Fixed an issue regarding the background mask

Signed-off-by: Jan Andre Reuter <[email protected]>
3d-pli · Jul 19, 2021 · a8976d2 · a8976d2
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Showing 5 changed files with 13 additions and 7 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,5 +1,13 @@
 # Changelog
 
+## v2.2.1
+### Added
+
+### Changed
+
+### Fixed
+- Fixed an error regarding the mask caluclation which sometimes would not create a mask because of an error when using the average histogram
+
 ## v2.2.0
 ### Added
 - Added SLIXVisualizeParameter to the toolbox which enables visualizing directions either as a fiber orientation map or as vectors seen before in the example Jupyter notebook

diff --git a/SLIX/CPU/toolbox.py b/SLIX/CPU/toolbox.py
@@ -46,7 +46,7 @@ def background_mask(image):
     reversed_peaks = SLIX.toolbox.significant_peaks(image=avg_hist).flatten()
 
     # We can now calculate the index of our background threshold using the reversed_peaks
-    index = numpy.argmax(reversed_peaks)
+    index = numpy.argmax(peaks) + numpy.argmax(reversed_peaks[numpy.argmax(peaks):])
     # Reverse from 0 to 1 to original image scale and calculate the threshold position
     threshold = avg_bins[index] * numpy.percentile(avg_image, 99)
 
@@ -56,7 +56,7 @@ def background_mask(image):
 
 def peaks(image):
     """
-Detect all peaks from a full SLI measurement. Peaks will not be filtered
+    Detect all peaks from a full SLI measurement. Peaks will not be filtered
     in any way. To detect only significant peaks, filter the peaks by using
     the prominence as a threshold.
 

diff --git a/SLIX/GPU/toolbox.py b/SLIX/GPU/toolbox.py
@@ -52,12 +52,10 @@ def background_mask(image, return_numpy=True):
     # Reverse the histogram to search for minimal values with SLIX (again)
     avg_hist = -avg_hist
     reversed_peaks = SLIX.toolbox.significant_peaks(image=avg_hist).flatten()
-
     # We can now calculate the index of our background threshold using the reversed_peaks
-    index = numpy.argmax(reversed_peaks)
+    index = numpy.argmax(peaks) + numpy.argmax(reversed_peaks[numpy.argmax(peaks):])
     # Reverse from 0 to 1 to original image scale and calculate the threshold position
     threshold = avg_bins[index] * numpy.percentile(gpu_average, 99)
-
     # Return a mask with the calculated background image
     gpu_mask = gpu_average < threshold
 

diff --git a/SLIX/__init__.py b/SLIX/__init__.py
@@ -1,7 +1,7 @@
 """
 Scattered Light Imaging ToolboX (SLIX) – an open-source Python package that allows a fully automated evaluation of SLI measurements and the generation of different parameter maps
 """
-__version__ = '2.2.0'
+__version__ = '2.2.1'
 __all__ = ['toolbox', 'io', 'visualization', 'preparation',
            'attributemanager', 'CPU', 'GPU']
 

diff --git a/setup.cfg b/setup.cfg
@@ -1,6 +1,6 @@
 [metadata]
 name = SLIX
-version = 2.2.0
+version = 2.2.1
 author = Jan Andre Reuter, Miriam Menzel
 author_email = [email protected], [email protected]
 url = https://github.com/3d-pli/SLIX