Playground

src/deep_neurographs/swc_utils.py

@@ -46,7 +46,10 @@ def process_gsc_zip(bucket, zip_path, min_size=0):
         for thread in as_completed(threads):
             swc_id, result = thread.result()
             if len(result["id"]) > min_size:
-                swc_dicts[swc_id] = result
+                try:
+                    swc_dicts[swc_id] = result
+                except Exception as err:
+                    print(f"{swc_id} - {err}=, {type(err)}=")
     return swc_dicts
 
 
@@ -292,7 +295,6 @@ def write_graph(path, graph, color=None):
         entry, reindex = make_entry(graph, j, reindex[i], r, reindex)
         entry_list.append(entry)
     write_list(path, entry_list)
-    print("finished")
 
 
 def set_radius(graph, i):
@@ -301,6 +303,7 @@ def set_radius(graph, i):
     except:
         return 2
 
+
 def make_entry(graph, i, parent, r, reindex):
     """
     Makes an entry to be written in an swc file.

src/deep_neurographs/utils.py

@@ -429,6 +429,26 @@ def write_txt(path, contents):
     f.close()
 
 
+# --- coordinate conversions ---
+def img_to_patch(xyz, patch_centroid, patch_dims):
+    half_patch_dims = [patch_dims[i] // 2 for i in range(3)]
+    patch_coord = xyz - patch_centroid + half_patch_dims
+    return tuple(patch_coord.astype(int))
+
+
+def patch_to_img(xyz, patch_centroid, patch_dims):
+    half_patch_dims = [patch_dims[i] // 2 for i in range(3)]
+    return np.round(xyz + patch_centroid - half_patch_dims).astype(int)
+
+
+def to_world(xyz, shift=[0, 0, 0]):
+    return tuple([xyz[i] * ANISOTROPY[i] - shift[i] for i in range(3)])
+
+
+def to_img(xyz):
+    return (xyz / ANISOTROPY).astype(int)
+
+
 # --- math utils ---
 def get_avg_std(data, weights=None):
     avg = np.average(data, weights=weights)