def make_imageset(filenames, format_class=None, check_format=True,
single_file_indices=None, format_kwargs=None):
'''Create an image set'''
from dxtbx.format.Registry import Registry
from format.FormatMultiImage import FormatMultiImage
# Get the format object
if format_class == None and check_format:
format_class = Registry.find(filenames[0])
if format_class is None:
reader = NullReader(filenames, single_file_indices is not None)
else:
if issubclass(format_class, FormatMultiImage):
assert len(set(filenames)) == 1
if format_kwargs is None:
format_kwargs = {}
format_instance = format_class(filenames[0], **format_kwargs)
reader = SingleFileReader(format_instance)
else:
reader = MultiFileReader(format_class, filenames,
format_kwargs=format_kwargs)
# Return the imageset
return ImageSet(reader, indices=single_file_indices,
format_kwargs=format_kwargs)
def run(self):
from dxtbx.imageset import MultiFileReader, ImageSweep
from dxtbx.format.Registry import Registry
# Get the filenames
filenames = self.get_file_list()
# Create the format class
format_class = Registry.find(filenames[0])
# Create the reader
reader = MultiFileReader(format_class, filenames)
# Create the sweep
sweep = ImageSweep(reader)
# Run a load of tests
self.tst_get_item(sweep)
self.tst_len(sweep, len(filenames))
self.tst_iter(sweep)
self.tst_indices(sweep, range(0, 9))
self.tst_paths(sweep, filenames)
self.tst_is_valid(sweep)
self.tst_get_detectorbase(sweep, range(len(filenames)), 9)
self.tst_get_models(sweep, range(len(filenames)), 9)
self.tst_get_array_range(sweep, (0, 9))
self.tst_to_array(sweep, (3, 7), (3, 7, 50, 100, 100, 200))
self.tst_set_models(sweep)
def from_template(template, image_range=None, check_headers=False,
check_format=True):
'''Create a new sweep from a template.
Params:
template The template argument
image_range The image range
check_headers Check the headers to ensure all images are valid
Returns:
A list of sweeps
'''
import os
from dxtbx.format.Registry import Registry
from dxtbx.sweep_filenames import template_image_range
if not check_format: assert not check_headers
# Check the template is valid
if template.count('#') < 1:
raise ValueError("Invalid template")
# Get the template format
pfx = template.split('#')[0]
sfx = template.split('#')[-1]
template_format = '%s%%0%dd%s' % (pfx, template.count('#'), sfx)
# Get the template image range
if image_range is None:
image_range = template_image_range(template)
# Set the image range
array_range = (image_range[0] - 1, image_range[1])
# Create the sweep file list
filenames = SweepFileList(template_format, array_range)
# Get the format class
if check_format:
format_class = Registry.find(filenames[0])
from format.FormatMultiImage import FormatMultiImage
if issubclass(format_class, FormatMultiImage):
assert len(filenames) == 1
format_instance = format_class(filenames[0])
reader = SingleFileReader(format_instance)
else:
reader = MultiFileReader(format_class, filenames)
else:
reader = NullReader(filenames)
# Create the sweep object
sweep = ImageSweep(reader)
# Check the sweep is valid
if check_headers and not sweep.is_valid():
raise RuntimeError('Invalid sweep of images')
# Return the sweep
return [sweep]
def dxtbx_spotfinder_factory(phil_params): from dxtbx.format.Registry import Registry reader = Registry.find(phil_params.distl.image[0]) from spotfinder.dxtbx_toolbox.practical_heuristics import heuristics_base Spotfinder = heuristics_base(phil_params) return Spotfinder
def make_imageset(filenames,
format_class=None,
check_format=True,
single_file_indices=None,
format_kwargs=None):
'''Create an image set'''
from dxtbx.format.Registry import Registry
from dxtbx.format.Format import Format
from dxtbx.format.FormatMultiImage import FormatMultiImage
# Get the format object
if format_class == None:
if check_format:
format_class = Registry.find(filenames[0])
else:
if single_file_indices is None or len(single_file_indices) == 0:
format_class = Format
else:
format_class = FormatMultiImage
else:
format_class = format_class
imageset = format_class.get_imageset(
filenames,
single_file_indices = single_file_indices,
as_imageset = True,
format_kwargs = format_kwargs,
check_format = check_format)
# Return the imageset
return imageset
def TestRegistry2(files):
'''First find the class, then read every frame with it.'''
s = time.time()
format = Registry.find(files[0])
b0 = format(files[0]).get_beam()
g0 = format(files[0]).get_goniometer()
d0 = format(files[0]).get_detector()
for f in files:
print f
i = format(f)
print i.get_beam()
print i.get_goniometer()
print i.get_detector()
print i.get_scan()
print i.get_cube()
print i.get_beam() == b0, i.get_goniometer() == g0, \
i.get_detector() == d0
return time.time() - s
def run(self):
from dxtbx.imageset import MultiFileReader, ImageSet
from dxtbx.format.Registry import Registry
# Get the filenames
filenames = self.get_file_list()
# Create the format class
format_class = Registry.find(filenames[0])
# Create the reader
reader = MultiFileReader(format_class, filenames)
# Create the imageset
imageset = ImageSet(reader)
# Run a load of tests
self.tst_get_item(imageset)
self.tst_len(imageset, len(filenames))
self.tst_iter(imageset)
self.tst_indices(imageset, range(0, 9))
self.tst_paths(imageset, filenames)
self.tst_is_valid(imageset)
self.tst_get_detectorbase(imageset, range(len(filenames)), 9)
self.tst_get_models(imageset, range(len(filenames)), 9)
def _create_imageset(filelist, check_headers):
'''Create an image set'''
from dxtbx.format.Registry import Registry
# Extract info from filelist
template, indices, is_sweep = filelist
# Get the template format
count = template.count('#')
if count > 0:
pfx = template.split('#')[0]
sfx = template.split('#')[-1]
template_format = '%s%%0%dd%s' % (pfx, template.count('#'), sfx)
filenames = [template_format % index for index in indices]
else:
filenames = [template]
# Sort the filenames
filenames = sorted(filenames)
# Get the format object
format_class = Registry.find(filenames[0])
# Create the imageset
imageset = format_class.get_imageset(filenames, as_imageset=True)
# Return the image set
return imageset
def pydiffdump_fast(files):
'''First find the class, then read every frame with it.'''
s = time.time()
format = Registry.find(files[0])
scan = None
for f in files:
i = format(f)
print 'Beam:'
print i.get_xbeam()
print 'Goniometer:'
print i.get_xgoniometer()
print 'Detector:'
print i.get_xdetector()
print 'Scan:'
print i.get_xscan()
if scan is None:
scan = i.get_xscan()
else:
scan += i.get_xscan()
print scan
return time.time() - s
def test_nexus_file(dials_regression):
filename = os.path.join(dials_regression, "image_examples",
"LCLS_cspad_nexus",
"cxi78513_bslz4_r0014_subset4_master.h5")
from dxtbx.format.Registry import Registry
format_class = Registry.find(filename)
iset = format_class.get_imageset([filename])
assert len(iset) == 2
for i in range(len(iset)):
data = iset.get_raw_data(i)
mask = iset.get_mask(i)
b = iset.get_beam(i)
d = iset.get_detector(i)
g = iset.get_goniometer(i)
s = iset.get_scan(i)
iset = format_class.get_imageset([filename], single_file_indices=[1])
assert len(iset) == 1
for i in range(len(iset)):
data = iset.get_raw_data(i)
mask = iset.get_mask(i)
b = iset.get_beam(i)
d = iset.get_detector(i)
g = iset.get_goniometer(i)
s = iset.get_scan(i)
def test_SACLA_MPCCD_Cheetah_File(dials_regression, lazy):
filename = os.path.join(dials_regression, "image_examples",
"SACLA_MPCCD_Cheetah", "run266702-0-subset.h5")
from dxtbx.format.Registry import Registry
format_class = Registry.find(filename)
iset = format_class.get_imageset([filename], lazy=lazy)
assert len(iset) == 4
for i in range(len(iset)):
assert iset.get_raw_data(i)
# assert iset.get_mask(i)
assert iset.get_beam(i)
assert iset.get_detector(i)
assert iset.get_goniometer(i) is None
assert iset.get_scan(i) is None
iset = format_class.get_imageset([filename],
single_file_indices=[1],
lazy=lazy)
assert len(iset) == 1
for i in range(len(iset)):
assert iset.get_raw_data(i)
# assert iset.get_mask(i)
assert iset.get_beam(i)
assert iset.get_detector(i)
assert iset.get_goniometer(i) is None
assert iset.get_scan(i) is None
def pydiffdump(files):
'''Print the class which claims to work with each file.'''
s = time.time()
for f in files:
print f
format = Registry.find(f)
print format.__name__
if format.understand(f):
i = format(f)
print 'Beam:'
print i.get_beam()
print 'Goniometer:'
print i.get_goniometer()
print 'Detector:'
print i.get_detector()
print 'Scan:'
print i.get_scan()
return time.time() - s
def run(self):
from dxtbx.format.Registry import Registry
format_class = Registry.find(self.filename)
iset = format_class.get_imageset([self.filename])
assert len(iset) == 2
for i in range(len(iset)):
data = iset.get_raw_data(i)
mask = iset.get_mask(i)
b = iset.get_beam(i)
d = iset.get_detector(i)
g = iset.get_goniometer(i)
s = iset.get_scan(i)
print 'OK'
iset = format_class.get_imageset([self.filename],
single_file_indices=[1])
assert len(iset) == 1
for i in range(len(iset)):
data = iset.get_raw_data(i)
mask = iset.get_mask(i)
b = iset.get_beam(i)
d = iset.get_detector(i)
g = iset.get_goniometer(i)
s = iset.get_scan(i)
print 'OK'
def read(self, path):
if self.command_line.options.verbose:
print "Processing %s" % path
from dxtbx.format.Registry import Registry
from dxtbx.format.FormatMultiImage import FormatMultiImage
format_class = Registry.find(path)
assert not issubclass(
format_class,
FormatMultiImage), "Average container files seperately"
img_instance = format_class(path)
beam = img_instance.get_beam()
assert len(img_instance.get_detector()) == 1
detector = img_instance.get_detector()[0]
beam_center = detector.get_beam_centre(beam.get_s0())
detector_address = format_class.__name__
distance = detector.get_distance()
img = img_instance.get_raw_data().as_1d().as_double()
pixel_size = 0.5 * sum(detector.get_pixel_size())
saturated_value = int(round(detector.get_trusted_range()[1]))
size = detector.get_image_size()
wavelength = beam.get_wavelength()
active_areas = flex.int((0, 0, size[0], size[1]))
return beam_center, detector_address, distance, img, pixel_size, saturated_value, size, wavelength, active_areas
def read_single_image(path):
if command_line.options.verbose:
sys.stdout.write("Processing %s...\n" % path)
from dxtbx.format.Registry import Registry
format_class = Registry.find(path)
i = format_class(path)
beam = i.get_beam()
assert len(i.get_detector()) == 1
detector = i.get_detector()[0]
beam_center = detector.get_beam_centre(beam.get_s0())
detector_address = format_class.__name__
distance = detector.get_distance()
img = i.get_raw_data().as_1d().as_double()
pixel_size = 0.5 * sum(detector.get_pixel_size())
saturated_value = int(round(detector.get_trusted_range()[1]))
size = detector.get_image_size()
scan = i.get_scan()
if scan is None:
time_tuple = (0, 0)
else:
time_tuple = (scan.get_epochs()[0], 0)
wavelength = beam.get_wavelength()
active_areas = flex.int((0, 0, size[0], size[1]))
return beam_center, detector_address, distance, img, pixel_size, saturated_value, size, time_tuple, wavelength, active_areas
def ImageFactory(filename, optional_index=None):
from iotbx.detectors import url_support
from libtbx.utils import Sorry
if os.path.isfile(filename):
if not os.access(filename, os.R_OK):
raise Sorry("No read access to file %s" % filename)
from dxtbx.format.Registry import Registry
format_instance = Registry.find(filename)
instance = format_instance(filename)
if optional_index is not None:
return instance.get_detectorbase(optional_index)
return instance.get_detectorbase()
A = url_support.potential_url_request(filename)
if A.is_url_request():
for utype in all_url_types:
try:
I = utype(filename)
I.readHeader()
return I
except Exception:
pass
raise ImageException(filename +
" does not work as a functioning image URL")
raise ImageException(filename +
" not recognized as any known detector image type")
def cbf_file_to_basis_dict(path): """ Maps a cbf file to a dictionary of tuples and basis objects, in the same form as the above from read_optical_metrology_from_flat_file @param path cbf file path """ from dxtbx.format.Registry import Registry reader = Registry.find(path) instance = reader(path) return map_detector_to_basis_dict(instance.get_detector())
def cbf_file_to_basis_dict(path): """ Maps a cbf file to a dictionary of tuples and basis objects, in the same form as the above from read_optical_metrology_from_flat_file @param path cbf file path """ from dxtbx.format.Registry import Registry reader = Registry.find(path) instance = reader(path) return map_detector_to_basis_dict(instance.get_detector())
def find_format(self, filename):
''' Check the current and child formats, otherwise search the registry. '''
from dxtbx.format.Registry import Registry
try:
if self._format_class == None or not self.understand(filename):
self._format_class = Registry.find(filename)
self._format_class = self.check_child_formats(filename)
except Exception:
return None
return self._format_class
def find_format(self, filename):
''' Check the current and child formats, otherwise search the registry. '''
from dxtbx.format.Registry import Registry
try:
if self._format_class == None or not self.understand(filename):
self._format_class = Registry.find(filename)
self._format_class = self.check_child_formats(filename)
except Exception:
return None
return self._format_class
def centroid_files_and_imageset(centroid_files):
from dxtbx.format.Registry import Registry
# Create the format class
format_class = Registry.find(centroid_files[0])
# Create the reader
imageset = format_class.get_imageset(centroid_files, as_imageset=True)
return centroid_files, imageset
def tst_dxtbx_compressed():
import libtbx.load_env
try:
dials_regression = libtbx.env.dist_path('dials_regression')
except KeyError:
print 'FAIL: dials_regression not configured'
return
import os
from dxtbx.format.Registry import Registry
from dials_regression.image_examples.get_all_working_images import \
get_all_working_images
# test that reading gz or bz2 compressed files works: it doesn't!
from libtbx import smart_open
from libtbx.test_utils import open_tmp_directory
import shutil
tmp_dir = open_tmp_directory()
print tmp_dir
for directory, image in get_all_working_images():
file_path = os.path.join(dials_regression, 'image_examples', directory,
image)
for ext in ('.gz', '.bz2')[:]:
compressed_path = os.path.join(tmp_dir,
os.path.basename(file_path)) + ext
with open(file_path, 'rb') as f_in, smart_open.for_writing(
compressed_path) as f_out:
shutil.copyfileobj(f_in, f_out)
print file_path, compressed_path
format = Registry.find(compressed_path)
try:
i = format(compressed_path)
except Exception:
print 'Error reading compressed file: %s' % compressed_path
import traceback
traceback.print_exc()
else:
print 'Successfully read compressed file: %s' % compressed_path
det = i.get_detector()
if det is not None:
size = det[0].get_image_size()
b = i.get_beam()
g = i.get_goniometer()
s = i.get_scan()
try:
d = i.get_raw_data()
except IOError:
pass
print 'OK'
def __init__(self, filename=None, imageset=None):
""" Provide a file name or imageset as input """
assert [filename, imageset].count(
None
) == 1, "Supply either filename or imageset"
if filename is not None:
format_class = Registry.find(filename)
imageset = format_class.get_imageset([filename])
self.imageset = imageset
def __call__(self, filename):
''' Check the current and child formats, otherwise search the registry. '''
from dxtbx.format.Registry import Registry
try:
if self._format_class == None or not self.understand(filename):
self._format_class = Registry.find(filename)
self._format_class = self.check_child_formats(filename)
if self._verbose:
print 'Using %s for %s' % (self._format_class.__name__, filename)
except Exception:
return None
return self._format_class
def __call__(self, filename):
''' Check the current and child formats, otherwise search the registry. '''
from dxtbx.format.Registry import Registry
try:
if self._format_class == None or not self.understand(filename):
self._format_class = Registry.find(filename)
self._format_class = self.check_child_formats(filename)
if self._verbose:
print('Using %s for %s' % (self._format_class.__name__, filename))
except Exception:
return None
return self._format_class
def oneImage(self,framenumber):
self.reporters[framenumber] = []
from dxtbx.format.Registry import Registry
filename = self.phil_params.distl.image[framenumber]
reader = Registry.find(filename)
img = reader(filename)
detector = img.get_detector()
beam = img.get_beam()
S0 = beam.get_s0()
data = img.get_raw_data()
scan = img.get_scan()
print scan
if scan is None:
print "No scan"
RR = (0,1)
else:
print scan.get_oscillation()
RR = scan.get_oscillation_range()
from spotfinder.dxtbx_toolbox import Distl
sfall = Distl(params = self.phil_params, detector = detector, beam = beam, data = data)
resolutions = flex.double()
spotlist = []
from dials.model.data import ReflectionList,Reflection
reflections = ReflectionList()
for ip,panel in enumerate(detector):
for spot in sfall.finderlist[ip].spots:
resolutions.append( panel.get_resolution_at_pixel(S0, (spot.ctr_mass_x(), spot.ctr_mass_y())) )
spotlist.append(spot)
refl = Reflection()
refl.panel_number = ip
refl.centroid_position = (spot.ctr_mass_x(), spot.ctr_mass_y(),0.0)
refl.centroid_variance = (0.5,0.5,0.0)
reflections.append(refl)
selection = (resolutions>0.0)
if self.phil_params.distl.res.outer is not None:
selection = (selection and (resolutions>self.phil_params.distl.res.outer))
if self.phil_params.distl.res.inner is not None:
selection = (selection and (resolutions<self.phil_params.distl.res.inner))
reflections = reflections.select(selection)
return dict(detector=detector, beam=beam, reflections=reflections, scan = scan,
gonio = img.get_goniometer())
def load(filename):
"""Use DXTBX to get the files from the input filename.
Params:
filename The input filename
Returns:
The dxtbx format instance
"""
from dxtbx.format.Registry import Registry
format_instance = Registry.find(filename)
return format_instance(filename)
def load(filename):
"""Use DXTBX to get the files from the input filename.
Params:
filename The input filename
Returns:
The dxtbx format instance
"""
from dxtbx.format.Registry import Registry
format_instance = Registry.find(filename)
return format_instance(filename)
def _create_sweep(filelist, check_headers):
"""Create a sweep"""
import os
from dxtbx.format.Registry import Registry
# Extract info from filelist
template, indices, is_sweep = filelist
# Get the template format
count = template.count("#")
if count > 0:
pfx = template.split("#")[0]
sfx = template.split("#")[-1]
template_format = "%s%%0%dd%s" % (pfx, template.count("#"), sfx)
filenames = [template_format % index for index in indices]
else:
filenames = [template]
# Sort the filenames
filenames = sorted(filenames)
# Get the format object
format_class = Registry.find(filenames[0])
# Get the first image and our understanding
first_image = filenames[0]
# Get the directory and first filename and set the template format
directory, first_image_name = os.path.split(first_image)
first_image_number = indices[0]
# Get the template format
pfx = template.split("#")[0]
sfx = template.split("#")[-1]
template_format = "%s%%0%dd%s" % (pfx, template.count("#"), sfx)
# Set the image range
array_range = (min(indices) - 1, max(indices))
# Create the sweep file list
filenames = SweepFileList(template_format, array_range)
# Create the sweep object
sweep = ImageSweep(MultiFileReader(format_class, filenames))
# Check the sweep is valid
if check_headers and not sweep.is_valid():
raise RuntimeError("Invalid sweep of images")
# Return the sweep
return sweep
def _create_sweep(filelist, check_headers):
'''Create a sweep'''
import os
from dxtbx.format.Registry import Registry
# Extract info from filelist
template, indices, is_sweep = filelist
# Get the template format
count = template.count('#')
if count > 0:
pfx = template.split('#')[0]
sfx = template.split('#')[-1]
template_format = '%s%%0%dd%s' % (pfx, template.count('#'), sfx)
filenames = [template_format % index for index in indices]
else:
filenames = [template]
# Sort the filenames
filenames = sorted(filenames)
# Get the format object
format_class = Registry.find(filenames[0])
# Get the first image and our understanding
first_image = filenames[0]
# Get the directory and first filename and set the template format
directory, first_image_name = os.path.split(first_image)
first_image_number = indices[0]
# Get the template format
pfx = template.split('#')[0]
sfx = template.split('#')[-1]
template_format = '%s%%0%dd%s' % (pfx, template.count('#'), sfx)
# Set the image range
array_range = (min(indices) - 1, max(indices))
# Create the sweep file list
filenames = SweepFileList(template_format, array_range)
# Create the sweep object
sweep = ImageSweep(MultiFileReader(format_class, filenames))
# Check the sweep is valid
if check_headers and not sweep.is_valid():
raise RuntimeError('Invalid sweep of images')
# Return the sweep
return sweep
def print_detector_info2(image):
"""
Print out information on the detector given an image
"""
format_instance = Registry.find(image)
instance = format_instance(image)
# adds parameters (iotbx)
temp = instance.get_detectorbase()
print "\nInformation from dxtbx Registry"
print "================================="
for key, val in temp.parameters.iteritems():
print "%20s::%s" % (key, val)
def print_detector_info2(image):
"""
Print out information on the detector given an image
"""
format_instance = Registry.find(image)
instance = format_instance(image)
# adds parameters (iotbx)
temp = instance.get_detectorbase()
print "\nInformation from dxtbx Registry"
print "================================="
for key, val in temp.parameters.iteritems():
print "%20s::%s" % (key, val)
def load(filename):
"""Use DXTBX to load the input filename.
:param filename: The input filename
:type filename: str or py.path
:returns: A dxtbx Format-subclass instance for the file type
:raises IOError: if the file format could not be determined
"""
from dxtbx.format.Registry import Registry
# Unwrap py.path objects into strings
if hasattr(filename, "strpath"):
filename = filename.strpath
format_instance = Registry.find(filename)
return format_instance(filename)
def load(filename):
"""Use DXTBX to load the input filename.
:param filename: The input filename
:type filename: os.PathLike or str or bytes
:returns: A dxtbx Format-subclass instance for the file type
:raises IOError: if the file format could not be determined
"""
from dxtbx.format.Registry import Registry
# Unwrap PEP-519-style objects. This covers py.path, pathlib, ...
if hasattr(filename, "__fspath__"):
filename = filename.__fspath__()
format_instance = Registry.find(filename)
return format_instance(filename)
def _create_sweep(filelist, check_headers):
'''Create a sweep'''
import os
from dxtbx.format.Registry import Registry
# Extract info from filelist
template, indices, is_sweep = filelist
# Get the template format
count = template.count('#')
if count > 0:
pfx = template.split('#')[0]
sfx = template.split('#')[-1]
template_format = '%s%%0%dd%s' % (pfx, template.count('#'), sfx)
filenames = [template_format % index for index in indices]
else:
filenames = [template]
# Sort the filenames
filenames = sorted(filenames)
# Get the format object
format_class = Registry.find(filenames[0])
# Get the first image and our understanding
first_image = filenames[0]
# Get the directory and first filename and set the template format
directory, first_image_name = os.path.split(first_image)
first_image_number = indices[0]
# Get the template format
pfx = template.split('#')[0]
sfx = template.split('#')[-1]
template_format = '%s%%0%dd%s' % (pfx, template.count('#'), sfx)
# Set the image range
array_range = (min(indices) - 1, max(indices))
# Create the sweep file list
filenames = [template_format % (i + 1) for i in range(*array_range)]
sweep = format_class.get_imageset(filenames,
template=template,
as_sweep=True)
# Return the sweep
return sweep
def run(self):
from dxtbx.imageset import MultiFileState
from dxtbx.format.Registry import Registry
# Get the filenames
filenames = self.get_filenames()
# Get the parameters we need
format_class = Registry.find(filenames[0])
# Create the state object
state = MultiFileState(format_class)
# Run a load of tests
self.tst_format_class(state, format_class)
self.tst_load_file(state, filenames)
def get_item(key):
format_class = None
image_file = image_glob % key
json_file = json_glob % key
print(image_file)
if format_class is None:
format_class = Registry.find(image_file)
i = format_class(image_file)
Z = i.get_smv_header(image_file)
ABC = Z[1]["DIRECT_SPACE_ABC"]
abc = tuple([float(a) for a in ABC.split(",")])
from dxtbx.model.experiment_list import ExperimentListFactory
EC = ExperimentListFactory.from_json_file(json_file,
check_format=False)[0].crystal
return dict(serial_no=key, ABC=abc, integrated_crystal_model=EC)
def compare_two_images(reference, test, tolerance_count=10):
print("Comparing", reference, test)
from dxtbx.format.Registry import Registry
beam = []
data = []
detector = []
headers = []
for i, fk in enumerate([reference, test]):
format_instance = Registry.find(fk)
instance = format_instance(fk)
beam.append(instance.get_beam())
detector.append(instance.get_detector())
data.append(instance.get_raw_data())
if True: #optional test
print(beam[-1])
print(instance.get_goniometer())
print(detector[-1])
print(instance.get_scan())
headers.append(instance.get_smv_header(fk))
if headers[0] == headers[1]:
print("Both headers identical")
else:
#print headers[0]
#print headers[1]
for key in headers[0][1]:
if key not in headers[1][1]: print("second data lacks key", key)
elif headers[0][1][key] != headers[1][1][key]:
print("Key comparison:", key, headers[0][1][key],
headers[1][1][key])
assert len(data[1]) == len(data[0])
diff_data = data[1] - data[0]
no_differences = True
ndiff = 0
for idiff, diff in enumerate(diff_data):
if diff != 0:
if ndiff < 200:
print("difference index %d:(%d,%d)" %
(idiff, idiff // 3000, idiff % 3000),
diff) # only print the first 200 differences
ndiff += 1
no_differences = False
print("There are %d differences" % ndiff)
#assert no_differences
assert ndiff < tolerance_count, "There are %d differences" % ndiff
def test_format(dials_regression, image):
from dxtbx.format.Registry import Registry
db_fail_count = 0
print(image)
image = os.path.join(dials_regression, *(image.split('/')))
format_class = Registry.find(image)
reader = format_class.get_reader()([image])
masker = format_class.get_masker()([image])
N = len(reader)
for i in range(N):
data = reader.read(i)
mask = masker.get(i)
iset = format_class.get_imageset([image])
def cbf2img(file):
from dxtbx.format.Registry import Registry
import sys, os
f = None
if file.split(".")[-1].lower() == "cbf" and os.path.exists(file):
if f is None:
f = Registry.find(file)
img = f(file)
db = img.get_detectorbase()
db.readHeader()
db.read()
db.show_header()
destpath = file.rstrip(".cbf") + ".img"
print "Writing %s as %s"%(file,destpath)
db.debug_write(destpath)
def print_header():
import sys
from dxtbx.format.Registry import Registry
from scitbx.array_family import flex
# this will do the lookup for every frame - this is strictly not needed
# if all frames are from the same instrument
for arg in sys.argv[1:]:
print '=== %s ===' % arg
format_class = Registry.find(arg)
print 'Using header reader: %s' % format_class.__name__
i = format_class(arg)
beam = i.get_beam()
goniometer = i.get_goniometer()
detector = i.get_detector()
scan = i.get_scan()
if beam is None:
print 'No beam model found'
else:
print beam
if detector is None:
print 'No detector model found'
else:
print detector
if goniometer is None:
print 'No goniometer model found'
else:
print goniometer
if scan is None:
print 'No scan model found'
else:
print scan
from dxtbx.format.FormatMultiImage import FormatMultiImage
if not issubclass(format_class, FormatMultiImage):
try:
raw_data = i.get_raw_data()
if not isinstance(raw_data, tuple):
raw_data = (raw_data,)
d = [p.as_1d() for p in raw_data]
print 'Total Counts: %d' % sum([flex.sum(p.select(p >= 0)) for p in d])
except AttributeError, e:
print "Could not read image data"
def TestRegistry(files):
'''Print the class which claims to work with each file.'''
s = time.time()
for f in files:
print f
format = Registry.find(f)
print format.__name__
if format.understand(f):
i = format(f)
print i.get_beam()
print i.get_goniometer()
print i.get_detector()
return time.time() - s
def print_total():
import sys
from dxtbx.format.Registry import Registry
# this will do the lookup for every frame - this is strictly not needed
# if all frames are from the same instrument
for arg in sys.argv[1:]:
print '=== %s ===' % arg
format_class = Registry.find(arg)
print 'Using header reader: %s' % format_class.__name__
i = format_class(arg)
image_size = i.get_detector()[0].get_image_size()
d = i.get_raw_data()
if not isinstance(d, tuple):
d = (d,)
d = [p.as_1d() for p in d]
total = sum([sum(p.select(p >= 0)) for p in d])
print 'Total Counts: %d' % total
print 'Average Counts: %.2f' % (total / (image_size[0] * image_size[1]))
def make_imageset(filenames, format_class=None, check_format=True):
"""Create an image set"""
from dxtbx.format.Registry import Registry
from format.FormatMultiImage import FormatMultiImage
# Get the format object
if format_class == None and check_format:
format_class = Registry.find(filenames[0])
if format_class is None:
reader = NullReader(filenames)
else:
if issubclass(format_class, FormatMultiImage):
assert len(filenames) == 1
format_instance = format_class(filenames[0])
reader = SingleFileReader(format_instance)
else:
reader = MultiFileReader(format_class, filenames)
# Return the imageset
return ImageSet(reader)
def run_tests(self, filenames):
from dxtbx.imageset import MultiFileReader
from dxtbx.format.Registry import Registry
# Get the parameters we need
format_class = Registry.find(filenames[0])
# Create the reader
reader = MultiFileReader(format_class, filenames)
# Run a load of tests
self.tst_get_image_paths(reader, filenames)
self.tst_get_format_class(reader, format_class)
self.tst_get_image_size(reader)
self.tst_get_path(reader, filenames)
self.tst_get_detectorbase(reader)
self.tst_get_models(reader)
self.tst_read(reader)
self.tst_get_format(reader)
self.tst_is_valid(reader)
def ImageFactory(filename):
from iotbx.detectors import url_support
from libtbx.utils import Sorry
if os.path.isfile(filename):
if not os.access(filename, os.R_OK):
raise Sorry("No read access to file %s" % filename)
from dxtbx.format.Registry import Registry
format_instance = Registry.find(filename)
instance = format_instance(filename)
return instance.get_detectorbase()
A = url_support.potential_url_request(filename)
if A.is_url_request():
for utype in all_url_types:
try:
I = utype(filename)
I.readHeader()
return I
except Exception:
pass
raise ImageException(filename+" does not work as a functioning image URL")
raise ImageException(filename+" not recognized as any known detector image type")
def _create_imageset(filelist, check_headers):
"""Create an image set"""
from dxtbx.format.Registry import Registry
# Extract info from filelist
template, indices, is_sweep = filelist
# Get the template format
count = template.count("#")
if count > 0:
pfx = template.split("#")[0]
sfx = template.split("#")[-1]
template_format = "%s%%0%dd%s" % (pfx, template.count("#"), sfx)
filenames = [template_format % index for index in indices]
else:
filenames = [template]
# Sort the filenames
filenames = sorted(filenames)
# Get the format object
format_class = Registry.find(filenames[0])
# Create the image set object
from format.FormatMultiImage import FormatMultiImage
if issubclass(format_class, FormatMultiImage):
assert len(filenames) == 1
format_instance = format_class(filenames[0])
image_set = ImageSet(SingleFileReader(format_instance))
else:
image_set = ImageSet(MultiFileReader(format_class, filenames))
# Check the image set is valid
if check_headers and not image_set.is_valid():
raise RuntimeError("Invalid ImageSet")
# Return the image set
return image_set
def TestRegistry3(files):
'''First find the class, then read every frame with it, then add the scans
together to make sure that they all make sense.'''
s = time.time()
format = Registry.find(files[0])
scan = format(files[0]).get_scan()
for f in files[1:]:
i = format(f)
scan += i.get_scan()
print scan
print scan[:len(scan) // 2]
print scan[:]
print scan[:len(scan)]
print scan[1 + len(scan) // 2:]
return time.time() - s
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
def run(argv=None):
import libtbx.option_parser
if (argv is None):
argv = sys.argv
command_line = (libtbx.option_parser.option_parser(
usage="%s [-v] [-p poly_mask] [-c circle_mask] [-a avg_max] [-s stddev_max] [-m maxproj_min] [-x mask_pix_val] [-o output] avg_path stddev_path max_path" % libtbx.env.dispatcher_name)
.option(None, "--verbose", "-v",
action="store_true",
default=False,
dest="verbose",
help="Print more information about progress")
.option(None, "--poly_mask", "-p",
type="string",
default=None,
dest="poly_mask",
help="Polygon to mask out. Comma-seperated string of xy pairs.")
.option(None, "--circle_mask", "-c",
type="string",
default=None,
dest="circle_mask",
help="Circle to mask out. Comma-seperated string of x, y, and radius.")
.option(None, "--avg_max", "-a",
type="float",
default=2000.0,
dest="avg_max",
help="Maximum ADU that pixels in the average image are allowed to have before masked out")
.option(None, "--stddev_max", "-s",
type="float",
default=10.0,
dest="stddev_max",
help="Maximum ADU that pixels in the standard deviation image are allowed to have before masked out")
.option(None, "--maxproj_min", "-m",
type="float",
default=300.0,
dest="maxproj_min",
help="Minimum ADU that pixels in the maximum projection image are allowed to have before masked out")
.option(None, "--mask_pix_val", "-x",
type="int",
default=-2,
dest="mask_pix_val",
help="Value for masked out pixels")
.option(None, "--detector_format_version", "-d",
type="string",
default=None,
dest="detector_format_version",
help="detector format version string")
.option(None, "--output", "-o",
type="string",
default="mask_.pickle",
dest="destpath",
help="output file path, should be *.pickle")
).process(args=argv[1:])
# Must have exactly three remaining arguments.
paths = command_line.args
if (len(paths) != 3):
command_line.parser.print_usage(file=sys.stderr)
return
if command_line.options.detector_format_version is None:
address = timestamp = None
else:
from xfel.cxi.cspad_ana.cspad_tbx import evt_timestamp
from xfel.detector_formats import address_and_timestamp_from_detector_format_version
address, timestamp = address_and_timestamp_from_detector_format_version(command_line.options.detector_format_version)
timestamp = evt_timestamp((timestamp,0))
poly_mask = None
if not command_line.options.poly_mask == None:
poly_mask = []
poly_mask_tmp = command_line.options.poly_mask.split(",")
if len(poly_mask_tmp) % 2 != 0:
command_line.parser.print_usage(file=sys.stderr)
return
odd = True
for item in poly_mask_tmp:
try:
if odd:
poly_mask.append(int(item))
else:
poly_mask[-1] = (poly_mask[-1],int(item))
except ValueError:
command_line.parser.print_usage(file=sys.stderr)
return
odd = not odd
circle_mask = None
if command_line.options.circle_mask is not None:
circle_mask_tmp = command_line.options.circle_mask.split(",")
if len(circle_mask_tmp) != 3:
command_line.parser.print_usage(file=sys.stderr)
return
try:
circle_mask = (int(circle_mask_tmp[0]),int(circle_mask_tmp[1]),int(circle_mask_tmp[2]))
except ValueError:
command_line.parser.print_usage(file=sys.stderr)
return
avg_path = paths[0]
stddev_path = paths[1]
max_path = paths[2]
# load the three images
format_class = Registry.find(avg_path)
avg_f = format_class(avg_path)
avg_i = avg_f.get_detectorbase()
avg_d = avg_i.get_raw_data()
stddev_f = format_class(stddev_path)
stddev_i = stddev_f.get_detectorbase()
stddev_d = stddev_i.get_raw_data()
max_f = format_class(max_path)
max_i = max_f.get_detectorbase()
max_d = max_i.get_raw_data()
# first find all the pixels in the average that are less than zero or greater
# than a cutoff and set them to the masking value
avg_d.set_selected((avg_d <= 0) | (avg_d > command_line.options.avg_max), command_line.options.mask_pix_val)
# set all the rest of the pixels to zero. They will be accepted
avg_d.set_selected(avg_d != command_line.options.mask_pix_val, 0)
# mask out the overly noisy or flat pixels
avg_d.set_selected(stddev_d <= 0, command_line.options.mask_pix_val)
avg_d.set_selected(stddev_d >= command_line.options.stddev_max, command_line.options.mask_pix_val)
# these are the non-bonded pixels
avg_d.set_selected(max_d < command_line.options.maxproj_min, command_line.options.mask_pix_val)
# calculate the beam center
panel = avg_f.get_detector()[0]
bcx, bcy = panel.get_beam_centre(avg_f.get_beam().get_s0())
if poly_mask is not None or circle_mask is not None:
minx = miny = 0
maxx = avg_d.focus()[0]
maxy = avg_d.focus()[1]
if poly_mask is not None:
minx = min([x[0] for x in poly_mask])
miny = min([y[1] for y in poly_mask])
maxx = max([x[0] for x in poly_mask])
maxy = max([y[1] for y in poly_mask])
if circle_mask is not None:
circle_x, circle_y, radius = circle_mask
if circle_x - radius < minx: minx = circle_x - radius
if circle_y - radius < miny: miny = circle_y - radius
if circle_x + radius > maxx: maxx = circle_x + radius
if circle_y + radius > maxy: maxy = circle_y + radius
sel = avg_d == command_line.options.mask_pix_val
for j in xrange(miny, maxy):
for i in xrange(minx, maxx):
idx = j * avg_d.focus()[0] + i
if not sel[idx]:
if poly_mask is not None and point_in_polygon((i,j),poly_mask):
sel[idx] = True
elif circle_mask is not None and point_inside_circle(i,j,circle_x,circle_y,radius):
sel[idx] = True
avg_d.set_selected(sel,command_line.options.mask_pix_val)
# have to re-layout the data to match how it was stored originally
shifted_int_data_old = avg_d
shifted_int_data_new = shifted_int_data_old.__class__(
flex.grid(shifted_int_data_old.focus()))
shifted_int_data_new += command_line.options.mask_pix_val
phil = avg_i.horizons_phil_cache
manager = avg_i.get_tile_manager(phil)
for i,shift in enumerate(manager.effective_translations()):
shift_slow = shift[0]
shift_fast = shift[1]
ur_slow = phil.distl.detector_tiling[4 * i + 0] + shift_slow
ur_fast = phil.distl.detector_tiling[4 * i + 1] + shift_fast
ll_slow = phil.distl.detector_tiling[4 * i + 2] + shift_slow
ll_fast = phil.distl.detector_tiling[4 * i + 3] + shift_fast
#print "Shifting tile at (%d, %d) by (%d, %d)" % (ur_slow-shift_slow, ur_fast-shift_fast, -shift_slow, -shift_fast)
shifted_int_data_new.matrix_paste_block_in_place(
block = shifted_int_data_old.matrix_copy_block(
i_row=ur_slow,i_column=ur_fast,
n_rows=ll_slow-ur_slow, n_columns=ll_fast-ur_fast),
i_row = ur_slow - shift_slow,
i_column = ur_fast - shift_fast
)
d = dpack(
active_areas=avg_i.parameters['ACTIVE_AREAS'],
address=address,
beam_center_x=bcx,
beam_center_y=bcy,
data=shifted_int_data_new,
distance=avg_i.distance,
timestamp=timestamp,
wavelength=avg_i.wavelength,
xtal_target=None,
pixel_size=avg_i.pixel_size,
saturated_value=avg_i.saturation)
dwritef2(d, command_line.options.destpath)
#the minimum number of pixels to mask out cooresponding to the interstitial regions for the CS-PAD
min_count = 818265 # (1765 * 1765) - (194 * 185 * 64)
masked_out = len(avg_d.as_1d().select((avg_d == command_line.options.mask_pix_val).as_1d()))
assert masked_out >= min_count
print "Masked out %d pixels out of %d (%.2f%%)"% \
(masked_out-min_count,len(avg_d)-min_count,(masked_out-min_count)*100/(len(avg_d)-min_count))
def failover_dxtbx(image_file):
'''Failover to use the dxtbx to read the image headers...'''
# replacement dxtbx for rigaku saturns sometimes
from dxtbx.format.Registry import Registry
from dxtbx.model.detector_helpers_types import detector_helpers_types
global last_format
if last_format:
iformat = last_format
else:
iformat = Registry.find(image_file)
from xia2.Handlers.Streams import Debug
Debug.write('Using dxtbx format instance: %s' % iformat.__name__)
if not iformat.understand(image_file):
raise RuntimeError, 'image file %s not understood by dxtbx' % \
image_file
last_format = iformat
i = iformat(image_file)
b = i.get_beam()
g = i.get_goniometer()
d = i.get_detector()
s = i.get_scan()
header = { }
if not hasattr(d, 'get_image_size'):
# cope with new detector as array of panels dxtbx api
fast, slow = map(int, d[0].get_image_size())
_f, _s = d[0].get_pixel_size()
F = matrix.col(d[0].get_fast_axis())
S = matrix.col(d[0].get_slow_axis())
N = F.cross(S)
origin = matrix.col(d[0].get_origin())
else:
fast, slow = map(int, d.get_image_size())
_f, _s = d.get_pixel_size()
F = matrix.col(d.get_fast_axis())
S = matrix.col(d.get_slow_axis())
N = F.cross(S)
origin = matrix.col(d.get_origin())
beam = matrix.col(b.get_direction())
# FIXME detector has methods to compute the beam centre now...
centre = - (origin - origin.dot(N) * N)
x = centre.dot(F)
y = centre.dot(S)
header['fast_direction'] = F.elems
header['slow_direction'] = S.elems
header['rotation_axis'] = g.get_rotation_axis()
if hasattr(s, 'get_exposure_time'):
header['exposure_time'] = s.get_exposure_time()
else:
header['exposure_time'] = s.get_exposure_times()[0]
header['distance'] = math.fabs(origin.dot(N))
if math.fabs(beam.angle(N, deg = True) - 180) < 0.1:
header['two_theta'] = 180 - beam.angle(N, deg = True)
else:
header['two_theta'] = - beam.angle(N, deg = True)
header['raw_beam'] = x, y
header['phi_start'] = s.get_oscillation()[0]
header['phi_width'] = s.get_oscillation()[1]
header['phi_end'] = sum(s.get_oscillation())
header['pixel'] = _f, _s
# FIXME this is very bad as it relates to teh legacy backwards Mosflm
# beam centre standard still... FIXME-SCI-948
header['beam'] = y, x
header['epoch'] = s.get_image_epoch(s.get_image_range()[0])
header['date'] = time.ctime(header['epoch'])
header['wavelength'] = b.get_wavelength()
header['size'] = fast, slow
if hasattr(i, 'detector_class'):
header['detector_class'] = i.detector_class
header['detector'] = i.detector
else:
if hasattr(d, 'get_type'):
# cope with new detector as array of panels API
dtype = d.get_type()
else:
dtype = d[0].get_type()
detector_type = detector_helpers_types.get(
dtype, fast, slow, int(1000 * _f), int(1000 * _s))
header['detector_class'] = detector_type.replace('-', ' ')
header['detector'] = detector_type.split('-')[0]
return header
def event(self, evt, env):
from dxtbx.format.Registry import Registry
from os.path import exists
from time import sleep
# Nop if there is no image. For experiments configured to have
# exactly one event per calibration cycle, this should never
# happen.
if self._path is None:
evt.put(skip_event_flag(), "skip_event")
return
# Skip this event if the template isn't in the path
if self._template is not None and not True in [t in self._path for t in self._template.split(',')]:
evt.put(skip_event_flag(), "skip_event")
return
if "phi" in self._path:
evt.put(skip_event_flag(), "skip_event")
return
# Wait for the image to appear in the file system, probing for it
# at exponentially increasing delays.
t = 1
t_tot = 0
if not exists(self._path):
self._logger.info("Waiting for path %s"%self._path)
while not exists(self._path):
if t_tot > 1:
self._logger.info("Timeout waiting for path %s"%self._path)
evt.put(skip_event_flag(), "skip_event")
self._logger.info("Image not found: %s"%self._path)
return
sleep(t)
t_tot += t
t *= 2
# Find a matching Format object and instantiate it using the
# given path. If the Format object does not understand the image,
# try determining a new format. XXX Emits "Couldn't create a
# detector model for this image".
if self._fmt is None:
self._fmt = Registry.find(self._path)
if self._fmt is None:
evt.put(skip_event_flag(), "skip_event")
return
img = self._fmt(self._path)
if img is None:
self._fmt = Registry.find(self._path)
if self._fmt is None:
evt.put(skip_event_flag(), "skip_event")
return
img = self._fmt(self._path)
if img is None:
evt.put(skip_event_flag(), "skip_event")
return
self._logger.info(
"Reading %s using %s" % (self._path, self._fmt.__name__))
# Get the raw image data and convert to double precision floating
# point array. XXX Why will img.get_raw_data() not work, like it
# does in print_header?
db = img.get_detectorbase()
db.readHeader()
db.read()
data = db.get_raw_data().as_double()
# Get the pixel size and store it for common_mode.py
detector = img.get_detector()[0]
ps = detector.get_pixel_size()
assert ps[0] == ps[1]
pixel_size = ps[0]
evt.put(ps[0],"marccd_pixel_size")
evt.put(detector.get_trusted_range()[1],"marccd_saturated_value")
evt.put(detector.get_distance(),"marccd_distance")
# If the beam center isn't provided in the config file, get it from the
# image. It will probably be wrong.
if self._beam_x is None or self._beam_y is None:
self._beam_x, self._beam_y = detector.get_beam_centre_px(img.get_beam().get_s0())
self._beam_x = int(round(self._beam_x))
self._beam_y = int(round(self._beam_y))
# Crop the data so that the beam center is in the center of the image
maxy, maxx = data.focus()
minsize = min([self._beam_x,self._beam_y,maxx-self._beam_x,maxy-self._beam_y])
data = data[self._beam_y-minsize:self._beam_y+minsize,self._beam_x-minsize:self._beam_x+minsize]
evt.put((minsize,minsize),"marccd_beam_center")
evt.put(flex.int([0,0,minsize*2,minsize*2]),"marccd_active_areas")
# Store the image in the event.
evt.put(data, self._address)
# Store the .mmcd file name in the event
evt.put(self._mccd_name, "mccd_name")
evt_time = cspad_tbx.evt_time(evt) # tuple of seconds, milliseconds
timestamp = cspad_tbx.evt_timestamp(evt_time) # human readable format
self._logger.info("converted %s to pickle with timestamp %s" %(self._path, timestamp))
# This should not be necessary as the machine is configured with
# one event per calibration cycle.
self._path = None
def make_sweep(
template, indices, format_class=None, beam=None, detector=None, goniometer=None, scan=None, check_format=True
):
"""Create a sweep"""
import os
from dxtbx.format.Registry import Registry
from format.FormatMultiImage import FormatMultiImage
indices = sorted(indices)
# Get the template format
count = template.count("#")
if count > 0:
pfx = template.split("#")[0]
sfx = template.split("#")[-1]
template_format = "%s%%0%dd%s" % (pfx, template.count("#"), sfx)
filenames = [template_format % index for index in indices]
else:
template_format = None
filenames = [template]
# Sort the filenames
filenames = sorted(filenames)
# Get the first image and our understanding
first_image = filenames[0]
# Get the directory and first filename and set the template format
directory, first_image_name = os.path.split(first_image)
first_image_number = indices[0]
# Set the image range
array_range = (min(indices) - 1, max(indices))
if scan is not None:
assert array_range == scan.get_array_range()
# Get the format object and reader
if format_class is None and check_format:
format_class = Registry.find(filenames[0])
# Create the reader
indices = None
if format_class is None:
if template_format is not None:
filenames = SweepFileList(template_format, array_range)
reader = NullReader(filenames)
else:
if issubclass(format_class, FormatMultiImage):
assert len(filenames) == 1
format_instance = format_class(filenames[0])
if scan is not None:
image0 = scan.get_array_range()[0]
indices = list(range(scan.get_num_images()))
reader = SingleFileReader(format_instance)
else:
assert template_format is not None
filenames = SweepFileList(template_format, array_range)
reader = MultiFileReader(format_class, filenames)
# Create the sweep object
sweep = ImageSweep(reader, indices=indices, beam=beam, detector=detector, goniometer=goniometer, scan=scan)
# Return the sweep
return sweep