.deepcopy(self.params), composite_tag = "%04d"%i)
for item in item_list:
tag, filename = item
datablock = do_import(filename)
imagesets = datablock.extract_imagesets()
if len(imagesets) == 0 or len(imagesets[0]) == 0:
logger.info("Zero length imageset in file: %s"%filename)
return
if len(imagesets) > 1:
raise Abort("Found more than one imageset in file: %s"%filename)
if len(imagesets[0]) > 1:
raise Abort("Found a multi-image file. Run again with pre_import=True")
if self.reference_detector is not None:
from dxtbx.model import Detector
imagesets[0].set_detector(Detector.from_dict(self.reference_detector.to_dict()))
update_geometry(imagesets[0])
processor.process_datablock(tag, datablock)
processor.finalize()
def test_cspad_cbf_in_memory(self):
from os.path import join, exists
import os, dxtbx
from uuid import uuid4
from dials.command_line.stills_process import phil_scope, Processor
from libtbx.phil import parse
from dxtbx.imageset import ImageSet, ImageSetData, MemReader, MemMasker
from dxtbx.datablock import DataBlockFactory
from dxtbx.format.FormatCBFCspad import FormatCBFCspadInMemory
import cPickle as pickle
dirname = 'tmp_%s' % uuid4().hex
os.mkdir(dirname)
os.chdir(dirname)
assert exists(join(self.lcls_path, 'idx-20130301060858801.cbf'))
f = open("process_lcls.phil", 'w')
f.write("""
dispatch.squash_errors = False
spotfinder {
filter.min_spot_size=2
threshold.dispersion.gain=25
threshold.dispersion.global_threshold=100
}
indexing {
known_symmetry {
space_group = P6122
unit_cell = 92.9 92.9 130.4 90 90 120
}
refinement_protocol.d_min_start=1.7
stills.refine_candidates_with_known_symmetry=True
}
""")
f.close()
params = phil_scope.fetch(
parse(file_name="process_lcls.phil")).extract()
params.output.datablock_filename = None
processor = Processor(params)
mem_img = dxtbx.load(join(self.lcls_path, 'idx-20130301060858801.cbf'))
raw_data = mem_img.get_raw_data(
) # cache the raw data to prevent swig errors
mem_img = FormatCBFCspadInMemory(mem_img._cbf_handle)
mem_img._raw_data = raw_data
mem_img._cbf_handle = None # drop the file handle to prevent swig errors
imgset = ImageSet(
ImageSetData(MemReader([mem_img]), MemMasker([mem_img])))
imgset.set_beam(mem_img.get_beam())
imgset.set_detector(mem_img.get_detector())
datablock = DataBlockFactory.from_imageset(imgset)[0]
processor.process_datablock("20130301060858801",
datablock) # index/integrate the image
result = "idx-20130301060858801_integrated.pickle"
#n_refls = range(140,152) # large ranges to handle platform-specific differences
# 09/20/17 Changes to still indexer: refine candidate basis vectors in target symmetry if supplied
#n_refls = range(128,140) # large ranges to handle platform-specific differences
# 09/27/17 Bugfix for refine_candidates_with_known_symmetry
n_refls = range(
140, 152) # large ranges to handle platform-specific differences
table = pickle.load(open(result, 'rb'))
assert len(table) in n_refls, len(table)
assert 'id' in table
assert (table['id'] == 0).count(False) == 0
print 'OK'