edit creation of scan2d object to remove datapoints where attenuators…

… are moving

src/islatu/background.py

@@ -14,8 +14,8 @@
 from scipy.stats import norm
 from scipy.optimize import curve_fit
 
-from .region import Region
-from .image import Image
+from islatu.region import Region
+from islatu.image import Image
 
 
 @dataclass
@@ -70,8 +70,8 @@ def roi_subtraction(image, list_of_regions: List[Region]):
         # the intensity measured in all the background regions so far.
         sum_of_bkg_areas += np.sum(
             image.array_original[
-                int(region.x_start):int(region.x_end),
-                int(region.y_start):int(region.y_end)
+                int(region.y_start):int(region.y_end),
+                int(region.x_start):int(region.x_end)
             ]
         )
         # Add the number of pixels in this background ROI to the total number of

src/islatu/cropping.py

@@ -19,4 +19,4 @@ def crop_to_region(array: np.ndarray, region: Region):
         region:
             The instance of Region to crop to.
     """
-    return array[region.x_start:region.x_end, region.y_start:region.y_end]
+    return array[region.y_start:region.y_end,region.x_start:region.x_end]

src/islatu/io.py

@@ -24,12 +24,12 @@ class and its children.
 import h5py
 
 
-from .scan import Scan2D
-from .image import Image
-from .data import Data
-from .region import Region
-from .debug import debug
-from .metadata import Metadata
+from islatu.scan import Scan2D
+from islatu.image import Image
+from islatu.data import Data
+from islatu.region import Region
+from islatu.debug import debug
+from islatu.metadata import Metadata
 
 
 class NexusBase(Metadata):
@@ -70,7 +70,7 @@ def detector(self):
         Raises:
             ValueError if more than one NXdetector is found.
         """
-        det, = self.instrument.NXdetector
+        det, = self.instrument.NXdetector[0]
         return det
 
     @property
@@ -560,7 +560,7 @@ def load_images_from_h5(h5_file_path,datanxfilepath,transpose=False):
     return images
 
 
-def i07_nxs_parser(file_path: str):
+def i07_nxs_parser(file_path: str,remove_indices=None):
     """
     Parses a .nxs file acquired from the I07 beamline at diamond, returning an
     instance of Scan2D. This process involves loading the images contained in
@@ -577,15 +577,17 @@ def i07_nxs_parser(file_path: str):
     """
     # Use the magical parser class that does everything for us.
     i07_nxs = I07Nexus(file_path)
-
+    detname=list(i07_nxs.entry.instrument.keys())[0]
+    if 'attenuation_filters_moving' in i07_nxs.entry[f'{detname}'].keys():
+        remove_indices=np.where(np.array(i07_nxs.entry[f'{detname}/attenuation_filters_moving']))[0]
     # Load the images, taking a transpose if necessary (because which axis is
     # x and which is why is determined by fast vs slow detector axes in memory).
     if i07_nxs.detector_name in [
             I07Nexus.excalibur_detector_2021,
             I07Nexus.excalibur_04_2022,
             I07Nexus.pilatus_02_2024,
             I07Nexus.excalibur_08_2024]:
-        images = load_images_from_h5(i07_nxs.local_data_path,i07_nxs._src_data_path[1], transpose=True)
+        images = load_images_from_h5(i07_nxs.local_data_path,i07_nxs._src_data_path[1], transpose=False)
 
     # The dependent variable.
     rough_intensity = i07_nxs.default_signal
@@ -602,14 +604,13 @@ def i07_nxs_parser(file_path: str):
         data = Data(rough_intensity, rough_intensity_e, i07_nxs.probe_energy,
                     theta=axis)
     elif i07_nxs.default_axis_type == 'tth':
-        data = Data(rough_intensity, rough_intensity_e, i07_nxs.probe_energy,
-                    theta=axis/2)
+        data = Data(rough_intensity, rough_intensity_e, i07_nxs.probe_energy,                theta=axis/2)
     else:
         raise NotImplementedError(
             f"{i07_nxs.default_axis_type} is not a supported axis type.")
 
     # Returns the Scan2D object
-    return Scan2D(data, i07_nxs, images)
+    return Scan2D(data, i07_nxs, images, remove_indices)
 
 
 def _try_to_find_files(filenames: List[str],

src/islatu/refl_profile.py

@@ -6,9 +6,9 @@
 
 from typing import List
 
-from .scan import Scan
-from .stitching import concatenate, rebin
-from .data import Data
+from islatu.scan import Scan
+from islatu.stitching import concatenate, rebin
+from islatu.data import Data
 
 
 class Profile(Data):
@@ -136,9 +136,9 @@ def transmission_normalisation(self,overwrite_transmissions=None):
         """
         for i,scan in enumerate(self.scans):
             if overwrite_transmissions is not None:
-                overwrite_transmission=overwrite_transmissions[i]
+                overwrite_transmission = overwrite_transmissions[i]
             else:
-                overwrite_transmission=None
+                overwrite_transmission = None
             scan.transmission_normalisation(overwrite_transmission)
 
         self.concatenate()

src/islatu/runner.py

@@ -455,11 +455,13 @@ def i07reduce(run_numbers, yaml_file, directory='/dls/{}/data/{}/{}/',
 
     if q_subsample_dicts is not None:
         log_processing_stage(
-            "Doctoring data.\nSorry, I mean: Bounding q-vectors.")
+            "Bounding q-vectors.")
         # We'll need to subsample a subset of our scans.
         for q_subsample_dict in q_subsample_dicts:
             refl.subsample_q(**q_subsample_dict)
         debug.log("Limited q-range on specified scans.")
+
+
 
     # Rebin the data, if the user requested this.
     if the_boss.data.rebin:

src/islatu/scan.py

@@ -51,7 +51,7 @@ def subsample_q(self, q_min=0, q_max=float('inf')):
         # be used like this, and they encourage np.asarray(condition).nonzero()
 
         # Now remove all data points at these qs.
-        self.remove_data_points(illegal_q_indices)
+        self.remove_data_points(illegal_q_indices)   
 
     def transmission_normalisation(self,overwrite_transmission):
         """
@@ -107,11 +107,13 @@ class Scan2D(Scan):
             The detector images in the given scan.
     """
 
-    def __init__(self, data: Data, metadata: Metadata, images: List[Image]) \
+    def __init__(self, data: Data, metadata: Metadata, images: List[Image],remove_indices=None) \
             -> None:
         super().__init__(data, metadata)
         self.images = images
-
+        if remove_indices is not None:
+            self.remove_data_points(remove_indices)
+
     def crop(self, crop_function, **kwargs):
         """
         Crop every image in images according to crop_function.