make point writing and array to atlas abilities more portable to other projects

PyNutil/io/atlas_loader.py

@@ -3,6 +3,25 @@ import pandas as pd
 import numpy as np
 import nrrd
 
+def load_atlas_labels(atlas=None, atlas_name=None):
+    if atlas_name:
+        atlas = brainglobe_atlasapi.BrainGlobeAtlas(atlas_name=atlas_name)
+    if not atlas_name and not atlas:
+        raise Exception("Either atlas or atlas name must be specified")
+    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)
+    return atlas_labels
 
 def load_atlas_data(atlas_name):
     """
@@ -23,20 +42,7 @@ def load_atlas_data(atlas_name):
         A dataframe containing atlas labels and RGB information.
     """
     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_labels = pd.DataFrame(atlas_structures)
+    atlas_labels = load_atlas_labels(atlas)
     atlas_volume = process_atlas_volume(atlas.annotation)
     hemi_map = process_atlas_volume(atlas.hemispheres)
     print("atlas labels loaded ✅")

PyNutil/io/file_operations.py

 import os
 import json
-from .read_and_write import write_points_to_meshview
+from .read_and_write import write_hemi_points_to_meshview
 
 
 def save_analysis_output(
@@ -212,14 +212,14 @@ def _save_per_section_meshview(
     output_folder,
     prepend,
 ):
-    write_points_to_meshview(
+    write_hemi_points_to_meshview(
         pixel_points[prev_pl : pl + prev_pl],
         labeled_points[prev_pl : pl + prev_pl],
         points_hemi_labels[prev_pl : pl + prev_pl],
         f"{output_folder}/per_section_meshview/{prepend}{split_fn}_pixels.json",
         atlas_labels,
     )
-    write_points_to_meshview(
+    write_hemi_points_to_meshview(
         centroids[prev_cl : cl + prev_cl],
         labeled_points_centroids[prev_cl : cl + prev_cl],
         centroids_hemi_labels[prev_cl : cl + prev_cl],
@@ -239,14 +239,14 @@ def _save_whole_series_meshview(
     output_folder,
     prepend,
 ):
-    write_points_to_meshview(
+    write_hemi_points_to_meshview(
         pixel_points,
         labeled_points,
         points_hemi_labels,
         f"{output_folder}/whole_series_meshview/{prepend}pixels_meshview.json",
         atlas_labels,
     )
-    write_points_to_meshview(
+    write_hemi_points_to_meshview(
         centroids,
         labeled_points_centroids,
         centroids_hemi_labels,

PyNutil/io/read_and_write.py

@@ -9,7 +9,7 @@ import numpy as np
 import struct
 import cv2
 from .reconstruct_dzi import reconstruct_dzi
-
+from .atlas_loader import load_atlas_labels
 
 def open_custom_region_file(path):
     """
@@ -283,7 +283,7 @@ def write_points(points_dict, filename, info_file):
 
 # related to read and write: write_points_to_meshview
 # this function combines create_region_dict and write_points functions
-def write_points_to_meshview(points, point_names, hemi_label, filename, info_file):
+def write_hemi_points_to_meshview(points, point_names, hemi_label, filename, info_file):
     """
     Combines point data and region information into MeshView JSON files.
 
@@ -307,16 +307,32 @@ def write_points_to_meshview(points, point_names, hemi_label, filename, info_fil
         split_fn_left = filename.split("/")
         split_fn_left[-1] = "left_hemisphere_" + split_fn_left[-1]
         outname_left = os.sep.join(split_fn_left)
-        left_region_dict = create_region_dict(
-            points[hemi_label == 1], point_names[hemi_label == 1]
-        )
-        write_points(left_region_dict, outname_left, info_file)
+        write_points_to_meshview(points[hemi_label == 1], point_names[hemi_label == 1], outname_left, info_file)
         split_fn_right = filename.split("/")
         split_fn_right[-1] = "right_hemisphere_" + split_fn_right[-1]
         outname_right = os.sep.join(split_fn_right)
-        right_region_dict = create_region_dict(
-            points[hemi_label == 2], point_names[hemi_label == 2]
-        )
-        write_points(right_region_dict, outname_right, info_file)
-    region_dict = create_region_dict(points, point_names)
+        write_points_to_meshview(points[hemi_label == 2], point_names[hemi_label == 2], outname_right, info_file)
+    write_points_to_meshview(points, point_names, filename, info_file)
+
+# related to read and write: write_points_to_meshview
+# this function combines create_region_dict and write_points functions
+def write_points_to_meshview(points, point_ids, filename, info_file):
+    """
+    Combines point data and region information into MeshView JSON files.
+
+    Parameters
+    ----------
+    points : numpy.ndarray
+        2D array containing [N, 3] point coordinates.
+    point_ids : numpy.ndarray
+        1D array of region labels corresponding to each point.
+    filename : str
+        Base path for output JSON. Separate hemispheres use prefixed filenames.
+    info_file : pandas.DataFrame or string
+        A table with region IDs, names, and color data (r, g, b) for each region.
+        If string, this should correspond to the relevant brainglobe atlas
+    """
+    if isinstance(info_file, str):
+        info_file = load_atlas_labels(info_file)
+    region_dict = create_region_dict(points, point_ids)
     write_points(region_dict, filename, info_file)

PyNutil/processing/transformations.py

@@ -46,6 +46,25 @@ def transform_to_atlas_space(anchoring, y, x, reg_height, reg_width):
     o = np.reshape(o, (3, 1))
     return (o + xyz_u + xyz_v).T
 
+def image_to_atlas_space(image, anchoring):
+    """
+    Transforms to atlas space an image using the QuickNII anchoring vector.
+
+
+    Args:
+        image (ndarray): An Image which you would like to apply the anchoring vector to
+        anchoring (list): Anchoring vector.
+
+    Returns:
+        ndarray: Transformed coordinates for every pixel in the image.
+    """
+    width = image.shape[1]
+    height = image.shape[0]
+    x = np.arange(width)
+    y = np.arange(height)
+    x_coords, y_coords = np.meshgrid(x, y)
+    coordinates = transform_to_atlas_space(anchoring, y_coords.flatten(), x_coords.flatten(), height, width)
+    return coordinates
 
 def get_transformed_coordinates(
     non_linear,