Merge pull request cctbx#659 from cctbx/ESRF_SMX

Add format class to understand Jungfrau4M serial data from ID29, ESRF

newsfragments/659.feature

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+Add format class to read Jungfrau4M serial images from beamline ID29 at ESRF

src/dxtbx/format/FormatHDF5ESRFJungfrau4M.py

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+from __future__ import annotations
+
+import sys
+
+import h5py
+
+from scitbx.array_family import flex
+
+from dxtbx import flumpy
+from dxtbx.format.FormatHDF5 import FormatHDF5
+
+
+class FormatHDF5ESRFJungfrau4M(FormatHDF5):
+
+    # A class to understand still-shot images from ESRF collected on a Jungfrau 4M.
+
+    _cached_mask = None
+
+    @staticmethod
+    def understand(image_file):
+        with h5py.File(image_file, "r") as h5_handle:
+            if len(h5_handle) != 1:
+                return False
+            key = list(h5_handle.keys())[0]
+            if "instrument" not in h5_handle[key]:
+                return False
+            # instrument name is of form jungfrau4m_rr[X]_smx where X is empty, 4 or another number
+            instrument = list(h5_handle[key]["instrument"].keys())[0]
+            if not instrument.startswith("jungfrau4m_rr"):
+                return False
+            if not instrument.endswith("smx"):
+                return False
+        return True
+
+    def _start(self):
+        super()._start()
+        image_file = self.get_image_file()
+        self._h5_handle = h5py.File(image_file, "r")
+        self.key = list(self._h5_handle.keys())[0]
+        self.instrument_name = list(self._h5_handle[self.key]["instrument"].keys())[0]
+        instrument = self._h5_handle[self.key]["instrument"][self.instrument_name]
+        self.n_images = instrument["data"].shape[0]
+        self.adus_per_photon = instrument["detector_information"]["adus_per_photon"]
+        self.image_size = tuple(instrument["data"].shape[1:])
+        wavelength = instrument["beam"]["incident_wavelength"][()]
+        x_pixel_size = (
+            instrument["detector_information"]["x_pixel_size"][()] * 1000
+        )  # convert m to mm
+        y_pixel_size = (
+            instrument["detector_information"]["y_pixel_size"][()] * 1000
+        )  # convert m to mm
+        distance = (
+            instrument["detector_information"]["detector_distance"][()] * 1000
+        )  # convert m to mm
+        beam_center_x = instrument["detector_information"]["beam_center_x"][()]  # in px
+        beam_center_y = instrument["detector_information"]["beam_center_y"][()]  # in px
+
+        beam_center_x *= x_pixel_size
+        beam_center_y *= y_pixel_size
+        trusted_range = (
+            instrument["detector_information"]["underload_value"][()],
+            instrument["detector_information"]["saturation_value"][()],
+        )
+        exposure_time = instrument["acquisition"]["exposure_time"][()]
+
+        self._detector_model = self._detector_factory.simple(
+            sensor="UNKNOWN",
+            distance=distance,
+            beam_centre=(
+                beam_center_x,
+                beam_center_y,
+            ),
+            fast_direction="+x",
+            slow_direction="-y",
+            pixel_size=(
+                x_pixel_size,
+                y_pixel_size,
+            ),
+            image_size=(self.image_size[1], self.image_size[0]),
+            trusted_range=trusted_range,
+            mask=self.get_static_mask(),
+        )
+        self._beam_model = self._beam_factory.simple(wavelength)
+        self._scan_model = self._scan_factory.make_scan(
+            image_range=(1, self.n_images),
+            exposure_times=exposure_time,
+            oscillation=(0.0, 0.0),
+            epochs=list(range(self.n_images)),
+        )
+        # Add a placeholder goniometer model, which has no practical effect on processing as the oscillation is 0.
+        # Some dxtbx format logic assumes both or neither scan + goniometer are None for still images
+        self._goniometer_model = self._goniometer_factory.known_axis((0, 1, 0))
+
+    def get_raw_data(self, index=None):
+        if index is None:
+            index = 0
+        # data can be int32 with adus_per_photon != 1.0 or float16 with adus_per_photon == 1.0
+        data = (
+            (
+                self._h5_handle[self.key]["measurement"]["data"][index]
+                / self.adus_per_photon
+            )
+            if self.adus_per_photon != 1.0
+            else self._h5_handle[self.key]["measurement"]["data"][index]
+        )
+        return flex.double(data.astype(float))
+
+    def get_num_images(self):
+        return self.n_images
+
+    def get_beam(self, index=None):
+        return self._beam(index)
+
+    def _beam(self, index=None):
+        return self._beam_model
+
+    def get_detector(self, index=None):
+        return self._detector(index)
+
+    def get_static_mask(self):
+        if FormatHDF5ESRFJungfrau4M._cached_mask is None:
+            mask = self._h5_handle[self.key]["instrument"][self.instrument_name][
+                "detector_information"
+            ]["pixel_mask"]
+            mask = flumpy.from_numpy(mask[()])
+            mask_array = mask == 0
+            FormatHDF5ESRFJungfrau4M._cached_mask = mask_array
+        return FormatHDF5ESRFJungfrau4M._cached_mask
+
+    def _detector(self, index=None):
+        return self._detector_model
+
+    def _goniometer(self):
+        return self._goniometer_model
+
+    def _scan(self):
+        return self._scan_model
+
+
+if __name__ == "__main__":
+    for arg in sys.argv[1:]:
+        print(FormatHDF5ESRFJungfrau4M.understand(arg))