def process(input_data, output, config, monitor_name, observer):
"""
Integrate a set of data.
:param List[str] input_data: List of input filenames
:param str output: Filename of directory output
:param dict config: Dictionary to configure `pyFAI.worker.Worker`
:param IntegrationObserver observer: Observer of the processing
:param:
"""
worker = pyFAI.worker.Worker()
worker_config = config.copy()
json_monitor_name = worker_config.pop("monitor_name", None)
if monitor_name is None:
monitor_name = json_monitor_name
elif json_monitor_name is not None:
logger.warning("Monitor name from command line argument override the one from the configuration file.")
worker.set_config(worker_config, consume_keys=True)
worker.output = "raw"
# Check unused keys
for key in worker_config.keys():
# FIXME this should be read also
if key in ["application", "version"]:
continue
logger.warning("Configuration key '%s' from json is unused", key)
worker.safe = False # all processing are expected to be the same.
start_time = time.time()
if observer is not None:
observer.worker_initialized(worker)
# Skip invalide data
valid_data = []
for item in input_data:
if isinstance(item, six.string_types):
if os.path.isfile(item):
valid_data.append(item)
else:
if "::" in item:
try:
fabio.open(item)
valid_data.append(item)
except Exception:
logger.warning("File %s do not exists. File ignored.", item)
else:
logger.warning("File %s do not exists. File ignored.", item)
elif isinstance(item, fabio.fabioimage.FabioImage):
valid_data.append(item)
elif isinstance(item, numpy.ndarray):
valid_data.append(item)
else:
logger.warning("Type %s unsopported. Data ignored.", item)
if observer is not None:
observer.processing_started(len(valid_data))
# Integrate files one by one
for iitem, item in enumerate(valid_data):
logger.debug("Processing %s", item)
# TODO rework it as source
if isinstance(item, six.string_types):
kind = "filename"
fabio_image = fabio.open(item)
filename = fabio_image.filename
multiframe = fabio_image.nframes > 1
elif isinstance(item, fabio.fabioimage.FabioImage):
kind = "fabio-image"
fabio_image = item
multiframe = fabio_image.nframes > 1
filename = fabio_image.filename
elif isinstance(item, numpy.ndarray):
kind = "numpy-array"
filename = None
fabio_image = None
multiframe = False
if observer is not None:
observer.processing_data(iitem + 1, filename=filename)
if filename:
output_name = os.path.splitext(filename)[0]
else:
output_name = "array_%d" % iitem
if multiframe:
extension = "_pyFAI.h5"
else:
if worker.do_2D():
extension = ".azim"
else:
extension = ".dat"
output_name = "%s%s" % (output_name, extension)
if output:
if os.path.isdir(output):
basename = os.path.basename(output_name)
outpath = os.path.join(output, basename)
else:
outpath = os.path.abspath(output)
else:
outpath = output_name
if fabio_image is None:
if item.ndim == 3:
writer = HDF5Writer(outpath)
writer.init(fai_cfg=config)
for iframe, data in enumerate(item):
result = worker.process(data=data,
writer=writer)
if observer is not None:
if observer.is_interruption_requested():
break
observer.data_result(iitem, result)
else:
data = item
writer = DefaultAiWriter(outpath, worker.ai)
result = worker.process(data=data,
writer=writer)
if observer is not None:
observer.data_result(iitem, result)
else:
if multiframe:
writer = HDF5Writer(outpath, append_frames=True)
writer.init(fai_cfg=config)
for iframe in range(fabio_image.nframes):
fimg = fabio_image.getframe(iframe)
normalization_factor = get_monitor_value(fimg, monitor_name)
data = fimg.data
result = worker.process(data=data,
metadata=fimg.header,
normalization_factor=normalization_factor,
writer=writer)
if observer is not None:
if observer.is_interruption_requested():
break
observer.data_result(iitem, result)
writer.close()
else:
writer = DefaultAiWriter(outpath, worker.ai)
normalization_factor = get_monitor_value(fabio_image, monitor_name)
data = fabio_image.data
result = worker.process(data,
normalization_factor=normalization_factor,
writer=writer)
if observer is not None:
observer.data_result(iitem, result)
writer.close()
if observer is not None:
if observer.is_interruption_requested():
break
if observer is not None:
if observer.is_interruption_requested():
logger.info("Processing was aborted")
observer.processing_interrupted()
else:
observer.processing_succeeded()
observer.processing_finished()
logger.info("Processing done in %.3fs !", (time.time() - start_time))
return 0
def integrate_shell(options, args):
import json
config = json.load(open(options.json))
ai = pyFAI.worker.make_ai(config)
worker = pyFAI.worker.Worker(azimuthalIntegrator=ai)
# TODO this will init again the azimuthal integrator, there is a problem on the architecture
worker.setJsonConfig(options.json)
worker.safe = False # all processing are expected to be the same.
start_time = time.time()
# Skip unexisting files
image_filenames = []
for item in args:
if os.path.exists(item) and os.path.isfile(item):
image_filenames.append(item)
else:
logger.warning("File %s do not exists. Ignored." % item)
image_filenames = sorted(image_filenames)
progress_bar = ProgressBar("Integration", len(image_filenames), 20)
# Integrate files one by one
for i, item in enumerate(image_filenames):
logger.debug("Processing %s" % item)
if len(item) > 100:
message = os.path.basename(item)
else:
message = item
progress_bar.update(i + 1, message=message)
img = fabio.open(item)
multiframe = img.nframes > 1
custom_ext = True
if options.output:
if os.path.isdir(options.output):
outpath = os.path.join(options.output, os.path.splitext(os.path.basename(item))[0])
else:
outpath = os.path.abspath(options.output)
custom_ext = False
else:
outpath = os.path.splitext(item)[0]
if custom_ext:
if multiframe:
outpath = outpath + "_pyFAI.h5"
else:
if worker.do_2D():
outpath = outpath + ".azim"
else:
outpath = outpath + ".dat"
if multiframe:
writer = HDF5Writer(outpath)
writer.init(config)
for i in range(img.nframes):
fimg = img.getframe(i)
normalization_factor = get_monitor_value(fimg, options.monitor_key)
data = img.data
res = worker.process(data=data,
metadata=fimg.header,
normalization_factor=normalization_factor)
if not worker.do_2D():
res = res.T[1]
writer.write(res, index=i)
writer.close()
else:
normalization_factor = get_monitor_value(img, options.monitor_key)
data = img.data
writer = DefaultAiWriter(outpath, worker.ai)
worker.process(data,
normalization_factor=normalization_factor,
writer=writer)
writer.close()
progress_bar.clear()
logger.info("Processing done in %.3fs !" % (time.time() - start_time))
def integrate_shell(options, args):
import json
with open(options.json) as f:
config = json.load(f)
ai = pyFAI.worker.make_ai(config)
worker = pyFAI.worker.Worker(azimuthalIntegrator=ai)
# TODO this will init again the azimuthal integrator, there is a problem on the architecture
worker.setJsonConfig(options.json)
worker.safe = False # all processing are expected to be the same.
start_time = time.time()
# Skip unexisting files
image_filenames = []
for item in args:
if os.path.exists(item) and os.path.isfile(item):
image_filenames.append(item)
else:
logger.warning("File %s do not exists. Ignored.", item)
image_filenames = sorted(image_filenames)
progress_bar = ProgressBar("Integration", len(image_filenames), 20)
# Integrate files one by one
for i, item in enumerate(image_filenames):
logger.debug("Processing %s", item)
if len(item) > 100:
message = os.path.basename(item)
else:
message = item
progress_bar.update(i + 1, message=message)
img = fabio.open(item)
multiframe = img.nframes > 1
custom_ext = True
if options.output:
if os.path.isdir(options.output):
outpath = os.path.join(
options.output,
os.path.splitext(os.path.basename(item))[0])
else:
outpath = os.path.abspath(options.output)
custom_ext = False
else:
outpath = os.path.splitext(item)[0]
if custom_ext:
if multiframe:
outpath = outpath + "_pyFAI.h5"
else:
if worker.do_2D():
outpath = outpath + ".azim"
else:
outpath = outpath + ".dat"
if multiframe:
writer = HDF5Writer(outpath)
writer.init(config)
for i in range(img.nframes):
fimg = img.getframe(i)
normalization_factor = get_monitor_value(
fimg, options.monitor_key)
data = img.data
res = worker.process(data=data,
metadata=fimg.header,
normalization_factor=normalization_factor)
if not worker.do_2D():
res = res.T[1]
writer.write(res, index=i)
writer.close()
else:
normalization_factor = get_monitor_value(img, options.monitor_key)
data = img.data
writer = DefaultAiWriter(outpath, worker.ai)
worker.process(data,
normalization_factor=normalization_factor,
writer=writer)
writer.close()
progress_bar.clear()
logger.info("Processing done in %.3fs !", (time.time() - start_time))
return 0