Restructure and cleanup code, OOP

PyNutil/PyNutil.py → PyNutil/coordinate_extraction.py

@@ -29,6 +29,8 @@ def getCentroidsAndArea(Segmentation, pixelCutOff=0):
 
 
 
+
+
 def transformToRegistration(SegHeight, SegWidth, RegHeight, RegWidth):
     """this function returns the scaling factors to transform the segmentation to the registration space"""
     Yscale = RegHeight/SegHeight
@@ -94,14 +96,19 @@ def SegmentationToAtlasSpace(slice, SegmentationPath, pixelID='auto', nonLinear=
     RegWidth  = slice["width"]
     #this calculates reg/seg
     Yscale , Xscale = transformToRegistration(SegHeight,SegWidth,  RegHeight,RegWidth)
-    #this creates a triangulation using the reg width
-    triangulation   = triangulate(RegWidth, RegHeight, slice["markers"])
-    #scale the seg coordinates to reg/seg
     scaledY,scaledX = scalePositions(ID_pixels[0], ID_pixels[1], Yscale, Xscale)
     if nonLinear:
-        newX, newY = transform_vec(triangulation, scaledX, scaledY)
+        if "markers" in slice:
+            #this creates a triangulation using the reg width
+            triangulation   = triangulate(RegWidth, RegHeight, slice["markers"])
+            newX, newY = transform_vec(triangulation, scaledX, scaledY)
+        else:
+            print(f"no markers found for " + slice["filename"])
+            newX, newY = scaledX, scaledY
     else:
         newX, newY = scaledX, scaledY
+
+
     #scale U by Uxyz/RegWidth and V by Vxyz/RegHeight
     points = transformToAtlasSpace(slice['anchoring'], newY, newX, RegHeight, RegWidth)
     # points = points.reshape(-1)
@@ -113,7 +120,7 @@ def FolderToAtlasSpace(folder, QUINT_alignment, pixelID=[0, 0, 0], nonLinear=Tru
     slices = loadVisuAlignJson(QUINT_alignment)
     points = []
     segmentationFileTypes = [".png", ".tif", ".tiff", ".jpg", ".jpeg"] 
-    Segmentations = [file for file in glob(folder + "*") if any([file.endswith(type) for type in segmentationFileTypes])]
+    Segmentations = [file for file in glob(folder + "/*") if any([file.endswith(type) for type in segmentationFileTypes])]
     SectionNumbers = number_sections(Segmentations)
     #order segmentations and sectionNumbers
     # Segmentations = [x for _,x in sorted(zip(SectionNumbers,Segmentations))]
@@ -125,12 +132,13 @@ def FolderToAtlasSpace(folder, QUINT_alignment, pixelID=[0, 0, 0], nonLinear=Tru
         ##this converts the segmentation to a point cloud
         points.extend(SegmentationToAtlasSpace(current_slice, SegmentationPath, pixelID, nonLinear))
     return np.array(points)
+
 def FolderToAtlasSpaceMultiThreaded(folder, QUINT_alignment, pixelID=[0, 0, 0], nonLinear=True):
     "apply Segmentation to atlas space to all segmentations in a folder"
     slices = loadVisuAlignJson(QUINT_alignment)
     
     segmentationFileTypes = [".png", ".tif", ".tiff", ".jpg", ".jpeg"] 
-    Segmentations = [file for file in glob(folder + "*") if any([file.endswith(type) for type in segmentationFileTypes])]
+    Segmentations = [file for file in glob(folder + "/*") if any([file.endswith(type) for type in segmentationFileTypes])]
     SectionNumbers = number_sections(Segmentations)
     #order segmentations and sectionNumbers
     # Segmentations = [x for _,x in sorted(zip(SectionNumbers,Segmentations))]
@@ -172,12 +180,17 @@ def SegmentationToAtlasSpaceMultiThreaded(slice, SegmentationPath, pixelID='auto
     RegWidth  = slice["width"]
     #this calculates reg/seg
     Yscale , Xscale = transformToRegistration(SegHeight,SegWidth,  RegHeight,RegWidth)
-    #this creates a triangulation using the reg width
-    triangulation   = triangulate(RegWidth, RegHeight, slice["markers"])
+
     #scale the seg coordinates to reg/seg
     scaledY,scaledX = scalePositions(ID_pixels[0], ID_pixels[1], Yscale, Xscale)
     if nonLinear:
-        newX, newY = transform_vec(triangulation, scaledX, scaledY)
+        if "markers" in slice:
+            #this creates a triangulation using the reg width
+            triangulation   = triangulate(RegWidth, RegHeight, slice["markers"])
+            newX, newY = transform_vec(triangulation, scaledX, scaledY)
+        else:
+            print(f"no markers found for " + slice["filename"])
+            newX, newY = scaledX, scaledY
     else:
         newX, newY = scaledX, scaledY
     #scale U by Uxyz/RegWidth and V by Vxyz/RegHeight

PyNutil/dream_workflow.py

+import PyNutil
+
+#define parameters
+#specify loacation of segmentation folder
+segmentation_folder = r"blabla/blabla"
+#specify location of json file
+json_file = r"blabla/blabla.json"
+#specify colour to quantify
+colour = [255, 255, 255]
+#specify output location
+output_path = r"blabla/blabla/output"
+
+quantifier = PyNutil(segmentation_folder,
+                                    json_file,
+                                    colour,
+                                    output_path)
+
+quantifier.build_quantifier()
+
+#define your mask as either a png, or a qcalign damage map
+#this mask will be applied to all 
+quantifier.load_mask(mask_path=r"blablabla/")
+
+#load a custom region file
+quantifier.load_custom_regions(custom_region_json=r"blablabla/")
+#run coordinate extraction
+#ideally extract coordinates per section and whole brain
+points = quantifier.get_coordinates()
+
+quantifier.save_coordinates()
+
+objects = quantifier.get_objects()
+
+loads = quantifier.get_loads()
+
+quantifier.save_segmentation_atlas_overlays()
\ No newline at end of file

PyNutil/folder_of_segmentations_to_meshview_multithreaded.py

@@ -8,24 +8,31 @@ import csv
 
 from datetime import datetime
 
+#import json and use it to define volume_path, segmentation_folder, alignment_json, label_path, colour, allen_colours
+
+
 #import our function for converting a folder of segmentations to points
 from PyNutil import FolderToAtlasSpace, labelPoints, WritePointsToMeshview, FolderToAtlasSpaceMultiThreaded
-
+label_path = "../annotation_volumes//allen2022_colours.csv"
+colour = [255, 0, 255]
 volume_path = "../annotation_volumes//annotation_10_reoriented.nrrd"
 data, header = nrrd.read(volume_path)
+points_json_path = "../outputs/points.json"
+segmentation_folder = "../test_data/oneSection15"
+alignment_json = "../test_data/C68_nonlinear_no_markers.json"
+allen_colours = "../annotation_volumes//allen2022_colours.csv"
+counts_per_label_name = "../outputs/counts_per_allenID.csv"
 
 startTime = datetime.now()
 
-segmentation_folder = "../test_data/tTA_2877_NOP/"
-alignment_json = "../test_data/tTA_2877_NOP_horizontal_final_2017.json"
+
 #now we can use our function to convert the folder of segmentations to points
-points = FolderToAtlasSpaceMultiThreaded(segmentation_folder,alignment_json, pixelID=[0, 0, 255], nonLinear=True)
+points = FolderToAtlasSpaceMultiThreaded(segmentation_folder,alignment_json, pixelID=colour, nonLinear=True)
 
 time_taken = datetime.now() - startTime
 
 print(f"Folder to atlas took: {time_taken}")
 #first we need to find the label file for the volume
-label_path = "../annotation_volumes//allen2022_colours.csv"
 #then the path to the volume
 
 #read the label files
@@ -34,7 +41,7 @@ label_df = pd.read_csv(label_path)
 #now we can get the labels for each point
 labels = labelPoints(points, data, scale_factor=2.5)
 #save points to a meshview json
-WritePointsToMeshview(points, labels,"../outputs/points.json", label_df)
+WritePointsToMeshview(points, labels,points_json_path, label_df)
 
 #Task:
 # Make a pandas dataframe
@@ -48,7 +55,6 @@ counts_per_label = list(zip(counted_labels,label_counts))
 
 df_counts_per_label = pd.DataFrame(counts_per_label, columns=["allenID","pixel count"])
 
-allen_colours = "../annotation_volumes//allen2022_colours.csv"
 
 df_allen_colours =pd.read_csv(allen_colours, sep=",")
 df_allen_colours
@@ -74,7 +80,7 @@ df_counts_per_label_name = pd.DataFrame(new_rows)
 df_counts_per_label_name
 
 # write to csv file
-df_counts_per_label_name.to_csv("../outputs/counts_per_allenID.csv", sep=";", na_rep='', index= False)
+df_counts_per_label_name.to_csv(counts_per_label_name, sep=";", na_rep='', index= False)
 
 #r = df_allen_colours["r"]
 #g = df_allen_colours["g"]

PyNutil/main.py

+
+
+
+
+class PyNutil:
+    def __init__(self, segmentation_folder) -> None:
+        self.segmentation_folder = segmentation_folder
+        self.json_file = json_file
+        self.colour = colour
+        self.output_path = output_path
+
+    def build_quantifier(self):
+        #do all the expensive computations
+