def prepare_write(self, data_info, engine): if data_info.source_filename: output_name = os.path.splitext(data_info.source_filename)[0] else: output_name = "array_%d" % data_info.data_id if self._is_2d: extension = ".azim" else: extension = ".dat" if data_info.frame_id is not None: output_name = "%s_%04d" % (output_name, data_info.frame_id) output_name = "%s%s" % (output_name, extension) if self._output_path: if os.path.isdir(self._output_path): basename = os.path.basename(output_name) outpath = os.path.join(self._output_path, basename) else: outpath = os.path.abspath(self._output_path) else: outpath = output_name if os.path.exists(outpath): if self._mode == HDF5Writer.MODE_DELETE: os.unlink(outpath) self._writer = DefaultAiWriter(outpath, engine) self._writer.init(fai_cfg=self._fai_cfg, lima_cfg=self._lima_cfg)
def create_file_header(self): try: # pyFAI version 0.12.0 return self.pattern_geometry.makeHeaders(polarization_factor=self.polarization_factor) except AttributeError: # pyFAI after version 0.12.0 from pyFAI.io import DefaultAiWriter return DefaultAiWriter(None, self.pattern_geometry).make_headers()
class MultiFileWriter(pyFAI.io.Writer): """Broadcast writing to differnet files for each frames""" def __init__(self, output_path, mode=HDF5Writer.MODE_ERROR): super(MultiFileWriter, self).__init__() if mode in [HDF5Writer.MODE_OVERWRITE, HDF5Writer.MODE_APPEND]: raise ValueError("Mode %s unsupported" % mode) self._writer = None self._output_path = output_path self._mode = mode def init(self, fai_cfg=None, lima_cfg=None): self._fai_cfg = fai_cfg self._lima_cfg = lima_cfg self._is_2d = self._fai_cfg.get("do_2D", False) is True def prepare_write(self, data_info, engine): if data_info.source_filename: output_name = os.path.splitext(data_info.source_filename)[0] else: output_name = "array_%d" % data_info.data_id if self._is_2d: extension = ".azim" else: extension = ".dat" if data_info.frame_id is not None: output_name = "%s_%04d" % (output_name, data_info.frame_id) output_name = "%s%s" % (output_name, extension) if self._output_path: if os.path.isdir(self._output_path): basename = os.path.basename(output_name) outpath = os.path.join(self._output_path, basename) else: outpath = os.path.abspath(self._output_path) else: outpath = output_name if os.path.exists(outpath): if self._mode == HDF5Writer.MODE_DELETE: os.unlink(outpath) self._writer = DefaultAiWriter(outpath, engine) self._writer.init(fai_cfg=self._fai_cfg, lima_cfg=self._lima_cfg) def write(self, data): self._writer.write(data) self._writer.close() self._writer = None def close(self): pass
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 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 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