Support reading for lambda-detector Nexus files

src/fabio/fabioformats.py

@@ -34,7 +34,7 @@
 __contact__ = "[email protected]"
 __license__ = "MIT"
 __copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
-__date__ = "10/02/2023"
+__date__ = "02/05/2024"
 __status__ = "stable"
 __docformat__ = 'restructuredtext'
 
@@ -91,6 +91,7 @@ def importer(module_name):
     ("mrcimage", "MrcImage"),
     ("esperantoimage", "EsperantoImage"),
     ("limaimage", "LimaImage"),
+    ("lambdaimage", "LambdaImage"),
     # For compatibility (maybe not needed)
     ("adscimage", "AdscImage"),
     ("sparseimage", "SparseImage"),

src/fabio/lambdaimage.py

@@ -0,0 +1,259 @@
+# coding: utf-8
+#
+#    Project: X-ray image reader
+#             https://github.com/silx-kit/fabio
+#
+#    Copyright (C) European Synchrotron Radiation Facility, Grenoble, France
+#
+#  Permission is hereby granted, free of charge, to any person
+#  obtaining a copy of this software and associated documentation files
+#  (the "Software"), to deal in the Software without restriction,
+#  including without limitation the rights to use, copy, modify, merge,
+#  publish, distribute, sublicense, and/or sell copies of the Software,
+#  and to permit persons to whom the Software is furnished to do so,
+#  subject to the following conditions:
+#
+#  The above copyright notice and this permission notice shall be
+#  included in all copies or substantial portions of the Software.
+#
+#  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+#  EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+#  OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+#  NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+#  HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+#  WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+#  FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+#  OTHER DEALINGS IN THE SOFTWARE.
+
+"""
+Basic read support for NeXus/HDF5 files saved by Lambda-detectors. 
+"""
+
+__authors__ = ["Jérôme Kieffer"]
+__contact__ = "[email protected]"
+__license__ = "MIT"
+__copyright__ = "ESRF"
+__date__ = "02/05/2024"
+
+import logging
+logger = logging.getLogger(__name__)
+import posixpath
+import os
+import numpy
+from .fabioimage import FabioImage
+from .fabioutils import NotGoodReader
+from . import nexus
+try:
+    import h5py
+except ImportError:
+    h5py = None
+try:
+    import hdf5plugin
+except ImportError:
+    hdf5plugin = None
+
+
+class LambdaImage(FabioImage):
+    """FabIO image class for Images for Lambda detector
+
+    Lambda detector are medipix based detectors sold by X-Spectrum: 
+    https://x-spectrum.de/products/lambda/
+    """
+
+    DESCRIPTION = "HDF5 file produces by Lambda"
+
+    DEFAULT_EXTENSIONS = ["h5", "hdf5", "nxs"]
+    DETECTOR_GRP = "/entry/instrument/detector"
+
+    def __init__(self, data=None, header=None):
+        """
+        Set up initial values
+        """
+        if not h5py:
+            raise RuntimeError("fabio.LambdaImage cannot be used without h5py. Please install h5py and restart")
+
+        self.dataset = [data]
+        self._data = None
+        FabioImage.__init__(self, data, header)
+        self.h5 = None
+
+    @property
+    def nframes(self):
+        """Returns the number of frames contained in this file
+
+        :rtype: int
+        """
+        return len(self.dataset)
+
+    def get_data(self):
+        if self._data is None and len(self.dataset) >= self.currentframe:
+            self._data = self.dataset[self.currentframe]
+        return self._data
+
+    def set_data(self, data, index=None):
+        """Set the data for frame index
+
+        :param data: numpy array
+        :param int index: index of the frame (by default: current one)
+        :raises IndexError: If the frame number is out of the available range.
+        """
+        if index is None:
+            index = self.currentframe
+        if isinstance(self.dataset, list):
+            if index == len(self.dataset):
+                self.dataset.append(data)
+            elif index > len(self.dataset):
+            # pad dataset with None ?
+                self.dataset += [None] * (1 + index - len(self.dataset))
+                self.dataset[index] = data
+            else:
+                self.dataset[index] = data
+        if index == self.currentframe:
+            self._data = data
+
+    data = property(get_data, set_data)
+
+    def __repr__(self):
+        if self.h5 is None:
+            return "%s object at %s" % (self.__class__.__name__, hex(id(self)))
+        else:
+            return "Lambda/nexus dataset with %i frames from %s" % (self.nframes, self.h5.filename)
+
+    def _readheader(self, infile):
+        """
+        Read and decode the header of an image:
+
+        :param infile: Opened python file (can be stringIO or bzipped file)
+        """
+        # list of header key to keep the order (when writing)
+        self.header = self.check_header()
+        data_path = posixpath.join(self.DETECTOR_GRP, "data")
+        description_path = posixpath.join(self.DETECTOR_GRP, "description")
+        name_path = posixpath.join(self.DETECTOR_GRP, "local_name")
+        with h5py.File(infile, mode="r") as h5:
+            if not (data_path in h5 and description_path in h5):
+                raise NotGoodReader("HDF5's does not look like a Lambda-detector NeXus file.")
+            description = h5[description_path][()]
+            if isinstance(description, bytes):
+                description = description.decode()
+            else:
+                description = str(description)
+            if description != "Lambda":
+                raise NotGoodReader("Nexus file does not look like it has been written by a Lambda-detector.")
+            if name_path in h5:
+                self.header["detector"] = str(h5[name_path][()]) 
+            else:
+                self.header["detector"] = "detector"
+
+    def read(self, fname, frame=None):
+        """
+        Try to read image
+
+        :param fname: name of the file
+        :param frame: number of the frame
+        """
+
+        self.resetvals()
+        with self._open(fname) as infile:
+            self._readheader(infile)
+            # read the image data and declare it
+
+        self.dataset = None
+        # read the image data
+        self.h5 = h5py.File(fname, mode="r")
+        data_path = posixpath.join(self.DETECTOR_GRP, "data")
+        if data_path in self.h5:
+            ds = self.h5[data_path]
+        else:
+            raise NotGoodReader("HDF5's default entry does not exist.")
+        self.dataset = ds
+        self._nframes = ds.shape[0]
+
+        if frame is not None:
+            return self.getframe(int(frame))
+        else:
+            self.currentframe = 0
+            self.data = self.dataset[self.currentframe]
+            self._shape = None
+            return self
+
+    def getframe(self, num):
+        """ returns the frame numbered 'num' in the stack if applicable"""
+        if self.nframes > 1:
+            new_img = None
+            if (num >= 0) and num < self.nframes:
+                data = self.dataset[num]
+                new_img = self.__class__(data=data, header=self.header)
+                new_img.dataset = self.dataset
+                new_img.h5 = self.h5
+                new_img._nframes = self.nframes
+                new_img.currentframe = num
+            else:
+                raise IOError(f"getframe({num}) out of range [0, {self.nframes}[")
+        else:
+            new_img = FabioImage.getframe(self, num)
+        return new_img
+
+    def previous(self):
+        """ returns the previous file in the series as a FabioImage """
+        new_image = None
+        if self.nframes == 1:
+            new_image = FabioImage.previous(self)
+        else:
+            new_idx = self.currentframe - 1
+            new_image = self.getframe(new_idx)
+        return new_image
+
+    def next(self):
+        """Returns the next file in the series as a fabioimage
+
+        :raise IOError: When there is no next file or image in the series.
+        """
+        new_image = None
+        if self.nframes == 1:
+            new_image = FabioImage.next(self)
+        else:
+            new_idx = self.currentframe + 1
+            new_image = self.getframe(new_idx)
+        return new_image
+
+    def close(self):
+        if self.h5 is not None:
+            self.h5.close()
+            self.dataset = None
+
+    def write(self, filename):
+        """Write a file that looks like one saved by Lambda-detector."""
+        start_time = nexus.get_isotime()
+        abs_name = os.path.abspath(filename)
+        mode = "w"
+        if hdf5plugin is None:
+            logger.warning("hdf5plugin is needed for bitshuffle-LZ4 compression, falling back on gzip (slower)")
+            compression = {"compression":"gzip",
+                           "compression_opts":1}
+        else:
+            compression = hdf5plugin.Bitshuffle()
+
+        with nexus.Nexus(abs_name, mode=mode) as nxs:
+            entry = nxs.new_entry(entry="entry",
+                                  program_name=None,
+                                  force_time=start_time,
+                                  force_name=True)
+            instrument_grp = nxs.new_class(entry, "instrument", class_type="NXinstrument")
+            detector_grp = nxs.new_class(instrument_grp, "detector", class_type="NXdetector")
+            detector_grp["description"] = b"Lambda"
+            detector_grp["local_name"] = self.header.get("detector", "detector").encode()
+            detector_grp["layout"] = "X".join(str(i) for i in self.shape[-1::-1]).encode()
+            header_grp = nxs.new_class(detector_grp, "collection", class_type="NXcollection")
+            acq_grp = nxs.new_class(detector_grp, "acquisition", class_type="NXcollection")
+
+            acq_grp["frame_numbers"] = numpy.int32(self.nframes)
+
+            shape = (self.nframes,) + self.shape
+            dataset = detector_grp.create_dataset("data", shape=shape, chunks=(1,) + self.shape, dtype=self.dtype, **compression)
+            dataset.attrs["interpretation"] = "image"
+            for i, frame in enumerate(self.dataset):
+                dataset[i] = frame
+
+# This is for compatibility with old code:
+lambdaimage = LambdaImage

src/fabio/meson.build

@@ -34,6 +34,7 @@ py.install_sources([
 	'jpeg2kimage.py',
 	'jpegimage.py',
 	'kcdimage.py',
+	'lambdaimage.py',
 	'limaimage.py',
 	'mar345image.py',
 	'marccdimage.py',

src/fabio/openimage.py

@@ -96,7 +96,7 @@
     (b"No", "kcd"),
     (b"<", "xsd"),
     (b"\n\xb8\x03\x00", 'pixi'),
-    (b"\x89\x48\x44\x46\x0d\x0a\x1a\x0a", "eiger/lima/sparse/hdf5"),
+    (b"\x89\x48\x44\x46\x0d\x0a\x1a\x0a", "eiger/lima/sparse/hdf5/lambda"),
     (b"R-AXIS", 'raxis'),
     (b"\x93NUMPY", 'numpy'),
     (b"\\$FFF_START", 'fit2d'),
@@ -118,11 +118,12 @@ def do_magic(byts, filename):
     for magic, format_type in MAGIC_NUMBERS:
         if byts.startswith(magic):
             if "/" in format_type:
-                if format_type == "eiger/lima/sparse/hdf5":
+                if format_type == "eiger/lima/sparse/hdf5/lambda":
                     if "::" in filename:
                         return "hdf5"
                     else:
-                        # check if the creator is LIMA
+                        # check if the creator is LIMA or other
+                        lambda_path = "/entry/instrument/detector/description"
                         import h5py
                         with h5py.File(filename, "r") as h:
                             creator = h.attrs.get("creator")
@@ -144,6 +145,8 @@ def do_magic(byts, filename):
                                 return "lima"
                             elif str(creator).startswith("pyFAI"):
                                 return "sparse"
+                            elif lambda_path in h and h[lambda_path][()].decode() == "Lambda":
+                                return "lambda"
                             else:
                                 return "eiger"
                 elif format_type == "marccd/tif":

src/fabio/test/codecs/__init__.py

@@ -30,7 +30,7 @@
 __contact__ = "[email protected]"
 __license__ = "GPLv3+"
 __copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
-__date__ = "09/02/2023"
+__date__ = "02/05/2024"
 
 import sys
 import unittest
@@ -58,6 +58,7 @@ def suite():
     from . import test_numpyimage
     from . import test_pilatusimage
     from . import test_eigerimage
+    from . import test_lambdaimage
     from . import test_hdf5image
     from . import test_fit2dimage
     from . import test_speimage
@@ -108,6 +109,7 @@ def suite():
     testSuite.addTest(test_hipicimage.suite())
     testSuite.addTest(test_binaryimage.suite())
     testSuite.addTest(test_xcaliburimage.suite())
+    testSuite.addTest(test_lambdaimage.suite())
     return testSuite
 
 

src/fabio/test/codecs/meson.build

@@ -18,6 +18,7 @@ py.install_sources(
  'test_jpeg2kimage.py',
  'test_jpegimage.py',
  'test_kcdimage.py',
+ 'test_lambdaimage.py',
  'test_limaimage.py',
  'test_mar345image.py',
  'test_mccdimage.py',