class FormatNexusJungfrauHack(FormatNexus): @staticmethod def understand(image_file): try: with h5py.File(image_file, "r") as handle: return "/entry/instrument/JF1M" in handle except OSError: return False def _start(self): # Read the file structure self._reader = reader = NXmxReader(self._image_file) # Only support 1 set of models at the moment assert len(reader.entries) == 1, "Currently only supports 1 NXmx entry" assert len(reader.entries[0].data) == 1, "Currently only supports 1 NXdata" assert ( len(reader.entries[0].instruments) == 1 ), "Currently only supports 1 NXinstrument" assert len(reader.entries[0].samples) == 1, "Currently only supports 1 NXsample" assert ( len(reader.entries[0].samples[0].beams) == 1 or len(reader.entries[0].instruments[0].beams) == 1 ), "Currently only supports 1 NXbeam" # Get the NXmx model objects entry = reader.entries[0] self.instrument = instrument = entry.instruments[0] detector = instrument.detectors[0] sample = entry.samples[0] beam = sample.beams[0] if sample.beams else instrument.beams[0] data = entry.data[0] # Construct the models self._beam_factory = BeamFactory(beam) self._beam_factory.load_model(0) self._setup_detector(detector, self._beam_factory.model) self._setup_gonio_and_scan(sample, detector) if self._scan_model: array_range = self._scan_model.get_array_range() num_images = array_range[1] - array_range[0] else: num_images = 0 self._raw_data = DataFactory(data, max_size=num_images) def _setup_detector(self, detector, beam): nx_detector = detector.handle nx_module = detector.modules[0].handle # Get the detector name and type if "type" in nx_detector: detector_type = str(nx_detector["type"][()]) else: detector_type = "unknown" detector_name = str(nx_detector.name) # Get the trusted range of pixel values if "saturation_value" in nx_detector: trusted_range = (-1, float(nx_detector["saturation_value"][()])) else: trusted_range = (-1, 99999999) # Get the detector thickness thickness = nx_detector["sensor_thickness"] thickness_value = float(thickness[()]) thickness_units = thickness.attrs["units"] thickness_value = float(convert_units(thickness_value, thickness_units, "mm")) # Get the detector material material = nx_detector["sensor_material"][()] if hasattr(material, "shape"): material = "".join(m.decode() for m in material) detector_material = clean_string(str(material)) material = { "Si": "Si", np.string_("Si"): "Si", np.string_("Silicon"): "Si", np.string_("Sillicon"): "Si", np.string_("CdTe"): "CdTe", np.string_("GaAs"): "GaAs", }.get(detector_material) if not material: raise RuntimeError("Unknown material: %s" % detector_material) try: x_pixel = nx_detector["x_pixel_size"][()] * 1000.0 y_pixel = nx_detector["y_pixel_size"][()] * 1000.0 legacy_beam_x = float(x_pixel * nx_detector["beam_center_x"][()]) legacy_beam_y = float(y_pixel * nx_detector["beam_center_y"][()]) legacy_distance = float(1000 * nx_detector["detector_distance"][()]) except KeyError: legacy_beam_x = 0 legacy_beam_y = 0 # Get the fast pixel size and vector fast_pixel_direction = nx_module["fast_pixel_direction"] fast_pixel_direction_value = float(fast_pixel_direction[()]) fast_pixel_direction_units = fast_pixel_direction.attrs["units"] fast_pixel_direction_vector = fast_pixel_direction.attrs["vector"] fast_pixel_direction_value = convert_units( fast_pixel_direction_value, fast_pixel_direction_units, "mm" ) fast_axis = matrix.col(fast_pixel_direction_vector).normalize() # Get the slow pixel size and vector slow_pixel_direction = nx_module["slow_pixel_direction"] slow_pixel_direction_value = float(slow_pixel_direction[()]) slow_pixel_direction_units = slow_pixel_direction.attrs["units"] slow_pixel_direction_vector = slow_pixel_direction.attrs["vector"] slow_pixel_direction_value = convert_units( slow_pixel_direction_value, slow_pixel_direction_units, "mm" ) slow_axis = matrix.col(slow_pixel_direction_vector).normalize() origin = matrix.col((0.0, 0.0, -legacy_distance)) if origin.elems[0] == 0.0 and origin.elems[1] == 0: origin = -(origin + legacy_beam_x * fast_axis + legacy_beam_y * slow_axis) # Change of basis to convert from NeXus to IUCr/ImageCIF convention cob = matrix.sqr((-1, 0, 0, 0, 1, 0, 0, 0, -1)) origin = cob * matrix.col(origin) fast_axis = cob * fast_axis slow_axis = cob * slow_axis # Ensure that fast and slow axis are orthogonal normal = fast_axis.cross(slow_axis) slow_axis = -fast_axis.cross(normal) # Compute the attenuation coefficient. # This will fail for undefined composite materials # mu_at_angstrom returns cm^-1, but need mu in mm^-1 table = attenuation_coefficient.get_table(material) wavelength = beam.get_wavelength() mu = table.mu_at_angstrom(wavelength) / 10.0 # Construct the detector model pixel_size = (fast_pixel_direction_value, slow_pixel_direction_value) # image size stored slow to fast but dxtbx needs fast to slow image_size = tuple(int(x) for x in reversed(nx_module["data_size"][-2:])) image_size = (1030, 1064) self.model = Detector() self.model.add_panel( Panel( detector_type, detector_name, tuple(fast_axis), tuple(slow_axis), tuple(origin), pixel_size, image_size, trusted_range, thickness_value, material, mu, ) ) # Set the parallax correction for panel in self.model: panel.set_px_mm_strategy(ParallaxCorrectedPxMmStrategy(mu, thickness_value)) panel.set_type("SENSOR_PAD") self._detector_model = self.model def _setup_gonio_and_scan(self, sample, detector): with h5py.File(self._image_file, "r") as handle: phi = handle["/entry/sample/goniometer/omega"][()] image_range = (1, len(phi)) oscillation = (float(phi[0]), float(phi[1] - phi[0])) # Get the exposure time num_images = len(phi) exposure_time = flex.double(num_images, 0) epochs = flex.double(num_images, 0.0) for i in range(1, len(epochs)): epochs[i] = epochs[i - 1] + exposure_time[i - 1] self._scan_model = Scan(image_range, oscillation, exposure_time, epochs) self._goniometer_model = self._goniometer_factory.known_axis((-1, 0, 0)) def _end(self): return def _goniometer(self): return self._goniometer_model def _detector(self): return self._detector_model def _scan(self): return self._scan_model def get_goniometer(self, index=None): return self._goniometer() def get_detector(self, index=None): return self._detector() def get_beam(self, index=None): return self._beam(index) def get_scan(self, index=None): if index is None: return self._scan() scan = self._scan() if scan is not None: return scan[index] return scan def get_raw_data(self, index): return self._raw_data[index] def get_static_mask(self, index=None, goniometer=None): return MaskFactory(self.instrument.detectors, index).mask def get_num_images(self): if self._scan() is not None: return self._scan().get_num_images() return len(self._raw_data) def get_image_file(self, index=None): return self._image_file def get_detectorbase(self, index=None): raise NotImplementedError @staticmethod def get_instrument_name(handle): if "short_name" in handle["/entry/instrument"].attrs: name = handle["/entry/instrument"].attrs["short_name"] elif "/entry/instrument/name" in handle: if "short_name" in handle["/entry/instrument/name"].attrs: name = handle["/entry/instrument/name"].attrs["short_name"] else: name = handle["/entry/instrument/name"][()] else: name = None return name
class FormatHDF5EigerNearlyNexus(FormatHDF5): @staticmethod def understand(image_file): try: return is_eiger_nearly_nexus_file(image_file) except IOError: return False def _start(self): # Read the file structure temp_file = "tmp_master_%s.nxs" % uuid.uuid1().hex fixer = EigerNXmxFixer(self._image_file, temp_file) reader = NXmxReader(handle=fixer.handle) # Only support 1 set of models at the moment assert len(reader.entries) == 1, "Currently only supports 1 NXmx entry" assert len(reader.entries[0].data) == 1, "Currently only supports 1 NXdata" assert ( len(reader.entries[0].instruments) == 1 ), "Currently only supports 1 NXinstrument" assert len(reader.entries[0].samples) == 1, "Currently only supports 1 NXsample" assert ( len(reader.entries[0].instruments[0].detectors) == 1 ), "Currently only supports 1 NXdetector" assert ( len(reader.entries[0].instruments[0].detectors[0].modules) == 1 ), "Currently only supports 1 NXdetector_module" assert ( len(reader.entries[0].samples[0].beams) == 1 or len(reader.entries[0].instruments[0].beams) == 1 ), "Currently only supports 1 NXbeam" # Get the NXmx model objects entry = reader.entries[0] self.instrument = instrument = entry.instruments[0] detector = instrument.detectors[0] sample = entry.samples[0] beam = sample.beams[0] if sample.beams else instrument.beams[0] # Use data from original master file data = NXdata(fixer.handle_orig[entry.data[0].handle.name]) self._raw_data = DataFactory(data, cached_information=fixer.data_factory_cache) # Construct the models self._beam_factory = BeamFactory(beam) self._beam_factory.load_model(0) self._detector_model = DetectorFactory( detector, self._beam_factory.model, shape=self._raw_data.shape() ).model # Override the minimum trusted value - for Eiger should be -1 for panel in self._detector_model: trusted = panel.get_trusted_range() panel.set_trusted_range((-1, trusted[1])) self._goniometer_model = GoniometerFactory(sample).model self._scan_model = generate_scan_model(sample, detector) # update model for masking Eiger detectors for f0, f1, s0, s1 in determine_eiger_mask(self._detector_model): self._detector_model[0].add_mask(f0 - 1, s0 - 1, f1, s1) def _end(self): return def _goniometer(self): return self._goniometer_model def _detector(self): return self._detector_model def _beam(self, index=None): self._beam_model, _ = self._beam_factory.read_models(index) return self._beam_model def _scan(self): return self._scan_model def get_goniometer(self, index=None): return self._goniometer() def get_detector(self, index=None): return self._detector() def get_beam(self, index=None): return self._beam(index) def get_scan(self, index=None): if index is None: return self._scan() return self._scan()[index] def get_raw_data(self, index): return self._raw_data[index] def get_static_mask(self, index=None, goniometer=None): return MaskFactory(self.instrument.detectors, index).mask def get_num_images(self): scan = self._scan() if isinstance(scan, list): return sum(s.get_num_images() for s in scan) return scan.get_num_images() def get_image_file(self, index=None): return self._image_file def detectorbase_start(self, index=0): self.detectorbase = EIGERImage(self._image_file, index=index) self.detectorbase.readHeader(dxtbx_instance=self) def model_get_raw_data(ptr, index): return self.get_raw_data(index) self.detectorbase.get_raw_data_callback = model_get_raw_data def get_detectorbase(self, index=0): self.detectorbase_start(index) return self.detectorbase def get_vendortype(self): return gv(self.get_detector())
class FormatNexus(FormatHDF5): @staticmethod def understand(image_file): try: return is_nexus_file(image_file) except IOError: return False def _start(self): # Read the file structure self._reader = reader = NXmxReader(self._image_file) # Only support 1 set of models at the moment assert len(reader.entries) == 1, "Currently only supports 1 NXmx entry" assert len( reader.entries[0].data) == 1, "Currently only supports 1 NXdata" assert (len(reader.entries[0].instruments) == 1 ), "Currently only supports 1 NXinstrument" assert len(reader.entries[0].samples ) == 1, "Currently only supports 1 NXsample" assert (len(reader.entries[0].samples[0].beams) == 1 or len(reader.entries[0].instruments[0].beams) == 1), "Currently only supports 1 NXbeam" # Get the NXmx model objects entry = reader.entries[0] self.instrument = instrument = entry.instruments[0] detector = instrument.detectors[0] sample = entry.samples[0] beam = sample.beams[0] if sample.beams else instrument.beams[0] data = entry.data[0] # Construct the models self._beam_factory = BeamFactory(beam) self._beam_factory.load_model(0) self._setup_gonio_and_scan(sample, detector) if self._scan_model: array_range = self._scan_model.get_array_range() num_images = array_range[1] - array_range[0] else: num_images = 0 if len(instrument.detector_groups) == 0: assert ( len(reader.entries[0].instruments[0].detectors) == 1 ), "Currently only supports 1 NXdetector unless in a detector group" assert ( len(reader.entries[0].instruments[0].detectors[0].modules) == 1 ), "Currently only supports 1 NXdetector_module unless in a detector group" self._raw_data = DataFactory(data, max_size=num_images) self._detector_model = DetectorFactory( detector, self._beam_factory.model, shape=self._raw_data.shape()).model else: self._raw_data = detectorgroupdatafactory(data, instrument) self._detector_model = DetectorFactoryFromGroup( instrument, self._beam_factory.model).model def _setup_gonio_and_scan(self, sample, detector): """Set up rotation-specific models""" self._goniometer_model = GoniometerFactory(sample).model self._scan_model = generate_scan_model(sample, detector) def _end(self): return def _goniometer(self): return self._goniometer_model def _detector(self): return self._detector_model def _beam(self, index=None): self._beam_model, _ = self._beam_factory.read_models(index) return self._beam_model def _scan(self): return self._scan_model def get_goniometer(self, index=None): return self._goniometer() def get_detector(self, index=None): return self._detector() def get_beam(self, index=None): return self._beam(index) def get_spectrum(self, index=None): self._beam_model, _ = self._beam_factory.read_models(index) return self._beam_factory.spectrum def get_scan(self, index=None): if index is None: return self._scan() scan = self._scan() if scan is not None: return scan[index] return scan def get_raw_data(self, index): return self._raw_data[index] def get_static_mask(self, index=None, goniometer=None): return MaskFactory(self.instrument.detectors, index).mask def get_num_images(self): if self._scan() is not None: return self._scan().get_num_images() return len(self._raw_data) def get_image_file(self, index=None): return self._image_file def get_detectorbase(self, index=None): raise NotImplementedError @staticmethod def get_instrument_name(handle): if "short_name" in handle["/entry/instrument"].attrs: name = handle["/entry/instrument"].attrs["short_name"] elif "/entry/instrument/name" in handle: if "short_name" in handle["/entry/instrument/name"].attrs: name = handle["/entry/instrument/name"].attrs["short_name"] else: name = handle["/entry/instrument/name"][()] else: name = None return name