def __call__(self):
"""
Do the processing.
:return: The processed data
"""
# Set the job index
job.index = self.index
# Get the start time
start_time = time()
# Check all reflections have same imageset and get it
exp_id = list(set(self.reflections["id"]))
imageset = self.experiments[exp_id[0]].imageset
for i in exp_id[1:]:
assert (self.experiments[i].imageset == imageset
), "Task can only handle 1 imageset"
# Get the sub imageset
frame00, frame01 = self.frames
try:
frame10, frame11 = imageset.get_array_range()
except Exception:
frame10, frame11 = (0, len(imageset))
try:
assert frame00 < frame01
assert frame10 < frame11
assert frame00 >= frame10
assert frame01 <= frame11
index0 = frame00 - frame10
index1 = index0 + (frame01 - frame00)
assert index0 < index1
assert index0 >= 0
assert index1 <= len(imageset)
imageset = imageset[index0:index1]
except Exception:
raise RuntimeError("Programmer Error: bad array range")
try:
frame0, frame1 = imageset.get_array_range()
except Exception:
frame0, frame1 = (0, len(imageset))
# Initialise the dataset
image_volume = MultiPanelImageVolume()
for panel in self.experiments[0].detector:
image_volume.add(
ImageVolume(frame0, frame1,
panel.get_image_size()[1],
panel.get_image_size()[0]))
# Read all the images into a block of data
read_time = 0.0
for i in range(len(imageset)):
st = time()
image = imageset.get_corrected_data(i)
mask = imageset.get_mask(i)
if self.params.integration.lookup.mask is not None:
assert len(mask) == len(
self.params.lookup.mask
), "Mask/Image are incorrect size %d %d" % (
len(mask),
len(self.params.integration.lookup.mask),
)
mask = tuple(m1 & m2 for m1, m2 in zip(
self.params.integration.lookup.mask, mask))
image_volume.set_image(frame0 + i, make_image(image, mask))
read_time += time() - st
del image
del mask
# Process the data
st = time()
data = self.executor.process(image_volume, self.experiments,
self.reflections)
process_time = time() - st
# Set the result values
return dials.algorithms.integration.Result(
index=self.index,
reflections=self.reflections,
read_time=read_time,
process_time=process_time,
total_time=time() - start_time,
extract_time=0,
data=data,
)
def __call__(self):
'''
Do the processing.
:return: The processed data
'''
from dials.model.data import make_image
from dials.model.data import MultiPanelImageVolume
from dials.model.data import ImageVolume
from dials.algorithms.integration.processor import job
from time import time
# Set the job index
job.index = self.index
# Get the start time
start_time = time()
# Check all reflections have same imageset and get it
exp_id = list(set(self.reflections['id']))
imageset = self.experiments[exp_id[0]].imageset
for i in exp_id[1:]:
assert self.experiments[i].imageset == imageset, "Task can only handle 1 imageset"
# Get the sub imageset
frame00, frame01 = self.frames
try:
frame10, frame11 = imageset.get_array_range()
except Exception:
frame10, frame11 = (0, len(imageset))
try:
assert frame00 < frame01
assert frame10 < frame11
assert frame00 >= frame10
assert frame01 <= frame11
index0 = frame00 - frame10
index1 = index0 + (frame01 - frame00)
assert index0 < index1
assert index0 >= 0
assert index1 <= len(imageset)
imageset = imageset[index0:index1]
except Exception:
raise RuntimeError('Programmer Error: bad array range')
try:
frame0, frame1 = imageset.get_array_range()
except Exception:
frame0, frame1 = (0, len(imageset))
# Initialise the dataset
image_volume = MultiPanelImageVolume()
for panel in self.experiments[0].detector:
image_volume.add(ImageVolume(
frame0,
frame1,
panel.get_image_size()[1],
panel.get_image_size()[0]))
# Read all the images into a block of data
read_time = 0.0
for i in range(len(imageset)):
st = time()
image = imageset.get_corrected_data(i)
mask = imageset.get_mask(i)
if self.params.integration.lookup.mask is not None:
assert len(mask) == len(self.params.lookup.mask), \
"Mask/Image are incorrect size %d %d" % (
len(mask),
len(self.params.integration.lookup.mask))
mask = tuple(m1 & m2 for m1, m2 in zip(self.params.integration.lookup.mask, mask))
image_volume.set_image(frame0 + i, make_image(image, mask))
read_time += time() - st
del image
del mask
# Process the data
st = time()
data = self.executor.process(
image_volume,
self.experiments,
self.reflections)
process_time = time() - st
# Set the result values
result = Result(self.index, self.reflections)
result.read_time = read_time
result.process_time = process_time
result.total_time = time() - start_time
result.data = data
return result