Merge pull request #12 from Neural-Systems-at-UIO/OOP

Oop

PyNutil/counting_and_load.py

@@ -101,6 +101,13 @@ def pixel_count_per_region(
         new_rows.append(row)
 
     df_counts_per_label_name = pd.DataFrame(new_rows)
+    
+    #Task for Sharon:
+    #If you can get the areas per region from the flat file here 
+    #you can then use those areas to calculate the load per region here
+    # and add to dataframe
+    #see messing around pyflat.py
+
     return df_counts_per_label_name
 
 

PyNutil/main.py

@@ -211,12 +211,13 @@ class PyNutil:
             labeled_points, labeled_points_centroids, self.atlas_labels
         )
         prev_pl = 0
+        prev_cl = 0
         per_section_df = []
         current_centroids = None
         current_points = None
-        for pl in self.points_len:
+        for pl,cl in zip(self.points_len, self.centroids_len):
             if hasattr(self, "centroids"):
-                current_centroids = labeled_points_centroids[prev_pl : prev_pl + pl]
+                current_centroids = labeled_points_centroids[prev_cl : prev_cl + cl]
             if hasattr(self, "pixel_points"):
                 current_points = labeled_points[prev_pl : prev_pl + pl]
             current_df = pixel_count_per_region(
@@ -224,6 +225,7 @@ class PyNutil:
             )
             per_section_df.append(current_df)
             prev_pl += pl
+            prev_cl += cl
 
         self.labeled_points = labeled_points
         self.labeled_points_centroids = labeled_points_centroids
@@ -272,7 +274,7 @@ class PyNutil:
             self.segmentation_filenames,
             self.per_section_df,
         ):
-            split_fn = fn.split("/")[-1].split(".")[0]
+            split_fn = fn.split(os.sep)[-1].split(".")[0]
             df.to_csv(
                 f"{output_folder}/per_section_reports/{split_fn}.csv",
                 sep=";",

messing_around_files/testing_openflatfile.py

@@ -39,7 +39,7 @@ with open(base, "rb") as f:
 """assign label file values into image array"""
 
 labelfile = pd.read_csv(r"metadata/annotation_volumes\allen2017_colours.csv")
-labelfile[]
+#labelfile[]
 print(list(zip(val,count)))
 
 

scripts/create_test_data.py

+from PIL import Image, ImageDraw
+
+
+def generate_test_image(width, height, file_path):
+    # Create an empty white image
+    image = Image.new(mode = "RGB", size = (width, height), color=(255,255,255))
+
+    # Save the image as a PNG file
+    image.save(file_path)
+
+# Example usage
+width = 1000  # Specify the width of the image in pixels
+height = 1000  # Specify the height of the image in pixels
+file_path = 'testimage.png'  # Specify the file path for saving the image
+
+# Generate and save the black and white image
+generate_test_image(width, height, file_path)
+
+
+"""This is used to generate the test data"""
+
+def generate_image_with_squares(width, height, square_diameter, square_locations, num_images):
+    # Create a white image with objects of specified size at specified x, y locations
+    for i in range(1, num_images + 1):
+        image = Image.new('RGB', (width, height), color=(255, 255, 255))
+
+        # Create a draw object
+        draw = ImageDraw.Draw(image)
+
+        # Draw black squares
+        for location in square_locations:
+            x, y = location
+            square = (x, y, x + (square_size - 1), y + (square_size - 1))
+            # square defines the bounding box
+            draw.rectangle(square, fill=(0, 0, 0))
+
+        file_name = f"../test_data/PyTest/test_s00{i}.png"
+        image.save(file_name, "PNG")
+
+# Example usage
+width = 1500  # Specify the width of the image in pixels
+height = 1000 # Specify the height of the image in pixels
+square_diameter = 10  # Specify the size of the black squares in pixels
+square_locations = [(500, 500), (500, 600), (500, 700), (1000, 500), (1000,600),(1000,700)]  # Specify the x, y locations of the black squares
+num_images = 5
+
+# Generate the white image with black squares
+image = generate_image_with_squares(width, height, square_diameter, square_locations,num_images)
+

test/test7_PyNutil.json

+{   "volume_path": "allen2017",
+    "label_path": "annotation_volumes/allen2017_colours.csv",
+    "segmentation_folder": "test_data/PyTest_seg",
+    "alignment_json": "test_data/PyNutil_testdataset_Nonlin_SY.json",
+    "nonlinear": true,
+    "colour": [0, 0, 0],
+    "points_json_path": "outputs/test7_PyNutil.json"
+}
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test/test8_PyNutil_fixed.json

+{   "volume_path": "allen2017",
+    "label_path": "annotation_volumes/allen2017_colours.csv",
+    "segmentation_folder": "test_data/PyTest_seg",
+    "alignment_json": "test_data/PyNutil_testdataset_Nonlin_SY_fixed.json",
+    "nonlinear": true,
+    "colour": [0, 0, 0],
+    "points_json_path": "outputs/test8_PyNutil.json"
+}
\ No newline at end of file

testOOP.py

 from PyNutil import PyNutil
 
-pnt = PyNutil(settings_file=r"test/PVMouse_81264_test.json")
-# pnt = PyNutil(settings_file=r"test/test3.json")
+pnt = PyNutil(settings_file=r"test/test8_PyNutil_fixed.json")
+# pnt = PyNutil(settings_file=r"test/test7_PyNutil.json")
 # pnt.build_quantifier()
 
 pnt.get_coordinates(object_cutoff=0)
 
 pnt.quantify_coordinates()
 
-pnt.save_analysis("outputs/test4_2017")
+pnt.save_analysis("outputs/test8_PyNutil")

test_data/PyNutil_testdataset_Nonlin_SY.json

+{"name":"PyNutil_testdataset","target":"ABA_Mouse_CCFv3_2017_25um.cutlas","target-resolution":[456.0, 528.0, 320.0],"slices":[
+{"filename":"test_s001.png","nr":1,"width":1500,"height":1000,"anchoring":[-5.145275115966797, 361.8014440433213, 331.1490739071843, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0]}, 
+{"filename":"test_s002.png","nr":2,"width":1500,"height":1000,"anchoring":[-3.8589563369750977, 318.7157039711191, 340.24552914037605, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0],"markers":[[636.8098159509204, 603.4958601655935, 672.6993865030674, 593.3762649494021], [902.9868982011025, 615.5567336628567, 843.8650306748466, 610.8555657773691], [561.2609204260139, 750.3661510917975, 558.5889570552147, 775.5289788408462]]}, 
+{"filename":"test_s003.png","nr":3,"width":1500,"height":1000,"anchoring":[-2.8942172527313232, 275.6299638989171, 350.0189942541106, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0],"markers":[[761.0429447852762, 629.2548298068077, 761.0429447852761, 629.2548298068077], [204.29447852760745, 613.6154553817848, 365.3374233128834, 612.695492180313], [482.6376861494953, 714.9876920193675, 623.0061349693251, 747.0101195952162], [434.00208292806684, 606.7676930120547, 578.8343558282207, 601.6559337626494], [959.8159509202455, 636.6145354185834, 980.0613496932516, 628.3348666053357], [957.8161415293836, 523.3987679117937, 953.3742331288344, 547.3781048758049]]}, 
+{"filename":"test_s004.png","nr":4,"width":1500,"height":1000,"anchoring":[-3.0282087922096252, 232.54422382671487, 364.1366059225139, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0],"markers":[[522.6993865030674, 712.9714811407543, 519.9386503067485, 715.7313707451704], [630.6438500513034, 523.1833943062713, 550.3067484662577, 519.7792088316469], [916.4047791164191, 534.1886045162021, 962.5766871165645, 523.4590616375344], [950.8076359295408, 705.46368100121, 949.6932515337423, 701.0119595216191], [1096.1208774051677, 649.3153717520049, 1099.6932515337426, 656.8537258509658], [1030.2378410339393, 594.2011916220456, 1065.644171779141, 604.4158233670653]]}, 
+{"filename":"test_s005.png","nr":5,"width":1500,"height":1000,"anchoring":[-0.6163610816001892, 189.45848375451277, 374.2485759765199, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0],"markers":[[6.441717791411037, 588.7764489420423, 186.80981595092024, 425.0229990800368], [766.3836793259812, 987.3315412211099, 834.6625766871166, 946.6421343146276], [447.4522362685242, 740.6361518118404, 565.9509202453987, 643.0542778288868], [392.2943778764543, 594.4761834437141, 542.9447852760735, 478.3808647654094], [1117.436664514756, 564.5422630203066, 788.6503067484659, 422.2631094756209], [1045.7025247722827, 975.3508578153971, 893.5582822085888, 873.045078196872]]}]}
\ No newline at end of file

test_data/PyNutil_testdataset_Nonlin_SY_fixed.json

+{"name":"PyNutil_testdataset","target":"ABA_Mouse_CCFv3_2017_25um.cutlas","target-resolution":[456.0, 528.0, 320.0],"slices":[
+{"filename":"test_s001.png","nr":1,"width":1500,"height":1000,"anchoring":[-5.145275115966797, 361.8014440433213, 331.1490739071843, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0]}, 
+{"filename":"test_s002.png","nr":2,"width":1500,"height":1000,"anchoring":[-3.8589563369750977, 318.7157039711191, 340.24552914037605, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0],"markers":[[636.8098159509204, 603.4958601655935, 672.6993865030674, 593.3762649494021], [902.9868982011025, 615.5567336628567, 843.8650306748466, 610.8555657773691], [561.2609204260139, 750.3661510917975, 558.5889570552147, 775.5289788408462]]}, 
+{"filename":"test_s003.png","nr":3,"width":1500,"height":1000,"anchoring":[-2.8942172527313232, 275.6299638989171, 350.0189942541106, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0],"markers":[[761.0429447852762, 629.2548298068077, 761.0429447852761, 629.2548298068077], [204.29447852760745, 613.6154553817848, 365.3374233128834, 612.695492180313], [482.6376861494953, 714.9876920193675, 623.0061349693251, 747.0101195952162], [434.00208292806684, 606.7676930120547, 578.8343558282207, 601.6559337626494], [959.8159509202455, 636.6145354185834, 980.0613496932516, 628.3348666053357], [957.8161415293836, 523.3987679117937, 953.3742331288344, 547.3781048758049]]}, 
+{"filename":"test_s004.png","nr":4,"width":1500,"height":1000,"anchoring":[-3.0282087922096252, 232.54422382671487, 364.1366059225139, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0],"markers":[[522.6993865030674, 712.9714811407543, 530.6338374725239, 715.7313707451705], [630.6438500513034, 523.1833943062713, 550.3067484662577, 519.7792088316469], [916.4047791164191, 534.1886045162021, 962.5766871165645, 523.4590616375344], [950.8076359295408, 705.46368100121, 949.6932515337423, 701.0119595216191], [1096.1208774051677, 649.3153717520049, 1099.6932515337426, 656.8537258509658], [1030.2378410339393, 594.2011916220456, 1065.644171779141, 604.4158233670653]]}, 
+{"filename":"test_s005.png","nr":5,"width":1500,"height":1000,"anchoring":[-0.6163610816001892, 189.45848375451277, 374.2485759765199, 456.0, 0.0, 0.0, 0.0, 0.0, -320.0],"markers":[[6.441717791411037, 588.7764489420423, 186.80981595092024, 425.0229990800368], [766.3836793259812, 987.3315412211099, 834.6625766871166, 946.6421343146276], [447.4522362685242, 740.6361518118404, 565.9509202453987, 643.0542778288868], [392.2943778764543, 594.4761834437141, 542.9447852760735, 478.3808647654094], [1117.436664514756, 564.5422630203066, 788.6503067484659, 422.2631094756209], [1045.7025247722827, 975.3508578153971, 893.5582822085888, 873.045078196872]]}]}
\ No newline at end of file