Version 1.0.5 Changes:

1. Update PortPy.AI upgrade with easy to run notebooks
2. Update PortPy visualization.py
3. Update vmat scp dose prediction
4. Add random leaf position initialization feature to VMAT SCP

examples/dose_mimicking.ipynb

@@ -108,7 +108,7 @@
    "outputs": [],
    "source": [
     "# import the predicted dose to PortPy. Point to dose file of the benchmark plan available in PortPy\n",
-    "pred_dose = pp.convert_dose_rt_dicom_to_portpy(my_plan=my_plan, dose_file_name=r'\\\\pisiz3echo\\ECHO\\Research\\Data_newformat\\PortPy\\data\\zip_files\\export_clinic\\rt_dose_echo_imrt.dcm')\n",
+    "pred_dose = pp.convert_dose_rt_dicom_to_portpy(my_plan=my_plan, dose_file_name=r'\\\\PortPy\\data\\zip_files\\export_clinic\\rt_dose_echo_imrt.dcm')\n",
     "pred_dose_1d = inf_matrix.dose_3d_to_1d(dose_3d=pred_dose)"
    ]
   },
@@ -281,8 +281,8 @@
    "outputs": [],
    "source": [
     "# Specify the location and name of the DICOM RT Dose file\n",
-    "dose_file_name = r'\\\\pisiz3echo\\ECHO\\Research\\Data_newformat\\PortPy\\data\\zip_files\\Test_Export_Fluence_Patient_4\\RD.1.2.246.352.71.7.565238251846.2574850.20241014203936.dcm'\n",
-    "dose_file_name = r'\\\\pisiz3echo\\ECHO\\Research\\Data_newformat\\PortPy\\data\\zip_files\\export_clinic\\PredFluRMR\\RD.1.2.246.352.71.7.565238251846.2716655.20241105165313.dcm'\n",
+    "\n",
+    "dose_file_name = r'PortPy\\data\\zip_files\\export_clinic\\PredFluRMR\\RD.dcm'\n",
     "# Convert the DICOM dose into PortPy format\n",
     "ecl_dose_3d = pp.convert_dose_rt_dicom_to_portpy(my_plan=my_plan, dose_file_name=dose_file_name)\n",
     "ecl_dose_1d = inf_matrix.dose_3d_to_1d(dose_3d=ecl_dose_3d)"