def run(args):
if ("--help" in args or "-h" in args) :
print "Write a CBF header from a SLAC metrology file. Parameters:"
master_phil.show(attributes_level=2)
return
user_phil = []
for arg in args:
if (os.path.isfile(arg)) :
user_phil.append(libtbx.phil.parse("""metrology_file=\"%s\"""" % arg))
else :
try :
user_phil.append(libtbx.phil.parse(arg))
except RuntimeError as e :
raise Sorry("Unrecognized argument '%s' (error: %s)" % (arg, str(e)))
params = master_phil.fetch(sources=user_phil).extract()
if (params.metrology_file is None) :
master_phil.show()
raise Usage("metrology_file must be defined (either metrology_file=XXX, or the file path alone).")
assert params.plot is not None
assert params.out is not None
print params.metrology_file
metro = read_slac_metrology(params.metrology_file, plot=params.plot)
write_cspad_cbf(None, metro, 'cbf', None, params.out, None, 0, header_only=True)
def run(self):
params, options = self.parser.parse_args(show_diff_phil=True)
experiments = flatten_experiments(params.input.experiments)
detector = experiments[0].detector
metro = map_detector_to_basis_dict(detector)
write_cspad_cbf(None, metro, 'cbf', None, params.output_def_file, None, detector.hierarchy().get_distance(), header_only=True)
print "Done"
def run(args):
command_line = (option_parser().option(
"-o",
"--output_filename",
action="store",
type="string",
help="Filename for the output cbf file",
default="gain_map.cbf"
).option(
"-m",
"--metrology",
action="store",
type="string",
help="CBF or DEF file",
default=None
).option(
"-d",
"--distance",
action="store",
type="int",
help=
"Detector distance put into the gain cbf file. Not needed for processing.",
default="0"
).option(
"-w",
"--wavelength",
action="store",
type="float",
help=
"Incident beam wavelength put into the gain cbf file. Not needed for processing.",
default="0")).process(args=args)
output_filename = command_line.options.output_filename
metrology = command_line.options.metrology
assert metrology is not None and os.path.isfile(metrology)
args = command_line.args
assert len(args) == 1
if args[0].endswith('.txt') or args[0].endswith('.gain'):
raw_data = numpy.loadtxt(args[0])
assert raw_data.shape in [(5920, 388), (11840, 194)]
tiles = convert_detector(raw_data)
else:
raise Usage(
"Gain input file should be a text file with extension .txt or .gain"
)
metro = cbf_file_to_basis_dict(metrology)
write_cspad_cbf(tiles, metro, 'cbf', None, output_filename,
command_line.options.wavelength,
command_line.options.distance)
def run(argv=None):
if argv is None:
argv = sys.argv[1:]
command_line = libtbx.option_parser.option_parser(
usage="%s files" % libtbx.env.dispatcher_name).process(args=argv)
paths = command_line.args
if len(paths) <= 0:
raise Usage("No files specified")
for path in paths:
# Load the metrology dictionary, containting basis shifts for each item in the hierarchy
metro = cbf_file_to_basis_dict(path)
# Remove from the hiearchy all but the central sensors (sensor 1 of each quadrant).
# Need to remove the sesnor basis shifts and the corresponding asic shifts
for quad in range(4):
for sensor in [0, 2, 3, 4, 5, 6, 7]:
metro.pop((0, quad, sensor))
for asic in range(2):
metro.pop((0, quad, sensor, asic))
# Renumber the sensors to 0 instead of 1
for key in metro:
if len(key) == 3:
detector, quad, sensor = key
metro[(detector, quad, 0)] = metro.pop(key)
elif len(key) == 4:
detector, quad, sensor, asic = key
metro[(detector, quad, 0, asic)] = metro.pop(key)
# Build the tiles dictionary for only sensor 1 of each quadrant. Rename that sensor to zero.
img = dxtbx.load(path)
tiles = {}
for quad in range(4):
src_sensor = 1
dest_sensor = 0
for asic in range(2):
tiles[(0, quad, dest_sensor, asic)] = img.get_raw_data()[
(quad * 16) + (src_sensor * 2) +
asic] # FIXME get the panel ID from dxtbx
destpath = os.path.splitext(path)[0] + "_pinwheel.cbf"
hierarchy = img.get_detector().hierarchy()
beam = img.get_beam()
# write the result. Have to call abs on the root distance because of a bug with the hierarchy matrix.
write_cspad_cbf(tiles, metro, 'cbf', None, destpath,
beam.get_wavelength(), hierarchy.get_distance())
def run(argv=None):
if argv is None:
argv = sys.argv[1:]
command_line = libtbx.option_parser.option_parser(
usage="%s files" % libtbx.env.dispatcher_name).process(args=argv)
paths = command_line.args
if len(paths) <= 0:
raise Usage("No files specified")
for path in paths:
# Load the metrology dictionary, containting basis shifts for each item in the hierarchy
metro = cbf_file_to_basis_dict(path)
# Remove from the hiearchy all but the central sensors (sensor 1 of each quadrant).
# Need to remove the sesnor basis shifts and the corresponding asic shifts
for quad in range(4):
for sensor in [0,2,3,4,5,6,7]:
metro.pop((0,quad,sensor))
for asic in range(2):
metro.pop((0,quad,sensor,asic))
# Renumber the sensors to 0 instead of 1
for key in metro:
if len(key) == 3:
detector, quad, sensor = key
metro[(detector,quad,0)] = metro.pop(key)
elif len(key) == 4:
detector, quad, sensor, asic = key
metro[(detector,quad,0,asic)] = metro.pop(key)
# Build the tiles dictionary for only sensor 1 of each quadrant. Rename that sensor to zero.
img = dxtbx.load(path)
tiles = {}
for quad in range(4):
src_sensor = 1
dest_sensor = 0
for asic in range(2):
tiles[(0,quad,dest_sensor,asic)] = img.get_raw_data()[(quad*16)+(src_sensor*2)+asic] # FIXME get the panel ID from dxtbx
destpath = os.path.splitext(path)[0] + "_pinwheel.cbf"
hierarchy = img.get_detector().hierarchy()
beam = img.get_beam()
# write the result. Have to call abs on the root distance because of a bug with the hierarchy matrix.
write_cspad_cbf(tiles, metro, 'cbf', None, destpath, beam.get_wavelength(), hierarchy.get_distance())
def run(args):
command_line = (
option_parser()
.option(
"-o",
"--output_filename",
action="store",
type="string",
help="Filename for the output cbf file",
default="gain_map.cbf",
)
.option("-m", "--metrology", action="store", type="string", help="CBF or DEF file", default=None)
.option(
"-d",
"--distance",
action="store",
type="int",
help="Detector distance put into the gain cbf file. Not needed for processing.",
default="0",
)
.option(
"-w",
"--wavelength",
action="store",
type="float",
help="Incident beam wavelength put into the gain cbf file. Not needed for processing.",
default="0",
)
).process(args=args)
output_filename = command_line.options.output_filename
metrology = command_line.options.metrology
assert metrology is not None and os.path.isfile(metrology)
args = command_line.args
assert len(args) == 1
if args[0].endswith(".txt") or args[0].endswith(".gain"):
raw_data = numpy.loadtxt(args[0])
assert raw_data.shape in [(5920, 388), (11840, 194)]
tiles = convert_detector(raw_data)
else:
raise Usage("Gain input file should be a text file with extension .txt or .gain")
metro = cbf_file_to_basis_dict(metrology)
write_cspad_cbf(
tiles, metro, "cbf", None, output_filename, command_line.options.wavelength, command_line.options.distance
)
def run(self):
params, options = self.parser.parse_args(show_diff_phil=True)
experiments = flatten_experiments(params.input.experiments)
detector = experiments[0].detector
metro = map_detector_to_basis_dict(detector)
write_cspad_cbf(None,
metro,
'cbf',
None,
params.output_def_file,
None,
detector.hierarchy().get_distance(),
header_only=True)
print("Done")
def run(self):
params, options = self.parser.parse_args(show_diff_phil=True)
datablocks = flatten_datablocks(params.input.datablock)
experiments = flatten_experiments(params.input.experiments)
if len(datablocks) > 0:
detector = datablocks[0].unique_detectors()[0]
else:
detector = experiments[0].detector
metro = map_detector_to_basis_dict(detector)
write_cspad_cbf(None,
metro,
'cbf',
None,
params.output_def_file,
None,
detector.hierarchy().get_distance(),
header_only=True)
print "Done"
.help = Directory with optical metrology information posistioning quadrants and sensors, corrected for
.help = rectangularity
.optional = False
out = None
.type = str
.help = Output file name
.optional = False
""")
if (__name__ == "__main__") :
user_phil = []
for arg in sys.argv[1:]:
if (os.path.isdir(arg)) :
user_phil.append(libtbx.phil.parse("""metrology_dir=\"%s\"""" % arg))
else :
try :
user_phil.append(libtbx.phil.parse(arg))
except RuntimeError, e :
raise Sorry("Unrecognized argument '%s' (error: %s)" % (arg, str(e)))
params = master_phil.fetch(sources=user_phil).extract()
if (params.metrology_dir is None) :
master_phil.show()
raise Usage("metrology_dir must be defined (either metrology_dir=XXX, or the directory path alone).")
assert params.out is not None
metro_phil = metrology2phil(params.metrology_dir, verbose=True)
write_cspad_cbf(None, metro_phil, 'calibdir', None, params.out, None, 0, header_only=True)
for p in xrange(num_sections):
for s in xrange(section_len):
for a in xrange(2):
x1,y1,x2,y2 = active_areas[tile_id]
block = data[x1:x2,y1:y2]
asics[(0, p, s, a)] = block.matrix_rot90(-rotations[tile_id])
tile_id += 1
if not 'asic_focus' in locals():
asic_focus = asics[(0, p, s, a)].focus()
else:
assert asic_focus == asics[(0, p, s, a)].focus()
# make the tiles dictionary
for p in xrange(num_sections):
tiles[(0,p)] = type(data)(flex.grid(asic_focus[0]*section_len,asic_focus[1]*2))
for s in xrange(section_len):
tiles[(0,p)].matrix_paste_block_in_place(asics[(0,p,s,0)],
i_row = s*asic_focus[0],
i_column = 0)
tiles[(0,p)].matrix_paste_block_in_place(asics[(0,p,s,1)],
i_row = s*asic_focus[0],
i_column = asic_focus[1])
tiles[(0,p)].reshape(flex.grid((section_len,asic_focus[0],asic_focus[1]*2)))
# Write the cbf file
destpath = os.path.splitext(filename)[0] + ".cbf"
write_cspad_cbf(tiles, metro, metro_style, img['TIMESTAMP'], destpath,
img['WAVELENGTH'], img['DISTANCE'])
from __future__ import division
from __future__ import print_function
# script to convert the output of refined_quadrants to a cbf header that
# can be applied to a cspad cbf with cxi.apply_metrology
# Note the hardcoded wavelength and distance. For development only.
from dials.util.command_line import Importer
importer = Importer(["refined_experiments.json"], check_format=False)
experiment = importer.experiments[0]
detector = experiment.detector
from xfel.cftbx.detector.cspad_cbf_tbx import (
write_cspad_cbf,
map_detector_to_basis_dict,
)
metro = map_detector_to_basis_dict(detector)
write_cspad_cbf(None,
metro,
"cbf",
None,
"quad_refined.def",
1.81587,
105,
header_only=True)
print("Done")
print "Write a CBF header from a SLAC metrology file. Parameters:"
master_phil.show(attributes_level=2)
return
user_phil = []
for arg in args:
if (os.path.isfile(arg)) :
user_phil.append(libtbx.phil.parse("""metrology_file=\"%s\"""" % arg))
else :
try :
user_phil.append(libtbx.phil.parse(arg))
except RuntimeError, e :
raise Sorry("Unrecognized argument '%s' (error: %s)" % (arg, str(e)))
params = master_phil.fetch(sources=user_phil).extract()
if (params.metrology_file is None) :
master_phil.show()
raise Usage("metrology_file must be defined (either metrology_file=XXX, or the file path alone).")
assert params.plot is not None
assert params.out is not None
print params.metrology_file
metro = read_slac_metrology(params.metrology_file, plot=params.plot)
write_cspad_cbf(None, metro, 'cbf', None, params.out, None, 0, header_only=True)
if (__name__ == "__main__") :
args = sys.argv[1:]
run(args)
asics[(0, p, s,
a)] = block.matrix_rot90(-rotations[tile_id])
tile_id += 1
if not 'asic_focus' in locals():
asic_focus = asics[(0, p, s, a)].focus()
else:
assert asic_focus == asics[(0, p, s, a)].focus()
# make the tiles dictionary
for p in range(num_sections):
tiles[(0, p)] = type(data)(flex.grid(asic_focus[0] * section_len,
asic_focus[1] * 2))
for s in range(section_len):
tiles[(0,
p)].matrix_paste_block_in_place(asics[(0, p, s, 0)],
i_row=s * asic_focus[0],
i_column=0)
tiles[(0,
p)].matrix_paste_block_in_place(asics[(0, p, s, 1)],
i_row=s * asic_focus[0],
i_column=asic_focus[1])
tiles[(0, p)].reshape(
flex.grid((section_len, asic_focus[0], asic_focus[1] * 2)))
# Write the cbf file
destpath = os.path.splitext(filename)[0] + ".cbf"
write_cspad_cbf(tiles, metro, metro_style, img['TIMESTAMP'], destpath,
img['WAVELENGTH'], img['DISTANCE'])
except RuntimeError, e:
raise Sorry("Unrecognized argument '%s' (error: %s)" %
(arg, str(e)))
params = master_phil.fetch(sources=user_phil).extract()
if (params.metrology_file is None):
master_phil.show()
raise Usage(
"metrology_file must be defined (either metrology_file=XXX, or the file path alone)."
)
assert params.plot is not None
assert params.out is not None
print params.metrology_file
metro = read_slac_metrology(params.metrology_file, plot=params.plot)
write_cspad_cbf(None,
metro,
'cbf',
None,
params.out,
None,
0,
header_only=True)
if (__name__ == "__main__"):
args = sys.argv[1:]
run(args)
def run(argv=None):
"""Compute mean, standard deviation, and maximum projection images
from a set of CSPAD cbf images given on the command line.
@param argv Command line argument list
@return @c 0 on successful termination, @c 1 on error, and @c 2
for command line syntax errors
"""
import libtbx.load_env
from libtbx import option_parser
from scitbx.array_family import flex
from dxtbx.format.Registry import Registry
from xfel.cftbx.detector.cspad_cbf_tbx import cbf_file_to_basis_dict, write_cspad_cbf
# from xfel.cxi.cspad_ana import cspad_tbx
# from iotbx.detectors.cspad_detector_formats import reverse_timestamp
if argv is None:
argv = sys.argv
command_line = (option_parser.option_parser(
usage="%s [-v] [-a PATH] [-m PATH] [-s PATH] " \
"image1 image2 [image3 ...]" % libtbx.env.dispatcher_name)
.option(None, "--average-path", "-a",
type="string",
default=None,
dest="avg_path",
metavar="PATH",
help="Write average image to PATH")
.option(None, "--maximum-path", "-m",
type="string",
default=None,
dest="max_path",
metavar="PATH",
help="Write maximum projection image to PATH")
.option(None, "--stddev-path", "-s",
type="string",
default=None,
dest="stddev_path",
metavar="PATH",
help="Write standard deviation image to PATH")
.option(None, "--verbose", "-v",
action="store_true",
default=False,
dest="verbose",
help="Print more information about progress")
).process(args=argv[1:])
# Note that it is not an error to omit the output paths, because
# certain statistics could still be printed, e.g. with the verbose
# option.
paths = command_line.args
if len(paths) == 0:
command_line.parser.print_usage(file=sys.stderr)
return 2
# Loop over all images and accumulate statistics.
nfail = 0
nmemb = 0
for path in paths:
if command_line.options.verbose:
sys.stdout.write("Processing %s...\n" % path)
try:
# Promote the image to double-precision floating point type.
# All real-valued flex arrays have the as_double() function.
# Warn if the header items across the set of images do not match
# up. Note that discrepancies regarding the image size are
# fatal.
if not 'reader' in locals():
reader = Registry.find(path)
img = reader(path)
if 'detector' in locals():
test_detector = img.get_detector()
if len(test_detector) != len(detector):
sys.stderr.write("Detectors do not have the same number of panels\n")
return 1
for t, d in zip(test_detector, detector):
if t.get_image_size() != d.get_image_size():
sys.stderr.write("Panel sizes do not match\n")
return 1
if t.get_pixel_size() != d.get_pixel_size():
sys.stderr.write("Pixel sizes do not match\n")
return 1
if t.get_d_matrix() != d.get_d_matrix():
sys.stderr.write("Detector panels are not all in the same location. The average will use the positions of the first image.\n")
detector = test_detector
else:
detector = img.get_detector()
data = [img.get_raw_data()[i].as_1d().as_double() for i in xrange(len(detector))]
wavelength = img.get_beam().get_wavelength()
distance = flex.mean(flex.double([d.get_directed_distance() for d in detector]))
except Exception:
nfail += 1
continue
# The sum-of-squares image is accumulated using long integers, as
# this delays the point where overflow occurs. But really, this
# is just a band-aid...
if nmemb == 0:
max_img = copy.deepcopy(data)
sum_distance = distance
sum_img = copy.deepcopy(data)
ssq_img = [flex.pow2(d) for d in data]
sum_wavelength = wavelength
metro = cbf_file_to_basis_dict(path)
else:
sel = [(d > max_d).as_1d() for d, max_d in zip(data, max_img)]
for d, max_d, s in zip(data, max_img, sel): max_d.set_selected(s, d.select(s))
sum_distance += distance
for d, sum_d in zip(data, sum_img): sum_d += d
for d, ssq_d in zip(data, ssq_img): ssq_d += flex.pow2(d)
sum_wavelength += wavelength
nmemb += 1
# Early exit if no statistics were accumulated.
if command_line.options.verbose:
sys.stderr.write("Processed %d images (%d failed)\n" % (nmemb, nfail))
if nmemb == 0:
return 0
# Calculate averages for measures where other statistics do not make
# sense. Note that avg_img is required for stddev_img.
avg_img = [sum_d.as_double() / nmemb for sum_d in sum_img]
avg_distance = sum_distance / nmemb
avg_wavelength = sum_wavelength / nmemb
def make_tiles(data, detector):
"""
Assemble a tiles dictionary as required by write_cspad_cbf, consisting of 4 arrays of shape 8x185x388.
Assumes the order in the data array matches the order of the enumerated detector panels.
"""
assert len(data) == 64
tiles = {}
s, f = 185, 194
for q_id in xrange(4):
tiles[0,q_id] = flex.double((flex.grid(s*8, f*2)))
for s_id in xrange(8):
for a_id in xrange(2):
asic_idx = (q_id*16) + (s_id*2) + a_id
asic = data[asic_idx]
asic.reshape(flex.grid((s, f)))
tiles[0, q_id].matrix_paste_block_in_place(asic, s_id*s, a_id*f)
tiles[0, q_id].reshape(flex.grid((8, s, f*2)))
return tiles
# Output the average image, maximum projection image, and standard
# deviation image, if requested.
if command_line.options.avg_path is not None:
tiles = make_tiles(avg_img, detector)
write_cspad_cbf(tiles, metro, 'cbf', None, command_line.options.avg_path, avg_wavelength, avg_distance)
if command_line.options.max_path is not None:
tiles = make_tiles(max_img, detector)
write_cspad_cbf(tiles, metro, 'cbf', None, command_line.options.max_path, avg_wavelength, avg_distance)
if command_line.options.stddev_path is not None:
stddev_img = [ssq_d.as_double() - sum_d.as_double() * avg_d for ssq_d, sum_d, avg_d in zip(ssq_img, sum_img, avg_img)]
# Accumulating floating-point numbers introduces errors, which may
# cause negative variances. Since a two-pass approach is
# unacceptable, the standard deviation is clamped at zero.
for stddev_d in stddev_img:
stddev_d.set_selected(stddev_d < 0, 0)
if nmemb == 1:
stddev_img = [flex.sqrt(stddev_d) for stddev_d in stddev_img]
else:
stddev_img = [flex.sqrt(stddev_d / (nmemb - 1)) for stddev_d in stddev_img]
tiles = make_tiles(stddev_img, detector)
write_cspad_cbf(tiles, metro, 'cbf', None, command_line.options.stddev_path, avg_wavelength, avg_distance)
return 0
from __future__ import division # script to convert the output of refined_quadrants to a cbf header that # can be applied to a cspad cbf with cxi.apply_metrology # Note the hardcoded wavelength and distance. For development only. from dials.util.command_line import Importer importer = Importer(['refined_experiments.json'], check_format=False) experiment = importer.experiments[0] detector = experiment.detector from xfel.cftbx.detector.cspad_cbf_tbx import write_cspad_cbf, map_detector_to_basis_dict metro = map_detector_to_basis_dict(detector) write_cspad_cbf(None, metro, 'cbf', None, 'quad_refined.def', 1.81587, 105, header_only=True) print "Done"
user_phil = []
for arg in sys.argv[1:]:
if (os.path.isdir(arg)):
user_phil.append(
libtbx.phil.parse("""metrology_dir=\"%s\"""" % arg))
else:
try:
user_phil.append(libtbx.phil.parse(arg))
except RuntimeError, e:
raise Sorry("Unrecognized argument '%s' (error: %s)" %
(arg, str(e)))
params = master_phil.fetch(sources=user_phil).extract()
if (params.metrology_dir is None):
master_phil.show()
raise Usage(
"metrology_dir must be defined (either metrology_dir=XXX, or the directory path alone)."
)
assert params.out is not None
metro_phil = metrology2phil(params.metrology_dir, verbose=True)
write_cspad_cbf(None,
metro_phil,
'calibdir',
None,
params.out,
None,
0,
header_only=True)
def run(argv=None):
"""Compute mean, standard deviation, and maximum projection images
from a set of CSPAD cbf images given on the command line.
@param argv Command line argument list
@return @c 0 on successful termination, @c 1 on error, and @c 2
for command line syntax errors
"""
import libtbx.load_env
from libtbx import option_parser
from scitbx.array_family import flex
from dxtbx.format.Registry import Registry
from xfel.cftbx.detector.cspad_cbf_tbx import cbf_file_to_basis_dict, write_cspad_cbf
# from xfel.cxi.cspad_ana import cspad_tbx
# from iotbx.detectors.cspad_detector_formats import reverse_timestamp
if argv is None:
argv = sys.argv
command_line = (option_parser.option_parser(
usage="%s [-v] [-a PATH] [-m PATH] [-s PATH] " \
"image1 image2 [image3 ...]" % libtbx.env.dispatcher_name)
.option(None, "--average-path", "-a",
type="string",
default=None,
dest="avg_path",
metavar="PATH",
help="Write average image to PATH")
.option(None, "--maximum-path", "-m",
type="string",
default=None,
dest="max_path",
metavar="PATH",
help="Write maximum projection image to PATH")
.option(None, "--stddev-path", "-s",
type="string",
default=None,
dest="stddev_path",
metavar="PATH",
help="Write standard deviation image to PATH")
.option(None, "--verbose", "-v",
action="store_true",
default=False,
dest="verbose",
help="Print more information about progress")
).process(args=argv[1:])
# Note that it is not an error to omit the output paths, because
# certain statistics could still be printed, e.g. with the verbose
# option.
paths = command_line.args
if len(paths) == 0:
command_line.parser.print_usage(file=sys.stderr)
return 2
# Loop over all images and accumulate statistics.
nfail = 0
nmemb = 0
for path in paths:
if command_line.options.verbose:
sys.stdout.write("Processing %s...\n" % path)
try:
# Promote the image to double-precision floating point type.
# All real-valued flex arrays have the as_double() function.
# Warn if the header items across the set of images do not match
# up. Note that discrepancies regarding the image size are
# fatal.
if not 'reader' in locals():
reader = Registry.find(path)
img = reader(path)
if 'detector' in locals():
test_detector = img.get_detector()
if len(test_detector) != len(detector):
sys.stderr.write(
"Detectors do not have the same number of panels\n")
return 1
for t, d in zip(test_detector, detector):
if t.get_image_size() != d.get_image_size():
sys.stderr.write("Panel sizes do not match\n")
return 1
if t.get_pixel_size() != d.get_pixel_size():
sys.stderr.write("Pixel sizes do not match\n")
return 1
if t.get_d_matrix() != d.get_d_matrix():
sys.stderr.write(
"Detector panels are not all in the same location. The average will use the positions of the first image.\n"
)
detector = test_detector
else:
detector = img.get_detector()
data = [
img.get_raw_data()[i].as_1d().as_double()
for i in range(len(detector))
]
wavelength = img.get_beam().get_wavelength()
distance = flex.mean(
flex.double([d.get_directed_distance() for d in detector]))
except Exception:
nfail += 1
continue
# The sum-of-squares image is accumulated using long integers, as
# this delays the point where overflow occurs. But really, this
# is just a band-aid...
if nmemb == 0:
max_img = copy.deepcopy(data)
sum_distance = distance
sum_img = copy.deepcopy(data)
ssq_img = [flex.pow2(d) for d in data]
sum_wavelength = wavelength
metro = cbf_file_to_basis_dict(path)
else:
sel = [(d > max_d).as_1d() for d, max_d in zip(data, max_img)]
for d, max_d, s in zip(data, max_img, sel):
max_d.set_selected(s, d.select(s))
sum_distance += distance
for d, sum_d in zip(data, sum_img):
sum_d += d
for d, ssq_d in zip(data, ssq_img):
ssq_d += flex.pow2(d)
sum_wavelength += wavelength
nmemb += 1
# Early exit if no statistics were accumulated.
if command_line.options.verbose:
sys.stderr.write("Processed %d images (%d failed)\n" % (nmemb, nfail))
if nmemb == 0:
return 0
# Calculate averages for measures where other statistics do not make
# sense. Note that avg_img is required for stddev_img.
avg_img = [sum_d.as_double() / nmemb for sum_d in sum_img]
avg_distance = sum_distance / nmemb
avg_wavelength = sum_wavelength / nmemb
def make_tiles(data, detector):
"""
Assemble a tiles dictionary as required by write_cspad_cbf, consisting of 4 arrays of shape 8x185x388.
Assumes the order in the data array matches the order of the enumerated detector panels.
"""
assert len(data) == 64
tiles = {}
s, f = 185, 194
for q_id in range(4):
tiles[0, q_id] = flex.double((flex.grid(s * 8, f * 2)))
for s_id in range(8):
for a_id in range(2):
asic_idx = (q_id * 16) + (s_id * 2) + a_id
asic = data[asic_idx]
asic.reshape(flex.grid((s, f)))
tiles[0, q_id].matrix_paste_block_in_place(
asic, s_id * s, a_id * f)
tiles[0, q_id].reshape(flex.grid((8, s, f * 2)))
return tiles
# Output the average image, maximum projection image, and standard
# deviation image, if requested.
if command_line.options.avg_path is not None:
tiles = make_tiles(avg_img, detector)
write_cspad_cbf(tiles, metro, 'cbf', None,
command_line.options.avg_path, avg_wavelength,
avg_distance)
if command_line.options.max_path is not None:
tiles = make_tiles(max_img, detector)
write_cspad_cbf(tiles, metro, 'cbf', None,
command_line.options.max_path, avg_wavelength,
avg_distance)
if command_line.options.stddev_path is not None:
stddev_img = [
ssq_d.as_double() - sum_d.as_double() * avg_d
for ssq_d, sum_d, avg_d in zip(ssq_img, sum_img, avg_img)
]
# Accumulating floating-point numbers introduces errors, which may
# cause negative variances. Since a two-pass approach is
# unacceptable, the standard deviation is clamped at zero.
for stddev_d in stddev_img:
stddev_d.set_selected(stddev_d < 0, 0)
if nmemb == 1:
stddev_img = [flex.sqrt(stddev_d) for stddev_d in stddev_img]
else:
stddev_img = [
flex.sqrt(stddev_d / (nmemb - 1)) for stddev_d in stddev_img
]
tiles = make_tiles(stddev_img, detector)
write_cspad_cbf(tiles, metro, 'cbf', None,
command_line.options.stddev_path, avg_wavelength,
avg_distance)
return 0