PortPy Version 1.2.0

1. Add beamlet dose prediction module to portpy.ai
2. create example notebook for it
3. Add scorecard to evaluation.py
4. Update vmat scp to latest version with bug fixes.
5. Make dose prediction module site independent

Minor changes.
Enhance project structure and functionality:
- Update .gitignore to include new data directories.
- Modify __init__.py to import scorecard functions.
- Adjust test assertions for expected solution values.
- Refine optimization.py to use np.inf for max constraints.
- Update pred_dose_to_original_portpy.py for improved plan initialization.
- Revise requirements.txt for updated package versions.
- Enhance single_dataset.py and dosepred3d_dataset.py to handle additional data fields.
- Add new optimization parameters in optimization_params_Prostate_5Gy_5Fx_vmat.json.

Author: gourav3017

portpy/photon/structures.py

@@ -194,15 +194,10 @@ def expand(self, struct_name: str = None, margin_mm: float = None, new_struct_na
 
         # getting kernel size for expansion or shrinking
         if margin_mm > 0:
-            # num_voxels = np.round(margin_mm / np.asarray(self._ct_voxel_resolution_xyz_mm)).astype(int)
-            res_xyz = np.asarray(self._ct_voxel_resolution_xyz_mm)
-            res_zyx = res_xyz[[2, 1, 0]]
-            num_voxels = np.round(margin_mm / res_zyx).astype(int)
-            num_voxels = np.maximum(num_voxels, 1)
+            num_voxels = np.maximum(np.round(margin_mm / np.asarray(self._ct_voxel_resolution_xyz_mm)).astype(int), 1)
             kernel = ndimage.generate_binary_structure(rank=3, connectivity=2)  # ball kernel
             # creating different iterations along z and xy directions
-            ratio = num_voxels[0] / num_voxels[2] if num_voxels[2] > 0 else 1
-            num_iterations = max(1, int(np.round(ratio)))
+            num_iterations = max(1, int(num_voxels[0] / num_voxels[2]))
             iterations_in_one_step = max(1, int(np.round(num_voxels[0] / num_iterations)))
             # margin_mask_3d = ndimage.binary_dilation(mask_3d, struct_name=struct).astype(mask_3d.dtype)
             for i in range(num_iterations):
@@ -246,16 +241,10 @@ def shrink(self, struct_name: str = None, margin_mm: float = None, new_struct_na
 
 
         # getting kernel size for expansion or shrinking
-
-        # num_voxels = np.round(margin_mm / np.asarray(self._ct_voxel_resolution_xyz_mm)).astype(int)
-        res_xyz = np.asarray(self._ct_voxel_resolution_xyz_mm)
-        res_zyx = res_xyz[[2, 1, 0]]
-        num_voxels = np.round(margin_mm / res_zyx).astype(int)
-        num_voxels = np.maximum(num_voxels, 1)
+        num_voxels = np.maximum(np.round(margin_mm / np.asarray(self._ct_voxel_resolution_xyz_mm)).astype(int), 1)
         struct = ndimage.generate_binary_structure(rank=3, connectivity=2)  # ball kernel
         # creating different iterations along z and xy directions
-        ratio = num_voxels[0] / num_voxels[2] if num_voxels[2] > 0 else 1
-        num_iterations = max(1, int(np.round(ratio)))
+        num_iterations = max(1, int(num_voxels[0] / num_voxels[2]))
         iterations_in_one_step = max(1, int(np.round(num_voxels[0] / num_iterations)))
         for i in range(num_iterations):
             if i == 0:

tests/test_basic_tutorial.py

@@ -72,7 +72,7 @@ def test_plan_creation(plan_and_solution):
     assert hasattr(plan, "beams")
     assert len(plan.beams.get_all_beam_ids()) > 0
     assert sol is not None
-    assert np.isclose(sol['obj_value'], 84.71, rtol=0.01)
+    assert np.isclose(sol['obj_value'], 54.50, rtol=0.01)
 
 
 def test_visualization_methods(plan_and_solution):