Add nxtomo reader

.readthedocs.yaml

@@ -1,9 +1,9 @@
 version: 2
 
 build:
-  os: "ubuntu-20.04"
+  os: 'ubuntu-20.04'
   tools:
-    python: "mambaforge-4.10"
+    python: 'mambaforge-4.10'
 
 # Build documentation in the docs/ directory with Sphinx
 sphinx:
@@ -15,4 +15,4 @@ conda:
 python:
   install:
     - method: pip
-      path: .
+      path: .

environment-nocuda.yml

@@ -21,4 +21,5 @@ dependencies:
   - astra-toolbox
   - bqplot
   - pip:
-      - bqplot-image-gl
+      - bqplot-image-gl
+      - tomoscan

environment.yml

@@ -24,3 +24,4 @@ dependencies:
   - bqplot
   - pip:
       - bqplot-image-gl
+      - tomoscan

examples/data/nxtomo/create_tomo.py

@@ -0,0 +1,99 @@
+import os
+import pathlib
+
+import dxchange
+import numpy
+from nxtomo import NXtomo
+from nxtomo.nxobject.nxdetector import ImageKey
+from tomoscan.esrf.scan.nxtomoscan import NXtomoScan
+
+THIS_PATH = pathlib.Path(os.path.dirname(os.path.abspath(__file__)))
+DATA_PATH = pathlib.Path(THIS_PATH / "tomo_00077.h5")  # from tomobank
+
+# I took most of this from the tomoscan tutorial, but I had to modify it.
+# I am not sure how you are storing your "projections" data. Basically, we want
+# projection images along x and y in a [Z, Y, X] array, like is output by dxchange.read_aps_32id.
+# You can modify your data import method in tomopyui.backend.io to get it into the right format.
+proj, flat, dark, theta = dxchange.read_aps_32id(fname=DATA_PATH, proj=(0, 477))
+
+binning = 8
+proj_binned = proj[:, ::binning, ::binning]
+dark_binned = dark[:, ::binning, ::binning]
+flat_binned = flat[:, ::binning, ::binning]
+assert proj_binned.shape[2] == dark_binned.shape[2] == flat_binned.shape[2]
+assert proj_binned.shape[1] == dark_binned.shape[1] == flat_binned.shape[1]
+proj_rotation_angles = theta * 180 / numpy.pi
+assert len(proj_rotation_angles) == len(proj_binned)
+
+my_nxtomo = NXtomo()
+
+# create the array
+data = numpy.concatenate(
+    [
+        dark_binned,
+        flat_binned,
+        proj_binned,
+    ]
+)
+assert data.ndim == 3
+print(data.shape)
+# then register the data to the detector
+my_nxtomo.instrument.detector.data = data
+
+image_key_control = numpy.concatenate(
+    [
+        [ImageKey.DARK_FIELD] * len(dark_binned),
+        [ImageKey.FLAT_FIELD] * len(flat_binned),
+        [ImageKey.PROJECTION] * len(proj_binned),
+    ]
+)
+
+# insure with have the same number of frames and image key
+assert len(image_key_control) == len(data)
+# print position of flats in the sequence
+print("flats indexes are", numpy.where(image_key_control == ImageKey.FLAT_FIELD))
+# then register the image keys to the detector
+my_nxtomo.instrument.detector.image_key_control = image_key_control
+
+rotation_angle = numpy.concatenate(
+    [
+        [0 for x in range(len(dark_binned))],
+        [0 for x in range(len(flat_binned))],
+        proj_rotation_angles,
+    ]
+)
+assert len(rotation_angle) == len(data)
+# register rotation angle to the sample
+my_nxtomo.sample.rotation_angle = rotation_angle
+
+my_nxtomo.instrument.detector.field_of_view = "Full"
+
+my_nxtomo.instrument.detector.x_pixel_size = (
+    my_nxtomo.instrument.detector.y_pixel_size
+) = 1e-7  # pixel size must be provided in SI: meter
+my_nxtomo.instrument.detector.x_pixel_size = (
+    my_nxtomo.instrument.detector.y_pixel_size
+) = 0.1
+my_nxtomo.instrument.detector.x_pixel_size.unit = (
+    my_nxtomo.instrument.detector.y_pixel_size.unit
+) = "micrometer"
+
+nx_tomo_file_path = pathlib.Path(THIS_PATH / "tomo_00077.nx")
+my_nxtomo.save(file_path=str(nx_tomo_file_path), data_path="entry", overwrite=True)
+
+has_tomoscan = False
+try:
+    import tomoscan
+except ImportError:
+    has_tomoscan = False
+    from tomoscan.esrf import NXtomoScan
+    from tomoscan.validator import ReconstructionValidator
+
+    has_tomoscan = True
+
+if has_tomoscan:
+    scan = NXtomoScan(nx_tomo_file_path, entry="entry")
+    validator = ReconstructionValidator(
+        scan, check_phase_retrieval=False, check_values=True
+    )
+    assert validator.is_valid()