some refactoring

slider/chart_reg.py

@@ -130,15 +130,15 @@ def register_chart_to_slide(chart, slide, slide_res, outdir, boundary_key=None,
 
     # initial scaling based on boundng boxes
 
-    init = init_scale(img, slide_res, edge_crds)
+    init_xfm = init_scale(img, slide_res, edge_crds)
 
-    print(init)
+    print(init_xfm)
     print(
-        f"Rotation: {init.rotation}, Translation: {init.translation}, Scale: {init.scale}"
+        f"Rotation: {init_xfm.rotation}, Translation: {init_xfm.translation}, Scale: {init_xfm.scale}"
     )
 
     # calculate normal line to boundary points
-    xfm_edge_coords = apply_xfm(init, edge_crds)
+    xfm_edge_coords = apply_xfm(init_xfm, edge_crds)
     init_nrmls = normal(xfm_edge_coords)
 
     # refine edge_coords (to image)
@@ -147,20 +147,20 @@ def register_chart_to_slide(chart, slide, slide_res, outdir, boundary_key=None,
     )
 
     # estimate opimised affine transform
-    opt = transform.SimilarityTransform()
-    opt.estimate(edge_crds[exclude_mask, :], refined_edge_coords[exclude_mask, :])
-    print(opt)
+    opt_xfm = transform.SimilarityTransform()
+    opt_xfm.estimate(edge_crds[exclude_mask, :], refined_edge_coords[exclude_mask, :])
+    print(opt_xfm)
     print(
-        f"Rotation: {opt.rotation}, Translation: {opt.translation}, Scale: {opt.scale}"
+        f"Rotation: {opt_xfm.rotation}, Translation: {opt_xfm.translation}, Scale: {opt_xfm.scale}"
     )
 
     # # save opt transform
-    # np.savetxt(f"{out}/chart-to-image.xfm", opt.params)
+    np.savetxt(f"{outdir}/chart-to-image.xfm", opt_xfm.params)
 
     # apply opt-xfm to contours and cells and save
 
     contour_xfm = [
-        (contour.name, apply_xfm(opt, contour.points[:, :2] * [1, -1]).tolist(), contour.closed) for contour in chart.contours
+        (contour.name, apply_xfm(opt_xfm, contour.points[:, :2] * [1, -1]).tolist(), contour.closed) for contour in chart.contours
     ]
 
     if do_plots:
@@ -202,7 +202,7 @@ def register_chart_to_slide(chart, slide, slide_res, outdir, boundary_key=None,
 
     if chart.n_cells > 0:
         cells = np.concatenate([cell.point[:2][np.newaxis, :] for cell in chart.cells]) * [1, -1]
-        cells_xfm = apply_xfm(init, cells )
+        cells_xfm = apply_xfm(init_xfm, cells )
         with open(f"{outdir}/cells.json", "w") as fp:
             json.dump(cells_xfm.tolist(), fp, indent=4)
 
@@ -296,15 +296,9 @@ def refine_edge_coord(img, img_res, edge_coords, normals, do_plots=True):
 
     
     line_int = brainmask[line_y, line_x]
-    # line_int = img[line_y, line_x]
-
-    
 
     # exlude constant rows
     constant_idx = np.all(line_int == line_int[:, 0][:, np.newaxis], axis=1)
-    # line_int = line_int[~constant_idx, :]
-
-    # print(line_int)
 
     min_idx = np.argmax(np.abs(np.diff(line_int, axis=-1)), axis=-1)
 
@@ -316,12 +310,6 @@ def refine_edge_coord(img, img_res, edge_coords, normals, do_plots=True):
         axis=-1,
     )
 
-    print(constant_idx.shape)
-    print(refined_edge_coords.shape)
-    # refined_edge_coords = refined_edge_coords[~constant_idx, :]
-    print(refined_edge_coords.shape)
-
-
     # TODO: plot edge_coords + refined_edge_coords
     if do_plots:
         fig, ax = plt.subplots(figsize=(20, 30))

slider/external/neurolucida.py

@@ -238,7 +238,7 @@ def parse_contour(c0):
 
     return c0_dict
 
-def parse_cell(cell):
+def parse_asterisk(cell):
     '''Convert cell (asterisk) section into a dictionary'''
 
     cell_dict = {}
@@ -257,18 +257,18 @@ def parse_cell(cell):
 
 def to_data(sections):
     # convert sections to dicts
-    cells    = []
-    contour = []
+    asterisks    = []
+    contours = []
     
     for section in sections:
         if section[0] == 'Asterisk':  # Cell
-            cells.append(parse_cell(section))           
+            asterisks.append(parse_asterisk(section))           
         else:
-            contour.append(parse_contour(section))
+            contours.append(parse_contour(section))
 
-    if len(cells)>0: cells = np.asarray(cells)
+    if len(asterisks)>0: asterisks = np.asarray(asterisks)
 
-    return contour, cells
+    return contours, asterisks
         
 
 def read(file):
@@ -277,7 +277,7 @@ def read(file):
 
     with open(file, encoding='utf-8', errors='replace') as fd:
         sections = _parse_sections(fd)
-    contour, cells = to_data(sections)
-    return contour, cells
+    contour, asterisk = to_data(sections)
+    return contour, asterisk