Remove unused function and imports

2d_spots_in_fibers.py

 #@ OpService ops
 #@ CommandService command
+#@ RoiManager rm
 #@ File (label="select image", description="select your input image", style=file) path_to_image
 #@ Integer (label="select image file series", description="leave 1 if not needed", value=1, min=1, max=20, stepSize=1, persist=false, style=slider) series_number
 #@ File (label="Fiber Segmentation", description="select the Fiber Segmentation RoiSet .zip file", style=file) fiber_segmentation_roiset
@@ -19,6 +20,8 @@ from ij import IJ
 from ij.plugin import ImageCalculator
 from ij.plugin.frame import RoiManager
 from ij.measure import ResultsTable
+from ij.measure import Measurements as M
+from ij.plugin.filter import Analyzer
 # Bio-Formats imports
 from loci.plugins import BF
 from loci.common import Region
@@ -332,37 +335,50 @@ def convert_labelimage_to_binary(label_imp, scale_binary=True):
 
     return binary_imp
 
-# TODO: test simpler way using IJ roi measure
-def measure_intensity_sum(label_imp, target_imp):
-    """Measure the sum intensity for each label in a label image on another target image.
-    Uses imglib2 and ops for this and works with both 2D and 3D label images.
+
+def measure_intensity_sum(imp, rm):
+    """
+    Measure theraw integrated intensity for all rois in target imp.
 
     Parameters
     ----------
-    label_imp : ImagePlus
-        the input label image
-    target_imp : ImagePlus
-        the target image in which to measure
+    imp : ImagePlus
+        The image from which the intensity will be measured.
+    rm : RoiManager
+        The ROI Manager containing the regions of interest to be analyzed.
 
     Returns
     -------
-    array
-        label id and corresponding sum intensity [label_id, sum_intensity] 
+    label_id : list of str
+        A list of labels corresponding to each ROI.
+    sum_intensity : list of int
+        A list of summed integrated intensities for each ROI.
+
+    Notes
+    -----
+    The results are stored in a `ij.ResultsTable`,
+    from which the raw integrated density values are extracted.
+
+    Example
+    -------
+    >>> labels, intensities = measure_intensity_sum(image, roi_manager)
     """
+
+    rt_ = ResultsTable()
+    options = M.INTEGRATED_DENSITY
+    an = Analyzer (imp, options, rt_)
+    an.setPrecision(0)
+    
     label_id = []
     sum_intensity = []
-    target_img = ImageJFunctions.wrap(target_imp) # convert ImagePlus to img to use ops/region measurements on it
-    regions = convert_labelimage_to_imglib2regions(label_imp)
-    
-    for region in regions:
-        label_id.append(region.getLabel() + 1) # region.getlabel() starts counting from 0. So the label with int 1 has the index 0.
-        input = Regions.sample(region, target_img) # returns an iterableInterval
-        sum = ops.stats().sum(input).getRealDouble()
-        sum_intensity.append(sum)
-        # other measurements see https://forum.image.sc/t/can-i-get-to-measurements-using-imagej-ops/4448/5
-    result = [label_id, sum_intensity]
+
+    for index, roi in enumerate(rm.getRoisAsArray()):
+        imp.setRoi(roi)
+        an.measure()
+        label_id.append(roi.getName())
+        sum_intensity.append(int(rt_.getColumn("RawIntDen")[index]))
     
-    return result
+    return label_id, sum_intensity
 
 
 def add_results_to_resultstable(results_table, column, values):