add testing framework

PyNutil/__init__.py

-from .main import PyNutil
\ No newline at end of file
+from .main import PyNutil

PyNutil/coordinate_extraction.py

@@ -67,6 +67,7 @@ def transform_to_registration(seg_height, seg_width, reg_height, reg_width):
     x_scale = reg_width / seg_width
     return y_scale, x_scale
 
+
 # related to coordinate extraction
 def find_matching_pixels(segmentation, id):
     """This function returns the Y and X coordinates of all the pixels in the segmentation that match the id provided."""
@@ -207,14 +208,14 @@ def folder_to_atlas_space(
     [t.join() for t in threads]
     # Flatten points_list
 
-    points_len = [
-        len(points) if None not in points else 0 for points in points_list
-        ]
+    points_len = [len(points) if None not in points else 0 for points in points_list]
     centroids_len = [
-             len(centroids) if None not in centroids else 0 for centroids in centroids_list
-         ]
+        len(centroids) if None not in centroids else 0 for centroids in centroids_list
+    ]
     points_list = [points for points in points_list if None not in points]
-    centroids_list = [centroids for centroids in centroids_list if None not in centroids]
+    centroids_list = [
+        centroids for centroids in centroids_list if None not in centroids
+    ]
     if len(points_list) == 0:
         points = np.array([])
     else:
@@ -224,7 +225,6 @@ def folder_to_atlas_space(
     else:
         centroids = np.concatenate(centroids_list)
 
-
     return (
         np.array(points),
         np.array(centroids),
@@ -234,6 +234,7 @@ def folder_to_atlas_space(
         segmentations,
     )
 
+
 def load_segmentation(segmentation_path: str):
     """Load a segmentation from a file."""
     print(f"working on {segmentation_path}")
@@ -243,6 +244,7 @@ def load_segmentation(segmentation_path: str):
     else:
         return cv2.imread(segmentation_path)
 
+
 def detect_pixel_id(segmentation: np.array):
     """Remove the background from the segmentation and return the pixel id."""
     segmentation_no_background = segmentation[~np.all(segmentation == 0, axis=2)]
@@ -250,7 +252,17 @@ def detect_pixel_id(segmentation: np.array):
     print("detected pixel_id: ", pixel_id)
     return pixel_id
 
-def get_region_areas(use_flat, atlas_labels, flat_file_atlas, seg_width, seg_height, slice_dict, atlas_volume, triangulation):
+
+def get_region_areas(
+    use_flat,
+    atlas_labels,
+    flat_file_atlas,
+    seg_width,
+    seg_height,
+    slice_dict,
+    atlas_volume,
+    triangulation,
+):
     if use_flat:
         region_areas = flat_to_dataframe(
             atlas_labels, flat_file_atlas, (seg_width, seg_height)
@@ -262,17 +274,30 @@ def get_region_areas(use_flat, atlas_labels, flat_file_atlas, seg_width, seg_hei
             (seg_width, seg_height),
             slice_dict["anchoring"],
             atlas_volume,
-            triangulation
+            triangulation,
         )
     return region_areas
 
-def get_transformed_coordinates(non_linear, slice_dict, method, scaled_x, scaled_y, centroids, scaled_centroidsX, scaled_centroidsY, triangulation):
+
+def get_transformed_coordinates(
+    non_linear,
+    slice_dict,
+    method,
+    scaled_x,
+    scaled_y,
+    centroids,
+    scaled_centroidsX,
+    scaled_centroidsY,
+    triangulation,
+):
     new_x, new_y, centroids_new_x, centroids_new_y = None, None, None, None
     if non_linear and "markers" in slice_dict:
         if method in ["per_pixel", "all"] and scaled_x is not None:
             new_x, new_y = transform_vec(triangulation, scaled_x, scaled_y)
         if method in ["per_object", "all"] and centroids is not None:
-            centroids_new_x, centroids_new_y = transform_vec(triangulation, scaled_centroidsX, scaled_centroidsY)
+            centroids_new_x, centroids_new_y = transform_vec(
+                triangulation, scaled_centroidsX, scaled_centroidsY
+            )
     else:
         if method in ["per_pixel", "all"]:
             new_x, new_y = scaled_x, scaled_y
@@ -280,6 +305,7 @@ def get_transformed_coordinates(non_linear, slice_dict, method, scaled_x, scaled
             centroids_new_x, centroids_new_y = scaled_centroidsX, scaled_centroidsY
     return new_x, new_y, centroids_new_x, centroids_new_y
 
+
 def segmentation_to_atlas_space(
     slice_dict,
     segmentation_path,
@@ -305,20 +331,51 @@ def segmentation_to_atlas_space(
         triangulation = triangulate(reg_width, reg_height, slice_dict["markers"])
     else:
         triangulation = None
-    region_areas = get_region_areas(use_flat, atlas_labels, flat_file_atlas, seg_width, seg_height, slice_dict, atlas_volume, triangulation)
-    y_scale, x_scale = transform_to_registration(seg_height, seg_width, reg_height, reg_width)
+    region_areas = get_region_areas(
+        use_flat,
+        atlas_labels,
+        flat_file_atlas,
+        seg_width,
+        seg_height,
+        slice_dict,
+        atlas_volume,
+        triangulation,
+    )
+    y_scale, x_scale = transform_to_registration(
+        seg_height, seg_width, reg_height, reg_width
+    )
     centroids, points = None, None
-    scaled_centroidsX, scaled_centroidsY, scaled_x, scaled_y = None, None, None, None 
+    scaled_centroidsX, scaled_centroidsY, scaled_x, scaled_y = None, None, None, None
     if method in ["per_object", "all"]:
-        centroids, scaled_centroidsX, scaled_centroidsY = get_centroids(segmentation, pixel_id, y_scale, x_scale, object_cutoff)
+        centroids, scaled_centroidsX, scaled_centroidsY = get_centroids(
+            segmentation, pixel_id, y_scale, x_scale, object_cutoff
+        )
     if method in ["per_pixel", "all"]:
         scaled_y, scaled_x = get_scaled_pixels(segmentation, pixel_id, y_scale, x_scale)
 
-    new_x, new_y, centroids_new_x, centroids_new_y = get_transformed_coordinates(non_linear, slice_dict, method, scaled_x, scaled_y, centroids, scaled_centroidsX, scaled_centroidsY, triangulation)
+    new_x, new_y, centroids_new_x, centroids_new_y = get_transformed_coordinates(
+        non_linear,
+        slice_dict,
+        method,
+        scaled_x,
+        scaled_y,
+        centroids,
+        scaled_centroidsX,
+        scaled_centroidsY,
+        triangulation,
+    )
     if method in ["per_pixel", "all"] and new_x is not None:
-        points = transform_to_atlas_space(slice_dict["anchoring"], new_y, new_x, reg_height, reg_width)
+        points = transform_to_atlas_space(
+            slice_dict["anchoring"], new_y, new_x, reg_height, reg_width
+        )
     if method in ["per_object", "all"] and centroids_new_x is not None:
-        centroids = transform_to_atlas_space(slice_dict["anchoring"], centroids_new_y, centroids_new_x, reg_height, reg_width)
+        centroids = transform_to_atlas_space(
+            slice_dict["anchoring"],
+            centroids_new_y,
+            centroids_new_x,
+            reg_height,
+            reg_width,
+        )
     points_list[index] = np.array(points if points is not None else [])
     centroids_list[index] = np.array(centroids if centroids is not None else [])
     region_areas_list[index] = region_areas

PyNutil/counting_and_load.py

@@ -5,6 +5,7 @@ import cv2
 from .generate_target_slice import generate_target_slice
 from .visualign_deformations import transform_vec
 
+
 # related to counting and load
 def label_points(points, label_volume, scale_factor=1):
     """This function takes a list of points and assigns them to a region based on the region_volume.
@@ -119,7 +120,6 @@ def pixel_count_per_region(
 """Read flat file, write into an np array, assign label file values, return array"""
 
 
-
 def read_flat_file(file):
     with open(file, "rb") as f:
         b, w, h = struct.unpack(">BII", f.read(9))
@@ -163,6 +163,7 @@ def rescale_image(image, rescaleXY):
     w, h = rescaleXY
     return cv2.resize(image, (h, w), interpolation=cv2.INTER_NEAREST)
 
+
 def assign_labels_to_image(image, labelfile):
     w, h = image.shape
     allen_id_image = np.zeros((h, w))  # create an empty image array
@@ -186,7 +187,7 @@ def count_pixels_per_label(image, scale_factor=False):
 
 def warp_image(image, triangulation, rescaleXY):
     if rescaleXY is not None:
-        w,h = rescaleXY
+        w, h = rescaleXY
     else:
         h, w = image.shape
     reg_h, reg_w = image.shape
@@ -211,8 +212,14 @@ def warp_image(image, triangulation, rescaleXY):
     new_image = image[newY, newX]
     return new_image
 
+
 def flat_to_dataframe(
-    labelfile, file=None, rescaleXY=None, image_vector=None, volume=None, triangulation=None
+    labelfile,
+    file=None,
+    rescaleXY=None,
+    image_vector=None,
+    volume=None,
+    triangulation=None,
 ):
     if (image_vector is not None) and (volume is not None):
         image = generate_target_slice(image_vector, volume)

PyNutil/generate_target_slice.py

 import numpy as np
 import math
 
+
 def generate_target_slice(ouv, atlas):
     width = None
     height = None
     ox, oy, oz, ux, uy, uz, vx, vy, vz = ouv
-    width = np.floor(math.hypot(ux,uy,uz)).astype(int) + 1
-    height = np.floor(math.hypot(vx,vy,vz)).astype(int) + 1
+    width = np.floor(math.hypot(ux, uy, uz)).astype(int) + 1
+    height = np.floor(math.hypot(vx, vy, vz)).astype(int) + 1
     data = np.zeros((width, height), dtype=np.uint32).flatten()
     xdim, ydim, zdim = atlas.shape
     y_values = np.arange(height)
@@ -17,10 +18,12 @@ def generate_target_slice(ouv, atlas):
     wx = ux * (x_values / width)
     wy = uy * (x_values / width)
     wz = uz * (x_values / width)
-    lx = np.floor(hx[:, None] + wx).astype(int) 
-    ly = np.floor(hy[:, None] + wy).astype(int) 
-    lz = np.floor(hz[:, None] + wz).astype(int) 
-    valid_indices = (0 <= lx) & (lx < xdim) & (0 <= ly) & (ly < ydim) & (0 <= lz) & (lz < zdim)
+    lx = np.floor(hx[:, None] + wx).astype(int)
+    ly = np.floor(hy[:, None] + wy).astype(int)
+    lz = np.floor(hz[:, None] + wz).astype(int)
+    valid_indices = (
+        (0 <= lx) & (lx < xdim) & (0 <= ly) & (ly < ydim) & (0 <= lz) & (lz < zdim)
+    )
     valid_indices = valid_indices.flatten()
     lxf = lx.flatten()
     lyf = ly.flatten()
@@ -28,8 +31,7 @@ def generate_target_slice(ouv, atlas):
     valid_lx = lxf[valid_indices]
     valid_ly = lyf[valid_indices]
     valid_lz = lzf[valid_indices]
-    atlas_slice = atlas[valid_lx,valid_ly,valid_lz]
+    atlas_slice = atlas[valid_lx, valid_ly, valid_lz]
     data[valid_indices] = atlas_slice
     data_im = data.reshape((height, width))
     return data_im
-

PyNutil/main.py

@@ -109,11 +109,17 @@ class PyNutil:
         self.colour = colour
         self.atlas_name = atlas_name
         if (atlas_path or label_path) and atlas_name:
-            raise ValueError("Please only specify an atlas_path and a label_path or an atlas_name, atlas and label paths are only used for loading custom atlases")
+            raise ValueError(
+                "Please only specify an atlas_path and a label_path or an atlas_name, atlas and label paths are only used for loading custom atlases"
+            )
         if atlas_path and label_path:
-            self.atlas_volume, self.atlas_labels = self.load_custom_atlas(atlas_path, label_path)
+            self.atlas_volume, self.atlas_labels = self.load_custom_atlas(
+                atlas_path, label_path
+            )
         else:
-            self.atlas_volume, self.atlas_labels = self.load_atlas_data(atlas_name=atlas_name)
+            self.atlas_volume, self.atlas_labels = self.load_atlas_data(
+                atlas_name=atlas_name
+            )
         ###This is just because of the migration to BrainGlobe
 
     def load_atlas_data(self, atlas_name):
@@ -129,22 +135,23 @@ class PyNutil:
         # this could potentially be moved into init
         print("loading atlas volume")
         atlas = brainglobe_atlasapi.BrainGlobeAtlas(atlas_name=atlas_name)
-        atlas_structures = {'idx':[i['id'] for i in atlas.structures_list],
-            'name':[i['name'] for i in atlas.structures_list],
-            'r':[i['rgb_triplet'][0] for i in atlas.structures_list],
-            'g':[i['rgb_triplet'][1] for i in atlas.structures_list],
-            'b':[i['rgb_triplet'][2] for i in atlas.structures_list]
-            }
-        atlas_structures['idx'].insert(0,0)
-        atlas_structures['name'].insert(0,'Clear Label')
-        atlas_structures['r'].insert(0,0)
-        atlas_structures['g'].insert(0,0)
-        atlas_structures['b'].insert(0,0)
+        atlas_structures = {
+            "idx": [i["id"] for i in atlas.structures_list],
+            "name": [i["name"] for i in atlas.structures_list],
+            "r": [i["rgb_triplet"][0] for i in atlas.structures_list],
+            "g": [i["rgb_triplet"][1] for i in atlas.structures_list],
+            "b": [i["rgb_triplet"][2] for i in atlas.structures_list],
+        }
+        atlas_structures["idx"].insert(0, 0)
+        atlas_structures["name"].insert(0, "Clear Label")
+        atlas_structures["r"].insert(0, 0)
+        atlas_structures["g"].insert(0, 0)
+        atlas_structures["b"].insert(0, 0)
 
         atlas_labels = pd.DataFrame(atlas_structures)
-        if  "allen_mouse_" in atlas_name:
+        if "allen_mouse_" in atlas_name:
             print("reorienting allen atlas into quicknii space...")
-            atlas_volume = np.transpose(atlas.annotation,[2,0,1])[:,::-1,::-1]
+            atlas_volume = np.transpose(atlas.annotation, [2, 0, 1])[:, ::-1, ::-1]
         else:
             atlas_volume = atlas.annotation
         print("atlas labels loaded ✅")

PyNutil/metadata/__init__.py

-from . import *
\ No newline at end of file
+from . import *

PyNutil/read_and_write.py

@@ -29,8 +29,6 @@ def load_visualign_json(filename):
             "slices": slices,
         }
 
-
-
     else:
         slices = vafile["slices"]
     if len(slices) > 1:

PyNutil/visualign_deformations.py

 """This code was written by Gergely Csucs and Rembrandt Bakker"""
+
 import numpy as np
 
 

PyNutilGUI.py

-import tkinter 
+import tkinter
 
 from tkinter import *
 from tkinter import ttk
@@ -10,137 +10,182 @@ from tkinter import colorchooser
 
 from PyNutil import PyNutil
 
-#Basic GUI example   
+# Basic GUI example
 root = Tk()
-#root.geometry("300x300")
+# root.geometry("300x300")
 root.title("PyNutil")
 root.wm_iconbitmap("Logo_PyNutil.ico")
-#photo = tkinter.PhotoImage(file = 'Logo_PyNutil.ico')
-#root.wm_iconphoto(False, photo)
+# photo = tkinter.PhotoImage(file = 'Logo_PyNutil.ico')
+# root.wm_iconphoto(False, photo)
 
 arguments = {
-   "reference_atlas":None,
-   "registration_json":None,
-   "object_colour":None,
-   "segmentation_dir":None,
-   "output_dir": None 
+    "reference_atlas": None,
+    "registration_json": None,
+    "object_colour": None,
+    "segmentation_dir": None,
+    "output_dir": None,
 }
 
 atlas = brainglobe_atlasapi.list_atlases.get_all_atlases_lastversions()
 
 selected_atlas = StringVar(value="Reference Atlas")
 
-directory = ["select","select1", "select2"]
+directory = ["select", "select1", "select2"]
 selected_directory = StringVar(value="directory")
 
-colour = ["colour","black","red","blue","green"]
+colour = ["colour", "black", "red", "blue", "green"]
 selected_colour = StringVar(value=colour[0])
 
+
 def donothing():
-   filewin = Toplevel(root)
-   label = Label(filewin, text="Do nothing")
-   label.pack()
-   
+    filewin = Toplevel(root)
+    label = Label(filewin, text="Do nothing")
+    label.pack()
+
+
 def about_pynutil():
-   filewin = Toplevel(root)
-   label = Label(filewin, text="PyNutil is an application for brain-wide mapping using a reference brain atlas")
-   label.pack()
-   
+    filewin = Toplevel(root)
+    label = Label(
+        filewin,
+        text="PyNutil is an application for brain-wide mapping using a reference brain atlas",
+    )
+    label.pack()
+
+
 def open_registration_json():
-   value = askopenfilename()
-   arguments["registration_json"] = value
-   print(arguments["registration_json"])
+    value = askopenfilename()
+    arguments["registration_json"] = value
+    print(arguments["registration_json"])
+
 
 def choose_colour():
-   value = colorchooser.askcolor()
-   arguments["object_colour"] = value
-   print(list(value[0]))
-   
+    value = colorchooser.askcolor()
+    arguments["object_colour"] = value
+    print(list(value[0]))
+
+
 def open_segmentation_dir():
-   value = askdirectory()
-   arguments["segmentation_dir"] = value
-   print(arguments["segmentation_dir"])
-   
+    value = askdirectory()
+    arguments["segmentation_dir"] = value
+    print(arguments["segmentation_dir"])
+
+
 def select_output_dir():
-   value = askdirectory()
-   arguments["output_dir"] = value
-   print(arguments["output_dir"])
-   
+    value = askdirectory()
+    arguments["output_dir"] = value
+    print(arguments["output_dir"])
+
+
 def start_analysis():
-   pnt = PyNutil(
-      segmentation_folder= open_segmentation_dir, #'../tests/test_data/big_caudoputamen_test/',
-      alignment_json= open_registration_json, #'../tests/test_data/big_caudoputamen.json',
-      colour= choose_colour,        #[0, 0, 0],
-      atlas_name='allen_mouse_25um'
-      )
-   
-   pnt.get_coordinates(object_cutoff=0)
-   pnt.quantify_coordinates()
-   pnt.save_analysis("../tests/outputs/test9_PyNutil_bigcaudoputamen_new")
-
-#Creating a menu
-root.option_add('*tearOff', FALSE)
-#win = Toplevel(root)
-#menubar = Menu(win)
+    pnt = PyNutil(
+        segmentation_folder=open_segmentation_dir,  #'../tests/test_data/big_caudoputamen_test/',
+        alignment_json=open_registration_json,  #'../tests/test_data/big_caudoputamen.json',
+        colour=choose_colour,  # [0, 0, 0],
+        atlas_name="allen_mouse_25um",
+    )
+
+    pnt.get_coordinates(object_cutoff=0)
+    pnt.quantify_coordinates()
+    pnt.save_analysis("../tests/outputs/test9_PyNutil_bigcaudoputamen_new")
+
+
+# Creating a menu
+root.option_add("*tearOff", FALSE)
+# win = Toplevel(root)
+# menubar = Menu(win)
 menubar = Menu(root)
-#win['menu'] = menubar
+# win['menu'] = menubar
 root.config(menu=menubar)
 
-#menubar = Menu(root)
+# menubar = Menu(root)
 menu_file = Menu(menubar)
 menu_help = Menu(menubar)
-menubar.add_cascade(menu=menu_file, label='File')
-menubar.add_cascade(menu=menu_help, label='Help')
+menubar.add_cascade(menu=menu_file, label="File")
+menubar.add_cascade(menu=menu_help, label="Help")
 
-menu_file.add_command(label='New', command=donothing)
-menu_file.add_command(label='Exit', command=root.quit)
-menu_help.add_command(label='About PyNutil', command=about_pynutil)
+menu_file.add_command(label="New", command=donothing)
+menu_file.add_command(label="Exit", command=root.quit)
+menu_help.add_command(label="About PyNutil", command=about_pynutil)
 
-#Creating a content frame"
-mainframe = ttk.Frame(root, padding="12 12 12 12") # left top right bottom
+# Creating a content frame"
+mainframe = ttk.Frame(root, padding="12 12 12 12")  # left top right bottom
 mainframe.grid(column=0, row=0, sticky=(N, W, E, S))
-root.columnconfigure(0, weight=1) # column to expand if there is extra space
-root.rowconfigure(0, weight=1) # row to expand if there is extra space
+root.columnconfigure(0, weight=1)  # column to expand if there is extra space
+root.rowconfigure(0, weight=1)  # row to expand if there is extra space
 
-#Creating a content frame"
-bottomframe = ttk.Frame(root, padding="12 12 12 12") # left top right bottom
+# Creating a content frame"
+bottomframe = ttk.Frame(root, padding="12 12 12 12")  # left top right bottom
 mainframe.grid(column=0, row=0, sticky=(N, W, E, S))
-root.columnconfigure(0, weight=1) # column to expand if there is extra space
-root.rowconfigure(0, weight=1) # row to expand if there is extra space
+root.columnconfigure(0, weight=1)  # column to expand if there is extra space
+root.rowconfigure(0, weight=1)  # row to expand if there is extra space
 
 # Select reference atlas
-ttk.Label(mainframe, text="Select reference atlas:", width=25).grid(column=1, row=1, sticky=W)
-ttk.OptionMenu(mainframe, selected_atlas, "Reference Atlas", *atlas).grid(column=2, row=1, columnspan=2)
-ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(column=4, row=1, sticky=W)
-
-#Select registration JSON
-ttk.Label(mainframe, text="Select registration JSON:", width=25).grid(column=1, row=2, sticky=W)
-ttk.Button(mainframe, width=16, text="Browse...", command=open_registration_json).grid(column=2, row=2, sticky=W)
-Text(mainframe, height = 1, width =40 ).grid(column=3, row=2, sticky= W)
-ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(column=4, row=2, sticky=W)
-
-#Select segmentation folder
-ttk.Label(mainframe, text="Select segmentation folder:", width=25).grid(column=1, row=3, sticky=W)
-ttk.Button(mainframe, width=16, text="Browse...", command=open_segmentation_dir).grid(column=2, row=3, sticky=W)
-Text(mainframe, height = 1, width =40).grid(column=3, row=3, sticky= W)
-ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(column=4, row=3, sticky=W)
-
-#Select object colour
-ttk.Label(mainframe, text="Select object colour:", width=25).grid(column=1, row=4, sticky=W)
-ttk.Button(mainframe, width=16, text="Colour", command=choose_colour).grid(column=2, row=4, sticky=W)
-Text(mainframe, height = 1, width =40).grid(column=3, row=4, sticky= W)
-ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(column=4, row=4, sticky=W)
-
-#Select output directory
-ttk.Label(mainframe, text="Select output directory:", width=25).grid(column=1, row=5, sticky=W)
-ttk.Button(mainframe, width=16, text="Browse...", command=select_output_dir).grid(column=2, row=5, sticky=W)
-Text(mainframe, height = 1, width =40).grid(column=3, row=5, sticky= W)
-ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(column=4, row=5, sticky=W)
-
-#Start analysis
+ttk.Label(mainframe, text="Select reference atlas:", width=25).grid(
+    column=1, row=1, sticky=W
+)
+ttk.OptionMenu(mainframe, selected_atlas, "Reference Atlas", *atlas).grid(
+    column=2, row=1, columnspan=2
+)
+ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(
+    column=4, row=1, sticky=W
+)
+
+# Select registration JSON
+ttk.Label(mainframe, text="Select registration JSON:", width=25).grid(
+    column=1, row=2, sticky=W
+)
+ttk.Button(mainframe, width=16, text="Browse...", command=open_registration_json).grid(
+    column=2, row=2, sticky=W
+)
+Text(mainframe, height=1, width=40).grid(column=3, row=2, sticky=W)
+ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(
+    column=4, row=2, sticky=W
+)
+
+# Select segmentation folder
+ttk.Label(mainframe, text="Select segmentation folder:", width=25).grid(
+    column=1, row=3, sticky=W
+)
+ttk.Button(mainframe, width=16, text="Browse...", command=open_segmentation_dir).grid(
+    column=2, row=3, sticky=W
+)
+Text(mainframe, height=1, width=40).grid(column=3, row=3, sticky=W)
+ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(
+    column=4, row=3, sticky=W
+)
+
+# Select object colour
+ttk.Label(mainframe, text="Select object colour:", width=25).grid(
+    column=1, row=4, sticky=W
+)
+ttk.Button(mainframe, width=16, text="Colour", command=choose_colour).grid(
+    column=2, row=4, sticky=W
+)
+Text(mainframe, height=1, width=40).grid(column=3, row=4, sticky=W)
+ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(
+    column=4, row=4, sticky=W
+)
+
+# Select output directory
+ttk.Label(mainframe, text="Select output directory:", width=25).grid(
+    column=1, row=5, sticky=W
+)
+ttk.Button(mainframe, width=16, text="Browse...", command=select_output_dir).grid(
+    column=2, row=5, sticky=W
+)
+Text(mainframe, height=1, width=40).grid(column=3, row=5, sticky=W)
+ttk.Button(mainframe, text="Help", width=8, command="buttonpressed").grid(
+    column=4, row=5, sticky=W
+)
+
+# Start analysis
 ttk.Label(mainframe, text="Start analysis:", width=25).grid(column=1, row=6, sticky=W)
-ttk.Button(mainframe, width = 52, text="Run", command="buttonpressed").grid(column= 3, row=6)
-ttk.Button(mainframe, text="Docs", width=8, command="buttonpressed").grid(column=4, row=6, sticky=W)
+ttk.Button(mainframe, width=52, text="Run", command="buttonpressed").grid(
+    column=3, row=6
+)
+ttk.Button(mainframe, text="Docs", width=8, command="buttonpressed").grid(
+    column=4, row=6, sticky=W
+)
 
 # sunken frame around mainframe
 """
@@ -148,6 +193,6 @@ mainframe['borderwidth'] = 2
 mainframe['relief'] = 'sunken'
 """
 
-#button.configure()
+# button.configure()
 
 root.mainloop()

scripts/Tiling_script.py

@@ -2,7 +2,10 @@ import os
 import sys
 import numpy as np
 import tifffile as tiff
-path_to_file = r"/home/harryc/Downloads/mouse-s23/ext-d000009_PVMouse_81265_Samp1__s023.tif"
+
+path_to_file = (
+    r"/home/harryc/Downloads/mouse-s23/ext-d000009_PVMouse_81265_Samp1__s023.tif"
+)
 image_outdir = path_to_file.split(".")[0].split("/")[-1]
 if not os.path.exists(image_outdir):
     os.makedirs(image_outdir)
@@ -10,12 +13,12 @@ if not os.path.exists(image_outdir):
 img = tiff.imread(path_to_file)
 # Get the shape of the image
 shape = img.shape
-#Get the chunk size
+# Get the chunk size
 chunk_size = 512
-#invert the image if neccessary
+# invert the image if neccessary
 img = np.invert(img)
-#crop the image and save each chunk
+# crop the image and save each chunk
 for i in range(0, shape[0], chunk_size):
     for j in range(0, shape[1], chunk_size):
-        chunk = img[i:i+chunk_size, j:j+chunk_size]
-        tiff.imsave("{}/chunk_{}_{}.tif".format(image_outdir,i, j), chunk)
+        chunk = img[i : i + chunk_size, j : j + chunk_size]
+        tiff.imsave("{}/chunk_{}_{}.tif".format(image_outdir, i, j), chunk)

scripts/reformat_label_files.py

@@ -150,4 +150,4 @@ reformat_WHS_label(
     "../annotation_volumes/WHS_Atlas_Rat_Brain_v2.label",
     "../annotation_volumes/WHS_v2_colours.csv",
 )
-reformat_WHS_label("Kim_Unified_Mouse.label","Kim_Unified_Mouse_colours.csv")
\ No newline at end of file
+reformat_WHS_label("Kim_Unified_Mouse.label", "Kim_Unified_Mouse_colours.csv")

scripts/waln_to_json.py

@@ -2,45 +2,45 @@ import json
 import re
 import os
 
-'''
+"""
 Sharon Yates, 04.04.24.
 This is a script for converting WALN and WWRP files from WebAlign and WebWarp to VisuAlign compatible JSON files.
 To be used for testing purposes. 
-'''
+"""
+
 
 def waln_to_json(filename):
     with open(filename) as f:
         vafile = json.load(f)
     if filename.endswith(".waln") or filename.endswith("wwrp"):
-        slices = vafile["sections"] # define slices as "section" in waln
-        vafile["slices"] = slices 
-        
+        slices = vafile["sections"]  # define slices as "section" in waln
+        vafile["slices"] = slices
+
         for slice in slices:
             if "filename" in slice:
-                base_name = os.path.basename(slice["filename"]).split('.')[0]
-                new_filename = base_name + '.png'
+                base_name = os.path.basename(slice["filename"]).split(".")[0]
+                new_filename = base_name + ".png"
                 slice["filename"] = new_filename
             slice["nr"] = int(re.search(r"_s(\d+)", slice["filename"]).group(1))
             if "ouv" in slice:
-                slice["anchoring"] = slice["ouv"]        
+                slice["anchoring"] = slice["ouv"]
 
         name = os.path.basename(filename)
         va_compat_file = {
-            "name": name.replace(".waln",".json"),
-            "target": vafile["atlas"] + '.cutlas',
+            "name": name.replace(".waln", ".json"),
+            "target": vafile["atlas"] + ".cutlas",
             "target-resolution": [456, 528, 320],
-            "slices": slices
+            "slices": slices,
         }
         # save with .json extension need to see if i can remove this
         with open(
             filename.replace(".waln", ".json").replace(".wwrp", ".json"), "w"
         ) as f:
-            #json.dump(va_compat_file, f, indent=4) 
+            # json.dump(va_compat_file, f, indent=4)
             json.dump(va_compat_file, f, indent=4)
-            
+
     else:
         pass
-    
-waln_to_json("PyNutil_test.waln")    
-    
 
+
+waln_to_json("PyNutil_test.waln")

setup.py

 from setuptools import setup, find_packages
 from pathlib import Path
+
 this_directory = Path(__file__).parent
 long_description = (this_directory / "README.md").read_text()
 
 setup(
     name="PyNutil",
-    version='0.1.1',
+    version="0.1.1",
     packages=find_packages(),
-    license='MIT',
-    description='a package to translate data between common coordinate templates',
+    license="MIT",
+    description="a package to translate data between common coordinate templates",
     long_description=long_description,
-    long_description_content_type='text/markdown',
+    long_description_content_type="text/markdown",
     install_requires=[
-        'numpy',
-        'brainglobe-atlasapi',
-        'pandas',
-        'requests',
-        'pynrrd',
-        'xmltodict',
-        'opencv-python',
-        'scikit-image'
-    ]
+        "numpy",
+        "brainglobe-atlasapi",
+        "pandas",
+        "requests",
+        "pynrrd",
+        "xmltodict",
+        "opencv-python",
+        "scikit-image",
+    ],
 )

tests/README.md

+to run the tests run 
+```bash
+python -m unittest discover -s tests -v
+```
+from the root of the repository
\ No newline at end of file