Merge pull request #35 from OmooLab/feature/dev

fix: macos-arm64 cannot install

.github/workflows/build-addon.yml

@@ -22,7 +22,7 @@ jobs:
   #       id: draft_release
   #       uses: cardinalby/git-get-release-action@1.2.4
   #       with:
-  #         releaseName: Draft
+  #         releaseName: Upload
   #       env:
   #         GITHUB_TOKEN: ${{ github.token }}
 
@@ -50,17 +50,26 @@ jobs:
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
-  upload_blender_addon:
-    name: Upload Blender Add-on
+  build_blender_add-on:
+    name: Build Blender Extension
     needs: draft_release
     runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        platform: ["windows-x64", "linux-x64", "macos-arm64", "macos-x64"]
     steps:
       - name: Checkout Code
         uses: actions/checkout@v4
         with:
-          lfs: 'true'
-      - name: Zip Add-on
+          lfs: "true"
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: 3.11
+      - name: Build Add-on
         run: |
+          pip install tomlkit
+          python build.py ${{ matrix.platform }}
           zip -r package.zip bioxelnodes
       - name: Upload Release Asset
         id: upload-release-asset
@@ -70,5 +79,5 @@ jobs:
         with:
           upload_url: ${{ needs.draft_release.outputs.upload_url }} # This pulls from the CREATE RELEASE step above, referencing it's ID to get its outputs object, which include a `upload_url`. See this blog post for more info: https://jasonet.co/posts/new-features-of-github-actions/#passing-data-to-future-steps
           asset_path: ./package.zip
-          asset_name: BioxelNodes_${{ needs.draft_release.outputs.version }}.zip
+          asset_name: BioxelNodes_${{ needs.draft_release.outputs.version }}_${{ matrix.platform }}.zip
           asset_content_type: application/zip

.gitignore

@@ -131,4 +131,6 @@ blendcache_*
 
 *.ipynb
 
-.secrets
+.secrets
+
+!scipy_ndimage/*/**

.prettierrc

@@ -0,0 +1,11 @@
+{
+  "tabWidth": 2,
+  "overrides": [
+    {
+      "files": "*.md",
+      "options": {
+        "tabWidth": 4
+      }
+    }
+  ]
+}

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 OmooLab
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,3 +1,76 @@
-# BioxelNodes
-BioxelNodes is a blender add-on for better volume data visualization with cycles.
+[中文文档](https://uj6xfhbzp0.feishu.cn/wiki/Qx3VwHuNPimeI8kr6nDcvl1DnHf?from=from_copylink)
 
+# Bioxel Nodes
+
+[![For Blender](https://img.shields.io/badge/Blender-orange?style=for-the-badge&logo=blender&logoColor=white&color=black)](https://blender.org/)
+![GitHub License](https://img.shields.io/github/license/OmooLab/BioxelNodes?style=for-the-badge&labelColor=black)
+![GitHub Release](https://img.shields.io/github/v/release/OmooLab/BioxelNodes?style=for-the-badge&labelColor=black)
+![GitHub Repo stars](https://img.shields.io/github/stars/OmooLab/BioxelNodes?style=for-the-badge&labelColor=black)
+
+[![Discord](https://img.shields.io/discord/1265129134397587457?style=for-the-badge&logo=discord&label=Discord&labelColor=white&color=black)](https://discord.gg/pYkNyq2TjE)
+
+Bioxel Nodes is a Blender addon for scientific volumetric data visualization. It using Blender's powerful **Geometry Nodes** and **Cycles** to process and render volumetric data.
+
+![cover](https://omoolab.github.io/BioxelNodes/latest/assets/cover.png)
+
+-   Realistic rendering result, also support EEVEE NEXT.
+-   Support multiple formats.
+-   Support 4D volumetric data.
+-   All kinds of cutters.
+-   Simple and powerful nodes.
+-   Based on blender natively, can work without addon.
+
+**Read the [getting started](https://omoolab.github.io/BioxelNodes/latest/installation) to begin your journey into visualizing volumetric data!**
+
+Welcome to our [discord server](https://discord.gg/pYkNyq2TjE), if you have any problems with this add-on.
+
+## Support Multiple Formats
+
+| Format | EXT                                      | Test    |
+| ------ | ---------------------------------------- | ------- |
+| DICOM  | .dcm, .DCM, .DICOM, .ima, .IMA           | ✅ pass |
+| BMP    | .bmp, .BMP                               | ✅ pass |
+| JPEG   | .jpg, .JPG, .jpeg, .JPEG                 | ✅ pass |
+| PNG    | .png, .PNG                               | ✅ pass |
+| TIFF   | .tif, .TIF, .tiff, .TIFF                 | ✅ pass |
+| Nifti  | .nia, .nii, .nii.gz, .hdr, .img, .img.gz | ✅ pass |
+| Nrrd   | .nrrd, .nhdr                             | ✅ pass |
+| HDF5   | .hdf, .h4, .hdf4, .he2, .h5, .hdf5, .he5 | ✅ pass |
+| OME    | .ome.tiff, .ome.tif                      | ✅ pass |
+| MRC    | .mrc, .mrc.gz, .map, .map.gz             | ✅ pass |
+
+## Support 4D volumetric data
+
+![4d](https://omoolab.github.io/BioxelNodes/latest/assets/4d-time.gif)
+
+🥰 4D volumetric data can also be imported into Blender.
+
+## Support EEVEE NEXT
+
+![eevee](https://omoolab.github.io/BioxelNodes/latest/assets/eevee.gif)
+
+👍 EEVEE NEXT is absolutely AWESOME! Bioxel Nodes is fully support EEVEE NEXT now! However, there are some limitations:
+
+1. Only one cutter supported.
+2. EEVEE result is not that great as Cycles does.
+
+## Known Limitations
+
+-   Only works with Cycles CPU , Cycles GPU (OptiX), EEVEE
+-   Section surface cannot be generated when convert to mesh (will be supported soon)
+
+## Compatible to Newer Version
+
+**v0.3.x is not compatible to v0.2.x, Updating this addon may break old files. Read the following carefully before upgradation**
+
+Before upgradation, you need to ask yourself whether this project file will be modified again or not, if it's an archived project file, I would recommend that you run **Bioxel Nodes > Save Staged Data** to make the addon nodes permanent. In this way, there will be no potential problem with the nodes not functioning due to the addon update.
+
+After the addon update, your old project files may not work either, this may be because you had executed **Save Staged Data**. If so, you need to execute **Bioxel Nodes > Relink Nodes to Addon** to relink them to make sure that the addon's new functionality and the addon nodes are synchronized.
+
+Also, the older shaders are not based on OSL, so if you find that you can't render volumes, you need to turn on **Open Shading Language (OSL)** in the Render Settings.
+
+## Roadmap
+
+-   Better multi-format import experience
+-   One-click bake model with texture
+-   AI Segmentation to Generate Labels

bioxelnodes/__init__.py

@@ -1,34 +1,19 @@
-from .nodes import custom_nodes
-from . import auto_load
-from . import menu
-
 import bpy
 
+from . import auto_load
+from . import menus
 
-bl_info = {
-    "name": "BiovelNodes",
-    "author": "Ma Nan",
-    "description": "",
-    "blender": (4, 0, 0),
-    "version": (0, 1, 0),
-    "location": "File -> Import",
-    "warning": "",
-    "category": "Import-Export"
-}
 
 auto_load.init()
 
 
 def register():
     auto_load.register()
-    custom_nodes.register()
-    menu.create_menu()
+    bpy.types.WindowManager.bioxelnodes_progress_factor = bpy.props.FloatProperty()
+    bpy.types.WindowManager.bioxelnodes_progress_text = bpy.props.StringProperty()
+    menus.add()
 
 
 def unregister():
-    try:
-        menu.remove_menu()
-        custom_nodes.unregister()
-        auto_load.unregister()
-    except RuntimeError:
-        pass
+    menus.remove()
+    auto_load.unregister()

bioxelnodes/auto_load.py

@@ -16,6 +16,7 @@ blender_version = bpy.app.version
 modules = None
 ordered_classes = None
 
+
 def init():
     global modules
     global ordered_classes
@@ -23,6 +24,7 @@ def init():
     modules = get_all_submodules(Path(__file__).parent)
     ordered_classes = get_ordered_classes_to_register(modules)
 
+
 def register():
     for cls in ordered_classes:
         bpy.utils.register_class(cls)
@@ -33,27 +35,36 @@ def register():
         if hasattr(module, "register"):
             module.register()
 
+
 def unregister():
     for cls in reversed(ordered_classes):
-        bpy.utils.unregister_class(cls)
+        try:
+            bpy.utils.unregister_class(cls)
+        except Exception as e:
+            print(f"Fail to unregister {cls}, skiped")
 
     for module in modules:
-        if module.__name__ == __name__:
-            continue
-        if hasattr(module, "unregister"):
-            module.unregister()
+        try:
+            if module.__name__ == __name__:
+                continue
+            if hasattr(module, "unregister"):
+                module.unregister()
+        except Exception as e:
+            print(f"Fail to unregister {module}, skiped")
 
 
 # Import modules
 #################################################
 
 def get_all_submodules(directory):
-    return list(iter_submodules(directory, directory.name))
+    return list(iter_submodules(directory, __package__))
+
 
 def iter_submodules(path, package_name):
     for name in sorted(iter_submodule_names(path)):
         yield importlib.import_module("." + name, package_name)
 
+
 def iter_submodule_names(path, root=""):
     for _, module_name, is_package in pkgutil.iter_modules([str(path)]):
         if is_package:
@@ -70,19 +81,24 @@ def iter_submodule_names(path, root=""):
 def get_ordered_classes_to_register(modules):
     return toposort(get_register_deps_dict(modules))
 
+
 def get_register_deps_dict(modules):
     my_classes = set(iter_my_classes(modules))
-    my_classes_by_idname = {cls.bl_idname : cls for cls in my_classes if hasattr(cls, "bl_idname")}
+    my_classes_by_idname = {
+        cls.bl_idname: cls for cls in my_classes if hasattr(cls, "bl_idname")}
 
     deps_dict = {}
     for cls in my_classes:
-        deps_dict[cls] = set(iter_my_register_deps(cls, my_classes, my_classes_by_idname))
+        deps_dict[cls] = set(iter_my_register_deps(
+            cls, my_classes, my_classes_by_idname))
     return deps_dict
 
+
 def iter_my_register_deps(cls, my_classes, my_classes_by_idname):
     yield from iter_my_deps_from_annotations(cls, my_classes)
     yield from iter_my_deps_from_parent_id(cls, my_classes_by_idname)
 
+
 def iter_my_deps_from_annotations(cls, my_classes):
     for value in typing.get_type_hints(cls, {}, {}).values():
         dependency = get_dependency_from_annotation(value)
@@ -90,6 +106,7 @@ def iter_my_deps_from_annotations(cls, my_classes):
             if dependency in my_classes:
                 yield dependency
 
+
 def get_dependency_from_annotation(value):
     if blender_version >= (2, 93):
         if isinstance(value, bpy.props._PropertyDeferred):
@@ -100,6 +117,7 @@ def get_dependency_from_annotation(value):
                 return value[1]["type"]
     return None
 
+
 def iter_my_deps_from_parent_id(cls, my_classes_by_idname):
     if bpy.types.Panel in cls.__bases__:
         parent_idname = getattr(cls, "bl_parent_id", None)
@@ -108,6 +126,7 @@ def iter_my_deps_from_parent_id(cls, my_classes_by_idname):
             if parent_cls is not None:
                 yield parent_cls
 
+
 def iter_my_classes(modules):
     base_types = get_register_base_types()
     for cls in get_classes_in_modules(modules):
@@ -115,6 +134,7 @@ def iter_my_classes(modules):
             if not getattr(cls, "is_registered", False):
                 yield cls
 
+
 def get_classes_in_modules(modules):
     classes = set()
     for module in modules:
@@ -122,11 +142,13 @@ def get_classes_in_modules(modules):
             classes.add(cls)
     return classes
 
+
 def iter_classes_in_module(module):
     for value in module.__dict__.values():
         if inspect.isclass(value):
             yield value
 
+
 def get_register_base_types():
     return set(getattr(bpy.types, name) for name in [
         "Panel", "Operator", "PropertyGroup", "FileHandler",
@@ -134,7 +156,7 @@ def get_register_base_types():
         "Node", "NodeSocket", "NodeTree",
         "UIList", "RenderEngine",
         "Gizmo", "GizmoGroup",
-    ])
+    ] if hasattr(bpy.types, name))
 
 
 # Find order to register to solve dependencies
@@ -151,5 +173,6 @@ def toposort(deps_dict):
                 sorted_values.add(value)
             else:
                 unsorted.append(value)
-        deps_dict = {value : deps_dict[value] - sorted_values for value in unsorted}
+        deps_dict = {value: deps_dict[value] -
+                     sorted_values for value in unsorted}
     return sorted_list

bioxelnodes/bioxel/container.py

@@ -0,0 +1,9 @@
+from .layer import Layer
+
+
+class Container():
+    def __init__(self,
+                 name,
+                 layers: list[Layer] = []) -> None:
+        self.name = name
+        self.layers = layers

bioxelnodes/bioxel/io.py

@@ -0,0 +1,43 @@
+from pathlib import Path
+import uuid
+
+
+# 3rd-party
+import h5py
+
+from .container import Container
+from .layer import Layer
+
+
+def load_container(load_file: str):
+    load_path = Path(load_file).resolve()
+    with h5py.File(load_path, 'r') as file:
+        layers = []
+        for key, layer_dset in file['layers'].items():
+            layers.append(Layer(data=layer_dset[:],
+                                name=layer_dset.attrs['name'],
+                                kind=layer_dset.attrs['kind'],
+                                affine=layer_dset.attrs['affine']))
+
+        container = Container(name=file.attrs['name'],
+                              layers=layers)
+
+        return container
+
+
+def save_container(container: Container, save_file: str, overwrite=False):
+    save_path = Path(save_file).resolve()
+    if overwrite:
+        if save_path.is_file():
+            save_path.unlink()
+
+    with h5py.File(save_path, "w") as file:
+        file.attrs['name'] = container.name
+        layer_group = file.create_group("layers")
+        for layer in container.layers:
+            layer_key = uuid.uuid4().hex[:8]
+            layer_dset = layer_group.create_dataset(name=layer_key,
+                                                    data=layer.data)
+            layer_dset.attrs['name'] = layer.name
+            layer_dset.attrs['kind'] = layer.kind
+            layer_dset.attrs['affine'] = layer.affine

bioxelnodes/bioxel/layer.py

@@ -0,0 +1,135 @@
+import copy
+import numpy as np
+
+from . import scipy
+from . import skimage as ski
+
+# 3rd-party
+import transforms3d
+
+# TODO: turn to dataclasses
+
+
+class Layer():
+    def __init__(self,
+                 data: np.ndarray,
+                 name: str,
+                 kind="scalar",
+                 affine=np.identity(4)) -> None:
+        if data.ndim != 5:
+            raise Exception("Data shape order should be TXYZC")
+
+        affine = np.array(affine)
+        if affine.shape != (4, 4):
+            raise Exception("affine shape should be (4,4)")
+
+        self.data = data
+        self.name = name
+        self.kind = kind
+        self.affine = affine
+
+    @property
+    def bioxel_size(self):
+        t, r, z, s = transforms3d.affines.decompose44(self.affine)
+        return z.tolist()
+
+    @property
+    def shape(self):
+        return self.data.shape[1:4]
+
+    @property
+    def dtype(self):
+        return self.data.dtype
+
+    @property
+    def origin(self):
+        t, r, z, s = transforms3d.affines.decompose44(self.affine)
+        return t.tolist()
+
+    @property
+    def euler(self):
+        t, r, z, s = transforms3d.affines.decompose44(self.affine)
+        return list(transforms3d.euler.mat2euler(r))
+
+    @property
+    def min(self):
+        return float(np.min(self.data))
+
+    @property
+    def frame_count(self):
+        return self.data.shape[0]
+
+    @property
+    def channel_count(self):
+        return self.data.shape[-1]
+
+    @property
+    def max(self):
+        return float(np.max(self.data))
+
+    def copy(self):
+        return copy.deepcopy(self)
+
+    def fill(self, value: float, mask: np.ndarray):
+        mask_frames = ()
+        if mask.ndim == 4:
+            if mask.shape[0] != self.frame_count:
+                raise Exception("Mask frame count is not same as ")
+            for f in range(self.frame_count):
+                mask_frame = mask[f, :, :, :]
+                mask_frame = scipy.minimum_filter(
+                    mask_frame.astype(np.float32), size=3)
+                # mask_frame = scipy.median_filter(
+                #     mask_frame.astype(np.float32), size=2)
+                mask_frames += (mask_frame,)
+        elif mask.ndim == 3:
+            for f in range(self.frame_count):
+                mask_frame = mask[:, :, :]
+                mask_frame = scipy.minimum_filter(
+                    mask_frame.astype(np.float32), size=3)
+                # mask_frame = scipy.median_filter(
+                #     mask_frame.astype(np.float32), size=2)
+                mask_frames += (mask_frame,)
+        else:
+            raise Exception("Mask shape order should be TXYZ or XYZ")
+
+        _mask = np.stack(mask_frames)
+        _mask = np.expand_dims(_mask, axis=-1)
+        self.data = _mask * value + (1-_mask) * self.data
+
+    def resize(self, shape:tuple, progress_callback=None):
+        if len(shape) != 3:
+            raise Exception("Shape must be 3 dim")
+
+        data = self.data
+
+        # TXYZC > TXYZ
+        if self.kind in ['label', 'scalar']:
+            data = np.amax(data, -1)
+
+        if self.kind in ['scalar']:
+            dtype = data.dtype
+            data = data.astype(np.float32)
+
+        data_frames = ()
+        for f in range(self.frame_count):
+            if progress_callback:
+                progress_callback(f, self.frame_count)
+
+            frame = ski.resize(data[f, :, :, :],
+                               shape,
+                               preserve_range=True,
+                               anti_aliasing=data.dtype.kind != "b")
+
+            data_frames += (frame,)
+
+        data = np.stack(data_frames)
+
+        if self.kind in ['scalar']:
+            data = data.astype(dtype)
+
+        # TXYZ > TXYZC
+        if self.kind in ['label', 'scalar']:
+            data = np.expand_dims(data, axis=-1)  # expend channel
+
+        self.data = data

bioxelnodes/bioxel/parse.py

@@ -0,0 +1,388 @@
+from pathlib import Path
+import numpy as np
+from .layer import Layer
+
+# 3rd-party
+import SimpleITK as sitk
+from pyometiff import OMETIFFReader
+import mrcfile
+import transforms3d
+
+
+"""
+Convert any volumetric data to 3D numpy array with order TXYZC
+"""
+
+SUPPORT_EXTS = ['', '.dcm', '.DCM', '.DICOM', '.ima', '.IMA',
+                '.bmp', '.BMP',
+                '.PIC', '.pic',
+                '.gipl', '.gipl.gz',
+                '.jpg', '.JPG', '.jpeg', '.JPEG',
+                '.lsm', '.LSM',
+                '.tif', '.TIF', '.tiff', '.TIFF',
+                '.mnc', '.MNC',
+                '.mrc', '.rec',
+                '.mha', '.mhd',
+                '.hdf', '.h4', '.hdf4', '.he2', '.h5', '.hdf5', '.he5',
+                '.nia', '.nii', '.nii.gz', '.hdr', '.img', '.img.gz',
+                '.nrrd', '.nhdr',
+                '.png', '.PNG',
+                '.vtk',
+                '.ome.tiff', '.ome.tif',
+                '.mrc', '.mrc.gz', '.map', '.map.gz']
+
+OME_EXTS = ['.ome.tiff', '.ome.tif',
+            '.tif', '.TIF', '.tiff', '.TIFF']
+
+MRC_EXTS = ['.mrc', '.mrc.gz', '.map', '.map.gz']
+
+DICOM_EXTS = ['', '.dcm', '.DCM', '.DICOM', '.ima', '.IMA']
+
+SEQUENCE_EXTS = ['.bmp', '.BMP',
+                 '.jpg', '.JPG', '.jpeg', '.JPEG',
+                 '.tif', '.TIF', '.tiff', '.TIFF',
+                 '.png', '.PNG']
+
+
+def get_ext(filepath: Path) -> str:
+    if filepath.name.endswith(".nii.gz"):
+        return ".nii.gz"
+    elif filepath.name.endswith(".img.gz"):
+        return ".img.gz"
+    elif filepath.name.endswith(".gipl.gz"):
+        return ".gipl.gz"
+    elif filepath.name.endswith(".ome.tiff"):
+        return ".ome.tiff"
+    elif filepath.name.endswith(".ome.tif"):
+        return ".ome.tif"
+    elif filepath.name.endswith(".mrc.gz"):
+        return ".mrc.gz"
+    elif filepath.name.endswith(".map.gz"):
+        return ".map.gz"
+    else:
+        return filepath.suffix
+
+
+def get_file_name(filepath: Path):
+    ext = get_ext(filepath)
+    return filepath.name.removesuffix(ext).replace(" ", "-")
+
+
+def get_file_index(filepath: Path):
+    name = get_file_name(filepath)
+    digits = ""
+
+    # Iterate through the characters in reverse order
+    started = False
+    for char in name[::-1]:
+        if char.isdigit():
+            started = True
+            # If the character is a digit, add it to the digits string
+            digits += char
+        else:
+            if started:
+                # If a non-digit character is encountered, stop the loop
+                break
+
+    # Reverse the digits string to get the correct order
+    last_number = digits[::-1]
+
+    return int(last_number) if last_number != "" else 0
+
+
+def get_sequence_name(filepath: Path) -> str:
+    name = get_file_name(filepath)
+    index = get_file_index(filepath)
+    return name.removesuffix(str(index))
+
+
+def collect_sequence(filepath: Path):
+    file_dict = {}
+    for f in filepath.parent.iterdir():
+        if f.is_file() \
+                and get_ext(filepath) == get_ext(f) \
+                and get_sequence_name(filepath) == get_sequence_name(f):
+            index = get_file_index(f)
+            file_dict[index] = f
+
+    for key in file_dict.copy().keys():
+        if not file_dict.get(key+1) \
+                and not file_dict.get(key-1):
+            del file_dict[key]
+
+    file_dict = dict(sorted(file_dict.items()))
+    sequence = [str(f) for f in file_dict.values()]
+
+    if len(sequence) == 0:
+        sequence = [str(filepath)]
+
+    return sequence
+
+
+def parse_volumetric_data(data_file: str, series_id="", progress_callback=None) -> Layer:
+    """Parse any volumetric data to numpy with shap (T,X,Y,Z,C)
+
+    Args:
+        data_file (str): file path
+        series_id (str, optional): DICOM series id. Defaults to "".
+
+    Returns:
+        _type_: _description_
+    """
+
+    data_path = Path(data_file).resolve()
+    ext = get_ext(data_path)
+
+    if progress_callback:
+        progress_callback(0, "Reading the Data...")
+
+    is_sequence = False
+    if ext in SEQUENCE_EXTS:
+        sequence = collect_sequence(data_path)
+        if len(sequence) > 1:
+            is_sequence = True
+
+    data = None
+    name = "",
+    description = ""
+    affine = np.identity(4)
+    spacing = (1, 1, 1)
+    origin = (0, 0, 0)
+    direction = (1, 0, 0, 0, 1, 0, 0, 0, 1)
+
+    # Parsing with mrcfile
+    if data is None and ext in MRC_EXTS and not is_sequence:
+        print("Parsing with mrcfile...")
+        # TODO: much to do with mrc
+        with mrcfile.open(data_path, 'r') as mrc:
+            data = mrc.data
+            # mrc.print_header()
+            # print(data.shape)
+            # print(mrc.voxel_size)
+
+            if mrc.is_single_image():
+                data = np.expand_dims(data, axis=0)  # expend frame
+                data = np.expand_dims(data, axis=-1)  # expend Z
+                data = np.expand_dims(data, axis=-1)  # expend channel
+
+            elif mrc.is_image_stack():
+                data = np.expand_dims(data, axis=-1)  # expend Z
+                data = np.expand_dims(data, axis=-1)  # expend channel
+
+            elif mrc.is_volume():
+                data = np.expand_dims(data, axis=0)  # expend frame
+                data = np.expand_dims(data, axis=-1)  # expend channel
+
+            elif mrc.is_volume_stack():
+                data = np.expand_dims(data, axis=-1)  # expend channel
+
+            name = get_file_name(data_path)
+            spacing = (mrc.voxel_size.x,
+                       mrc.voxel_size.y,
+                       mrc.voxel_size.z)
+
+    # Parsing with OMETIFFReader
+    if data is None and ext in OME_EXTS and not is_sequence:
+        print("Parsing with OMETIFFReader...")
+        reader = OMETIFFReader(fpath=data_path)
+        ome_image, metadata, xml_metadata = reader.read()
+
+        # TODO: some old bio-format tiff the header is not the same.
+        if progress_callback:
+            progress_callback(0.5, "Transpose to 'TXYZC'...")
+
+        try:
+            # print(ome_image.shape)
+            # for key in metadata:
+            #     print(f"{key},{metadata[key]}")
+            ome_order = metadata['DimOrder BF Array']
+            if ome_image.ndim == 2:
+                ome_order = ome_order.replace("T", "")\
+                    .replace("C", "").replace("Z", "")
+                bioxel_order = (ome_order.index('X'),
+                                ome_order.index('Y'))
+                data = np.transpose(ome_image, bioxel_order)
+                data = np.expand_dims(data, axis=0)  # expend frame
+                data = np.expand_dims(data, axis=-1)  # expend Z
+                data = np.expand_dims(data, axis=-1)  # expend channel
+
+            elif ome_image.ndim == 3:
+                # -> XYZC
+                ome_order = ome_order.replace("T", "").replace("C", "")
+                bioxel_order = (ome_order.index('X'),
+                                ome_order.index('Y'),
+                                ome_order.index('Z'))
+                data = np.transpose(ome_image, bioxel_order)
+                data = np.expand_dims(data, axis=0)  # expend frame
+                data = np.expand_dims(data, axis=-1)  # expend channel
+            elif ome_image.ndim == 4:
+                # -> XYZC
+                ome_order = ome_order.replace("T", "")
+                bioxel_order = (ome_order.index('X'),
+                                ome_order.index('Y'),
+                                ome_order.index('Z'),
+                                ome_order.index('C'))
+                data = np.transpose(ome_image, bioxel_order)
+                data = np.expand_dims(data, axis=0)  # expend frame
+            elif ome_image.ndim == 5:
+                # -> TXYZC
+                bioxel_order = (ome_order.index('T'),
+                                ome_order.index('X'),
+                                ome_order.index('Y'),
+                                ome_order.index('Z'),
+                                ome_order.index('C'))
+                data = np.transpose(ome_image, bioxel_order)
+
+            try:
+                spacing = (metadata['PhysicalSizeX'],
+                           metadata['PhysicalSizeY'],
+                           metadata['PhysicalSizeZ'])
+            except:
+                ...
+
+            name = get_file_name(data_path)
+        except:
+            ...
+
+    # Parsing with SimpleITK
+    if data is None:
+        print("Parsing with SimpleITK...")
+        if ext in DICOM_EXTS:
+            data_dirpath = data_path.parent
+            reader = sitk.ImageSeriesReader()
+            reader.MetaDataDictionaryArrayUpdateOn()
+            reader.LoadPrivateTagsOn()
+            series_files = reader.GetGDCMSeriesFileNames(
+                str(data_dirpath), series_id)
+            reader.SetFileNames(series_files)
+
+            itk_image = reader.Execute()
+            # for k in reader.GetMetaDataKeys(0):
+            #     v = reader.GetMetaData(0, k)
+            #     print(f'({k}) = = "{v}"')
+
+            def get_meta(key):
+                try:
+                    stirng = reader.GetMetaData(0, key).removesuffix(" ")
+                    if stirng in ["No study description",
+                                  "No series description",
+                                  ""]:
+                        return None
+                    else:
+                        return stirng
+                except:
+                    return None
+
+            study_description = get_meta("0008|1030")
+            series_description = get_meta("0008|103e")
+            series_modality = get_meta("0008|0060")
+
+            name = study_description or data_dirpath.name
+            if series_description and series_modality:
+                description = f"{series_description}-{series_modality}"
+            elif series_description:
+                description = series_description
+            elif series_modality:
+                description = series_modality
+            else:
+                description = ""
+
+            name = name.replace(" ", "-")
+            description = description.replace(" ", "-")
+
+        elif ext in SEQUENCE_EXTS and is_sequence:
+            itk_image = sitk.ReadImage(sequence)
+            name = get_sequence_name(data_path)
+        else:
+            itk_image = sitk.ReadImage(data_path)
+            name = get_file_name(data_path)
+
+        # for key in itk_image.GetMetaDataKeys():
+        #     print(f"{key},{itk_image.GetMetaData(key)}")
+
+        if progress_callback:
+            progress_callback(0.5, "Transpose to 'TXYZC'...")
+
+        if itk_image.GetDimension() == 2:
+
+            data = sitk.GetArrayFromImage(itk_image)
+
+            if data.ndim == 3:
+                data = np.transpose(data, (1, 0, 2))
+
+                data = np.expand_dims(data, axis=-2)  # expend Z
+            else:
+                data = np.transpose(data)
+                data = np.expand_dims(data, axis=-1)  # expend Z
+                data = np.expand_dims(data, axis=-1)  # expend channel
+
+            data = np.expand_dims(data, axis=0)  # expend frame
+
+        elif itk_image.GetDimension() == 3:
+            if ext not in SEQUENCE_EXTS:
+                itk_image = sitk.DICOMOrient(itk_image, 'RAS')
+                # After sitk.DICOMOrient(), origin and direction will also orient base on LPS
+                # so we need to convert them into RAS
+                # affine = axis_conversion(from_forward='-Z',
+                #                          from_up='-Y',
+                #                          to_forward='-Z',
+                #                          to_up='Y').to_4x4()
+
+                affine = np.array([[-1.0000,  0.0000, 0.0000, 0.0000],
+                                   [0.0000, -1.0000, 0.0000, 0.0000],
+                                   [0.0000,  0.0000, 1.0000, 0.0000],
+                                   [0.0000,  0.0000, 0.0000, 1.0000]])
+
+            spacing = tuple(itk_image.GetSpacing())
+            origin = tuple(itk_image.GetOrigin())
+            direction = tuple(itk_image.GetDirection())
+
+            data = sitk.GetArrayFromImage(itk_image)
+            # transpose ijk to kji
+            if data.ndim == 4:
+                data = np.transpose(data, (2, 1, 0, 3))
+            else:
+                data = np.transpose(data)
+                data = np.expand_dims(data, axis=-1)  # expend channel
+
+            data = np.expand_dims(data, axis=0)  # expend frame
+
+        elif itk_image.GetDimension() == 4:
+
+            spacing = tuple(itk_image.GetSpacing()[:3])
+            origin = tuple(itk_image.GetOrigin()[:3])
+            # FIXME: not sure...
+            direction = np.array(itk_image.GetDirection())
+            direction = direction.reshape(3, 3) if itk_image.GetDimension() == 3 \
+                else direction.reshape(4, 4)
+
+            direction = direction[1:, 1:]
+            direction = tuple(direction.flatten())
+
+            data = sitk.GetArrayFromImage(itk_image)
+
+            if data.ndim == 5:
+                data = np.transpose(data, (0, 3, 2, 1, 4))
+            else:
+                data = np.transpose(data, (0, 3, 2, 1))
+                data = np.expand_dims(data, axis=-1)
+
+        if itk_image.GetDimension() > 5:
+            raise Exception
+
+    t = origin
+    r = np.array(direction).reshape((3, 3))
+    affine = np.dot(affine,
+                    transforms3d.affines.compose(t, r, [1, 1, 1]))
+
+    meta = {
+        "name": name,
+        "description": description,
+        "spacing": spacing,
+        "affine": affine,
+        "xyz_shape": data.shape[1:4],
+        "frame_count": data.shape[0],
+        "channel_count": data.shape[-1],
+    }
+
+    return data, meta

bioxelnodes/bioxel/scipy/__init__.py

@@ -0,0 +1,5 @@
+from ._interpolation import zoom
+from ._filters import (gaussian_filter,
+                       median_filter,
+                       maximum_filter,
+                       minimum_filter)

bioxelnodes/bioxel/scipy/_interpolation.py

@@ -0,0 +1,313 @@
+import numpy as np
+import warnings
+
+from . import _ni_support
+from . import _nd_image
+from ._utils import normalize_axis_index
+
+
+def _prepad_for_spline_filter(input, mode, cval):
+    if mode in ['nearest', 'grid-constant']:
+        npad = 12
+        if mode == 'grid-constant':
+            padded = np.pad(input, npad, mode='constant',
+                               constant_values=cval)
+        elif mode == 'nearest':
+            padded = np.pad(input, npad, mode='edge')
+    else:
+        # other modes have exact boundary conditions implemented so
+        # no prepadding is needed
+        npad = 0
+        padded = input
+    return padded, npad
+
+def spline_filter1d(input, order=3, axis=-1, output=np.float64,
+                    mode='mirror'):
+    """
+    Calculate a 1-D spline filter along the given axis.
+
+    The lines of the array along the given axis are filtered by a
+    spline filter. The order of the spline must be >= 2 and <= 5.
+
+    Parameters
+    ----------
+    %(input)s
+    order : int, optional
+        The order of the spline, default is 3.
+    axis : int, optional
+        The axis along which the spline filter is applied. Default is the last
+        axis.
+    output : ndarray or dtype, optional
+        The array in which to place the output, or the dtype of the returned
+        array. Default is ``numpy.float64``.
+    %(mode_interp_mirror)s
+
+    Returns
+    -------
+    spline_filter1d : ndarray
+        The filtered input.
+
+    See Also
+    --------
+    spline_filter : Multidimensional spline filter.
+
+    Notes
+    -----
+    All of the interpolation functions in `ndimage` do spline interpolation of
+    the input image. If using B-splines of `order > 1`, the input image
+    values have to be converted to B-spline coefficients first, which is
+    done by applying this 1-D filter sequentially along all
+    axes of the input. All functions that require B-spline coefficients
+    will automatically filter their inputs, a behavior controllable with
+    the `prefilter` keyword argument. For functions that accept a `mode`
+    parameter, the result will only be correct if it matches the `mode`
+    used when filtering.
+
+    For complex-valued `input`, this function processes the real and imaginary
+    components independently.
+
+    .. versionadded:: 1.6.0
+        Complex-valued support added.
+
+    Examples
+    --------
+    We can filter an image using 1-D spline along the given axis:
+
+    >>> from scipy.ndimage import spline_filter1d
+    >>> import numpy as np
+    >>> import matplotlib.pyplot as plt
+    >>> orig_img = np.eye(20)  # create an image
+    >>> orig_img[10, :] = 1.0
+    >>> sp_filter_axis_0 = spline_filter1d(orig_img, axis=0)
+    >>> sp_filter_axis_1 = spline_filter1d(orig_img, axis=1)
+    >>> f, ax = plt.subplots(1, 3, sharex=True)
+    >>> for ind, data in enumerate([[orig_img, "original image"],
+    ...             [sp_filter_axis_0, "spline filter (axis=0)"],
+    ...             [sp_filter_axis_1, "spline filter (axis=1)"]]):
+    ...     ax[ind].imshow(data[0], cmap='gray_r')
+    ...     ax[ind].set_title(data[1])
+    >>> plt.tight_layout()
+    >>> plt.show()
+
+    """
+    if order < 0 or order > 5:
+        raise RuntimeError('spline order not supported')
+    input = np.asarray(input)
+    complex_output = np.iscomplexobj(input)
+    output = _ni_support._get_output(output, input,
+                                     complex_output=complex_output)
+    if complex_output:
+        spline_filter1d(input.real, order, axis, output.real, mode)
+        spline_filter1d(input.imag, order, axis, output.imag, mode)
+        return output
+    if order in [0, 1]:
+        output[...] = np.array(input)
+    else:
+        mode = _ni_support._extend_mode_to_code(mode)
+        axis = normalize_axis_index(axis, input.ndim)
+        _nd_image.spline_filter1d(input, order, axis, output, mode)
+    return output
+
+
+def spline_filter(input, order=3, output=np.float64, mode='mirror'):
+    """
+    Multidimensional spline filter.
+
+    Parameters
+    ----------
+    %(input)s
+    order : int, optional
+        The order of the spline, default is 3.
+    output : ndarray or dtype, optional
+        The array in which to place the output, or the dtype of the returned
+        array. Default is ``numpy.float64``.
+    %(mode_interp_mirror)s
+
+    Returns
+    -------
+    spline_filter : ndarray
+        Filtered array. Has the same shape as `input`.
+
+    See Also
+    --------
+    spline_filter1d : Calculate a 1-D spline filter along the given axis.
+
+    Notes
+    -----
+    The multidimensional filter is implemented as a sequence of
+    1-D spline filters. The intermediate arrays are stored
+    in the same data type as the output. Therefore, for output types
+    with a limited precision, the results may be imprecise because
+    intermediate results may be stored with insufficient precision.
+
+    For complex-valued `input`, this function processes the real and imaginary
+    components independently.
+
+    .. versionadded:: 1.6.0
+        Complex-valued support added.
+
+    Examples
+    --------
+    We can filter an image using multidimentional splines:
+
+    >>> from scipy.ndimage import spline_filter
+    >>> import numpy as np
+    >>> import matplotlib.pyplot as plt
+    >>> orig_img = np.eye(20)  # create an image
+    >>> orig_img[10, :] = 1.0
+    >>> sp_filter = spline_filter(orig_img, order=3)
+    >>> f, ax = plt.subplots(1, 2, sharex=True)
+    >>> for ind, data in enumerate([[orig_img, "original image"],
+    ...                             [sp_filter, "spline filter"]]):
+    ...     ax[ind].imshow(data[0], cmap='gray_r')
+    ...     ax[ind].set_title(data[1])
+    >>> plt.tight_layout()
+    >>> plt.show()
+
+    """
+    if order < 2 or order > 5:
+        raise RuntimeError('spline order not supported')
+    input = np.asarray(input)
+    complex_output = np.iscomplexobj(input)
+    output = _ni_support._get_output(output, input,
+                                     complex_output=complex_output)
+    if complex_output:
+        spline_filter(input.real, order, output.real, mode)
+        spline_filter(input.imag, order, output.imag, mode)
+        return output
+    if order not in [0, 1] and input.ndim > 0:
+        for axis in range(input.ndim):
+            spline_filter1d(input, order, axis, output=output, mode=mode)
+            input = output
+    else:
+        output[...] = input[...]
+    return output
+
+
+def zoom(input, zoom, output=None, order=3, mode='constant', cval=0.0,
+         prefilter=True, *, grid_mode=False):
+    """
+    Zoom an array.
+
+    The array is zoomed using spline interpolation of the requested order.
+
+    Parameters
+    ----------
+    %(input)s
+    zoom : float or sequence
+        The zoom factor along the axes. If a float, `zoom` is the same for each
+        axis. If a sequence, `zoom` should contain one value for each axis.
+    %(output)s
+    order : int, optional
+        The order of the spline interpolation, default is 3.
+        The order has to be in the range 0-5.
+    %(mode_interp_constant)s
+    %(cval)s
+    %(prefilter)s
+    grid_mode : bool, optional
+        If False, the distance from the pixel centers is zoomed. Otherwise, the
+        distance including the full pixel extent is used. For example, a 1d
+        signal of length 5 is considered to have length 4 when `grid_mode` is
+        False, but length 5 when `grid_mode` is True. See the following
+        visual illustration:
+
+        .. code-block:: text
+
+                | pixel 1 | pixel 2 | pixel 3 | pixel 4 | pixel 5 |
+                     |<-------------------------------------->|
+                                        vs.
+                |<----------------------------------------------->|
+
+        The starting point of the arrow in the diagram above corresponds to
+        coordinate location 0 in each mode.
+
+    Returns
+    -------
+    zoom : ndarray
+        The zoomed input.
+
+    Notes
+    -----
+    For complex-valued `input`, this function zooms the real and imaginary
+    components independently.
+
+    .. versionadded:: 1.6.0
+        Complex-valued support added.
+
+    Examples
+    --------
+    >>> from scipy import ndimage, datasets
+    >>> import matplotlib.pyplot as plt
+
+    >>> fig = plt.figure()
+    >>> ax1 = fig.add_subplot(121)  # left side
+    >>> ax2 = fig.add_subplot(122)  # right side
+    >>> ascent = datasets.ascent()
+    >>> result = ndimage.zoom(ascent, 3.0)
+    >>> ax1.imshow(ascent, vmin=0, vmax=255)
+    >>> ax2.imshow(result, vmin=0, vmax=255)
+    >>> plt.show()
+
+    >>> print(ascent.shape)
+    (512, 512)
+
+    >>> print(result.shape)
+    (1536, 1536)
+    """
+    if order < 0 or order > 5:
+        raise RuntimeError('spline order not supported')
+    input = np.asarray(input)
+    if input.ndim < 1:
+        raise RuntimeError('input and output rank must be > 0')
+    zoom = _ni_support._normalize_sequence(zoom, input.ndim)
+    output_shape = tuple(
+        [int(round(ii * jj)) for ii, jj in zip(input.shape, zoom)])
+    complex_output = np.iscomplexobj(input)
+    output = _ni_support._get_output(output, input, shape=output_shape,
+                                     complex_output=complex_output)
+    if complex_output:
+        # import under different name to avoid confusion with zoom parameter
+        from scipy.ndimage._interpolation import zoom as _zoom
+
+        kwargs = dict(order=order, mode=mode, prefilter=prefilter)
+        _zoom(input.real, zoom, output=output.real,
+              cval=np.real(cval), **kwargs)
+        _zoom(input.imag, zoom, output=output.imag,
+              cval=np.imag(cval), **kwargs)
+        return output
+    if prefilter and order > 1:
+        padded, npad = _prepad_for_spline_filter(input, mode, cval)
+        filtered = spline_filter(padded, order, output=np.float64, mode=mode)
+    else:
+        npad = 0
+        filtered = input
+    if grid_mode:
+        # warn about modes that may have surprising behavior
+        suggest_mode = None
+        if mode == 'constant':
+            suggest_mode = 'grid-constant'
+        elif mode == 'wrap':
+            suggest_mode = 'grid-wrap'
+        if suggest_mode is not None:
+            warnings.warn(
+                (f"It is recommended to use mode = {suggest_mode} instead of {mode} "
+                 f"when grid_mode is True."),
+                stacklevel=2
+            )
+    mode = _ni_support._extend_mode_to_code(mode)
+
+    zoom_div = np.array(output_shape)
+    zoom_nominator = np.array(input.shape)
+    if not grid_mode:
+        zoom_div -= 1
+        zoom_nominator -= 1
+
+    # Zooming to infinite values is unpredictable, so just choose
+    # zoom factor 1 instead
+    zoom = np.divide(zoom_nominator, zoom_div,
+                     out=np.ones_like(input.shape, dtype=np.float64),
+                     where=zoom_div != 0)
+    zoom = np.ascontiguousarray(zoom)
+    _nd_image.zoom_shift(filtered, zoom, None, output, order, mode, cval, npad,
+                         grid_mode)
+    return output

bioxelnodes/bioxel/scipy/_ni_support.py

@@ -0,0 +1,119 @@
+# Copyright (C) 2003-2005 Peter J. Verveer
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions
+# are met:
+#
+# 1. Redistributions of source code must retain the above copyright
+#    notice, this list of conditions and the following disclaimer.
+#
+# 2. Redistributions in binary form must reproduce the above
+#    copyright notice, this list of conditions and the following
+#    disclaimer in the documentation and/or other materials provided
+#    with the distribution.
+#
+# 3. The name of the author may not be used to endorse or promote
+#    products derived from this software without specific prior
+#    written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS
+# OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+# ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY
+# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE
+# GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+# NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+from collections.abc import Iterable
+import operator
+import warnings
+import numpy as np
+
+
+def _extend_mode_to_code(mode):
+    """Convert an extension mode to the corresponding integer code.
+    """
+    if mode == 'nearest':
+        return 0
+    elif mode == 'wrap':
+        return 1
+    elif mode in ['reflect', 'grid-mirror']:
+        return 2
+    elif mode == 'mirror':
+        return 3
+    elif mode == 'constant':
+        return 4
+    elif mode == 'grid-wrap':
+        return 5
+    elif mode == 'grid-constant':
+        return 6
+    else:
+        raise RuntimeError('boundary mode not supported')
+
+
+def _normalize_sequence(input, rank):
+    """If input is a scalar, create a sequence of length equal to the
+    rank by duplicating the input. If input is a sequence,
+    check if its length is equal to the length of array.
+    """
+    is_str = isinstance(input, str)
+    if not is_str and isinstance(input, Iterable):
+        normalized = list(input)
+        if len(normalized) != rank:
+            err = "sequence argument must have length equal to input rank"
+            raise RuntimeError(err)
+    else:
+        normalized = [input] * rank
+    return normalized
+
+
+def _get_output(output, input, shape=None, complex_output=False):
+    if shape is None:
+        shape = input.shape
+    if output is None:
+        if not complex_output:
+            output = np.zeros(shape, dtype=input.dtype.name)
+        else:
+            complex_type = np.promote_types(input.dtype, np.complex64)
+            output = np.zeros(shape, dtype=complex_type)
+    elif isinstance(output, (type, np.dtype)):
+        # Classes (like `np.float32`) and dtypes are interpreted as dtype
+        if complex_output and np.dtype(output).kind != 'c':
+            warnings.warn("promoting specified output dtype to complex", stacklevel=3)
+            output = np.promote_types(output, np.complex64)
+        output = np.zeros(shape, dtype=output)
+    elif isinstance(output, str):
+        output = np.dtype(output)
+        if complex_output and output.kind != 'c':
+            raise RuntimeError("output must have complex dtype")
+        elif not issubclass(output.type, np.number):
+            raise RuntimeError("output must have numeric dtype")
+        output = np.zeros(shape, dtype=output)
+    elif output.shape != shape:
+        raise RuntimeError("output shape not correct")
+    elif complex_output and output.dtype.kind != 'c':
+        raise RuntimeError("output must have complex dtype")
+    return output
+
+
+def _check_axes(axes, ndim):
+    if axes is None:
+        return tuple(range(ndim))
+    elif np.isscalar(axes):
+        axes = (operator.index(axes),)
+    elif isinstance(axes, Iterable):
+        for ax in axes:
+            axes = tuple(operator.index(ax) for ax in axes)
+            if ax < -ndim or ax > ndim - 1:
+                raise ValueError(f"specified axis: {ax} is out of range")
+        axes = tuple(ax % ndim if ax < 0 else ax for ax in axes)
+    else:
+        message = "axes must be an integer, iterable of integers, or None"
+        raise ValueError(message)
+    if len(tuple(set(axes))) != len(axes):
+        raise ValueError("axes must be unique")
+    return axes

bioxelnodes/bioxel/scipy/_utils.py

@@ -0,0 +1,10 @@
+
+def normalize_axis_index(axis, ndim):
+    # Check if `axis` is in the correct range and normalize it
+    if axis < -ndim or axis >= ndim:
+        msg = f"axis {axis} is out of bounds for array of dimension {ndim}"
+        raise Exception(msg)
+
+    if axis < 0:
+        axis = axis + ndim
+    return axis

bioxelnodes/bioxel/skimage/__init__.py

@@ -0,0 +1 @@
+from ._warps import resize

bioxelnodes/bioxel/skimage/_utils.py

@@ -0,0 +1,37 @@
+import numpy as np
+
+
+def convert_to_float(image, preserve_range):
+    """Convert input image to float image with the appropriate range.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    preserve_range : bool
+        Determines if the range of the image should be kept or transformed
+        using img_as_float. Also see
+        https://scikit-image.org/docs/dev/user_guide/data_types.html
+
+    Notes
+    -----
+    * Input images with `float32` data type are not upcast.
+
+    Returns
+    -------
+    image : ndarray
+        Transformed version of the input.
+
+    """
+    if image.dtype == np.float16:
+        return image.astype(np.float32)
+    if preserve_range:
+        # Convert image to double only if it is not single or double
+        # precision float
+        if image.dtype.char not in 'df':
+            image = image.astype(float)
+    else:
+        from .dtype import img_as_float
+
+        image = img_as_float(image)
+    return image

bioxelnodes/bioxel/skimage/_warps.py

@@ -0,0 +1,318 @@
+import warnings
+import numpy as np
+from .. import scipy as ndi
+from ._utils import convert_to_float
+
+def _clip_warp_output(input_image, output_image, mode, cval, clip):
+    """Clip output image to range of values of input image.
+
+    Note that this function modifies the values of `output_image` in-place
+    and it is only modified if ``clip=True``.
+
+    Parameters
+    ----------
+    input_image : ndarray
+        Input image.
+    output_image : ndarray
+        Output image, which is modified in-place.
+
+    Other parameters
+    ----------------
+    mode : {'constant', 'edge', 'symmetric', 'reflect', 'wrap'}
+        Points outside the boundaries of the input are filled according
+        to the given mode.  Modes match the behaviour of `numpy.pad`.
+    cval : float
+        Used in conjunction with mode 'constant', the value outside
+        the image boundaries.
+    clip : bool
+        Whether to clip the output to the range of values of the input image.
+        This is enabled by default, since higher order interpolation may
+        produce values outside the given input range.
+
+    """
+    if clip:
+        min_val = np.min(input_image)
+        if np.isnan(min_val):
+            # NaNs detected, use NaN-safe min/max
+            min_func = np.nanmin
+            max_func = np.nanmax
+            min_val = min_func(input_image)
+        else:
+            min_func = np.min
+            max_func = np.max
+        max_val = max_func(input_image)
+
+        # Check if cval has been used such that it expands the effective input
+        # range
+        preserve_cval = (
+            mode == 'constant'
+            and not min_val <= cval <= max_val
+            and min_func(output_image) <= cval <= max_func(output_image)
+        )
+
+        # expand min/max range to account for cval
+        if preserve_cval:
+            # cast cval to the same dtype as the input image
+            cval = input_image.dtype.type(cval)
+            min_val = min(min_val, cval)
+            max_val = max(max_val, cval)
+
+        # Convert array-like types to ndarrays (gh-7159)
+        min_val, max_val = np.asarray(min_val), np.asarray(max_val)
+        np.clip(output_image, min_val, max_val, out=output_image)
+
+
+def _validate_interpolation_order(image_dtype, order):
+    """Validate and return spline interpolation's order.
+
+    Parameters
+    ----------
+    image_dtype : dtype
+        Image dtype.
+    order : int, optional
+        The order of the spline interpolation. The order has to be in
+        the range 0-5. See `skimage.transform.warp` for detail.
+
+    Returns
+    -------
+    order : int
+        if input order is None, returns 0 if image_dtype is bool and 1
+        otherwise. Otherwise, image_dtype is checked and input order
+        is validated accordingly (order > 0 is not supported for bool
+        image dtype)
+
+    """
+
+    if order is None:
+        return 0 if image_dtype == bool else 1
+
+    if order < 0 or order > 5:
+        raise ValueError(
+            "Spline interpolation order has to be in the " "range 0-5.")
+
+    if image_dtype == bool and order != 0:
+        raise ValueError(
+            "Input image dtype is bool. Interpolation is not defined "
+            "with bool data type. Please set order to 0 or explicitly "
+            "cast input image to another data type."
+        )
+
+    return order
+
+
+def _preprocess_resize_output_shape(image, output_shape):
+    """Validate resize output shape according to input image.
+
+    Parameters
+    ----------
+    image: ndarray
+        Image to be resized.
+    output_shape: iterable
+        Size of the generated output image `(rows, cols[, ...][, dim])`. If
+        `dim` is not provided, the number of channels is preserved.
+
+    Returns
+    -------
+    image: ndarray
+        The input image, but with additional singleton dimensions appended in
+        the case where ``len(output_shape) > input.ndim``.
+    output_shape: tuple
+        The output image converted to tuple.
+
+    Raises
+    ------
+    ValueError:
+        If output_shape length is smaller than the image number of
+        dimensions
+
+    Notes
+    -----
+    The input image is reshaped if its number of dimensions is not
+    equal to output_shape_length.
+
+    """
+    output_shape = tuple(output_shape)
+    output_ndim = len(output_shape)
+    input_shape = image.shape
+    if output_ndim > image.ndim:
+        # append dimensions to input_shape
+        input_shape += (1,) * (output_ndim - image.ndim)
+        image = np.reshape(image, input_shape)
+    elif output_ndim == image.ndim - 1:
+        # multichannel case: append shape of last axis
+        output_shape = output_shape + (image.shape[-1],)
+    elif output_ndim < image.ndim:
+        raise ValueError(
+            "output_shape length cannot be smaller than the "
+            "image number of dimensions"
+        )
+
+    return image, output_shape
+
+
+def _to_ndimage_mode(mode):
+    """Convert from `numpy.pad` mode name to the corresponding ndimage mode."""
+    mode_translation_dict = dict(
+        constant='constant',
+        edge='nearest',
+        symmetric='reflect',
+        reflect='mirror',
+        wrap='wrap',
+    )
+    if mode not in mode_translation_dict:
+        raise ValueError(
+            f"Unknown mode: '{mode}', or cannot translate mode. The "
+            f"mode should be one of 'constant', 'edge', 'symmetric', "
+            f"'reflect', or 'wrap'. See the documentation of numpy.pad for "
+            f"more info."
+        )
+    return _fix_ndimage_mode(mode_translation_dict[mode])
+
+
+def _fix_ndimage_mode(mode):
+    # SciPy 1.6.0 introduced grid variants of constant and wrap which
+    # have less surprising behavior for images. Use these when available
+    grid_modes = {'constant': 'grid-constant', 'wrap': 'grid-wrap'}
+    return grid_modes.get(mode, mode)
+
+
+def resize(
+    image,
+    output_shape,
+    order=None,
+    mode='reflect',
+    cval=0,
+    clip=True,
+    preserve_range=False,
+    anti_aliasing=None,
+    anti_aliasing_sigma=None,
+):
+    """Resize image to match a certain size.
+
+    Performs interpolation to up-size or down-size N-dimensional images. Note
+    that anti-aliasing should be enabled when down-sizing images to avoid
+    aliasing artifacts. For downsampling with an integer factor also see
+    `skimage.transform.downscale_local_mean`.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    output_shape : iterable
+        Size of the generated output image `(rows, cols[, ...][, dim])`. If
+        `dim` is not provided, the number of channels is preserved. In case the
+        number of input channels does not equal the number of output channels a
+        n-dimensional interpolation is applied.
+
+    Returns
+    -------
+    resized : ndarray
+        Resized version of the input.
+
+    Other parameters
+    ----------------
+    order : int, optional
+        The order of the spline interpolation, default is 0 if
+        image.dtype is bool and 1 otherwise. The order has to be in
+        the range 0-5. See `skimage.transform.warp` for detail.
+    mode : {'constant', 'edge', 'symmetric', 'reflect', 'wrap'}, optional
+        Points outside the boundaries of the input are filled according
+        to the given mode.  Modes match the behaviour of `numpy.pad`.
+    cval : float, optional
+        Used in conjunction with mode 'constant', the value outside
+        the image boundaries.
+    clip : bool, optional
+        Whether to clip the output to the range of values of the input image.
+        This is enabled by default, since higher order interpolation may
+        produce values outside the given input range.
+    preserve_range : bool, optional
+        Whether to keep the original range of values. Otherwise, the input
+        image is converted according to the conventions of `img_as_float`.
+        Also see https://scikit-image.org/docs/dev/user_guide/data_types.html
+    anti_aliasing : bool, optional
+        Whether to apply a Gaussian filter to smooth the image prior
+        to downsampling. It is crucial to filter when downsampling
+        the image to avoid aliasing artifacts. If not specified, it is set to
+        True when downsampling an image whose data type is not bool.
+        It is also set to False when using nearest neighbor interpolation
+        (``order`` == 0) with integer input data type.
+    anti_aliasing_sigma : {float, tuple of floats}, optional
+        Standard deviation for Gaussian filtering used when anti-aliasing.
+        By default, this value is chosen as (s - 1) / 2 where s is the
+        downsampling factor, where s > 1. For the up-size case, s < 1, no
+        anti-aliasing is performed prior to rescaling.
+
+    Notes
+    -----
+    Modes 'reflect' and 'symmetric' are similar, but differ in whether the edge
+    pixels are duplicated during the reflection.  As an example, if an array
+    has values [0, 1, 2] and was padded to the right by four values using
+    symmetric, the result would be [0, 1, 2, 2, 1, 0, 0], while for reflect it
+    would be [0, 1, 2, 1, 0, 1, 2].
+
+    Examples
+    --------
+    >>> from skimage import data
+    >>> from skimage.transform import resize
+    >>> image = data.camera()
+    >>> resize(image, (100, 100)).shape
+    (100, 100)
+
+    """
+
+    image, output_shape = _preprocess_resize_output_shape(image, output_shape)
+    input_shape = image.shape
+    input_type = image.dtype
+
+    if input_type == np.float16:
+        image = image.astype(np.float32)
+
+    if anti_aliasing is None:
+        anti_aliasing = (
+            not input_type == bool
+            and not (np.issubdtype(input_type, np.integer) and order == 0)
+            and any(x < y for x, y in zip(output_shape, input_shape))
+        )
+
+    if input_type == bool and anti_aliasing:
+        raise ValueError("anti_aliasing must be False for boolean images")
+
+    factors = np.divide(input_shape, output_shape)
+    order = _validate_interpolation_order(input_type, order)
+    if order > 0:
+        image = convert_to_float(image, preserve_range)
+
+    # Translate modes used by np.pad to those used by scipy.ndimage
+    ndi_mode = _to_ndimage_mode(mode)
+    if anti_aliasing:
+        if anti_aliasing_sigma is None:
+            anti_aliasing_sigma = np.maximum(0, (factors - 1) / 2)
+        else:
+            anti_aliasing_sigma = np.atleast_1d(anti_aliasing_sigma) * np.ones_like(
+                factors
+            )
+            if np.any(anti_aliasing_sigma < 0):
+                raise ValueError(
+                    "Anti-aliasing standard deviation must be "
+                    "greater than or equal to zero"
+                )
+            elif np.any((anti_aliasing_sigma > 0) & (factors <= 1)):
+                warnings.warn(
+                    "Anti-aliasing standard deviation greater than zero but "
+                    "not down-sampling along all axes",
+                    stacklevel=2
+                )
+        filtered = ndi.gaussian_filter(
+            image, anti_aliasing_sigma, cval=cval, mode=ndi_mode
+        )
+    else:
+        filtered = image
+
+    zoom_factors = [1 / f for f in factors]
+    out = ndi.zoom(
+        filtered, zoom_factors, order=order, mode=ndi_mode, cval=cval, grid_mode=True
+    )
+
+    _clip_warp_output(image, out, mode, cval, clip)
+
+    return out

bioxelnodes/bioxel/skimage/dtype.py

@@ -0,0 +1,600 @@
+import warnings
+from warnings import warn
+
+import numpy as np
+
+
+__all__ = [
+    'img_as_float32',
+    'img_as_float64',
+    'img_as_float',
+    'img_as_int',
+    'img_as_uint',
+    'img_as_ubyte',
+    'img_as_bool',
+    'dtype_limits',
+]
+
+# Some of these may or may not be aliases depending on architecture & platform
+_integer_types = (
+    np.int8,
+    np.byte,
+    np.int16,
+    np.short,
+    np.int32,
+    np.int64,
+    np.longlong,
+    np.int_,
+    np.intp,
+    np.intc,
+    int,
+    np.uint8,
+    np.ubyte,
+    np.uint16,
+    np.ushort,
+    np.uint32,
+    np.uint64,
+    np.ulonglong,
+    np.uint,
+    np.uintp,
+    np.uintc,
+)
+_integer_ranges = {t: (np.iinfo(t).min, np.iinfo(t).max) for t in _integer_types}
+dtype_range = {
+    bool: (False, True),
+    np.bool_: (False, True),
+    float: (-1, 1),
+    np.float16: (-1, 1),
+    np.float32: (-1, 1),
+    np.float64: (-1, 1),
+}
+
+with warnings.catch_warnings():
+    warnings.filterwarnings('ignore', category=DeprecationWarning)
+
+    # np.bool8 is a deprecated alias of np.bool_
+    if hasattr(np, 'bool8'):
+        dtype_range[np.bool8] = (False, True)
+
+dtype_range.update(_integer_ranges)
+
+_supported_types = list(dtype_range.keys())
+
+
+def dtype_limits(image, clip_negative=False):
+    """Return intensity limits, i.e. (min, max) tuple, of the image's dtype.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    clip_negative : bool, optional
+        If True, clip the negative range (i.e. return 0 for min intensity)
+        even if the image dtype allows negative values.
+
+    Returns
+    -------
+    imin, imax : tuple
+        Lower and upper intensity limits.
+    """
+    imin, imax = dtype_range[image.dtype.type]
+    if clip_negative:
+        imin = 0
+    return imin, imax
+
+
+def _dtype_itemsize(itemsize, *dtypes):
+    """Return first of `dtypes` with itemsize greater than `itemsize`
+
+    Parameters
+    ----------
+    itemsize: int
+        The data type object element size.
+
+    Other Parameters
+    ----------------
+    *dtypes:
+        Any Object accepted by `np.dtype` to be converted to a data
+        type object
+
+    Returns
+    -------
+    dtype: data type object
+        First of `dtypes` with itemsize greater than `itemsize`.
+
+    """
+    return next(dt for dt in dtypes if np.dtype(dt).itemsize >= itemsize)
+
+
+def _dtype_bits(kind, bits, itemsize=1):
+    """Return dtype of `kind` that can store a `bits` wide unsigned int
+
+    Parameters:
+    kind: str
+        Data type kind.
+    bits: int
+        Desired number of bits.
+    itemsize: int
+        The data type object element size.
+
+    Returns
+    -------
+    dtype: data type object
+        Data type of `kind` that can store a `bits` wide unsigned int
+
+    """
+
+    s = next(
+        i
+        for i in (itemsize,) + (2, 4, 8)
+        if bits < (i * 8) or (bits == (i * 8) and kind == 'u')
+    )
+
+    return np.dtype(kind + str(s))
+
+
+def _scale(a, n, m, copy=True):
+    """Scale an array of unsigned/positive integers from `n` to `m` bits.
+
+    Numbers can be represented exactly only if `m` is a multiple of `n`.
+
+    Parameters
+    ----------
+    a : ndarray
+        Input image array.
+    n : int
+        Number of bits currently used to encode the values in `a`.
+    m : int
+        Desired number of bits to encode the values in `out`.
+    copy : bool, optional
+        If True, allocates and returns new array. Otherwise, modifies
+        `a` in place.
+
+    Returns
+    -------
+    out : array
+        Output image array. Has the same kind as `a`.
+    """
+    kind = a.dtype.kind
+    if n > m and a.max() < 2**m:
+        mnew = int(np.ceil(m / 2) * 2)
+        if mnew > m:
+            dtype = f'int{mnew}'
+        else:
+            dtype = f'uint{mnew}'
+        n = int(np.ceil(n / 2) * 2)
+        warn(
+            f'Downcasting {a.dtype} to {dtype} without scaling because max '
+            f'value {a.max()} fits in {dtype}',
+            stacklevel=3,
+        )
+        return a.astype(_dtype_bits(kind, m))
+    elif n == m:
+        return a.copy() if copy else a
+    elif n > m:
+        # downscale with precision loss
+        if copy:
+            b = np.empty(a.shape, _dtype_bits(kind, m))
+            np.floor_divide(a, 2 ** (n - m), out=b, dtype=a.dtype, casting='unsafe')
+            return b
+        else:
+            a //= 2 ** (n - m)
+            return a
+    elif m % n == 0:
+        # exact upscale to a multiple of `n` bits
+        if copy:
+            b = np.empty(a.shape, _dtype_bits(kind, m))
+            np.multiply(a, (2**m - 1) // (2**n - 1), out=b, dtype=b.dtype)
+            return b
+        else:
+            a = a.astype(_dtype_bits(kind, m, a.dtype.itemsize), copy=False)
+            a *= (2**m - 1) // (2**n - 1)
+            return a
+    else:
+        # upscale to a multiple of `n` bits,
+        # then downscale with precision loss
+        o = (m // n + 1) * n
+        if copy:
+            b = np.empty(a.shape, _dtype_bits(kind, o))
+            np.multiply(a, (2**o - 1) // (2**n - 1), out=b, dtype=b.dtype)
+            b //= 2 ** (o - m)
+            return b
+        else:
+            a = a.astype(_dtype_bits(kind, o, a.dtype.itemsize), copy=False)
+            a *= (2**o - 1) // (2**n - 1)
+            a //= 2 ** (o - m)
+            return a
+
+
+def _convert(image, dtype, force_copy=False, uniform=False):
+    """
+    Convert an image to the requested data-type.
+
+    Warnings are issued in case of precision loss, or when negative values
+    are clipped during conversion to unsigned integer types (sign loss).
+
+    Floating point values are expected to be normalized and will be clipped
+    to the range [0.0, 1.0] or [-1.0, 1.0] when converting to unsigned or
+    signed integers respectively.
+
+    Numbers are not shifted to the negative side when converting from
+    unsigned to signed integer types. Negative values will be clipped when
+    converting to unsigned integers.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    dtype : dtype
+        Target data-type.
+    force_copy : bool, optional
+        Force a copy of the data, irrespective of its current dtype.
+    uniform : bool, optional
+        Uniformly quantize the floating point range to the integer range.
+        By default (uniform=False) floating point values are scaled and
+        rounded to the nearest integers, which minimizes back and forth
+        conversion errors.
+
+    .. versionchanged:: 0.15
+        ``_convert`` no longer warns about possible precision or sign
+        information loss. See discussions on these warnings at:
+        https://github.com/scikit-image/scikit-image/issues/2602
+        https://github.com/scikit-image/scikit-image/issues/543#issuecomment-208202228
+        https://github.com/scikit-image/scikit-image/pull/3575
+
+    References
+    ----------
+    .. [1] DirectX data conversion rules.
+           https://msdn.microsoft.com/en-us/library/windows/desktop/dd607323%28v=vs.85%29.aspx
+    .. [2] Data Conversions. In "OpenGL ES 2.0 Specification v2.0.25",
+           pp 7-8. Khronos Group, 2010.
+    .. [3] Proper treatment of pixels as integers. A.W. Paeth.
+           In "Graphics Gems I", pp 249-256. Morgan Kaufmann, 1990.
+    .. [4] Dirty Pixels. J. Blinn. In "Jim Blinn's corner: Dirty Pixels",
+           pp 47-57. Morgan Kaufmann, 1998.
+
+    """
+    image = np.asarray(image)
+    dtypeobj_in = image.dtype
+    if dtype is np.floating:
+        dtypeobj_out = np.dtype('float64')
+    else:
+        dtypeobj_out = np.dtype(dtype)
+    dtype_in = dtypeobj_in.type
+    dtype_out = dtypeobj_out.type
+    kind_in = dtypeobj_in.kind
+    kind_out = dtypeobj_out.kind
+    itemsize_in = dtypeobj_in.itemsize
+    itemsize_out = dtypeobj_out.itemsize
+
+    # Below, we do an `issubdtype` check.  Its purpose is to find out
+    # whether we can get away without doing any image conversion.  This happens
+    # when:
+    #
+    # - the output and input dtypes are the same or
+    # - when the output is specified as a type, and the input dtype
+    #   is a subclass of that type (e.g. `np.floating` will allow
+    #   `float32` and `float64` arrays through)
+
+    if np.issubdtype(dtype_in, dtype):
+        if force_copy:
+            image = image.copy()
+        return image
+
+    if not (dtype_in in _supported_types and dtype_out in _supported_types):
+        raise ValueError(f'Cannot convert from {dtypeobj_in} to ' f'{dtypeobj_out}.')
+
+    if kind_in in 'ui':
+        imin_in = np.iinfo(dtype_in).min
+        imax_in = np.iinfo(dtype_in).max
+    if kind_out in 'ui':
+        imin_out = np.iinfo(dtype_out).min
+        imax_out = np.iinfo(dtype_out).max
+
+    # any -> binary
+    if kind_out == 'b':
+        return image > dtype_in(dtype_range[dtype_in][1] / 2)
+
+    # binary -> any
+    if kind_in == 'b':
+        result = image.astype(dtype_out)
+        if kind_out != 'f':
+            result *= dtype_out(dtype_range[dtype_out][1])
+        return result
+
+    # float -> any
+    if kind_in == 'f':
+        if kind_out == 'f':
+            # float -> float
+            return image.astype(dtype_out)
+
+        if np.min(image) < -1.0 or np.max(image) > 1.0:
+            raise ValueError("Images of type float must be between -1 and 1.")
+        # floating point -> integer
+        # use float type that can represent output integer type
+        computation_type = _dtype_itemsize(
+            itemsize_out, dtype_in, np.float32, np.float64
+        )
+
+        if not uniform:
+            if kind_out == 'u':
+                image_out = np.multiply(image, imax_out, dtype=computation_type)
+            else:
+                image_out = np.multiply(
+                    image, (imax_out - imin_out) / 2, dtype=computation_type
+                )
+                image_out -= 1.0 / 2.0
+            np.rint(image_out, out=image_out)
+            np.clip(image_out, imin_out, imax_out, out=image_out)
+        elif kind_out == 'u':
+            image_out = np.multiply(image, imax_out + 1, dtype=computation_type)
+            np.clip(image_out, 0, imax_out, out=image_out)
+        else:
+            image_out = np.multiply(
+                image, (imax_out - imin_out + 1.0) / 2.0, dtype=computation_type
+            )
+            np.floor(image_out, out=image_out)
+            np.clip(image_out, imin_out, imax_out, out=image_out)
+        return image_out.astype(dtype_out)
+
+    # signed/unsigned int -> float
+    if kind_out == 'f':
+        # use float type that can exactly represent input integers
+        computation_type = _dtype_itemsize(
+            itemsize_in, dtype_out, np.float32, np.float64
+        )
+
+        if kind_in == 'u':
+            # using np.divide or np.multiply doesn't copy the data
+            # until the computation time
+            image = np.multiply(image, 1.0 / imax_in, dtype=computation_type)
+            # DirectX uses this conversion also for signed ints
+            # if imin_in:
+            #     np.maximum(image, -1.0, out=image)
+        elif kind_in == 'i':
+            # From DirectX conversions:
+            # The most negative value maps to -1.0f
+            # Every other value is converted to a float (call it c)
+            # and then result = c * (1.0f / (2⁽ⁿ⁻¹⁾-1)).
+
+            image = np.multiply(image, 1.0 / imax_in, dtype=computation_type)
+            np.maximum(image, -1.0, out=image)
+
+        else:
+            image = np.add(image, 0.5, dtype=computation_type)
+            image *= 2 / (imax_in - imin_in)
+
+        return np.asarray(image, dtype_out)
+
+    # unsigned int -> signed/unsigned int
+    if kind_in == 'u':
+        if kind_out == 'i':
+            # unsigned int -> signed int
+            image = _scale(image, 8 * itemsize_in, 8 * itemsize_out - 1)
+            return image.view(dtype_out)
+        else:
+            # unsigned int -> unsigned int
+            return _scale(image, 8 * itemsize_in, 8 * itemsize_out)
+
+    # signed int -> unsigned int
+    if kind_out == 'u':
+        image = _scale(image, 8 * itemsize_in - 1, 8 * itemsize_out)
+        result = np.empty(image.shape, dtype_out)
+        np.maximum(image, 0, out=result, dtype=image.dtype, casting='unsafe')
+        return result
+
+    # signed int -> signed int
+    if itemsize_in > itemsize_out:
+        return _scale(image, 8 * itemsize_in - 1, 8 * itemsize_out - 1)
+
+    image = image.astype(_dtype_bits('i', itemsize_out * 8))
+    image -= imin_in
+    image = _scale(image, 8 * itemsize_in, 8 * itemsize_out, copy=False)
+    image += imin_out
+    return image.astype(dtype_out)
+
+
+def convert(image, dtype, force_copy=False, uniform=False):
+    warn(
+        "The use of this function is discouraged as its behavior may change "
+        "dramatically in scikit-image 1.0. This function will be removed "
+        "in scikit-image 1.0.",
+        FutureWarning,
+        stacklevel=2,
+    )
+    return _convert(image=image, dtype=dtype, force_copy=force_copy, uniform=uniform)
+
+
+if _convert.__doc__ is not None:
+    convert.__doc__ = (
+        _convert.__doc__
+        + """
+
+    Warns
+    -----
+    FutureWarning:
+        .. versionadded:: 0.17
+
+        The use of this function is discouraged as its behavior may change
+        dramatically in scikit-image 1.0. This function will be removed
+        in scikit-image 1.0.
+    """
+    )
+
+
+def img_as_float32(image, force_copy=False):
+    """Convert an image to single-precision (32-bit) floating point format.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    force_copy : bool, optional
+        Force a copy of the data, irrespective of its current dtype.
+
+    Returns
+    -------
+    out : ndarray of float32
+        Output image.
+
+    Notes
+    -----
+    The range of a floating point image is [0.0, 1.0] or [-1.0, 1.0] when
+    converting from unsigned or signed datatypes, respectively.
+    If the input image has a float type, intensity values are not modified
+    and can be outside the ranges [0.0, 1.0] or [-1.0, 1.0].
+
+    """
+    return _convert(image, np.float32, force_copy)
+
+
+def img_as_float64(image, force_copy=False):
+    """Convert an image to double-precision (64-bit) floating point format.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    force_copy : bool, optional
+        Force a copy of the data, irrespective of its current dtype.
+
+    Returns
+    -------
+    out : ndarray of float64
+        Output image.
+
+    Notes
+    -----
+    The range of a floating point image is [0.0, 1.0] or [-1.0, 1.0] when
+    converting from unsigned or signed datatypes, respectively.
+    If the input image has a float type, intensity values are not modified
+    and can be outside the ranges [0.0, 1.0] or [-1.0, 1.0].
+
+    """
+    return _convert(image, np.float64, force_copy)
+
+
+def img_as_float(image, force_copy=False):
+    """Convert an image to floating point format.
+
+    This function is similar to `img_as_float64`, but will not convert
+    lower-precision floating point arrays to `float64`.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    force_copy : bool, optional
+        Force a copy of the data, irrespective of its current dtype.
+
+    Returns
+    -------
+    out : ndarray of float
+        Output image.
+
+    Notes
+    -----
+    The range of a floating point image is [0.0, 1.0] or [-1.0, 1.0] when
+    converting from unsigned or signed datatypes, respectively.
+    If the input image has a float type, intensity values are not modified
+    and can be outside the ranges [0.0, 1.0] or [-1.0, 1.0].
+
+    """
+    return _convert(image, np.floating, force_copy)
+
+
+def img_as_uint(image, force_copy=False):
+    """Convert an image to 16-bit unsigned integer format.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    force_copy : bool, optional
+        Force a copy of the data, irrespective of its current dtype.
+
+    Returns
+    -------
+    out : ndarray of uint16
+        Output image.
+
+    Notes
+    -----
+    Negative input values will be clipped.
+    Positive values are scaled between 0 and 65535.
+
+    """
+    return _convert(image, np.uint16, force_copy)
+
+
+def img_as_int(image, force_copy=False):
+    """Convert an image to 16-bit signed integer format.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    force_copy : bool, optional
+        Force a copy of the data, irrespective of its current dtype.
+
+    Returns
+    -------
+    out : ndarray of int16
+        Output image.
+
+    Notes
+    -----
+    The values are scaled between -32768 and 32767.
+    If the input data-type is positive-only (e.g., uint8), then
+    the output image will still only have positive values.
+
+    """
+    return _convert(image, np.int16, force_copy)
+
+
+def img_as_ubyte(image, force_copy=False):
+    """Convert an image to 8-bit unsigned integer format.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    force_copy : bool, optional
+        Force a copy of the data, irrespective of its current dtype.
+
+    Returns
+    -------
+    out : ndarray of ubyte (uint8)
+        Output image.
+
+    Notes
+    -----
+    Negative input values will be clipped.
+    Positive values are scaled between 0 and 255.
+
+    """
+    return _convert(image, np.uint8, force_copy)
+
+
+def img_as_bool(image, force_copy=False):
+    """Convert an image to boolean format.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    force_copy : bool, optional
+        Force a copy of the data, irrespective of its current dtype.
+
+    Returns
+    -------
+    out : ndarray of bool (`bool_`)
+        Output image.
+
+    Notes
+    -----
+    The upper half of the input dtype's positive range is True, and the lower
+    half is False. All negative values (if present) are False.
+
+    """
+    return _convert(image, bool, force_copy)

bioxelnodes/bioxelutils/container.py

@@ -0,0 +1,180 @@
+import bpy
+
+from ..bioxel.container import Container
+from bpy_extras.io_utils import axis_conversion
+from mathutils import Matrix, Vector
+
+
+from .layer import Layer, get_container_layer_objs, layer_to_obj, obj_to_layer
+from ..nodes import custom_nodes
+from .node import get_nodes_by_type, move_node_to_node
+
+
+NODE_TYPE = {
+    "label": "BioxelNodes_MaskByLabel",
+    "scalar": "BioxelNodes_MaskByThreshold"
+}
+
+
+def calc_bbox_verts(origin: tuple, size: tuple):
+    bbox_origin = Vector(
+        (origin[0], origin[1], origin[2]))
+    bbox_size = Vector(
+        (size[0], size[1], size[2]))
+    bbox_verts = [
+        (
+            bbox_origin[0] + 0,
+            bbox_origin[1] + 0,
+            bbox_origin[2] + 0
+        ),
+        (
+            bbox_origin[0] + 0,
+            bbox_origin[1] + 0,
+            bbox_origin[2] + bbox_size[2]
+        ),
+        (
+            bbox_origin[0] + 0,
+            bbox_origin[1] + bbox_size[1],
+            bbox_origin[2] + 0
+        ),
+        (
+            bbox_origin[0] + 0,
+            bbox_origin[1] + bbox_size[1],
+            bbox_origin[2] + bbox_size[2]
+        ),
+        (
+            bbox_origin[0] + bbox_size[0],
+            bbox_origin[1] + 0,
+            bbox_origin[2] + 0
+        ),
+        (
+            bbox_origin[0] + bbox_size[0],
+            bbox_origin[1] + 0,
+            bbox_origin[2] + bbox_size[2],
+        ),
+        (
+            bbox_origin[0] + bbox_size[0],
+            bbox_origin[1] + bbox_size[1],
+            bbox_origin[2] + 0,
+        ),
+        (
+            bbox_origin[0] + bbox_size[0],
+            bbox_origin[1] + bbox_size[1],
+            bbox_origin[2] + bbox_size[2],
+        ),
+    ]
+    return bbox_verts
+
+
+def get_container_objs_from_selection():
+    container_objs = []
+    for obj in bpy.context.selected_objects:
+        if get_container_obj(obj):
+            container_objs.append(obj)
+
+    return list(set(container_objs))
+
+
+def get_container_obj(current_obj):
+    if current_obj:
+        if current_obj.get('bioxel_container'):
+            return current_obj
+        elif current_obj.get('bioxel_layer'):
+            parent = current_obj.parent
+            return parent if parent.get('bioxel_container') else None
+    return None
+
+
+def add_layers(layers: list[Layer],
+               container_obj: bpy.types.Object,
+               cache_dir: str):
+
+    container_node_group = container_obj.modifiers[0].node_group
+
+    for i, layer in enumerate(layers):
+        layer_obj = layer_to_obj(layer, container_obj, cache_dir)
+        mask_node = custom_nodes.add_node(container_node_group,
+                                          NODE_TYPE[layer.kind])
+        mask_node.label = layer_obj.name
+        mask_node.inputs[0].default_value = layer_obj
+
+        # Connect to output if no output linked
+        output_node = get_nodes_by_type(container_node_group,
+                                        'NodeGroupOutput')[0]
+        if len(output_node.inputs[0].links) == 0:
+            container_node_group.links.new(mask_node.outputs[0],
+                                           output_node.inputs[0])
+            move_node_to_node(mask_node, output_node, (-300, 0))
+        else:
+            move_node_to_node(mask_node, output_node, (0, -100 * (i+1)))
+
+    return container_obj
+
+
+def obj_to_container(container_obj: bpy.types.Object):
+    layer_objs = get_container_layer_objs(container_obj)
+    layers = [obj_to_layer(obj) for obj in layer_objs]
+    container = Container(name=container_obj.name,
+                          layers=layers)
+    return container
+
+
+def container_to_obj(container: Container,
+                     scene_scale: float,
+                     cache_dir: str):
+    # Wrapper a Container
+
+    # Make transformation
+    # (S)uperior  -Z -> Y
+    # (A)osterior  Y -> Z
+    mat_ras2blender = axis_conversion(from_forward='-Z',
+                                      from_up='Y',
+                                      to_forward='Y',
+                                      to_up='Z').to_4x4()
+
+    mat_scene_scale = Matrix.Scale(scene_scale,
+                                   4)
+
+    bpy.ops.mesh.primitive_cube_add(enter_editmode=False,
+                                    align='WORLD',
+                                    location=(0, 0, 0),
+                                    scale=(1, 1, 1))
+
+    container_obj = bpy.context.active_object
+
+    bbox_verts = calc_bbox_verts((0, 0, 0), container.layers[0].shape)
+    for i, vert in enumerate(container_obj.data.vertices):
+        transform = Matrix(container.layers[0].affine)
+        vert.co = transform @ Vector(bbox_verts[i])
+
+    container_obj.matrix_world = mat_ras2blender @ mat_scene_scale
+    container_obj.name = container.name
+    container_obj.data.name = container.name
+    container_obj.show_in_front = True
+    container_obj['bioxel_container'] = True
+
+    bpy.ops.node.new_geometry_nodes_modifier()
+    container_node_group = container_obj.modifiers[0].node_group
+    input_node = get_nodes_by_type(container_node_group,
+                                   'NodeGroupInput')[0]
+    container_node_group.links.remove(
+        input_node.outputs[0].links[0])
+
+    for i, layer in enumerate(container.layers):
+        layer_obj = layer_to_obj(layer, container_obj, cache_dir)
+        mask_node = custom_nodes.add_node(container_node_group,
+                                          NODE_TYPE[layer.kind])
+        mask_node.label = layer_obj.name
+        mask_node.inputs[0].default_value = layer_obj
+
+        # Connect to output if no output linked
+        output_node = get_nodes_by_type(container_node_group,
+                                        'NodeGroupOutput')[0]
+        if len(output_node.inputs[0].links) == 0:
+            container_node_group.links.new(mask_node.outputs[0],
+                                           output_node.inputs[0])
+            move_node_to_node(mask_node, output_node, (-300, 0))
+        else:
+            move_node_to_node(mask_node, output_node, (0, -100 * (i+1)))
+
+    return container_obj

bioxelnodes/bioxelutils/layer.py

@@ -0,0 +1,232 @@
+import random
+import re
+import bpy
+import numpy as np
+
+import pyopenvdb as vdb
+from pathlib import Path
+from uuid import uuid4
+
+from ..nodes import custom_nodes
+from ..bioxel.layer import Layer
+from .node import get_nodes_by_type, move_node_between_nodes
+
+
+def get_layer_obj(current_obj: bpy.types.Object):
+    if current_obj:
+        if current_obj.get('bioxel_layer') and current_obj.parent:
+            if current_obj.parent.get('bioxel_container'):
+                return current_obj
+    return None
+
+
+def get_container_layer_objs(container_obj: bpy.types.Object):
+    layer_objs = []
+    for obj in bpy.context.scene.objects:
+        if obj.parent == container_obj and get_layer_obj(obj):
+            layer_objs.append(obj)
+
+    return layer_objs
+
+
+def get_all_layer_objs():
+    layer_objs = []
+    for obj in bpy.context.scene.objects:
+        if get_layer_obj(obj):
+            layer_objs.append(obj)
+
+    return layer_objs
+
+
+def obj_to_layer(layer_obj: bpy.types.Object):
+    cache_filepath = Path(bpy.path.abspath(layer_obj.data.filepath)).resolve()
+    is_sequence = re.search(r'\.\d{4}\.',
+                            cache_filepath.name) is not None
+    if is_sequence:
+        cache_path = cache_filepath.parent
+        data_frames = ()
+        for f in cache_path.iterdir():
+            if not f.is_file() or f.suffix != ".vdb":
+                continue
+            grids, base_metadata = vdb.readAll(str(f))
+            grid = grids[0]
+            metadata = grid.metadata
+            data_frame = np.ndarray(grid["data_shape"], np.float32)
+            grid.copyToArray(data_frame)
+            data_frames += (data_frame,)
+        data = np.stack(data_frames)
+    else:
+        grids, base_metadata = vdb.readAll(str(cache_filepath))
+        grid = grids[0]
+        metadata = grid.metadata
+        data = np.ndarray(grid["data_shape"], np.float32)
+        grid.copyToArray(data)
+        data = np.expand_dims(data, axis=0)  # expend frame
+
+    name = metadata["layer_name"]
+    kind = metadata["layer_kind"]
+    affine = metadata["layer_affine"]
+    dtype = metadata.get("data_dtype") or "float32"
+    offset = metadata.get("data_offset") or 0
+    data = data - np.full_like(data, offset)
+    data = data.astype(dtype)
+
+    if kind in ["scalar", "label"]:
+        data = np.expand_dims(data, axis=-1)  # expend channel
+
+    layer = Layer(data=data,
+                  name=name,
+                  kind=kind,
+                  affine=affine)
+
+    return layer
+
+
+def layer_to_obj(layer: Layer,
+                 container_obj: bpy.types.Object,
+                 cache_dir: str):
+
+    data = layer.data
+
+    # TXYZC > TXYZ
+    if layer.kind in ['label', 'scalar']:
+        data = np.amax(data, -1)
+
+    offset = 0
+    if layer.kind in ['scalar']:
+        data = data.astype(np.float32)
+        orig_min = float(np.min(data))
+        if orig_min < 0:
+            offset = -orig_min
+
+        data = data + np.full_like(data, offset)
+
+    metadata = {
+        "layer_name": layer.name,
+        "layer_kind": layer.kind,
+        "layer_affine": layer.affine.tolist(),
+        "data_shape": layer.shape,
+        "data_dtype": layer.data.dtype.str,
+        "data_offset": offset
+    }
+
+    if layer.frame_count > 1:
+        print(f"Saving the Cache of {layer.name}...")
+        vdb_name = str(uuid4())
+        sequence_path = Path(cache_dir, vdb_name)
+        sequence_path.mkdir(parents=True, exist_ok=True)
+
+        cache_filepaths = []
+        for f in range(layer.frame_count):
+            grid = vdb.FloatGrid()
+            grid.copyFromArray(data[f, :, :, :].copy().astype(np.float32))
+            grid.transform = vdb.createLinearTransform(
+                layer.affine.transpose())
+            grid.metadata = metadata
+            grid.name = layer.kind
+
+            cache_filepath = Path(sequence_path,
+                                  f"{vdb_name}.{str(f+1).zfill(4)}.vdb")
+            vdb.write(str(cache_filepath), grids=[grid])
+            cache_filepaths.append(cache_filepath)
+
+        print(f"Loading the Cache of {layer.name}...")
+        files = [{"name": str(cache_filepath.name), "name": str(cache_filepath.name)}
+                 for cache_filepath in cache_filepaths]
+
+        bpy.ops.object.volume_import(filepath=str(cache_filepaths[0]),
+                                     directory=str(cache_filepaths[0].parent),
+                                     files=files, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))
+
+    else:
+        grid = vdb.FloatGrid()
+        grid.copyFromArray(data[0, :, :, :].copy().astype(np.float32))
+        grid.transform = vdb.createLinearTransform(
+            layer.affine.transpose())
+        grid.metadata = metadata
+        grid.name = layer.kind
+
+        print(f"Saving the Cache of {layer.name}...")
+        cache_filepath = Path(cache_dir, f"{uuid4()}.vdb")
+        vdb.write(str(cache_filepath), grids=[grid])
+        cache_filepaths = [cache_filepath]
+
+        print(f"Loading the Cache of {layer.name}...")
+        bpy.ops.object.volume_import(filepath=str(cache_filepaths[0]),
+                                     align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))
+
+    layer_obj = bpy.context.active_object
+    layer_obj.data.sequence_mode = 'REPEAT'
+
+    # Set props to VDB object
+    layer_obj.name = f"{container_obj.name}_{layer.name}"
+    layer_obj.data.name = f"{container_obj.name}_{layer.name}"
+
+    layer_obj.lock_location[0] = True
+    layer_obj.lock_location[1] = True
+    layer_obj.lock_location[2] = True
+    layer_obj.lock_rotation[0] = True
+    layer_obj.lock_rotation[1] = True
+    layer_obj.lock_rotation[2] = True
+    layer_obj.lock_scale[0] = True
+    layer_obj.lock_scale[1] = True
+    layer_obj.lock_scale[2] = True
+
+    layer_obj.visible_camera = False
+    layer_obj.visible_diffuse = False
+    layer_obj.visible_glossy = False
+    layer_obj.visible_transmission = False
+    layer_obj.visible_volume_scatter = False
+    layer_obj.visible_shadow = False
+
+    layer_obj.hide_select = True
+    layer_obj.hide_render = True
+    layer_obj.hide_viewport = True
+
+    layer_obj['bioxel_layer'] = True
+    layer_obj.parent = container_obj
+
+    for collection in layer_obj.users_collection:
+        collection.objects.unlink(layer_obj)
+
+    for collection in container_obj.users_collection:
+        collection.objects.link(layer_obj)
+
+    print(f"Creating Node for {layer.name}...")
+    bpy.ops.node.new_geometry_nodes_modifier()
+    node_group = layer_obj.modifiers[0].node_group
+    layer_node = custom_nodes.add_node(node_group,
+                                          "BioxelNodes__Layer")
+
+    layer_node.inputs['name'].default_value = layer.name
+    layer_node.inputs['shape'].default_value = layer.shape
+    layer_node.inputs['kind'].default_value = layer.kind
+
+    for i in range(layer.affine.shape[1]):
+        for j in range(layer.affine.shape[0]):
+            affine_key = f"affine{i}{j}"
+            layer_node.inputs[affine_key].default_value = layer.affine[j, i]
+
+    layer_node.inputs['id'].default_value = random.randint(-200000000,
+                                                              200000000)
+    layer_node.inputs['bioxel_size'].default_value = layer.bioxel_size[0]
+    layer_node.inputs['dtype'].default_value = layer.dtype.str
+    layer_node.inputs['dtype_num'].default_value = layer.dtype.num
+    layer_node.inputs['offset'].default_value = max(0, -layer.min)
+    layer_node.inputs['min'].default_value = layer.min
+    layer_node.inputs['max'].default_value = layer.max
+
+    input_node = get_nodes_by_type(node_group,
+                                   'NodeGroupInput')[0]
+    output_node = get_nodes_by_type(node_group,
+                                    'NodeGroupOutput')[0]
+
+    node_group.links.new(input_node.outputs[0],
+                         layer_node.inputs[0])
+    node_group.links.new(layer_node.outputs[0],
+                         output_node.inputs[0])
+
+    move_node_between_nodes(
+        layer_node, [input_node, output_node])
+
+    return layer_obj

bioxelnodes/bioxelutils/node.py

@@ -0,0 +1,26 @@
+def move_node_to_node(node, target_node, offset=(0, 0)):
+    node.location.x = target_node.location.x + offset[0]
+    node.location.y = target_node.location.y + offset[1]
+
+
+def move_node_between_nodes(node, target_nodes, offset=(0, 0)):
+    xs = []
+    ys = []
+    for target_node in target_nodes:
+        xs.append(target_node.location.x)
+        ys.append(target_node.location.y)
+
+    node.location.x = sum(xs) / len(xs) + offset[0]
+    node.location.y = sum(ys) / len(ys) + offset[1]
+
+
+def get_node_type(node):
+    node_type = type(node).__name__
+    if node_type == "GeometryNodeGroup":
+        node_type = node.node_tree.name
+
+    return node_type
+
+
+def get_nodes_by_type(node_group, type_name: str):
+    return [node for node in node_group.nodes if get_node_type(node) == type_name]

bioxelnodes/blender_manifest.toml

@@ -0,0 +1,38 @@
+schema_version = "1.0.0"
+
+id = "bioxelnodes"
+version = "0.3.1"
+name = "Bioxel Nodes"
+tagline = "For scientific volumetric data visualization in Blender"
+maintainer = "Ma Nan <icrdr2010@outlook.com>"
+type = "add-on"
+website = "https://omoolab.github.io/BioxelNodes/latest"
+
+tags = ["Geometry Nodes", "Render", "Import-Export"]
+blender_version_min = "4.2.0"
+license = ["SPDX:MIT"]
+copyright = ["2024 OmooLab"]
+platforms = ["windows-x64", "linux-x64", "macos-arm64", "macos-x64"]
+
+wheels = [
+  "./wheels/SimpleITK-2.3.1-cp311-cp311-win_amd64.whl",
+  "./wheels/SimpleITK-2.3.1-cp311-cp311-macosx_10_9_x86_64.whl",
+  "./wheels/SimpleITK-2.3.1-cp311-cp311-macosx_11_0_arm64.whl",
+  "./wheels/SimpleITK-2.3.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+  "./wheels/lxml-5.2.2-cp311-cp311-win_amd64.whl",
+  "./wheels/lxml-5.2.2-cp311-cp311-macosx_10_9_arm64.whl",
+  "./wheels/lxml-5.2.2-cp311-cp311-macosx_10_9_x86_64.whl",
+  "./wheels/lxml-5.2.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+  "./wheels/h5py-3.11.0-cp311-cp311-win_amd64.whl",
+  "./wheels/h5py-3.11.0-cp311-cp311-macosx_11_0_arm64.whl",
+  "./wheels/h5py-3.11.0-cp311-cp311-macosx_10_9_x86_64.whl",
+  "./wheels/h5py-3.11.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+  "./wheels/tifffile-2024.7.24-py3-none-any.whl",
+  "./wheels/pyometiff-1.0.0-py3-none-any.whl",
+  "./wheels/mrcfile-1.5.1-py2.py3-none-any.whl",
+  "./wheels/transforms3d-0.4.2-py3-none-any.whl",
+]
+
+[permissions]
+files = "Import/export volume data from/to disk"
+

bioxelnodes/convert.py

@@ -1,46 +0,0 @@
-import bpy
-from .utils import get_bioxels_obj
-
-
-class ConvertToMesh(bpy.types.Operator):
-    bl_idname = "bioxelnodes.convert_to_mesh"
-    bl_label = "Bioxels To Mesh"
-    bl_description = "Convert Bioxels To Mesh."
-    bl_options = {'UNDO'}
-
-    def execute(self, context):
-        bioxels_objs = []
-
-        for obj in bpy.context.selected_objects:
-            bioxels_obj = get_bioxels_obj(obj)
-            if bioxels_obj:
-                bioxels_objs.append(bioxels_obj)
-
-        if len(bioxels_objs)==0:
-            self.report({"WARNING"}, "Cannot find any bioxels.")
-            return {'FINISHED'}
-
-        for bioxels_obj in bioxels_objs:
-            bpy.ops.mesh.primitive_cube_add(
-                size=2, enter_editmode=False, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))
-            mesh_obj = bpy.context.active_object
-
-            mesh_obj.name = f"{bioxels_obj.parent.name}_Mesh"
-            bpy.ops.node.new_geometry_nodes_modifier()
-            modifier = mesh_obj.modifiers[0]
-            nodes = modifier.node_group.nodes
-            links = modifier.node_group.links
-
-            output_node = nodes.get("Group Output")
-            object_node = nodes.new("GeometryNodeObjectInfo")
-            realize_nodes = nodes.new("GeometryNodeRealizeInstances")
-            object_node.inputs[0].default_value = bioxels_obj
-            object_node.transform_space = 'RELATIVE'
-
-            links.new(object_node.outputs['Geometry'], realize_nodes.inputs[0])
-            links.new(realize_nodes.outputs[0], output_node.inputs[0])
-            bpy.ops.object.convert(target='MESH')
-            bpy.context.object.active_material_index = 1
-            bpy.ops.object.material_slot_remove()
-
-        return {'FINISHED'}

bioxelnodes/custom_nodes/__init__.py

@@ -1 +0,0 @@
-from .node_menu import CustomNodes

bioxelnodes/customnodes/__init__.py

@@ -0,0 +1 @@
+from .menus import CustomNodes

bioxelnodes/customnodes/menus.py

@@ -8,17 +8,19 @@ class CustomNodes():
         self,
         menu_items,
         nodes_file,
+        class_prefix="CUSTOMNODES_MT_NODES",
         root_label='CustomNodes',
         root_icon='NONE'
     ) -> None:
         if not Path(nodes_file).is_file():
-            raise FileNotFoundError(Path(nodes_file).resolve().as_posix())
+            raise FileNotFoundError(str(Path(nodes_file).resolve()))
 
         self.menu_items = menu_items
-        self.nodes_file = Path(nodes_file).resolve().as_posix()
-
+        self.nodes_file = str(Path(nodes_file).resolve())
+        self.class_prefix = class_prefix
         self.root_label = root_label
         self.root_icon = root_icon
+        self.class_prefix = class_prefix
 
         menu_classes = []
         self._create_menu_class(
@@ -28,7 +30,7 @@ class CustomNodes():
         )
         self.menu_classes = menu_classes
 
-        idname = f"CUSTOMNODES_MT_NODES__{root_label.replace(' ', '').upper()}"
+        idname = f"{class_prefix}_{root_label.replace(' ', '').upper()}"
 
         def add_node_menu(self, context):
             if ('GeometryNodeTree' == bpy.context.area.spaces[0].tree_type):
@@ -40,7 +42,7 @@ class CustomNodes():
 
     def _create_menu_class(self, menu_classes, items, label='CustomNodes', icon=0, idname_namespace=None):
         nodes_file = self.nodes_file
-        idname_namespace = idname_namespace or "CUSTOMNODES_MT_NODES_"
+        idname_namespace = idname_namespace or self.class_prefix
         idname = f"{idname_namespace}_{label.replace(' ', '').upper()}"
 
         # create submenu class if item is menu.
@@ -60,6 +62,7 @@ class CustomNodes():
         class Menu(bpy.types.Menu):
             bl_idname = idname
             bl_label = label
+            nodes_file = self.nodes_file
 
             def draw(self, context):
                 layout = self.layout
@@ -93,10 +96,13 @@ class CustomNodes():
     def _find_item(self, found_items, menu_items, node_type: str):
 
         for item in menu_items:
+            if item == 'separator':
+                continue
+
             if item.get("node_type") == node_type:
                 found_items.append(item)
 
-            item_items = item.get('items') if item != 'separator' else None
+            item_items = item.get('items')
             if item_items:
                 self._find_item(found_items, item_items, node_type)
 
@@ -105,30 +111,37 @@ class CustomNodes():
         self._find_item(found_items, self.menu_items, node_type)
         return found_items[0] if len(found_items) > 0 else None
 
-    def add_node(self, node_tree, node_type: str):
+    def add_node(self, node_group, node_type: str):
         item = self.find_item(node_type)
+        op = AddCustomNode()
+        op.nodes_file = self.nodes_file
+        op.node_type = node_type
         if item:
-            op = AddCustomNode()
-            op.nodes_file = self.nodes_file
-            op.node_type = item['node_type']
             op.node_label = item.get('label') or ""
             op.node_link = item.get('link') or True
             op.node_callback = item.get('node_callback') or ""
-            return op.add_node(node_tree)
         else:
-            raise RuntimeError("No custom node type found.")
+            op.node_label = ""
+            op.node_link = True
+            op.node_callback = ""
+        return op.add_node(node_group)
 
     def register(self):
         for cls in self.menu_classes:
             bpy.utils.register_class(cls)
 
         bpy.types.NODE_MT_add.append(self.add_node_menu)
+        bpy.types.Scene.customnodes_node_dir = bpy.props.StringProperty(
+            name="Node Directory",
+            subtype='DIR_PATH',
+            default="//"
+        )
 
     def unregister(self):
+        bpy.types.NODE_MT_add.remove(self.add_node_menu)
         try:
             for cls in reversed(self.menu_classes):
                 bpy.utils.unregister_class(cls)
 
-            bpy.types.NODE_MT_add.remove(self.add_node_menu)
         except RuntimeError:
             pass

bioxelnodes/customnodes/nodes.py

@@ -85,10 +85,16 @@ class AddCustomNode():
             except:
                 ...
 
-    def add_node(self, node_tree):
+    def add_node(self, node_group):
+        # Deselect all nodes first
+        for node in node_group.nodes:
+            if node.select:
+                node.select = False
+
         self.get_node_tree(self.node_type, self.node_link)
-        node = node_tree.new("GeometryNodeGroup")
+        node = node_group.nodes.new("GeometryNodeGroup")
         self.assign_node_tree(node)
+        node.show_options = False
 
         return node
 
@@ -116,5 +122,6 @@ class CUSTOMNODES_OT_Add_Custom_Node(bpy.types.Operator, AddCustomNode):
         node = bpy.context.active_node
 
         self.assign_node_tree(node)
+        node.show_options = False
 
         return {"FINISHED"}

bioxelnodes/exceptions.py

@@ -0,0 +1,4 @@
+class CancelledByUser(Exception):
+    def __init__(self):
+        message = 'Cancelled by user'
+        super().__init__(message)

bioxelnodes/external_package/__init__.py

@@ -1 +0,0 @@
-from .preferences import ExternalPackagePreferences

bioxelnodes/external_package/package.py

@@ -1,389 +0,0 @@
-"""
-Handling installation of external python packages inside of Blender's bundled python.
-"""
-import subprocess
-import sys
-import logging
-from importlib.metadata import version as get_version, PackageNotFoundError
-import bpy
-from pathlib import Path
-
-ADDON_NAME = __package__.split(".")[0]
-
-PYPI_MIRROR = {
-    # the original.
-    'Default': '',
-    # two mirrors in China Mainland to help those poor victims under GFW.
-    'BFSU (Beijing)': 'https://mirrors.bfsu.edu.cn/pypi/web/simple',
-    'TUNA (Beijing)': 'https://pypi.tuna.tsinghua.edu.cn/simple',
-    # append more if necessary.
-}
-
-
-class InstallationError(Exception):
-    """
-    Exception raised when there is an error installing a package.
-
-    Attributes
-    ----------
-    package_name : str
-        The name of the package that failed to install.
-    error_message : str
-        The error message returned by pip.
-
-    """
-
-    def __init__(self, package_name, error_message):
-        self.package_name = package_name
-        self.error_message = error_message
-        super().__init__(f"Failed to install {package_name}: {error_message}")
-
-
-class PackageInstaller():
-    def __init__(
-        self,
-        log_dir: str,
-        requirements_dir: str,
-        pypi_mirror_provider='Default',
-    ) -> None:
-        self.pypi_mirror_provider = pypi_mirror_provider
-        self.log_path: Path = Path(log_dir)
-        self.requirements_path: Path = Path(requirements_dir)
-
-    def start_logging(self, logfile_name: str = 'side-packages-install') -> logging.Logger:
-        """
-        Configure and start logging to a file.
-
-        Parameters
-        ----------
-        logfile_name : str, optional
-            The name of the log file. Defaults to 'side-packages-install'.
-
-        Returns
-        -------
-        logging.Logger
-            A Logger object that can be used to write log messages.
-
-        This function sets up a logging configuration with a specified log file name and logging level.
-        The log file will be created in the `ADDON_DIR/logs` directory. If the directory
-        does not exist, it will be created. The function returns a Logger object that can be used to
-        write log messages.
-
-        """
-        # Create the logs directory if it doesn't exist
-        self.log_path.mkdir(parents=True, exist_ok=True)
-
-        # Set up logging configuration
-        logfile_path = Path(self.log_path, f"{logfile_name}.log")
-        logging.basicConfig(filename=logfile_path, level=logging.INFO)
-
-        # Return logger object
-        return logging.getLogger()
-
-    @property
-    def pypi_mirror_url(self) -> str:
-        """
-        Process a PyPI mirror provider and return the corresponding URL.
-
-        Parameters
-        ----------
-        pypi_mirror_provider : str
-            The PyPI mirror provider to process.
-
-        Returns
-        -------
-        str
-            The URL of the PyPI mirror.
-
-        Raises
-        ------
-        ValueError
-            If the provided PyPI mirror provider is invalid.
-
-        """
-        if self.pypi_mirror_provider.startswith('https:'):
-            return self.pypi_mirror_provider
-        elif self.pypi_mirror_provider in PYPI_MIRROR.keys():
-            return PYPI_MIRROR[self.pypi_mirror_provider]
-        else:
-            raise ValueError(
-                f"Invalid PyPI mirror provider: {self.pypi_mirror_provider}")
-
-    @property
-    def packages(self) -> dict:
-        """
-        Read a requirements file and extract package information into a dictionary.
-
-        Parameters
-        ----------
-        requirements : str, optional
-            The path to the requirements file. If not provided, the function looks for a `requirements.txt`
-            file in the same directory as the script.
-
-        Returns
-        -------
-        dict
-            A dictionary containing package information. Each element of the dictionary is a dictionary containing the package name, version, and description.
-
-        Example
-        -------
-        Given the following requirements file:
-        ```python
-        Flask==1.1.2 # A micro web framework for Python
-        pandas==1.2.3 # A fast, powerful, flexible, and easy-to-use data analysis and manipulation tool
-        numpy==1.20.1 # Fundamental package for scientific computing
-        ```
-        The function would return the following dictionary:
-        ```python
-        [
-            {
-                "package": "Flask",
-                "version": "1.1.2",
-                "description": "A micro web framework for Python"
-            },
-            {
-                "package": "pandas",
-                "version": "1.2.3",
-                "description": "A fast, powerful, flexible, and easy-to-use data analysis and manipulation tool"
-            },
-            {
-                "package": "numpy",
-                "version": "1.20.1",
-                "description": "Fundamental package for scientific computing"
-            }
-        ]
-        ```
-        """
-        requirements_filepath = self.requirements_path / "requirements.txt"
-        if requirements_filepath.is_file():
-            with requirements_filepath.open('r') as f:
-                lines = f.read().splitlines()
-                packages = {}
-                for line in lines:
-                    try:
-                        package, description = line.split('#')
-                        package_meta = package.split('==')
-                        name = package_meta[0].strip()
-                        packages[name] = {
-                            "name": name,
-                            "version": package_meta[1].strip(),
-                            "description": description.strip()
-                        }
-                    except ValueError:
-                        # Skip line if it doesn't have the expected format
-                        pass
-            return packages
-        else:
-            raise FileNotFoundError(requirements_filepath)
-
-    def is_installed(self, package_name: str) -> bool:
-        """
-        Check if the specified package is installed and the version matches that specified
-        in the `requirements.txt` file.
-
-        Parameters
-        ----------
-        package : str
-            The name of the package to check.
-
-        Returns
-        -------
-        bool
-            True if the package is the current version, False otherwise.
-
-        """
-        package = self.packages.get(package_name)
-        try:
-            available_version = get_version(package['name'])
-            return available_version == package['version']
-        except PackageNotFoundError:
-            return False
-
-    def run_python(self, cmd_list: list = None, timeout: int = 600):
-        """
-        Runs pip command using the specified command list and returns the command output.
-
-        Parameters
-        ----------
-        cmd_list : list, optional
-            List of pip commands to be executed. Defaults to None.
-        mirror_url : str, optional
-            URL of a package repository mirror to be used for the command. Defaults to ''.
-        timeout : int, optional
-            Time in seconds to wait for the command to complete. Defaults to 600.
-
-        Returns
-        -------
-        tuple
-            A tuple containing the command list, command return code, command standard output,
-            and command standard error.
-
-        Example
-        -------
-        Install numpy using pip and print the command output
-        ```python
-        cmd_list = ["-m", "pip", "install", "numpy"]
-        mirror_url = 'https://pypi.org/simple/'
-        cmd_output = run_python(cmd_list, timeout=300)
-        print(cmd_output)
-        ```
-
-        """
-
-        # path to python.exe
-        python_exe = Path(sys.executable).resolve().as_posix()
-
-        # build the command list
-        cmd_list = [python_exe] + cmd_list
-
-        # add mirror to the command list if it's valid
-        if self.pypi_mirror_url and self.pypi_mirror_url.startswith('https'):
-            cmd_list += ['-i', self.pypi_mirror_url]
-
-        log = self.start_logging()
-        log.info(f"Running Pip: '{cmd_list}'")
-
-        # run the command and capture the output
-        result = subprocess.run(cmd_list, timeout=timeout,
-                                stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-
-        if result.returncode != 0:
-            log.error('Command failed: %s', cmd_list)
-            log.error('stdout: %s', result.stdout.decode())
-            log.error('stderr: %s', result.stderr.decode())
-        else:
-            log.info('Command succeeded: %s', cmd_list)
-            log.info('stdout: %s', result.stdout.decode())
-        # return the command list, return code, stdout, and stderr as a tuple
-        return result
-
-    def install_package(self, package: str) -> list:
-        """
-        Install a Python package and its dependencies using pip.
-
-        Parameters
-        ----------
-        package : str
-            The name of the package to install.
-        pypi_mirror_provider : str, optional
-            The name/url of the PyPI mirror provider to use. Default is 'Default'.
-
-        Returns
-        -------
-        list
-            A list of tuples containing the command list, return code, stdout, and stderr
-            for each pip command run.
-
-        Raises
-        ------
-        ValueError
-            If the package name is not provided.
-
-        Example
-        -------
-        To install the package 'requests' from the PyPI mirror 'MyMirror', use:
-        ```
-        install_package('requests', 'MyMirror')
-        ```
-
-        """
-        if not package:
-            raise ValueError("Package name must be provided.")
-
-        print(f"Installing {package}...")
-        print(f"Using PyPI mirror: {self.pypi_mirror_provider}")
-
-        self.run_python(["-m", "ensurepip"]),
-        self.run_python(["-m", "pip", "install", "--upgrade", "pip"])
-        result = self.run_python(["-m", "pip", "install", package, "--user"])
-
-        return result
-
-    def install_all_packages(self, pypi_mirror_provider: str = 'Default') -> list:
-        """
-        Install all packages listed in the 'requirements.txt' file.
-
-        Parameters
-        ----------
-        pypi_mirror_provider : str, optional
-            The PyPI mirror to use for package installation. Defaults to 'Default',
-            which uses the official PyPI repository.
-
-        Returns
-        -------
-        list
-            A list of tuples containing the installation results for each package.
-
-        Raises
-        ------
-        InstallationError
-            If there is an error during package installation.
-
-        Example
-        -------
-        To install all packages listed in the 'requirements.txt' file, run the following command:
-        ```
-        install_all_packages(pypi_mirror_provider='https://pypi.org/simple/')
-        ```
-
-        """
-        results = []
-        for package in self.packages.items():
-
-            try:
-                result = self.install_package(
-                    package=f"{package.get('name')}=={package.get('version')}"
-                )
-                results.append(result)
-            except InstallationError as e:
-                raise InstallationError(
-                    f"Error installing package {package.get('name')}: {str(e)}")
-        return results
-
-
-class EXTERNALPACKAGE_OT_Install_Package(bpy.types.Operator):
-    bl_idname = 'externalpackage.install_package'
-    bl_label = 'Install Given Python Package'
-    bl_options = {'REGISTER', 'INTERNAL'}
-
-    package: bpy.props.StringProperty(
-        name='Python Package',
-        description='Python Package to Install'
-    )  # type: ignore
-    version: bpy.props.StringProperty(
-        name='Python Package',
-        description='Python Package to Install'
-    )  # type: ignore
-
-    description: bpy.props.StringProperty(
-        name='Operator description',
-        default='Install specified python package.'
-    )  # type: ignore
-
-    @classmethod
-    def description(cls, context, properties):
-        return properties.description
-
-    def execute(self, context):
-        preferences = context.preferences.addons[ADDON_NAME].preferences
-        installer = PackageInstaller(
-            pypi_mirror_provider=preferences.pypi_mirror_provider,
-            log_dir=preferences.log_dir,
-            requirements_dir=preferences.requirements_dir
-        )
-
-        result = installer.install_package(f"{self.package}=={self.version}")
-        if result.returncode == 0 and installer.is_installed(self.package):
-            self.report(
-                {'INFO'},
-                f"Successfully installed {self.package} v{self.version}"
-            )
-        else:
-            self.report(
-                {'ERROR'},
-                f"""
-Error installing package. Please check the log files
-in {preferences.log_dir}.
-                """
-            )
-        return {'FINISHED'}

bioxelnodes/external_package/preferences.py

@@ -1,73 +0,0 @@
-import bpy
-from pathlib import Path
-from .package import PackageInstaller, PYPI_MIRROR
-
-# Defines the preferences panel for the addon, which shows the buttons for
-# installing and reinstalling the required python packages defined in 'requirements.txt'
-
-
-def get_pypi_mirrors(self, context, edit_text):
-    return PYPI_MIRROR.keys()
-
-
-class ExternalPackagePreferences():
-    requirements_dir: bpy.props.StringProperty(
-        name="requirements.txt Directory",
-        subtype='DIR_PATH',
-        default=Path(__file__).parent.as_posix()
-    )  # type: ignore
-
-    log_dir: bpy.props.StringProperty(
-        name="Python Log Directory",
-        subtype='DIR_PATH',
-        default=Path(Path.home(), '.externalpackage', 'logs').as_posix()
-    )  # type: ignore
-
-    pypi_mirror_provider: bpy.props.StringProperty(
-        name='pypi_mirror_provider',
-        description='PyPI Mirror Provider',
-        options={'TEXTEDIT_UPDATE', 'LIBRARY_EDITABLE'},
-        default='Default',
-        subtype='NONE',
-        search=get_pypi_mirrors,
-    )  # type: ignore
-
-    def draw(self, context):
-        layout = self.layout
-        layout.label(text="Install the required packages.")
-
-        col_main = layout.column(heading='', align=False)
-        row_import = col_main.row()
-        row_import.prop(self, 'pypi_mirror_provider', text='Set PyPI Mirror')
-
-        
-        installer = PackageInstaller(
-            pypi_mirror_provider=self.pypi_mirror_provider,
-            log_dir=self.log_dir,
-            requirements_dir=self.requirements_dir
-        )
-
-        for package in installer.packages.values():
-
-            name = package.get('name')
-            version = package.get('version')
-            description = package.get('description')
-
-            if installer.is_installed(name):
-                row = layout.row()
-                row.label(text=f"{name} version {version} is installed.")
-                op = row.operator('externalpackage.install_package',
-                                  text=f'Reinstall {name}')
-                op.package = name
-                op.version = version
-                op.description = f'Reinstall {name}'
-            else:
-                row = layout.row(heading=f"Package: {name}")
-                col = row.column()
-                col.label(text=str(description))
-                col = row.column()
-                op = col.operator('externalpackage.install_package',
-                                  text=f'Install {name}')
-                op.package = name
-                op.version = version
-                op.description = f'Install required python package: {name}'

bioxelnodes/io.py

@@ -1,486 +0,0 @@
-import bpy
-import shutil
-from bpy_extras.io_utils import axis_conversion
-import pyopenvdb as vdb
-import numpy as np
-from pathlib import Path
-from uuid import uuid4
-import mathutils
-from .utils import calc_bbox_verts, extract_last_number, get_bioxels_obj, show_message
-from .nodes import custom_nodes
-
-SUPPORT_EXTS = ['.dcm', '.tif', '.tiff', '.png', '.bmp', '', '.jpg']
-
-
-def get_data_files(filepath: str):
-    file_path = Path(filepath).resolve()
-    suffix = file_path.suffix
-
-    files = list(file_path.parent.iterdir())
-    files = [f for f in files if f.is_file() and f.suffix == suffix]
-
-    def last_number(file: Path):
-        return extract_last_number(file.stem)
-
-    files.sort(key=last_number)
-    files = [f.as_posix() for f in files]
-    return files
-
-
-def on_orig_spacing_changed(self, context):
-    if self.auto:
-        self.auto = False
-        new_orig_spacing = tuple(self.orig_spacing)
-
-        orig_shape = tuple(self.orig_shape)
-        bioxel_size = float(self.bioxel_size)
-
-        self.bioxels_shape = (
-            int(orig_shape[0] / bioxel_size * new_orig_spacing[0]),
-            int(orig_shape[1] / bioxel_size * new_orig_spacing[1]),
-            int(orig_shape[2] / bioxel_size * new_orig_spacing[2]),
-        )
-    else:
-        self.auto = True
-
-
-def on_bioxel_size_changed(self, context):
-    if self.auto:
-        self.auto = False
-        new_bioxel_size = float(self.bioxel_size)
-
-        orig_shape = tuple(self.orig_shape)
-        orig_spacing = tuple(self.orig_spacing)
-
-        self.bioxels_shape = (
-            int(orig_shape[0] / new_bioxel_size * orig_spacing[0]),
-            int(orig_shape[1] / new_bioxel_size * orig_spacing[1]),
-            int(orig_shape[2] / new_bioxel_size * orig_spacing[2]),
-        )
-    else:
-        self.auto = True
-
-
-def on_info_changed(self, context):
-    for region in context.area.regions:
-        if region.type == "UI":
-            region.tag_redraw()
-
-
-class ImportDICOMDialog(bpy.types.Operator):
-    bl_idname = "bioxelnodes.import_dicom_dialog"
-    bl_label = "Volume Data as Biovels"
-    bl_description = "Import Volume Data as Biovels (VDB)."
-    bl_options = {'UNDO'}
-
-    filepath: bpy.props.StringProperty(
-        subtype="FILE_PATH",
-        options={'HIDDEN'}
-    )  # type: ignore
-
-    bioxels_shape: bpy.props.IntVectorProperty(
-        name="Bioxels Shape",
-        min=0,
-        default=(100, 100, 100)
-    )  # type: ignore
-
-    bioxel_size: bpy.props.FloatProperty(
-        name="Bioxel Size",
-        soft_min=0.1, soft_max=10.0,
-        min=1e-2, max=1e2,
-        default=1,
-        update=on_bioxel_size_changed
-    )  # type: ignore
-
-    orig_spacing: bpy.props.FloatVectorProperty(
-        name="Original Spacing",
-        default=(1, 1, 1),
-        update=on_orig_spacing_changed
-    )  # type: ignore
-
-    orig_shape: bpy.props.IntVectorProperty(
-        name="Original Shape",
-        default=(100, 100, 100),
-        options={'HIDDEN'}
-    )  # type: ignore
-
-    auto: bpy.props.BoolProperty(
-        name="Auto Setting",
-        default=False,
-        options={'HIDDEN'}
-    )  # type: ignore
-
-    scene_scale: bpy.props.FloatProperty(
-        name="Scene Scale",
-        soft_min=0.001, soft_max=100.0,
-        min=1e-6, max=1e6,
-        default=0.01,
-    )  # type: ignore
-
-    do_add_segmentnode: bpy.props.BoolProperty(
-        name="Add Segment Node",
-        default=True,
-    )  # type: ignore
-
-    do_change_render_setting: bpy.props.BoolProperty(
-        name="Change Render Setting",
-        default=True,
-    )  # type: ignore
-
-    def execute(self, context):
-        if not self.filepath:
-            self.report({"WARNING"}, "Get no file path.")
-            return {'CANCELLED'}
-
-        if Path(self.filepath).suffix not in SUPPORT_EXTS:
-            self.report({"WARNING"}, "Not Supported extension.")
-            return {'CANCELLED'}
-
-        file_path = Path(self.filepath).resolve()
-        name = file_path.parent.name
-        files = get_data_files(self.filepath)
-
-        import SimpleITK as sitk
-        image = sitk.ReadImage(files)
-
-        bioxel_size = float(self.bioxel_size)
-
-        orig_spacing = tuple(self.orig_spacing)
-        image_spacing = image.GetSpacing()
-        image_shape = image.GetSize()
-
-        bioxels_spacing = (
-            image_spacing[0] / orig_spacing[0] * bioxel_size,
-            image_spacing[1] / orig_spacing[1] * bioxel_size,
-            image_spacing[2] / orig_spacing[2] * bioxel_size
-        )
-
-        bioxels_shape = (
-            int(image_shape[0] / bioxel_size * orig_spacing[0]),
-            int(image_shape[1] / bioxel_size * orig_spacing[1]),
-            int(image_shape[2] / bioxel_size * orig_spacing[2]),
-        )
-
-        print("Bioxel Size:", bioxel_size)
-        print("Bioxels Shape:", bioxels_shape)
-
-        print("Resampling...")
-        image = sitk.Resample(
-            image1=image,
-            size=bioxels_shape,
-            transform=sitk.Transform(),
-            interpolator=sitk.sitkLinear,
-            outputOrigin=image.GetOrigin(),
-            outputSpacing=bioxels_spacing,
-            outputDirection=image.GetDirection(),
-            defaultPixelValue=0,
-            outputPixelType=image.GetPixelID(),
-        )
-
-        try:
-            image = sitk.DICOMOrient(image, 'RAS')
-        except:
-            ...
-
-        array = sitk.GetArrayFromImage(image)
-        orig_dtype = str(array.dtype)
-        print(f"Coverting Dtype {orig_dtype} -> float")
-        array = array.astype(float)
-
-        # ITK indices, by convention, are [i,j,k] while NumPy indices are [k,j,i]
-        # https://www.slicer.org/wiki/Coordinate_systems
-
-        # ITK                  Numpy      3D
-        # R (ight)     i   ->    k   ->   x
-        # A (nterior)  j   ->    j   ->   y
-        # S (uperior)  k   ->    i   ->   z
-
-        array = np.transpose(array)
-        bioxels_max = float(np.max(array))
-        bioxels_min = float(np.min(array))
-
-        bioxels_offset = 0.0
-        if bioxels_min < 0 and orig_dtype[0] != "u":
-            bioxels_offset = -bioxels_min
-            array = array + np.full_like(array, bioxels_offset)
-            bioxels_max = float(np.max(array))
-            bioxels_min = float(np.min(array))
-            print("Offseted Max:", bioxels_max)
-            print("Offseted Min:", bioxels_min)
-
-        # Build VDB
-        grid = vdb.FloatGrid()
-        grid.copyFromArray(array.copy())
-
-        # After sitk.DICOMOrient(), origin and direction will also orient base on LPS
-        # so we need to convert them into RAS
-        mat_lps2ras = axis_conversion(
-            from_forward='-Z',
-            from_up='-Y',
-            to_forward='-Z',
-            to_up='Y'
-        ).to_4x4()
-
-        mat_location = mathutils.Matrix.Translation(
-            mathutils.Vector(image.GetOrigin())
-        )
-
-        mat_rotation = mathutils.Matrix(
-            np.array(image.GetDirection()).reshape((3, 3))
-        ).to_4x4()
-
-        mat_scale = mathutils.Matrix.Scale(
-            bioxel_size, 4
-        )
-
-        transfrom = mat_lps2ras @ mat_location @ mat_rotation @ mat_scale
-
-        grid.transform = vdb.createLinearTransform(transfrom.transposed())
-        grid.name = "value"
-
-        preferences = context.preferences.addons[__package__].preferences
-        vdb_dirpath = Path(preferences.cache_dir, 'VDBs')
-        vdb_dirpath.mkdir(parents=True, exist_ok=True)
-        vdb_path = Path(vdb_dirpath, f"{uuid4()}.vdb")
-
-        print(f"Storing the VDB file ({vdb_path.as_posix()})...")
-        vdb.write(vdb_path.as_posix(), grids=[grid])
-
-        # Read VDB
-        print(f"Importing the VDB file to Blender scene...")
-        bpy.ops.object.volume_import(
-            filepath=vdb_path.as_posix(), align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))
-
-        bioxels_obj = bpy.context.active_object
-
-        # Set props to VDB object
-        bioxels_obj.name = f"{name}_Bioxels"
-        bioxels_obj.data.name = f"{name}_Bioxels"
-
-        # Make transformation
-        scene_scale = float(self.scene_scale)
-
-        # (S)uperior  -Z -> Y
-        # (A)osterior  Y -> Z
-        mat_ras2blender = axis_conversion(
-            from_forward='-Z',
-            from_up='Y',
-            to_forward='Y',
-            to_up='Z'
-        ).to_4x4()
-
-        mat_scene_scale = mathutils.Matrix.Scale(
-            scene_scale, 4
-        )
-
-        bioxels_obj.matrix_world = mat_ras2blender @ mat_scene_scale
-
-        bioxels_obj.lock_location[0] = True
-        bioxels_obj.lock_location[1] = True
-        bioxels_obj.lock_location[2] = True
-        bioxels_obj.lock_rotation[0] = True
-        bioxels_obj.lock_rotation[1] = True
-        bioxels_obj.lock_rotation[2] = True
-        bioxels_obj.lock_scale[0] = True
-        bioxels_obj.lock_scale[1] = True
-        bioxels_obj.lock_scale[2] = True
-        bioxels_obj.hide_select = True
-        bioxels_obj['bioxels'] = True
-
-        bpy.ops.node.new_geometry_nodes_modifier()
-        node_tree = bioxels_obj.modifiers[0].node_group
-
-        # Wrapper a Container
-        bpy.ops.mesh.primitive_cube_add(
-            enter_editmode=False, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1)
-        )
-        container_obj = bpy.context.active_object
-        bbox_verts = calc_bbox_verts((0, 0, 0), bioxels_shape)
-        for index, vert in enumerate(container_obj.data.vertices):
-            co = transfrom @ mathutils.Vector(bbox_verts[index])
-            co = mat_ras2blender @ co
-            co = mat_scene_scale @ co
-            vert.co = co
-
-        bioxels_obj.parent = container_obj
-        container_obj.name = name
-        container_obj.data.name = name
-        container_obj.visible_camera = False
-        container_obj.visible_diffuse = False
-        container_obj.visible_glossy = False
-        container_obj.visible_transmission = False
-        container_obj.visible_volume_scatter = False
-        container_obj.visible_shadow = False
-        container_obj.display_type = 'WIRE'
-        container_obj['bioxels_container'] = True
-        container_obj['scene_scale'] = scene_scale
-        container_obj['bioxel_size'] = bioxel_size
-        container_obj['bioxels_max'] = bioxels_max
-        container_obj['bioxels_min'] = bioxels_min
-        container_obj['bioxels_offset'] = bioxels_offset
-        container_obj['bioxels_shape'] = bioxels_shape
-
-        bpy.ops.object.modifier_add(type='NODES')
-        container_obj.modifiers[0].node_group = node_tree
-        container_obj.modifiers[0].show_in_editmode = False
-        container_obj.modifiers[0].show_viewport = False
-        container_obj.modifiers[0].show_render = False
-
-        # Create BioxelNodes to VDB object
-        print(f"Creating BioxelNodes to the VDB...")
-
-        if self.do_add_segmentnode:
-            nodes = node_tree.nodes
-            links = node_tree.links
-
-            input_node = nodes.get("Group Input")
-            output_node = nodes.get("Group Output")
-            segment_node = custom_nodes.add_node(nodes, 'BioxelNodes_Segment')
-
-            links.new(input_node.outputs[0], segment_node.inputs[0])
-            links.new(segment_node.outputs[0], output_node.inputs[0])
-
-        # Change render setting for better result
-        if self.do_change_render_setting:
-            bpy.context.scene.render.engine = 'CYCLES'
-            bpy.context.scene.cycles.volume_bounces = 12
-            bpy.context.scene.cycles.transparent_max_bounces = 64
-
-        self.report({"INFO"}, "Successfully Imported")
-
-        return {'FINISHED'}
-
-    def invoke(self, context, event):
-        # print(tuple(self.orig_shape))
-        self.auto = True
-        self.bioxel_size = 1
-        context.window_manager.invoke_props_dialog(self)
-        return {'RUNNING_MODAL'}
-
-
-class ReadDICOM(bpy.types.Operator):
-    bl_idname = "bioxelnodes.read_dicom"
-    bl_label = "Volume Data as Biovels"
-    bl_description = "Import Volume Data as Biovels (VDB)."
-    bl_options = {'UNDO'}
-
-    filepath: bpy.props.StringProperty(
-        subtype="FILE_PATH"
-    )  # type: ignore
-
-    ok: bpy.props.BoolProperty(
-        default=True
-    )  # type: ignore
-
-    def execute(self, context):
-        files = get_data_files(self.filepath)
-
-        import SimpleITK as sitk
-        image = sitk.ReadImage(files)
-
-        print("Collecting Meta Data...")
-        print("Original Shape:", image.GetSize())
-        print("Original Spacing:", image.GetSpacing())
-        print("Original Origin:", image.GetOrigin())
-        print("Original Direction:", image.GetDirection())
-
-        bpy.ops.bioxelnodes.import_dicom_dialog(
-            'INVOKE_DEFAULT',
-            filepath=self.filepath,
-            orig_shape=image.GetSize(),
-            orig_spacing=image.GetSpacing()
-        )
-
-        self.report({"INFO"}, "Successfully Readed.")
-
-        return {'FINISHED'}
-
-    def modal(self, context, event):
-        self.execute(context)
-        return {'FINISHED'}
-
-    def invoke(self, context, event):
-        if not self.filepath:
-            return {'CANCELLED'}
-
-        if Path(self.filepath).suffix not in SUPPORT_EXTS:
-            return {'CANCELLED'}
-
-        show_message('Reading image data, it may take a while',
-                     'Please be patient...')
-        context.window_manager.modal_handler_add(self)
-        return {'RUNNING_MODAL'}
-
-
-class ImportDICOM(bpy.types.Operator):
-    bl_idname = "bioxelnodes.import_dicom"
-    bl_label = "Volume Data as Biovels"
-    bl_description = "Import Volume Data as Biovels (VDB)."
-    bl_options = {'UNDO'}
-
-    filepath: bpy.props.StringProperty(
-        subtype="FILE_PATH"
-    )  # type: ignore
-
-    def execute(self, context):
-        bpy.ops.bioxelnodes.read_dicom(
-            'INVOKE_DEFAULT',
-            filepath=self.filepath
-        )
-        return {'FINISHED'}
-
-    def invoke(self, context, event):
-        context.window_manager.fileselect_add(self)
-        return {'RUNNING_MODAL'}
-
-
-class BIOXELNODES_FH_ImportDicom(bpy.types.FileHandler):
-    bl_idname = "BIOXELNODES_FH_ImportDicom"
-    bl_label = "File handler for dicom import"
-    bl_import_operator = "bioxelnodes.read_dicom"
-    bl_file_extensions = ".dcm"
-
-    @classmethod
-    def poll_drop(cls, context):
-        return (context.area and context.area.type == 'VIEW_3D')
-
-
-class ExportVDB(bpy.types.Operator):
-    bl_idname = "bioxelnodes.export_vdb"
-    bl_label = "Bioxels as VDB"
-    bl_description = "Export Bioxels original VDB data."
-    bl_options = {'UNDO'}
-
-    filepath: bpy.props.StringProperty(
-        subtype="FILE_PATH"
-    )  # type: ignore
-
-    filename_ext = ".vdb"
-
-    def invoke(self, context, event):
-        bioxels_obj = None
-        for obj in bpy.context.selected_objects:
-            bioxels_obj = get_bioxels_obj(obj)
-            break
-
-        if bioxels_obj:
-            context.window_manager.fileselect_add(self)
-            return {'RUNNING_MODAL'}
-        else:
-            self.report({"WARNING"}, "Cannot find any bioxels.")
-            return {'CANCELLED'}
-
-    def execute(self, context):
-        bioxels_obj = None
-        for obj in bpy.context.selected_objects:
-            bioxels_obj = get_bioxels_obj(obj)
-            break
-
-        filepath = f"{self.filepath.split('.')[0]}.vdb"
-        output_path: Path = Path(filepath).resolve()
-        source_path: Path = Path(bioxels_obj.data.filepath).resolve()
-        # print('output_path', output_path)
-        # print('source_path', source_path)
-        shutil.copy(source_path, output_path)
-
-        return {'FINISHED'}

bioxelnodes/menu.py

@@ -1,33 +0,0 @@
-import bpy
-from .convert import ConvertToMesh
-from .io import ExportVDB, ImportDICOM
-
-
-def TOPBAR_FILE_IMPORT(self, context):
-    layout = self.layout
-    layout.separator()
-    layout.operator(ImportDICOM.bl_idname)
-
-
-def TOPBAR_FILE_EXPORT(self, context):
-    layout = self.layout
-    layout.separator()
-    layout.operator(ExportVDB.bl_idname)
-
-
-def VIEW3D_OBJECT(self, context):
-    layout = self.layout
-    layout.operator(ConvertToMesh.bl_idname)
-    layout.separator()
-
-
-def create_menu():
-    bpy.types.TOPBAR_MT_file_import.append(TOPBAR_FILE_IMPORT)
-    bpy.types.TOPBAR_MT_file_export.append(TOPBAR_FILE_EXPORT)
-    bpy.types.VIEW3D_MT_object_context_menu.prepend(VIEW3D_OBJECT)
-
-
-def remove_menu():
-    bpy.types.TOPBAR_MT_file_import.remove(TOPBAR_FILE_IMPORT)
-    bpy.types.TOPBAR_MT_file_export.remove(TOPBAR_FILE_EXPORT)
-    bpy.types.VIEW3D_MT_object_context_menu.remove(VIEW3D_OBJECT)

bioxelnodes/menus.py

@@ -0,0 +1,197 @@
+import bpy
+
+from .bioxelutils.container import get_container_objs_from_selection
+from .operators.layer import (CombineLabels, SignScalar,
+                              FillByLabel, FillByThreshold, FillByRange)
+from .operators.container import (SaveContainer, LoadContainer,
+                                  AddPieCutter, AddPlaneCutter,
+                                  AddCylinderCutter, AddCubeCutter, AddSphereCutter,
+                                  PickBboxWire, PickMesh, PickVolume)
+from .operators.io import (ExportVolumetricData,
+                           ImportAsLabelLayer, ImportAsScalarLayer)
+from .operators.misc import (CleanAllCaches,
+                             ReLinkNodes, SaveCaches, SaveStagedData)
+
+
+def container_is_selected():
+    container_objs = get_container_objs_from_selection()
+    return len(container_objs) > 0
+
+
+class PickFromContainerMenu(bpy.types.Menu):
+    bl_idname = "BIOXELNODES_MT_PICK"
+    bl_label = "Pick from Container"
+
+    def draw(self, context):
+        layout = self.layout
+        layout.operator(PickMesh.bl_idname)
+        layout.operator(PickVolume.bl_idname)
+        layout.operator(PickBboxWire.bl_idname)
+
+
+class ModifyLayerMenu(bpy.types.Menu):
+    bl_idname = "BIOXELNODES_MT_MODIFY_LAYERS"
+    bl_label = "Modify Layer"
+
+    def draw(self, context):
+        layout = self.layout
+        layout.operator(SignScalar.bl_idname)
+        layout.operator(FillByThreshold.bl_idname)
+        layout.operator(FillByRange.bl_idname)
+        layout.operator(FillByLabel.bl_idname)
+        layout.operator(CombineLabels.bl_idname)
+
+
+class AddCutterMenu(bpy.types.Menu):
+    bl_idname = "BIOXELNODES_MT_CUTTERS"
+    bl_label = "Add a Cutter to Container"
+
+    def draw(self, context):
+        layout = self.layout
+        layout.operator(AddPlaneCutter.bl_idname, text="Plane Cutter")
+        layout.operator(AddCylinderCutter.bl_idname, text="Cylinder Cutter")
+        layout.operator(AddCubeCutter.bl_idname, text="Cube Cutter")
+        layout.operator(AddSphereCutter.bl_idname, text="Sphere Cutter")
+        layout.operator(AddPieCutter.bl_idname, text="Pie Cutter")
+
+
+class ImportLayerMenu(bpy.types.Menu):
+    bl_idname = "BIOXELNODES_MT_LAYERS"
+    bl_label = "Import Volumetric Data"
+
+    def draw(self, context):
+        layout = self.layout
+        layout.operator(ImportAsScalarLayer.bl_idname, text="as Scalar")
+        layout.operator(ImportAsLabelLayer.bl_idname, text="as Label")
+
+
+class BioxelNodesView3DMenu(bpy.types.Menu):
+    bl_idname = "BIOXELNODES_MT_VIEW3D"
+    bl_label = "Bioxel Nodes"
+
+    def draw(self, context):
+        layout = self.layout
+        is_selected = container_is_selected()
+        layout.operator(ImportAsScalarLayer.bl_idname,
+                        text=ImportAsScalarLayer.bl_label+" (Add to)"
+                        if is_selected else ImportAsScalarLayer.bl_label+" (Init)")
+        layout.operator(ImportAsLabelLayer.bl_idname,
+                        text=ImportAsLabelLayer.bl_label+" (Add to)"
+                        if is_selected else ImportAsLabelLayer.bl_label+" (Init)")
+        layout.separator()
+        layout.operator(AddPlaneCutter.bl_idname)
+        layout.operator(AddCylinderCutter.bl_idname)
+        layout.operator(AddCubeCutter.bl_idname)
+        layout.operator(AddSphereCutter.bl_idname)
+        layout.operator(AddPieCutter.bl_idname)
+        layout.separator()
+        layout.operator(PickMesh.bl_idname)
+        layout.operator(PickVolume.bl_idname)
+        layout.operator(PickBboxWire.bl_idname)
+        layout.separator()
+        layout.operator(SaveCaches.bl_idname)
+
+
+class BioxelNodesOutlinerMenu(bpy.types.Menu):
+    bl_idname = "BIOXELNODES_MT_OUTLINER"
+    bl_label = "Bioxel Nodes"
+
+    def draw(self, context):
+        layout = self.layout
+        is_selected = container_is_selected()
+        layout.operator(ImportAsScalarLayer.bl_idname,
+                        text=ImportAsScalarLayer.bl_label+" (Add to)"
+                        if is_selected else ImportAsScalarLayer.bl_label+" (Init)")
+        layout.operator(ImportAsLabelLayer.bl_idname,
+                        text=ImportAsLabelLayer.bl_label+" (Add to)"
+                        if is_selected else ImportAsLabelLayer.bl_label+" (Init)")
+        layout.separator()
+        layout.operator(AddPlaneCutter.bl_idname)
+        layout.operator(AddCylinderCutter.bl_idname)
+        layout.operator(AddCubeCutter.bl_idname)
+        layout.operator(AddSphereCutter.bl_idname)
+        layout.operator(AddPieCutter.bl_idname)
+        layout.separator()
+        layout.operator(PickMesh.bl_idname)
+        layout.operator(PickVolume.bl_idname)
+        layout.operator(PickBboxWire.bl_idname)
+        layout.separator()
+        layout.operator(SaveCaches.bl_idname)
+        layout.separator()
+        layout.operator(SignScalar.bl_idname)
+        layout.operator(FillByThreshold.bl_idname)
+        layout.operator(FillByRange.bl_idname)
+        layout.operator(FillByLabel.bl_idname)
+        layout.operator(CombineLabels.bl_idname)
+
+
+def TOPBAR_FILE_IMPORT(self, context):
+    layout = self.layout
+    is_selected = container_is_selected()
+
+    layout.separator()
+    layout.menu(ImportLayerMenu.bl_idname, text="Volumetric Data as Bioxel (Add to)"
+                if is_selected else "Volumetric Data as Bioxel (Init)")
+
+
+def TOPBAR_FILE_EXPORT(self, context):
+    layout = self.layout
+    layout.separator()
+    layout.operator(ExportVolumetricData.bl_idname,
+                    text="Bioxel Layer (.vdb)")
+
+
+def VIEW3D_OBJECT(self, context):
+    layout = self.layout
+    layout.separator()
+    layout.menu(BioxelNodesView3DMenu.bl_idname, icon="FILE_VOLUME")
+
+
+def OUTLINER_OBJECT(self, context):
+    layout = self.layout
+    layout.separator()
+    layout.menu(BioxelNodesOutlinerMenu.bl_idname, icon="FILE_VOLUME")
+
+
+class BioxelNodesTopbarMenu(bpy.types.Menu):
+    bl_idname = "BIOXELNODES_MT_TOPBAR"
+    bl_label = "Bioxel Nodes"
+
+    def draw(self, context):
+        layout = self.layout
+        is_selected = container_is_selected()
+
+        layout.menu(ImportLayerMenu.bl_idname, text=ImportLayerMenu.bl_label+" (Add to)"
+                    if is_selected else ImportLayerMenu.bl_label+" (Init)")
+        layout.separator()
+        layout.operator(LoadContainer.bl_idname)
+        layout.operator(SaveContainer.bl_idname)
+        layout.separator()
+        layout.menu(AddCutterMenu.bl_idname)
+        layout.menu(PickFromContainerMenu.bl_idname)
+        layout.separator()
+        layout.operator(SaveStagedData.bl_idname)
+        layout.operator(ReLinkNodes.bl_idname)
+        layout.separator()
+        layout.operator(CleanAllCaches.bl_idname)
+
+
+def TOPBAR(self, context):
+    layout = self.layout
+    layout.menu(BioxelNodesTopbarMenu.bl_idname)
+
+
+def add():
+    bpy.types.TOPBAR_MT_file_import.append(TOPBAR_FILE_IMPORT)
+    # bpy.types.TOPBAR_MT_file_export.append(TOPBAR_FILE_EXPORT)
+    bpy.types.OUTLINER_MT_object.append(OUTLINER_OBJECT)
+    bpy.types.VIEW3D_MT_object_context_menu.append(VIEW3D_OBJECT)
+    bpy.types.TOPBAR_MT_editor_menus.append(TOPBAR)
+
+
+def remove():
+    bpy.types.TOPBAR_MT_file_import.remove(TOPBAR_FILE_IMPORT)
+    # bpy.types.TOPBAR_MT_file_export.remove(TOPBAR_FILE_EXPORT)
+    bpy.types.OUTLINER_MT_object.remove(OUTLINER_OBJECT)
+    bpy.types.VIEW3D_MT_object_context_menu.remove(VIEW3D_OBJECT)
+    bpy.types.TOPBAR_MT_editor_menus.remove(TOPBAR)

bioxelnodes/nodes.py

@@ -1,146 +1,228 @@
 
 from pathlib import Path
-from .custom_nodes import CustomNodes
-import bpy
-
-
-def add_driver_to_node_factory(source_prop, target_prop):
-    callback_str = f"""
-import bpy
-from bioxelnodes.utils import add_direct_driver, get_bioxels_obj
-bioxels_obj = get_bioxels_obj(bpy.context.active_object)
-container_obj = bioxels_obj.parent
-if bioxels_obj:
-    add_direct_driver(
-        target=node,
-        target_prop='{target_prop}',
-        source=container_obj,
-        source_prop='{source_prop}'
-    )
-else:
-    print('Cannot find any bioxels.')
-    """
-    return callback_str
-
-
-def set_prop_to_node_factory(source_prop, target_prop):
-    callback_str = f"""
-import bpy
-from bioxelnodes.utils import get_bioxels_obj
-bioxels_obj = get_bioxels_obj(bpy.context.active_object)
-container_obj = bioxels_obj.parent
-if bioxels_obj:
-    node.inputs.get('{target_prop}').default_value = container_obj.get('{source_prop}')
-else:
-    print('Cannot find any bioxels.')
-    """
-    return callback_str
+from .customnodes import CustomNodes
 
+NODE_FILE = "BioxelNodes_4.2"
 
 MENU_ITEMS = [
     {
-        'label': 'Present',
-        'icon': 'MESH_MONKEY',
-        'items': [
-            {
-                'label': 'Segment',
-                'icon': 'OUTLINER_OB_META',
-                'node_type': 'BioxelNodes_Segment',
-                'node_description': '',
-                'node_callback': "\n".join([
-                    set_prop_to_node_factory("bioxel_size", "Detail Size"),
-                    set_prop_to_node_factory("bioxels_offset", "Offset"),
-                ])
-            },
-            {
-                'label': 'Anatomy',
-                'icon': 'OUTLINER_OB_META',
-                'node_type': 'BioxelNodes_Anatomy',
-                'node_description': '',
-                'node_callback': "\n".join([
-                    set_prop_to_node_factory("bioxel_size", "Detail Size"),
-                    set_prop_to_node_factory("bioxels_offset", "Offset"),
-                ])
-            }
-        ]
-    },
-    {
-        'label': 'Segment',
+        'label': 'Methods',
         'icon': 'OUTLINER_DATA_VOLUME',
         'items': [
             {
-                'label': 'Segment by Level',
-                'icon': 'AREA_JOIN',
-                'node_type': 'BioxelNodes_SegmentByLevel',
-                'node_description': '',
-                'node_callback': "\n".join([
-                    set_prop_to_node_factory("bioxel_size", "Detail Size"),
-                    set_prop_to_node_factory("bioxels_offset", "Offset"),
-                ])
+                'label': 'Mask by Threshold',
+                'icon': 'EMPTY_SINGLE_ARROW',
+                'node_type': 'BioxelNodes_MaskByThreshold',
+                'node_description': ''
             },
             {
-                'label': 'Segment by Range',
-                'icon': 'AREA_SWAP',
-                'node_type': 'BioxelNodes_SegmentByRange',
-                'node_description': '',
-                'node_callback': "\n".join([
-                    set_prop_to_node_factory("bioxel_size", "Detail Size"),
-                    set_prop_to_node_factory("bioxels_offset", "Offset"),
-                ])
+                'label': 'Mask by Range',
+                'icon': 'IPO_CONSTANT',
+                'node_type': 'BioxelNodes_MaskByRange',
+                'node_description': ''
             },
             {
-                'label': 'Segment by Layers',
-                'icon': 'OUTLINER_OB_FORCE_FIELD',
-                'node_type': 'BioxelNodes_SegmentsByLayers',
-                'node_description': '',
-                'node_callback': "\n".join([
-                    set_prop_to_node_factory("bioxel_size", "Detail Size"),
-                    set_prop_to_node_factory("bioxels_offset", "Offset"),
-                ])
+                'label': 'Mask by Label',
+                'icon': 'MESH_CAPSULE',
+                'node_type': 'BioxelNodes_MaskByLabel',
+                'node_description': ''
             }
         ]
     },
     {
-        'label': 'Shader',
+        'label': 'Shaders',
         'icon': 'SHADING_RENDERED',
         'items': [
             {
-                'label': 'Segment Shader',
-                'icon': 'OUTLINER_OB_VOLUME',
-                'node_type': 'BioxelNodes_SegmentShader',
+                'label': 'Membrane Shader',
+                'icon': 'NODE_MATERIAL',
+                'node_type': 'BioxelNodes_AssignMembraneShader',
+                'node_description': ''
+            },
+            {
+                'label': 'Solid Shader',
+                'icon': 'SHADING_SOLID',
+                'node_type': 'BioxelNodes_AssignSolidShader',
+                'node_description': ''
+            },
+            {
+                'label': 'Slime Shader',
+                'icon': 'OUTLINER_DATA_META',
+                'node_type': 'BioxelNodes_AssignSlimeShader',
+                'node_description': ''
+            },
+            {
+                'label': 'Volume Shader',
+                'icon': 'VOLUME_DATA',
+                'node_type': 'BioxelNodes_AssignVolumeShader',
+                'node_description': ''
+            },
+            {
+                'label': 'Universal Shader',
+                'icon': 'MATSHADERBALL',
+                'node_type': 'BioxelNodes_AssignUniversalShader',
                 'node_description': ''
             }
         ]
     },
     {
-        'label': 'Slicer',
-        'icon': 'CLIPUV_DEHLT',
+        'label': 'Colors',
+        'icon': 'COLOR',
         'items': [
             {
-                'label': 'RAS Slicer',
-                'icon': 'EMPTY_DATA',
-                'node_type': 'BioxelNodes_RAS-Slicer',
+                'label': 'Color Presets',
+                'icon': 'COLOR',
+                'node_type': 'BioxelNodes_ColorPresets',
                 'node_description': ''
             },
             {
-                'label': 'Axis Slicer',
-                'icon': 'OUTLINER_OB_EMPTY',
-                'node_type': 'BioxelNodes_AxisSlicer',
+                'label': 'Color Presets MRI',
+                'icon': 'COLOR',
+                'node_type': 'BioxelNodes_ColorPresets_MRI',
+                'node_description': ''
+            },
+            "separator",
+            {
+                'label': 'Color Ramp 2',
+                'icon': 'IPO_QUAD',
+                'node_type': 'BioxelNodes_SetColorRamp2',
+                'node_description': ''
+            },
+            {
+                'label': 'Color Ramp 3',
+                'icon': 'IPO_CUBIC',
+                'node_type': 'BioxelNodes_SetColorRamp3',
+                'node_description': ''
+            },
+            {
+                'label': 'Color Ramp 4',
+                'icon': 'IPO_QUART',
+                'node_type': 'BioxelNodes_SetColorRamp4',
+                'node_description': ''
+            },
+            {
+                'label': 'Color Ramp 5',
+                'icon': 'IPO_QUINT',
+                'node_type': 'BioxelNodes_SetColorRamp5',
+                'node_description': ''
+            }
+        ]
+    },
+    {
+        'label': 'Cutters',
+        'icon': 'MOD_BEVEL',
+        'items': [
+            {
+                'label': 'Cut',
+                'icon': 'MOD_BEVEL',
+                'node_type': 'BioxelNodes_Cut',
+                'node_description': ''
+            },
+            "separator",
+            {
+                'label': 'Primitive Cutter',
+                'icon': 'MOD_LINEART',
+                'node_type': 'BioxelNodes_PrimitiveCutter',
+                'node_description': ''
+            },
+            "separator",
+            {
+                'label': 'Plane Cutter',
+                'icon': 'MESH_PLANE',
+                'node_type': 'BioxelNodes_PlaneObjectCutter',
+                'node_description': ''
+            },
+            {
+                'label': 'Cylinder Cutter',
+                'icon': 'MESH_CYLINDER',
+                'node_type': 'BioxelNodes_CylinderObjectCutter',
                 'node_description': '',
             },
             {
-                'label': 'Box Slicer',
-                'icon': 'MOD_WIREFRAME',
-                'node_type': 'BioxelNodes_BoxSlicer',
+                'label': 'Cube Cutter',
+                'icon': 'MESH_CUBE',
+                'node_type': 'BioxelNodes_CubeObjectCutter',
+                'node_description': '',
+            },
+            {
+                'label': 'Sphere Cutter',
+                'icon': 'MESH_UVSPHERE',
+                'node_type': 'BioxelNodes_SphereObjectCutter',
+                'node_description': '',
+            },
+            {
+                'label': 'Pie Cutter',
+                'icon': 'MESH_CONE',
+                'node_type': 'BioxelNodes_PieObjectCutter',
                 'node_description': '',
             }
         ]
     },
+    {
+        'label': 'Utils',
+        'icon': 'MODIFIER',
+        'items': [
+            {
+                'label': 'Join Component',
+                'icon': 'CONSTRAINT_BONE',
+                'node_type': 'BioxelNodes_JoinComponent',
+                'node_description': ''
+            },
+            "separator",
+            {
+                'label': 'Pick Mesh',
+                'icon': 'OUTLINER_OB_MESH',
+                'node_type': 'BioxelNodes_PickMesh',
+                'node_description': ''
+            },
+            {
+                'label': 'Pick Volume',
+                'icon': 'OUTLINER_OB_VOLUME',
+                'node_type': 'BioxelNodes_PickVolume',
+                'node_description': ''
+            },
+            {
+                'label': 'Pick Bbox Wire',
+                'icon': 'MESH_CUBE',
+                'node_type': 'BioxelNodes_PickBboxWire',
+                'node_description': ''
+            },
+            "separator",
+            {
+                'label': 'Inflate',
+                'icon': 'OUTLINER_OB_META',
+                'node_type': 'BioxelNodes_M_Inflate',
+                'node_description': ''
+            },
+            {
+                'label': 'Smooth',
+                'icon': 'MOD_SMOOTH',
+                'node_type': 'BioxelNodes_M_Smooth',
+                'node_description': ''
+            },
+            {
+                'label': 'Remove Small Island',
+                'icon': 'FORCE_LENNARDJONES',
+                'node_type': 'BioxelNodes_M_RemoveSmallIsland',
+                'node_description': ''
+            }
+        ]
+    }
 ]
 
+
 custom_nodes = CustomNodes(
     menu_items=MENU_ITEMS,
-    nodes_file=Path(__file__).parent/"assets/Nodes.blend",
-    root_label='BioxelNodes',
+    nodes_file=Path(__file__).parent / f"assets/Nodes/{NODE_FILE}.blend",
+    class_prefix="BIOXELNODES_MT_NODES",
+    root_label='Bioxel Nodes',
     root_icon="FILE_VOLUME",
 )
+
+
+def register():
+    custom_nodes.register()
+
+
+def unregister():
+    custom_nodes.unregister()

bioxelnodes/operators/container.py

@@ -0,0 +1,290 @@
+import bpy
+
+
+import bmesh
+
+from ..nodes import custom_nodes
+from ..bioxel.io import load_container, save_container
+from ..bioxelutils.layer import get_all_layer_objs
+from ..bioxelutils.container import (container_to_obj, obj_to_container,
+                                     get_container_objs_from_selection)
+from ..bioxelutils.node import get_nodes_by_type, move_node_between_nodes, move_node_to_node
+from .utils import change_render_setting, get_cache_dir, get_preferences, select_object
+
+
+class SaveContainer(bpy.types.Operator):
+    bl_idname = "bioxelnodes.save_container"
+    bl_label = "Save Container (.bioxel) (BETA)"
+    bl_description = "Clean all caches saved in temp"
+
+    filepath: bpy.props.StringProperty(
+        subtype="FILE_PATH"
+    )  # type: ignore
+
+    filename_ext = ".bioxel"
+
+    @classmethod
+    def poll(cls, context):
+        container_objs = get_container_objs_from_selection()
+        return len(container_objs) > 0
+
+    def execute(self, context):
+        container_objs = get_container_objs_from_selection()
+
+        if len(container_objs) == 0:
+            self.report({"WARNING"}, "Cannot find any bioxel container.")
+            return {'FINISHED'}
+
+        container = obj_to_container(container_objs[0])
+        save_path = f"{self.filepath.split('.')[0]}.bioxel"
+        save_container(container, save_path, overwrite=True)
+
+        self.report({"INFO"}, f"Successfully save to {save_path}")
+        return {'FINISHED'}
+
+    def invoke(self, context, event):
+        context.window_manager.fileselect_add(self)
+        return {'RUNNING_MODAL'}
+
+
+class LoadContainer(bpy.types.Operator):
+    bl_idname = "bioxelnodes.load_container"
+    bl_label = "Load Container (.bioxel) (BETA)"
+    bl_description = "Clean all caches saved in temp"
+
+    filepath: bpy.props.StringProperty(
+        subtype="FILE_PATH"
+    )  # type: ignore
+
+    filename_ext = ".bioxel"
+
+    def execute(self, context):
+        load_path = self.filepath
+        container = load_container(self.filepath)
+        is_first_import = len(get_all_layer_objs()) == 0
+
+        container_obj = container_to_obj(container,
+                                         scene_scale=0.01,
+                                         cache_dir=get_cache_dir(context))
+        select_object(container_obj)
+
+        if is_first_import:
+            change_render_setting(context)
+
+        self.report({"INFO"}, f"Successfully load {load_path}")
+        return {'FINISHED'}
+
+    def invoke(self, context, event):
+        context.window_manager.fileselect_add(self)
+        return {'RUNNING_MODAL'}
+
+
+class PickObject():
+    bl_options = {'UNDO'}
+
+    @classmethod
+    def poll(cls, context):
+        container_objs = get_container_objs_from_selection()
+        return len(container_objs) > 0
+
+    def execute(self, context):
+        container_objs = get_container_objs_from_selection()
+
+        if len(container_objs) == 0:
+            self.report({"WARNING"}, "Cannot find any bioxel container.")
+            return {'FINISHED'}
+
+        container_obj = container_objs[0]
+
+        bpy.ops.mesh.primitive_cube_add(
+            size=2, enter_editmode=False, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))
+        obj = bpy.context.active_object
+
+        obj.name = f"{self.object_type}_{container_obj.name}"
+
+        bpy.ops.node.new_geometry_nodes_modifier()
+        modifier = obj.modifiers[0]
+        node_group = modifier.node_group
+
+        output_node = get_nodes_by_type(node_group, 'NodeGroupOutput')[0]
+        pick_mesh_node = custom_nodes.add_node(node_group,
+                                               f"BioxelNodes_Pick{self.object_type}")
+
+        pick_mesh_node.inputs[0].default_value = container_obj
+        node_group.links.new(pick_mesh_node.outputs[0], output_node.inputs[0])
+
+        select_object(obj)
+
+        self.report({"INFO"}, f"Successfully picked")
+
+        return {'FINISHED'}
+
+
+class PickMesh(bpy.types.Operator, PickObject):
+    bl_idname = "bioxelnodes.pick_mesh"
+    bl_label = "Pick Mesh"
+    bl_description = "Pick Container Mesh"
+    object_type = "Mesh"
+
+
+class PickVolume(bpy.types.Operator, PickObject):
+    bl_idname = "bioxelnodes.pick_volume"
+    bl_label = "Pick Volume"
+    bl_description = "Pick Container Volume"
+    object_type = "Volume"
+
+
+class PickBboxWire(bpy.types.Operator, PickObject):
+    bl_idname = "bioxelnodes.pick_bbox_wire"
+    bl_label = "Pick Bbox Wire"
+    bl_description = "Pick Container Bbox Wire"
+    object_type = "BboxWire"
+
+
+class AddCutter():
+    bl_options = {'UNDO'}
+
+    @classmethod
+    def poll(cls, context):
+        container_objs = get_container_objs_from_selection()
+        return len(container_objs) > 0
+
+    def execute(self, context):
+        container_objs = get_container_objs_from_selection()
+
+        if len(container_objs) == 0:
+            self.report({"WARNING"}, "Cannot find any bioxel container.")
+            return {'FINISHED'}
+
+        container_obj = container_objs[0]
+
+        if self.object_type == "plane":
+            node_type = "BioxelNodes_PlaneObjectCutter"
+            bpy.ops.mesh.primitive_plane_add(
+                size=2, enter_editmode=False, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))
+        elif self.object_type == "cylinder":
+            node_type = "BioxelNodes_CylinderObjectCutter"
+            bpy.ops.mesh.primitive_cylinder_add(
+                radius=1, depth=2, enter_editmode=False, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))
+            bpy.context.object.rotation_euler[0] = container_obj.rotation_euler[0]
+        elif self.object_type == "cube":
+            node_type = "BioxelNodes_CubeObjectCutter"
+            bpy.ops.mesh.primitive_cube_add(
+                size=2, enter_editmode=False, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))
+        elif self.object_type == "sphere":
+            node_type = "BioxelNodes_SphereObjectCutter"
+            bpy.ops.mesh.primitive_ico_sphere_add(
+                radius=1, enter_editmode=False, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))
+        elif self.object_type == "pie":
+            node_type = "BioxelNodes_PieObjectCutter"
+            # Create mesh
+            pie_mesh = bpy.data.meshes.new('Pie')
+
+            # Create object
+            pie = bpy.data.objects.new('Pie', pie_mesh)
+
+            # Link object to scene
+            bpy.context.scene.collection.objects.link(pie)
+            # Get a BMesh representation
+            bm = bmesh.new()   # create an empty BMesh
+            bm.from_mesh(pie_mesh)   # fill it in from a Mesh
+
+            # Hot to create vertices
+            v_0 = bm.verts.new((0.0, -1.0, 0.0))
+            v_1 = bm.verts.new((-1.0, -1.0, 1.0))
+            v_2 = bm.verts.new((0.0, 1.0, 0.0))
+            v_3 = bm.verts.new((-1.0, 1.0, 1.0))
+            v_4 = bm.verts.new((1.0, -1.0, 1.0))
+            v_5 = bm.verts.new((1.0, 1.0, 1.0))
+
+            # Initialize the index values of this sequence.
+            bm.verts.index_update()
+
+            # How to create a face
+            # it's not necessary to create the edges before, I made it only to show how create
+            # edges too
+            bm.faces.new((v_0, v_1, v_3, v_2))
+            bm.faces.new((v_0, v_2, v_5, v_4))
+
+            # Finish up, write the bmesh back to the mesh
+            bm.to_mesh(pie_mesh)
+            bpy.context.view_layer.objects.active = pie
+
+        cutter_obj = bpy.context.active_object
+        cutter_obj.visible_camera = False
+        cutter_obj.visible_diffuse = False
+        cutter_obj.visible_glossy = False
+        cutter_obj.visible_transmission = False
+        cutter_obj.visible_volume_scatter = False
+        cutter_obj.visible_shadow = False
+        cutter_obj.hide_render = True
+        cutter_obj.display_type = 'WIRE'
+
+        modifier = container_obj.modifiers[0]
+        node_group = modifier.node_group
+        cutter_node = custom_nodes.add_node(node_group, node_type)
+        cutter_node.inputs[0].default_value = cutter_obj
+
+        cut_nodes = get_nodes_by_type(node_group,
+                                      'BioxelNodes_Cut')
+        output_node = get_nodes_by_type(node_group, 'NodeGroupOutput')[0]
+        if len(cut_nodes) == 0:
+            cut_node = custom_nodes.add_node(node_group, 'BioxelNodes_Cut')
+            if len(output_node.inputs[0].links) == 0:
+                node_group.links.new(cut_node.outputs[0],
+                                     output_node.inputs[0])
+                move_node_to_node(cut_node, output_node, (-300, 0))
+            else:
+                pre_output_node = output_node.inputs[0].links[0].from_node
+                node_group.links.new(pre_output_node.outputs[0],
+                                     cut_node.inputs[0])
+                node_group.links.new(cut_node.outputs[0],
+                                     output_node.inputs[0])
+                move_node_between_nodes(cut_node,
+                                        [pre_output_node, output_node])
+
+            node_group.links.new(cutter_node.outputs[0],
+                                 cut_node.inputs[1])
+
+            move_node_to_node(cutter_node, cut_node, (-300, -300))
+            select_object(cutter_obj)
+        else:
+            move_node_to_node(cutter_node, output_node, (0, -100))
+            select_object(container_obj)
+
+        return {'FINISHED'}
+
+
+class AddPlaneCutter(bpy.types.Operator, AddCutter):
+    bl_idname = "bioxelnodes.add_plane_cutter"
+    bl_label = "Add a Plane Cutter"
+    bl_description = "Add a Plane Cutter to Container"
+    object_type = "plane"
+
+
+class AddCylinderCutter(bpy.types.Operator, AddCutter):
+    bl_idname = "bioxelnodes.add_cylinder_cutter"
+    bl_label = "Add a Cylinder Cutter"
+    bl_description = "Add a Cylinder Cutter to Container"
+    object_type = "cylinder"
+
+
+class AddCubeCutter(bpy.types.Operator, AddCutter):
+    bl_idname = "bioxelnodes.add_cube_cutter"
+    bl_label = "Add a Cube Cutter"
+    bl_description = "Add a Cube Cutter to Container"
+    object_type = "cube"
+
+
+class AddSphereCutter(bpy.types.Operator, AddCutter):
+    bl_idname = "bioxelnodes.add_sphere_cutter"
+    bl_label = "Add a Sphere Cutter"
+    bl_description = "Add a Sphere Cutter to Container"
+    object_type = "sphere"
+
+
+class AddPieCutter(bpy.types.Operator, AddCutter):
+    bl_idname = "bioxelnodes.add_pie_cutter"
+    bl_label = "Add a Pie Cutter"
+    bl_description = "Add a Pie Cutter to Container"
+    object_type = "pie"

bioxelnodes/operators/io.py

@@ -0,0 +1,790 @@
+import math
+import bpy
+import shutil
+import threading
+import numpy as np
+from pathlib import Path
+
+
+from ..exceptions import CancelledByUser
+from ..props import BIOXELNODES_Series
+from ..bioxel.layer import Layer
+from ..bioxelutils.layer import (get_all_layer_objs,
+                                 get_layer_obj)
+from ..bioxelutils.container import (Container,
+                                     add_layers,
+                                     container_to_obj,
+                                     get_container_objs_from_selection)
+from ..bioxel.parse import (DICOM_EXTS, SUPPORT_EXTS,
+                            get_ext, parse_volumetric_data)
+from .utils import (change_render_setting, get_cache_dir, get_preferences,
+                    progress_update, progress_bar, select_object)
+
+# 3rd-party
+import SimpleITK as sitk
+import transforms3d
+
+FH_EXTS = ['', '.dcm', '.DCM', '.DICOM', '.ima', '.IMA',
+           '.gipl', '.gipl.gz',
+           '.mnc', '.MNC',
+           '.mrc', '.rec',
+           '.mha', '.mhd',
+           '.nia', '.nii', '.nii.gz', '.hdr', '.img', '.img.gz',
+           '.hdf', '.h4', '.hdf4', '.he2', '.h5', '.hdf5', '.he5',
+           '.nrrd', '.nhdr',
+           '.vtk',
+           '.gz'
+           '.ome.tiff', '.ome.tif',
+           '.mrc', '.mrc.gz', '.map', '.map.gz']
+
+
+def get_layer_shape(bioxel_size: float, orig_shape: tuple, orig_spacing: tuple):
+    shape = (int(orig_shape[0] / bioxel_size * orig_spacing[0]),
+             int(orig_shape[1] / bioxel_size * orig_spacing[1]),
+             int(orig_shape[2] / bioxel_size * orig_spacing[2]))
+
+    return (shape[0] if shape[0] > 0 else 1,
+            shape[1] if shape[1] > 0 else 1,
+            shape[2] if shape[2] > 0 else 1)
+
+
+def get_layer_size(shape: tuple, bioxel_size: float, scale: float = 1.0):
+    size = (float(shape[0] * bioxel_size * scale),
+            float(shape[1] * bioxel_size * scale),
+            float(shape[2] * bioxel_size * scale))
+
+    return size
+
+
+"""
+ImportVolumetricData
+                        -> ParseVolumetricData -> ImportVolumetricDataDialog
+FH_ImportVolumetricData
+
+ start import                  parse data               execute import
+"""
+
+
+class ImportVolumetricData():
+    bl_options = {'UNDO'}
+
+    filepath: bpy.props.StringProperty(subtype="FILE_PATH")  # type: ignore
+    directory: bpy.props.StringProperty(subtype='DIR_PATH')  # type: ignore
+
+    read_as = "scalar"
+
+    def execute(self, context):
+        container_objs = get_container_objs_from_selection()
+
+        if len(container_objs) > 0:
+            bpy.ops.bioxelnodes.parse_volumetric_data('INVOKE_DEFAULT',
+                                                      filepath=self.filepath,
+                                                      directory=self.directory,
+                                                      container_obj_name=container_objs[0].name,
+                                                      read_as=self.read_as)
+        else:
+            bpy.ops.bioxelnodes.parse_volumetric_data('INVOKE_DEFAULT',
+                                                      filepath=self.filepath,
+                                                      directory=self.directory,
+                                                      read_as=self.read_as)
+
+        return {'FINISHED'}
+
+    def invoke(self, context, event):
+        context.window_manager.fileselect_add(self)
+        return {'RUNNING_MODAL'}
+
+
+class ImportAsScalarLayer(bpy.types.Operator, ImportVolumetricData):
+    bl_idname = "bioxelnodes.import_as_scalar_layer"
+    bl_label = "Import as Scalar"
+    bl_description = "Import Volumetric Data to Container as Scalar"
+    read_as = "scalar"
+
+
+class ImportAsLabelLayer(bpy.types.Operator, ImportVolumetricData):
+    bl_idname = "bioxelnodes.import_as_label_layer"
+    bl_label = "Import as Label"
+    bl_description = "Import Volumetric Data to Container as Label"
+    read_as = "label"
+
+
+class BIOXELNODES_FH_ImportVolumetricData(bpy.types.FileHandler):
+    bl_idname = "BIOXELNODES_FH_ImportVolumetricData"
+    bl_label = "File handler for dicom import"
+    bl_import_operator = "bioxelnodes.parse_volumetric_data"
+    bl_file_extensions = ";".join(FH_EXTS)
+
+    @classmethod
+    def poll_drop(cls, context):
+        return (context.area and context.area.type == 'VIEW_3D')
+
+
+def get_series_ids(self, context):
+    items = []
+    for index, series_id in enumerate(self.series_ids):
+        items.append((
+            series_id.id,
+            series_id.label,
+            "",
+            index
+        ))
+
+    return items
+
+
+class ParseVolumetricData(bpy.types.Operator):
+    bl_idname = "bioxelnodes.parse_volumetric_data"
+    bl_label = "Import Volumetric Data"
+    bl_description = "Import Volumetric Data as Layer"
+    bl_options = {'UNDO'}
+
+    meta = None
+    thread = None
+    _timer = None
+
+    progress: bpy.props.FloatProperty(name="Progress",
+                                      options={"SKIP_SAVE"},
+                                      default=1)  # type: ignore
+
+    filepath: bpy.props.StringProperty(subtype="FILE_PATH")  # type: ignore
+    directory: bpy.props.StringProperty(subtype='DIR_PATH')  # type: ignore
+    container_obj_name: bpy.props.StringProperty()   # type: ignore
+
+    read_as: bpy.props.EnumProperty(name="Read as",
+                                    default="scalar",
+                                    items=[("scalar", "Scalar", ""),
+                                           ("label", "Labels", "")])  # type: ignore
+
+    series_id: bpy.props.EnumProperty(name="Select Series",
+                                      items=get_series_ids)  # type: ignore
+
+    series_ids: bpy.props.CollectionProperty(
+        type=BIOXELNODES_Series)  # type: ignore
+
+    def execute(self, context):
+        data_path = Path(self.filepath).resolve()
+        ext = get_ext(data_path)
+        if ext not in SUPPORT_EXTS:
+            self.report({"WARNING"}, "Not supported extension.")
+            return {'CANCELLED'}
+
+        print("Collecting Meta Data...")
+
+        def parse_volumetric_data_func(self, context, cancel):
+            def progress_callback(factor, text):
+                if cancel():
+                    raise CancelledByUser
+                progress_update(context, factor, text)
+
+            try:
+                series_id = self.series_id if self.series_id != "empty" else ""
+                data, meta = parse_volumetric_data(data_file=self.filepath,
+                                                   series_id=series_id,
+                                                   progress_callback=progress_callback)
+            except CancelledByUser:
+                return
+            except Exception as e:
+                self.has_error = e
+                return
+
+            if cancel():
+                return
+
+            self.meta = meta
+
+        # Init cancel flag
+        self.is_cancelled = False
+        self.has_error = None
+
+        # Create the thread
+        self.thread = threading.Thread(target=parse_volumetric_data_func,
+                                       args=(self, context, lambda: self.is_cancelled))
+
+        # Start the thread
+        self.thread.start()
+        # Add a timmer for modal
+        self._timer = context.window_manager.event_timer_add(time_step=0.1,
+                                                             window=context.window)
+        # Append progress bar to status bar
+        bpy.types.STATUSBAR_HT_header.append(progress_bar)
+
+        # Start modal handler
+        context.window_manager.modal_handler_add(self)
+        return {'RUNNING_MODAL'}
+
+    def modal(self, context, event):
+        # Check if user press 'ESC'
+        if event.type == 'ESC':
+            self.is_cancelled = True
+            progress_update(context, 0, "Canceling...")
+            return {'PASS_THROUGH'}
+
+        # Check if is the timer time
+        if event.type != 'TIMER':
+            return {'PASS_THROUGH'}
+
+        # Force update status bar
+        bpy.context.workspace.status_text_set_internal(None)
+
+        # Check if thread is still running
+        if self.thread.is_alive():
+            return {'PASS_THROUGH'}
+
+        # Release the thread
+        self.thread.join()
+        # Remove the timer
+        context.window_manager.event_timer_remove(self._timer)
+        # Remove the progress bar from status bar
+        bpy.types.STATUSBAR_HT_header.remove(progress_bar)
+
+        # Check if thread is cancelled by user
+        if self.is_cancelled:
+            self.report({"WARNING"}, "Canncelled by user.")
+            return {'CANCELLED'}
+
+        # Check if thread is cancelled by user
+        if self.has_error:
+            raise self.has_error
+
+        # Check if has return
+        if self.meta is None:
+            self.report({"ERROR"}, "Some thing went wrong.")
+            return {'CANCELLED'}
+
+        # If not canncelled...
+        for key, value in self.meta.items():
+            print(f"{key}: {value}")
+
+        orig_shape = self.meta['xyz_shape']
+        orig_spacing = self.meta['spacing']
+        min_size = min(orig_spacing[0],
+                       orig_spacing[1], orig_spacing[2])
+        bioxel_size = max(min_size, 1.0)
+
+        layer_shape = get_layer_shape(1, orig_shape, orig_spacing)
+        layer_size = get_layer_size(layer_shape,
+                                    bioxel_size)
+        log10 = math.floor(math.log10(max(*layer_size)))
+        log10 = max(1, log10)
+        log10 = min(3, log10)
+        scene_scale = math.pow(10, -log10)
+
+        if self.container_obj_name:
+            container_obj = bpy.data.objects.get(self.container_obj_name)
+            container_name = container_obj.name
+        else:
+            container_name = self.meta['name']
+
+        series_id = self.series_id if self.series_id != "empty" else ""
+        bpy.ops.bioxelnodes.import_volumetric_data_dialog(
+            'INVOKE_DEFAULT',
+            filepath=self.filepath,
+            container_name=container_name,
+            layer_name=self.meta['description'],
+            orig_shape=orig_shape,
+            orig_spacing=orig_spacing,
+            bioxel_size=bioxel_size,
+            series_id=series_id,
+            frame_count=self.meta['frame_count'],
+            channel_count=self.meta['channel_count'],
+            container_obj_name=self.container_obj_name,
+            read_as=self.read_as,
+            scene_scale=scene_scale
+        )
+
+        self.report({"INFO"}, "Successfully Readed.")
+        return {'FINISHED'}
+
+    def invoke(self, context, event):
+        if not self.filepath and not self.directory:
+            return {'CANCELLED'}
+
+        data_path = Path(self.filepath).resolve()
+        ext = get_ext(data_path)
+
+        # Series Selection
+        if ext in DICOM_EXTS:
+            data_dirpath = data_path.parent
+            reader = sitk.ImageSeriesReader()
+            reader.MetaDataDictionaryArrayUpdateOn()
+            reader.LoadPrivateTagsOn()
+
+            series_ids = reader.GetGDCMSeriesIDs(str(data_dirpath))
+            series_items = {}
+
+            for series_id in series_ids:
+                series_files = reader.GetGDCMSeriesFileNames(
+                    str(data_dirpath), series_id)
+                single = sitk.ImageFileReader()
+                single.SetFileName(series_files[0])
+                single.LoadPrivateTagsOn()
+                single.ReadImageInformation()
+
+                def get_meta(key):
+                    try:
+                        stirng = single.GetMetaData(key).removesuffix(" ")
+                        if stirng in ["No study description",
+                                      "No series description",
+                                      ""]:
+                            return "Unknown"
+                        else:
+                            return stirng
+                    except:
+                        return "Unknown"
+
+                study_description = get_meta("0008|1030")
+                series_description = get_meta("0008|103e")
+                series_modality = get_meta("0008|0060")
+                size_x = get_meta("0028|0011")
+                size_y = get_meta("0028|0010")
+                count = get_meta("0020|0013")
+                count = count if count != "Unknown" else 1
+
+                # some series image count = 0 ????
+                if int(count) == 0:
+                    continue
+
+                # series_id cannot be "" in blender selection
+                if series_id == "":
+                    series_id = "empty"
+
+                series_items[series_id] = "{:<20} {:>1}".format(f"{study_description}>{series_description}({series_modality})",
+                                                                f"({size_x}x{size_y})x{count}")
+
+            for key, value in series_items.items():
+                series_item = self.series_ids.add()
+                series_item.id = key
+                series_item.label = value
+
+            if len(series_items.keys()) > 1:
+                context.window_manager.invoke_props_dialog(self,
+                                                           width=400,
+                                                           title="Which series to import?")
+                return {'RUNNING_MODAL'}
+            elif len(series_items.keys()) == 1:
+                self.series_id = list(series_items.keys())[0]
+            else:
+                self.report({"ERROR"}, "Get no vaild series.")
+                return {'CANCELLED'}
+
+        self.execute(context)
+        return {'RUNNING_MODAL'}
+
+    def draw(self, context):
+        layout = self.layout
+        layout.label(
+            text='Detect multi-series in DICOM, pick one')
+        layout.prop(self, "series_id")
+
+
+def get_sequence_sources(self, context):
+    items = [("-1", "None (Static)", "")]
+    orig_shape = tuple(self.orig_shape)
+    if self.frame_count > 1:
+        items.append(("0", f"Frame (Get {self.frame_count} frames)", ""))
+    elif self.frame_count == 1 and self.channel_count > 1:
+        items.append(("4", f"Channel (Get {self.channel_count} frames)", ""))
+    elif self.frame_count == 1 and self.channel_count == 1:
+        items.append(("1", f"X (Get {orig_shape[0]} frames)", ""))
+        items.append(("2", f"Y (Get {orig_shape[1]} frames)", ""))
+        items.append(("3", f"Z (Get {orig_shape[2]} frames)", ""))
+
+    return items
+
+
+class ImportVolumetricDataDialog(bpy.types.Operator):
+    bl_idname = "bioxelnodes.import_volumetric_data_dialog"
+    bl_label = "Import Volumetric Data"
+    bl_description = "Import Volumetric Data as Layer"
+    bl_options = {'UNDO'}
+
+    layers = None
+    thread = None
+    _timer = None
+
+    filepath: bpy.props.StringProperty(subtype="FILE_PATH")  # type: ignore
+
+    container_name: bpy.props.StringProperty(
+        name="Container Name")   # type: ignore
+
+    layer_name: bpy.props.StringProperty(name="Layer Name")   # type: ignore
+
+    series_id: bpy.props.StringProperty()   # type: ignore
+
+    container_obj_name: bpy.props.StringProperty()   # type: ignore
+
+    frame_count: bpy.props.IntProperty()  # type: ignore
+
+    channel_count: bpy.props.IntProperty()  # type: ignore
+
+    read_as: bpy.props.EnumProperty(name="Read as",
+                                    default="scalar",
+                                    items=[("scalar", "Scalar", ""),
+                                           ("label", "Labels", "")])  # type: ignore
+
+    bioxel_size: bpy.props.FloatProperty(name="Bioxel Size (Larger size means small resolution)",
+                                         soft_min=0.1, soft_max=10.0,
+                                         min=0.1, max=1e2,
+                                         default=1)  # type: ignore
+
+    orig_spacing: bpy.props.FloatVectorProperty(name="Original Spacing",
+                                                default=(1, 1, 1))  # type: ignore
+
+    orig_shape: bpy.props.IntVectorProperty(name="Original Shape",
+                                            default=(100, 100, 100))  # type: ignore
+
+    scene_scale: bpy.props.FloatProperty(name="Scene Scale (Bioxel Unit pre Blender Unit)",
+                                         soft_min=0.0001, soft_max=10.0,
+                                         min=1e-6, max=1e6,
+                                         default=0.01)  # type: ignore
+
+    split_channels: bpy.props.BoolProperty(name="Split Channels",
+                                           default=False)  # type: ignore
+
+    sequence_source: bpy.props.EnumProperty(name="Time Sequence From",
+                                            items=get_sequence_sources)  # type: ignore
+
+    def execute(self, context):
+        def import_volumetric_data_func(self, context, cancel):
+            progress_update(context, 0.0, "Parsing Volumetirc Data...")
+
+            def progress_callback(factor, text):
+                if cancel():
+                    raise CancelledByUser
+                progress_update(context, factor*0.2, text)
+
+            try:
+                data, meta = parse_volumetric_data(data_file=self.filepath,
+                                                   series_id=self.series_id,
+                                                   progress_callback=progress_callback)
+            except CancelledByUser:
+                return
+            except Exception as e:
+                self.has_error = e
+                return
+
+            if cancel():
+                return
+
+            shape = get_layer_shape(self.bioxel_size,
+                                    self.orig_shape,
+                                    self.orig_spacing)
+
+            mat_scale = transforms3d.zooms.zfdir2aff(self.bioxel_size)
+            affine = np.dot(meta['affine'], mat_scale)
+            kind = self.read_as
+
+            if cancel():
+                return
+
+            # change shape as sequence or not
+            if self.sequence_source == "-1":
+                data = data[0:1, :, :, :, :]
+            elif self.sequence_source == "0":
+                # frame as frame
+                pass
+            elif self.sequence_source == "1":
+                # X as frame
+                data = data.transpose(1, 0, 2, 3, 4)
+                shape = (1, shape[1], shape[2])
+            elif self.sequence_source == "2":
+                # Y as frame
+                data = data.transpose(2, 1, 0, 3, 4)
+                shape = (shape[0], 1, shape[2])
+            elif self.sequence_source == "3":
+                # Z as frame
+                data = data.transpose(3, 1, 2, 0, 4)
+                shape = (shape[0], shape[1], 1)
+            else:
+                # channel as frame
+                data = data.transpose(4, 1, 2, 3, 0)
+
+            def progress_callback_factory(layer_name, progress, progress_step):
+                def progress_callback(frame, total):
+                    if cancel():
+                        raise CancelledByUser
+                    sub_progress_step = progress_step/total
+                    sub_progress = progress + frame * sub_progress_step
+                    progress_update(context, sub_progress,
+                                    f"Processing {layer_name} Frame {frame+1}...")
+                return progress_callback
+
+            layers = []
+            if kind == "label":
+                name = self.layer_name or "Label"
+                data = data.astype(int)
+                label_count = int(np.max(data))
+                progress_step = 0.7/label_count
+
+                for i in range(label_count):
+                    if cancel():
+                        return
+
+                    name_i = f"{name}_{i+1}"
+                    progress = 0.2+i*progress_step
+                    progress_update(context, progress,
+                                    f"Processing {name_i}...")
+
+                    progress_callback = progress_callback_factory(name_i,
+                                                                  progress,
+                                                                  progress_step)
+                    try:
+                        layer = Layer(data=data == np.full_like(data, i+1),
+                                      name=name_i,
+                                      kind=kind,
+                                      affine=affine)
+
+                        layer.resize(shape=shape,
+                                     progress_callback=progress_callback)
+
+                        layers.append(layer)
+                    except CancelledByUser:
+                        return
+                    except Exception as e:
+                        self.has_error = e
+                        return
+
+            elif kind == "scalar":
+                name = self.layer_name or "Scalar"
+
+                if self.split_channels:
+                    progress_step = 0.7/self.channel_count
+
+                    for i in range(self.channel_count):
+                        if cancel():
+                            return
+
+                        name_i = f"{name}_{i+1}"
+                        progress = 0.2 + i*progress_step
+                        progress_update(context, progress,
+                                        f"Processing {name_i}...")
+                        progress_callback = progress_callback_factory(name_i,
+                                                                      progress,
+                                                                      progress_step)
+                        try:
+                            layer = Layer(data=data[:, :, :, :, i:i+1],
+                                          name=name_i,
+                                          kind=kind,
+                                          affine=affine)
+
+                            layer.resize(shape=shape,
+                                         progress_callback=progress_callback)
+
+                            layers.append(layer)
+                        except CancelledByUser:
+                            return
+                        except Exception as e:
+                            self.has_error = e
+                            return
+                else:
+                    if cancel():
+                        return
+
+                    progress_update(context, 0.2,
+                                    f"Processing {name}...")
+                    progress_callback = progress_callback_factory(name,
+                                                                  0.2,
+                                                                  0.7)
+
+                    try:
+                        layer = Layer(data=data,
+                                      name=name,
+                                      kind=kind,
+                                      affine=affine)
+
+                        layer.resize(shape=shape,
+                                     progress_callback=progress_callback)
+
+                        layers.append(layer)
+                    except CancelledByUser:
+                        return
+                    except Exception as e:
+                        self.has_error = e
+                        return
+
+            if cancel():
+                return
+
+            self.layers = layers
+            progress_update(context, 0.9, "Creating Layers...")
+
+        self.is_cancelled = False
+        self.has_error = None
+
+        self.thread = threading.Thread(target=import_volumetric_data_func,
+                                       args=(self, context, lambda: self.is_cancelled))
+
+        self.thread.start()
+        self._timer = context.window_manager.event_timer_add(time_step=0.1,
+                                                             window=context.window)
+        bpy.types.STATUSBAR_HT_header.append(progress_bar)
+
+        context.window_manager.modal_handler_add(self)
+        return {'RUNNING_MODAL'}
+
+    def modal(self, context, event):
+        if event.type == 'ESC':
+            self.is_cancelled = True
+            progress_update(context, 0, "Canceling...")
+            return {'PASS_THROUGH'}
+
+        if event.type != 'TIMER':
+            return {'PASS_THROUGH'}
+
+        bpy.context.workspace.status_text_set_internal(None)
+        if self.thread.is_alive():
+            return {'PASS_THROUGH'}
+
+        self.thread.join()
+        context.window_manager.event_timer_remove(self._timer)
+        bpy.types.STATUSBAR_HT_header.remove(progress_bar)
+
+        if self.is_cancelled:
+            self.report({"WARNING"}, "Canncelled by user.")
+            return {'CANCELLED'}
+
+        # Check if thread is cancelled by user
+        if self.has_error:
+            raise self.has_error
+
+        # Check if has return
+        if self.layers is None:
+            self.report({"ERROR"}, "Some thing went wrong.")
+            return {'CANCELLED'}
+
+        is_first_import = len(get_all_layer_objs()) == 0
+
+        if self.container_obj_name:
+            container_obj = bpy.data.objects.get(self.container_obj_name)
+            if container_obj is None:
+                raise Exception("Could not find target container")
+
+            container_obj = add_layers(self.layers,
+                                       container_obj=container_obj,
+                                       cache_dir=get_cache_dir(context))
+        else:
+            container = Container(name=self.container_name,
+                                  layers=self.layers)
+
+            container_obj = container_to_obj(container,
+                                             scene_scale=self.scene_scale,
+                                             cache_dir=get_cache_dir(context))
+
+        select_object(container_obj)
+
+        # Change render setting for better result
+        if is_first_import:
+            change_render_setting(context)
+
+        self.report({"INFO"}, "Successfully Imported")
+        return {'FINISHED'}
+
+    def invoke(self, context, event):
+        if self.read_as == "label":
+            volume_dtype = "Label"
+        elif self.read_as == "scalar":
+            volume_dtype = "Scalar"
+        title = f"As {volume_dtype} Opitons (Add to Container: {self.container_obj_name})" \
+            if self.container_obj_name != "" else f"As {volume_dtype} Options (Init a Container)"
+        context.window_manager.invoke_props_dialog(self,
+                                                   width=500,
+                                                   title=title)
+        return {'RUNNING_MODAL'}
+
+    def draw(self, context):
+        layer_shape = get_layer_shape(self.bioxel_size,
+                                      self.orig_shape,
+                                      self.orig_spacing)
+
+        orig_shape = tuple(self.orig_shape)
+
+        # change shape as sequence or not
+        channel_count = self.channel_count
+        if self.sequence_source == "-1":
+            pass
+        elif self.sequence_source == "0":
+            # frame as frame
+            pass
+        elif self.sequence_source == "1":
+            layer_shape = (1, layer_shape[1], layer_shape[2])
+        elif self.sequence_source == "2":
+            layer_shape = (layer_shape[0], 1, layer_shape[2])
+        elif self.sequence_source == "3":
+            layer_shape = (layer_shape[0], layer_shape[1], 1)
+        else:
+            channel_count = 1
+
+        import_channel = channel_count if self.split_channels or channel_count == 1 else "combined"
+
+        bioxel_count = layer_shape[0] * layer_shape[1] * layer_shape[2]
+        layer_shape_text = f"Shape from {str(orig_shape)} to {str(layer_shape)}"
+        if bioxel_count > 100000000:
+            layer_shape_text += "**TOO LARGE!**"
+
+        layout = self.layout
+        if self.container_obj_name == "":
+            layout.prop(self, "container_name")
+        layout.prop(self, "layer_name")
+
+        panel = layout.box()
+        panel.prop(self, "bioxel_size")
+        row = panel.row()
+        row.prop(self, "orig_spacing")
+        panel.label(text=layer_shape_text)
+
+        panel = layout.box()
+        panel.prop(self, "sequence_source")
+
+        if self.read_as == "scalar":
+            panel = layout.box()
+            panel.prop(self, "split_channels",
+                       text=f"Split Channels (Get {channel_count} channels, import {import_channel} channels)")
+
+        if self.container_obj_name == "":
+            layer_size = get_layer_size(layer_shape,
+                                        self.bioxel_size,
+                                        self.scene_scale)
+            layer_size_text = f"Size will be: ({layer_size[0]:.2f}, {layer_size[1]:.2f}, {layer_size[2]:.2f}) m"
+            panel = layout.box()
+            panel.prop(self, "scene_scale")
+            panel.label(text=layer_size_text)
+
+
+class ExportVolumetricData(bpy.types.Operator):
+    bl_idname = "bioxelnodes.export_volumetric_data"
+    bl_label = "Export Layer as VDB"
+    bl_description = "Export Layer as VDB"
+    bl_options = {'UNDO'}
+
+    filepath: bpy.props.StringProperty(
+        subtype="FILE_PATH"
+    )  # type: ignore
+
+    filename_ext = ".vdb"
+
+    @classmethod
+    def poll(cls, context):
+        layer_obj = get_layer_obj(bpy.context.active_object)
+        return True if layer_obj else False
+
+    def invoke(self, context, event):
+        context.window_manager.fileselect_add(self)
+        return {'RUNNING_MODAL'}
+
+    def execute(self, context):
+        layer_obj = get_layer_obj(bpy.context.active_object)
+
+        filepath = f"{self.filepath.split('.')[0]}.vdb"
+        # "//"
+        source_dir = bpy.path.abspath(layer_obj.data.filepath)
+
+        output_path: Path = Path(filepath).resolve()
+        source_path: Path = Path(source_dir).resolve()
+        # print('output_path', output_path)
+        # print('source_path', source_path)
+        shutil.copy(source_path, output_path)
+
+        self.report({"INFO"}, f"Successfully exported to {output_path}")
+
+        return {'FINISHED'}

bioxelnodes/operators/layer.py

@@ -0,0 +1,251 @@
+from pathlib import Path
+import bpy
+
+import numpy as np
+
+
+from ..bioxel.layer import Layer
+from ..bioxelutils.node import get_nodes_by_type
+from ..bioxelutils.container import add_layers, get_container_obj
+from ..bioxelutils.layer import obj_to_layer, get_container_layer_objs, get_layer_obj
+from .utils import get_preferences, select_object
+
+
+def get_layer_prop_value(layer_obj: bpy.types.Object, prop: str):
+    try:
+        node_group = layer_obj.modifiers[0].node_group
+        layer_node = get_nodes_by_type(node_group, "BioxelNodes__Layer")[0]
+        return layer_node.inputs[prop].default_value
+    except:
+        return None
+
+
+def get_label_layer_selection(self, context):
+    items = [("None", "None", "")]
+    container_obj = get_container_obj(bpy.context.active_object)
+
+    for layer_obj in get_container_layer_objs(container_obj):
+        if get_layer_prop_value(layer_obj, "kind") == "label":
+            items.append((layer_obj.name,
+                          layer_obj.name,
+                          ""))
+
+    return items
+
+
+class LayerOperator():
+    bl_options = {'UNDO'}
+    base_obj: bpy.types.Object = None
+
+    def add_layer(self, context, layer):
+        preferences = get_preferences(context)
+        cache_dir = Path(preferences.cache_dir, 'VDBs')
+        container_obj = self.base_obj.parent
+
+        add_layers([layer],
+                   container_obj,
+                   cache_dir)
+
+        select_object(container_obj)
+
+    def invoke(self, context, event):
+        self.base_obj = get_layer_obj(bpy.context.active_object)
+        return self.execute(context)
+
+
+class ScalarOperator(LayerOperator):
+    @classmethod
+    def poll(cls, context):
+        label_objs = [obj for obj in context.selected_ids
+                      if get_layer_prop_value(obj, "kind") == "scalar"]
+        return True if len(label_objs) > 0 else False
+
+
+class LabelOperator(LayerOperator):
+    @classmethod
+    def poll(cls, context):
+        label_objs = [obj for obj in context.selected_ids
+                      if get_layer_prop_value(obj, "kind") == "label"]
+        return True if len(label_objs) > 0 else False
+
+
+class SignScalar(bpy.types.Operator, ScalarOperator):
+    bl_idname = "bioxelnodes.sign_scalar"
+    bl_label = "Sign Scalar"
+    bl_description = "Sign the scalar value"
+
+    def execute(self, context):
+        base_layer = obj_to_layer(self.base_obj)
+
+        modified_layer = base_layer.copy()
+        modified_layer.data = -base_layer.data
+        modified_layer.name = f"{base_layer.name}_Signed"
+
+        self.add_layer(context, modified_layer)
+        return {'FINISHED'}
+
+
+class FillOperator(ScalarOperator):
+    def invoke(self, context, event):
+        self.base_obj = get_layer_obj(bpy.context.active_object)
+        scalar_min = get_layer_prop_value(self.base_obj, "min")
+        self.fill_value = min(scalar_min, 0)
+        context.window_manager.invoke_props_dialog(self, width=400)
+        return {'RUNNING_MODAL'}
+
+
+class FillByThreshold(bpy.types.Operator, FillOperator):
+    bl_idname = "bioxelnodes.fill_by_threshold"
+    bl_label = "Fill Value by Threshold"
+    bl_description = "Fill Value by Threshold"
+
+    threshold: bpy.props.FloatProperty(
+        name="Threshold",
+        soft_min=0, soft_max=1024,
+        default=128,
+    )  # type: ignore
+
+    fill_value: bpy.props.FloatProperty(
+        name="Fill Value",
+        soft_min=0, soft_max=1024.0,
+        default=0,
+    )  # type: ignore
+
+    invert: bpy.props.BoolProperty(
+        name="Invert Area",
+        default=True,
+    )  # type: ignore
+
+    def execute(self, context):
+        base_layer = obj_to_layer(self.base_obj)
+
+        data = np.amax(base_layer.data, -1)
+        mask = data <= self.threshold \
+            if self.invert else data > self.threshold
+
+        modified_layer = base_layer.copy()
+        modified_layer.fill(self.fill_value, mask)
+        modified_layer.name = f"{base_layer.name}_{self.threshold}-Filled"
+
+        self.add_layer(context, modified_layer)
+
+        return {'FINISHED'}
+
+
+class FillByRange(bpy.types.Operator, FillOperator):
+    bl_idname = "bioxelnodes.fill_by_range"
+    bl_label = "Fill Value by Range"
+    bl_description = "Fill Value by Range"
+
+    from_min: bpy.props.FloatProperty(
+        name="From Min",
+        soft_min=0, soft_max=1024,
+        default=128,
+    )  # type: ignore
+
+    from_max: bpy.props.FloatProperty(
+        name="From Max",
+        soft_min=0, soft_max=1024,
+        default=256,
+    )  # type: ignore
+
+    fill_value: bpy.props.FloatProperty(
+        name="Fill Value",
+        soft_min=0, soft_max=1024.0,
+        default=0,
+    )  # type: ignore
+
+    invert: bpy.props.BoolProperty(
+        name="Invert Area",
+        default=True,
+    )  # type: ignore
+
+    def execute(self, context):
+        base_layer = obj_to_layer(self.base_obj)
+
+        data = np.amax(base_layer.data, -1)
+        mask = (data <= self.from_min) | (data >= self.from_max) if self.invert else \
+            (data > self.from_min) & (data < self.from_max)
+
+        modified_layer = base_layer.copy()
+        modified_layer.fill(self.fill_value, mask)
+        modified_layer.name = f"{base_layer.name}_{self.from_min}-{self.from_max}-Filled"
+
+        self.add_layer(context, modified_layer)
+        return {'FINISHED'}
+
+
+class FillByLabel(bpy.types.Operator, FillOperator):
+    bl_idname = "bioxelnodes.fill_by_label"
+    bl_label = "Fill Value by Label"
+    bl_description = "Fill Value by Label Area"
+
+    label_obj_name: bpy.props.EnumProperty(
+        name="Label Layer",
+        items=get_label_layer_selection
+    )  # type: ignore
+
+    fill_value: bpy.props.FloatProperty(
+        name="Fill Value",
+        soft_min=0, soft_max=1024.0,
+        default=0,
+    )  # type: ignore
+
+    invert: bpy.props.BoolProperty(
+        name="Invert Label",
+        default=True,
+    )  # type: ignore
+
+    def execute(self, context):
+        label_obj = bpy.data.objects.get(self.label_obj_name)
+        if not label_obj:
+            self.report({"WARNING"}, "Cannot find any label layer.")
+            return {'FINISHED'}
+
+        base_layer = obj_to_layer(self.base_obj)
+
+        label_layer = obj_to_layer(label_obj)
+        label_layer.resize(base_layer.shape)
+        mask = np.amax(label_layer.data, -1)
+        if self.invert:
+            mask = 1 - mask
+
+        modified_layer = base_layer.copy()
+        modified_layer.fill(self.fill_value, mask)
+        modified_layer.name = f"{base_layer.name}_{label_layer.name}-Filled"
+
+        self.add_layer(context, modified_layer)
+        return {'FINISHED'}
+
+
+class CombineLabels(bpy.types.Operator, LabelOperator):
+    bl_idname = "bioxelnodes.combine_labels"
+    bl_label = "Combine Labels"
+    bl_description = "Combine all selected labels"
+
+    def execute(self, context):
+        label_objs = [obj for obj in context.selected_ids
+                      if get_layer_prop_value(obj, "kind") == "label"]
+
+        if len(label_objs) < 2:
+            self.report({"WARNING"}, "Not enough layers.")
+            return {'FINISHED'}
+        base_obj = label_objs[0]
+        label_objs = label_objs[1:]
+        container_obj = base_obj.parent
+
+        base_layer = obj_to_layer(base_obj)
+        modified_layer = base_layer.copy()
+        label_names = [base_layer.name]
+
+        for label_obj in label_objs:
+            label_layer = obj_to_layer(label_obj)
+            label_layer.resize(base_layer.shape)
+            modified_layer.data = np.maximum(base_layer.data, label_layer.data)
+            label_names.append(label_layer.name)
+
+        modified_layer.name = f"{'-'.join(label_names)}-Combined"
+
+        self.add_layer(context, modified_layer)
+
+        return {'FINISHED'}

bioxelnodes/operators/misc.py

@@ -0,0 +1,215 @@
+import re
+import bpy
+from pathlib import Path
+import shutil
+
+
+from ..utils import copy_to_dir
+from .utils import get_cache_dir
+from ..nodes import custom_nodes
+from ..bioxelutils.container import get_container_objs_from_selection
+from ..bioxelutils.layer import get_all_layer_objs, get_container_layer_objs
+
+CLASS_PREFIX = "BIOXELNODES_MT_NODES"
+
+
+class ReLinkNodes(bpy.types.Operator):
+    bl_idname = "bioxelnodes.relink_nodes"
+    bl_label = "Relink Nodes to Addon"
+    bl_description = "Relink all nodes to addon source"
+
+    def execute(self, context):
+        file_name = Path(custom_nodes.nodes_file).name
+        for lib in bpy.data.libraries:
+            lib_path = Path(bpy.path.abspath(lib.filepath)).resolve()
+            lib_name = lib_path.name
+            if lib_name == file_name:
+                if str(lib_path) != custom_nodes.nodes_file:
+                    lib.filepath = custom_nodes.nodes_file
+
+        self.report({"INFO"}, f"Successfully relinked.")
+
+        return {'FINISHED'}
+
+
+def save_layer_cache(layer_obj, output_dir):
+    pattern = r'\.\d{4}\.'
+
+    # "//"
+    output_dir = bpy.path.abspath(output_dir)
+    source_dir = bpy.path.abspath(layer_obj.data.filepath)
+
+    source_path: Path = Path(source_dir).resolve()
+    is_sequence = re.search(pattern, source_path.name) is not None
+    name = layer_obj.name if is_sequence else f"{layer_obj.name}.vdb"
+    output_path: Path = Path(output_dir, name, source_path.name).resolve() \
+        if is_sequence else Path(output_dir, name).resolve()
+
+    if output_path != source_path:
+        copy_to_dir(source_path.parent if is_sequence else source_path,
+                    output_path.parent.parent if is_sequence else output_path.parent,
+                    new_name=name)
+
+    blend_path = Path(bpy.path.abspath("//")).resolve()
+
+    layer_obj.data.filepath = bpy.path.relpath(
+        str(output_path), start=str(blend_path))
+
+
+class SaveStagedData(bpy.types.Operator):
+    bl_idname = "bioxelnodes.save_staged_data"
+    bl_label = "Save Staged Data"
+    bl_description = "Save all staged data in this file for sharing"
+
+    save_layer: bpy.props.BoolProperty(
+        name="Save Layer VDB Cache",
+        default=True,
+    )  # type: ignore
+
+    cache_dir: bpy.props.StringProperty(
+        name="Cache Directory",
+        subtype='DIR_PATH',
+        default="//"
+    )  # type: ignore
+
+    save_lib: bpy.props.BoolProperty(
+        name="Save Node Library File",
+        default=True,
+    )  # type: ignore
+
+    lib_dir: bpy.props.StringProperty(
+        name="Library Directory",
+        subtype='DIR_PATH',
+        default="//"
+    )  # type: ignore
+
+    def execute(self, context):
+        if self.save_lib:
+            files = []
+            for classname in dir(bpy.types):
+                if CLASS_PREFIX in classname:
+                    cls = getattr(bpy.types, classname)
+                    files.append(cls.nodes_file)
+            files = list(set(files))
+
+            for file in files:
+                file_name = Path(file).name
+                # "//"
+                lib_dir = bpy.path.abspath(self.lib_dir)
+
+                output_path: Path = Path(lib_dir, file_name).resolve()
+                source_path: Path = Path(file).resolve()
+
+                if output_path != source_path:
+                    shutil.copy(source_path, output_path)
+
+                for lib in bpy.data.libraries:
+                    lib_path = Path(bpy.path.abspath(lib.filepath)).resolve()
+                    if lib_path == source_path:
+                        blend_path = Path(bpy.path.abspath("//")).resolve()
+                        lib.filepath = bpy.path.relpath(
+                            str(output_path), start=str(blend_path))
+
+                self.report({"INFO"}, f"Successfully saved to {output_path}")
+
+        if self.save_layer:
+            fails = []
+            for layer in get_all_layer_objs():
+                try:
+                    save_layer(layer, self.cache_dir)
+                except:
+                    fails.append(layer)
+
+            if len(fails) == 0:
+                self.report({"INFO"}, f"Successfully saved bioxel layers.")
+            else:
+                self.report(
+                    {"WARNING"}, f"{','.join([layer.name for layer in fails])} fail to save.")
+
+        return {'FINISHED'}
+
+    def invoke(self, context, event):
+        context.window_manager.invoke_props_dialog(self,
+                                                   width=500)
+        return {'RUNNING_MODAL'}
+
+    @classmethod
+    def poll(cls, context):
+        return bpy.data.is_saved
+
+    def draw(self, context):
+        layout = self.layout
+        panel = layout.box()
+        panel.prop(self, "save_layer")
+        panel.prop(self, "cache_dir")
+        panel = layout.box()
+        panel.prop(self, "save_lib")
+        panel.prop(self, "lib_dir")
+
+
+class SaveCaches(bpy.types.Operator):
+    bl_idname = "bioxelnodes.save_layers"
+    bl_label = "Save Caches"
+    bl_description = "Save Container's caches to directory."
+
+    cache_dir: bpy.props.StringProperty(
+        name="Layer Directory",
+        subtype='DIR_PATH',
+        default="//"
+    )  # type: ignore
+
+    @classmethod
+    def poll(cls, context):
+        container_objs = get_container_objs_from_selection()
+        return len(container_objs) > 0
+
+    def execute(self, context):
+        container_objs = get_container_objs_from_selection()
+
+        if len(container_objs) == 0:
+            self.report({"WARNING"}, "Cannot find any bioxel container.")
+            return {'FINISHED'}
+
+        fails = []
+        for container_obj in container_objs:
+            for layer_obj in get_container_layer_objs(container_obj):
+                try:
+                    save_layer_cache(layer_obj, self.cache_dir)
+                except:
+                    fails.append(layer_obj)
+
+        if len(fails) == 0:
+            self.report({"INFO"}, f"Successfully saved bioxel layers.")
+        else:
+            self.report(
+                {"WARNING"}, f"{','.join([layer.name for layer in fails])} fail to save.")
+
+        return {'FINISHED'}
+
+    def invoke(self, context, event):
+        context.window_manager.invoke_props_dialog(self,
+                                                   width=500)
+        return {'RUNNING_MODAL'}
+
+
+class CleanAllCaches(bpy.types.Operator):
+    bl_idname = "bioxelnodes.clear_all_caches"
+    bl_label = "Clean All Caches in Temp"
+    bl_description = "Clean all caches saved in temp"
+
+    def execute(self, context):
+        cache_dir = get_cache_dir(context)
+        try:
+            shutil.rmtree(cache_dir)
+            self.report({"INFO"}, f"Successfully cleaned caches.")
+            return {'FINISHED'}
+        except:
+            self.report({"WARNING"},
+                        "Fail to clean caches, you may do it manually.")
+            return {'CANCELLED'}
+
+    def invoke(self, context, event):
+        context.window_manager.invoke_confirm(self,
+                                              event,
+                                              message="All caches will be cleaned, include other project files, do you still want to clean?")
+        return {'RUNNING_MODAL'}

bioxelnodes/operators/utils.py

@@ -0,0 +1,60 @@
+import bpy
+from pathlib import Path
+from .. import __package__ as base_package
+
+
+def change_render_setting(context):
+    preferences = get_preferences(context)
+    if preferences.do_change_render_setting:
+        bpy.context.scene.render.engine = 'CYCLES'
+        try:
+            bpy.context.scene.cycles.shading_system = True
+            bpy.context.scene.cycles.volume_bounces = 12
+            bpy.context.scene.cycles.transparent_max_bounces = 16
+            bpy.context.scene.cycles.volume_preview_step_rate = 10
+            bpy.context.scene.cycles.volume_step_rate = 10
+        except:
+            pass
+
+        try:
+            bpy.context.scene.eevee.use_taa_reprojection = False
+            bpy.context.scene.eevee.volumetric_tile_size = '2'
+            bpy.context.scene.eevee.volumetric_shadow_samples = 128
+            bpy.context.scene.eevee.volumetric_samples = 256
+            bpy.context.scene.eevee.use_volumetric_shadows = True
+        except:
+            pass
+
+
+def select_object(target_obj):
+    for obj in bpy.data.objects:
+        obj.select_set(False)
+
+    target_obj.select_set(True)
+    bpy.context.view_layer.objects.active = target_obj
+
+
+def progress_bar(self, context):
+    row = self.layout.row()
+    row.progress(
+        factor=context.window_manager.bioxelnodes_progress_factor,
+        type="BAR",
+        text=context.window_manager.bioxelnodes_progress_text
+    )
+    row.scale_x = 2
+
+
+def progress_update(context, factor, text=""):
+    context.window_manager.bioxelnodes_progress_factor = factor
+    context.window_manager.bioxelnodes_progress_text = text
+
+
+def get_preferences(context):
+    return context.preferences.addons[base_package].preferences
+
+
+def get_cache_dir(context):
+    preferences = get_preferences(context)
+    cache_path = Path(preferences.cache_dir, 'VDBs')
+    cache_path.mkdir(parents=True, exist_ok=True)
+    return str(cache_path)

bioxelnodes/preferences.py

@@ -1,23 +1,23 @@
 import bpy
 from pathlib import Path
-from .external_package import ExternalPackagePreferences
 
-
-class BioxelNodesPreferences(bpy.types.AddonPreferences, ExternalPackagePreferences):
+class BioxelNodesPreferences(bpy.types.AddonPreferences):
     bl_idname = __package__
-    
+
     cache_dir: bpy.props.StringProperty(
-        name="Python Log Directory",
+        name="Set Cache Directory",
         subtype='DIR_PATH',
-        default=Path(Path.home(), '.bioxelnodes').as_posix()
+        default=str(Path(Path.home(), '.bioxelnodes'))
+    )  # type: ignore
+
+    do_change_render_setting: bpy.props.BoolProperty(
+        name="Change Render Setting",
+        default=True,
     )  # type: ignore
-    
 
     def draw(self, context):
         layout = self.layout
+
         layout.label(text="Configuration")
-        layout.prop(self, 'cache_dir', text='Set Cache Directory')
-        
-        # ExternalPackagePreferences Config
-        self.requirements_dir = Path(__file__).parent.as_posix()
-        super().draw(context)
+        layout.prop(self, 'cache_dir')
+        layout.prop(self, "do_change_render_setting")

bioxelnodes/props.py

@@ -0,0 +1,5 @@
+import bpy
+
+class BIOXELNODES_Series(bpy.types.PropertyGroup):
+    id: bpy.props.StringProperty()   # type: ignore
+    label: bpy.props.StringProperty()   # type: ignore

bioxelnodes/requirements.txt

@@ -1 +0,0 @@
-SimpleITK==2.3.1     # Insight Segmentation and Registration Toolkit.

bioxelnodes/utils.py

@@ -1,135 +1,32 @@
-import bpy
-import mathutils
+from pathlib import Path
+import shutil
 
 
-def show_message(message="", title="Message Box", icon='INFO'):
+def copy_to_dir(source_path, dir_path, new_name=None, exist_ok=True):
+    source = Path(source_path)
+    target = Path(dir_path)
 
-    def draw(self, context):
-        self.layout.label(text=message)
+    # Check if the source exists
+    if not source.exists():
+        raise FileNotFoundError
 
-    bpy.context.window_manager.popup_menu(draw, title=title, icon=icon)
+    # Check if the target exists
+    if not target.exists():
+        target.mkdir(parents=True, exist_ok=True)
 
+    target_path = target / new_name if new_name else target / source.name
+    # If source is a file, copy it to the target directory
+    if source.is_file():
+        try:
+            shutil.copy(source, target_path)
+        except shutil.SameFileError:
+            if exist_ok:
+                pass
+            else:
+                raise shutil.SameFileError
+    # If source is a directory, copy its contents to the target directory
+    elif source.is_dir():
+        shutil.copytree(source, target_path, dirs_exist_ok=exist_ok)
 
-def calc_bbox_verts(origin, size):
-    bbox_origin = mathutils.Vector(
-        (origin[0], origin[1], origin[2]))
-    bbox_size = mathutils.Vector(
-        (size[0], size[1], size[2]))
-    bbox_verts = [
-        (
-            bbox_origin[0] + 0,
-            bbox_origin[1] + 0,
-            bbox_origin[2] + 0
-        ),
-        (
-            bbox_origin[0] + 0,
-            bbox_origin[1] + 0,
-            bbox_origin[2] + bbox_size[2]
-        ),
-        (
-            bbox_origin[0] + 0,
-            bbox_origin[1] + bbox_size[1],
-            bbox_origin[2] + 0
-        ),
-        (
-            bbox_origin[0] + 0,
-            bbox_origin[1] + bbox_size[1],
-            bbox_origin[2] + bbox_size[2]
-        ),
-        (
-            bbox_origin[0] + bbox_size[0],
-            bbox_origin[1] + 0,
-            bbox_origin[2] + 0
-        ),
-        (
-            bbox_origin[0] + bbox_size[0],
-            bbox_origin[1] + 0,
-            bbox_origin[2] + bbox_size[2],
-        ),
-        (
-            bbox_origin[0] + bbox_size[0],
-            bbox_origin[1] + bbox_size[1],
-            bbox_origin[2] + 0,
-        ),
-        (
-            bbox_origin[0] + bbox_size[0],
-            bbox_origin[1] + bbox_size[1],
-            bbox_origin[2] + bbox_size[2],
-        ),
-    ]
-    return bbox_verts
-
-
-def get_bioxels_obj(current_obj):
-    bioxels_obj = None
-    if current_obj.get('bioxels_container'):
-        bioxels_values = []
-        for obj in bpy.data.objects:
-            if obj.parent == current_obj and obj.get('bioxels'):
-                bioxels_values.append(obj)
-
-        if len(bioxels_values) > 0:
-            bioxels_obj = bioxels_values[0]
-
-    elif current_obj.get('bioxels') and current_obj.parent:
-        if current_obj.parent.get('bioxels_container'):
-            bioxels_obj = current_obj
-
-    return bioxels_obj
-
-
-def extract_last_number(text):
-    # Initialize an empty string to store the digits
-    digits = ""
-
-    # Iterate through the characters in reverse order
-    started = False
-    for char in text[::-1]:
-        if char.isdigit():
-            started = True
-            # If the character is a digit, add it to the digits string
-            digits += char
-        else:
-            if started:
-                # If a non-digit character is encountered, stop the loop
-                break
-
-    # Reverse the digits string to get the correct order
-    last_number = digits[::-1]
-
-    return int(last_number)
-
-
-def add_driver(target_prop, var_sources, expression):
-
-    driver = target_prop.driver_add("default_value")
-    is_vector = isinstance(driver, list)
-    drivers = driver if is_vector else [driver]
-
-    for i, driver in enumerate(drivers):
-        for j, var_source in enumerate(var_sources):
-
-            source = var_source['source']
-            prop = var_source['prop']
-
-            var = driver.driver.variables.new()
-            var.name = f"var{j}"
-
-            var.targets[0].id_type = source.id_type
-            var.targets[0].id = source
-            var.targets[0].data_path = f'["{prop}"][{i}]'\
-                if is_vector else f'["{prop}"]'
-
-        driver.driver.expression = expression
-
-
-def add_direct_driver(target, target_prop, source, source_prop):
-    target_prop = target.inputs.get(target_prop)
-    drivers = [
-        {
-            "source": source,
-            "prop": source_prop
-        }
-    ]
-    expression = "var0"
-    add_driver(target_prop, drivers, expression)
+    if not target_path.exists():
+        raise Exception

build.py

@@ -0,0 +1,95 @@
+from pathlib import Path
+import shutil
+import subprocess
+import sys
+from dataclasses import dataclass
+import tomlkit
+
+
+@dataclass
+class Platform:
+    pypi_suffix: str
+    blender_tag: str
+
+
+required_packages = ["SimpleITK==2.3.1",
+                     "pyometiff==1.0.0",
+                     "mrcfile==1.5.1",
+                     "h5py==3.11.0",
+                     "transforms3d==0.4.2"]
+
+
+platforms = {"windows-x64": Platform(pypi_suffix="win_amd64",
+                                     blender_tag="windows-x64"),
+             "linux-x64": Platform(pypi_suffix="manylinux2014_x86_64",
+                                   blender_tag="linux-x64"),
+             "macos-arm64": Platform(pypi_suffix="macosx_12_0_arm64",
+                                     blender_tag="macos-arm64"),
+             "macos-x64": Platform(pypi_suffix="macosx_10_16_x86_64",
+                                   blender_tag="macos-x64")}
+
+packages_to_remove = {
+    "imagecodecs",
+    "numpy"
+}
+
+
+def run_python(args: str):
+    python = Path(sys.executable).resolve()
+    subprocess.run([python] + args.split(" "))
+
+
+def build_extension(platform: Platform, python_version="3.11") -> None:
+    wheel_dirpath = Path("./bioxelnodes/wheels")
+    toml_filepath = Path("bioxelnodes/blender_manifest.toml")
+    scipy_ndimage_dirpath = Path("./scipy_ndimage", platform.blender_tag)
+
+    # download required_packages
+    run_python(
+        f"-m pip download {' '.join(required_packages)} --dest {wheel_dirpath.as_posix()} --only-binary=:all: --python-version={python_version} --platform={platform.pypi_suffix}"
+    )
+
+    for f in wheel_dirpath.glob('*.whl'):
+        if any([package in f.name for package in packages_to_remove]):
+            f.unlink(missing_ok=True)
+
+        elif platform.blender_tag == "macos-arm64" and \
+                "lxml" in f.name and "universal2" in f.name:
+            f.rename(Path(f.parent,
+                          f.name.replace("universal2", "arm64")))
+
+    for ndimage_filepath in scipy_ndimage_dirpath.iterdir():
+        to_filepath = Path("./bioxelnodes/bioxel/scipy", ndimage_filepath.name)
+        shutil.copy(ndimage_filepath, to_filepath)
+
+    # Load the TOML file
+    with toml_filepath.open("r") as file:
+        manifest = tomlkit.parse(file.read())
+
+    manifest["platforms"] = [platform.blender_tag]
+    manifest["wheels"] = [f"./wheels/{f.name}"
+                          for f in wheel_dirpath.glob('*.whl')]
+
+    # build = tomlkit.table(True)
+    # generated = tomlkit.table()
+    # generated["platforms"] = [platform.blender_tag]
+    # generated["wheels"] = [f"./wheels/{f.name}"
+    #                        for f in wheel_dirpath.glob('*.whl')]
+
+    # build.append('generated', generated)
+    # manifest.append('build', build)
+
+    # Write the updated TOML file
+    with toml_filepath.open("w") as file:
+        text = tomlkit.dumps(manifest)
+        file.write(text)
+
+
+def main():
+    platform_name = sys.argv[1]
+    platform = platforms[platform_name]
+    build_extension(platform)
+
+
+if __name__ == "__main__":
+    main()

docs/color.md

@@ -0,0 +1 @@
+This type of node is responsible for setting the color properties of the shader

docs/concept.md

@@ -0,0 +1,46 @@
+# Concepts & Pipeline
+
+## Container, Layer, Component
+
+Bioxel Nodes imports volumetric data and put it into a **Container** as a **Layer**. One container may has more than one layer, and each layer stores the information of different fields under the same location, which is similar to the view layers in map app, except that here it is in 3D space.
+
+In order to visualize the volumetric data the way we want it to, we need to build renderable objects from layers. We call those objects **Component**. The following diagram shows the relationship of **Container**, **Layer**, and **Component**:
+
+![alt text](assets/features_concept.png)
+
+### Container Structure
+
+In Blender, container structure is like this:
+
+```bash
+Case_0000 # Container
+|-- Case_0000_CT # Layer
+|-- Case_0000_Label_1 # Layer
+`-- Case_0000_Label_2 # Layer
+```
+
+The container also stores the build process in geometry nodes:
+
+![alt text](assets/features_container.png)
+
+### Layer Type
+The layer is categorized into these by data type:
+
+-   Scalar
+-   Label
+-   Vector (Not implemented yet)
+-   Color (Not implemented yet)
+
+## Component Building Pipline
+
+In order to build a component, the general process is to first use a "Mask Method" node to build the surface of the component based on its layers, and then connect to a "Assign Shader" node to add the physical properties. Finally, if you need to cut the cross-section, then connect to a "Cut" node. The whole process is shown in the following diagram
+
+![alt text](assets/nodes_concept.png)
+
+A typical example looks like this:
+
+![alt text](assets/nodes_example.png)
+
+The "Mask Method" node tends to be very computationally intensive, and if it consumes too much time, then you can bake it with a "Bake" node after it (but you need to save the Blender file first).
+
+![alt text](assets/nodes_bake.png)

docs/cut.md

@@ -0,0 +1 @@
+This type of node is responsible for cutting components to present cross-section

docs/import.md

@@ -0,0 +1,41 @@
+
+## First Time Import Volume Data
+
+File > Import > Volume Data as Bioxel Layer
+
+### Resample
+
+![alt text](assets/features_resample.png)
+
+Sometimes the original data is too big, or the spacing in the original data is not reasonable, you can modify the `Bioxel Size` and `Original Spacing` to adjust the Shape of the layer.
+
+A bioxel is like a pixel, the larger the `Bioxel Size`, the lower the resolution of the image, Original Spacing will be read from the original data record, but sometimes the image doesn't have original spacing, you may need to input it manually to get the correct shape.
+
+### Read as
+
+-   as Scalar
+
+    ![alt text](assets/features_as-scalar.png)
+
+    In some cases the environment value is higher than the value of the target object, you can check `Invert Scalar` to adjust the value for better result.
+
+-   as Labels
+
+    Many AI segmentation task datasets, provide segmentation data, which are often an integer value representing a layer of segmentation labels. You can set it to `Labels` to load them.
+
+-   _as Vector (Not implemented yet)_
+
+-   _as Color (Not implemented yet)_
+
+### Others
+
+![alt text](assets/features_import-others.png)
+
+`Scene Scale` determines how many units of length in the Blender world correspond to one unit of length in the Bioxel world. Since Blender defaults to meters, and the default size of blender primitives are around 1 blender unit. Therefore `Scene Scale` set to 0.01 is appropriate.
+
+`Orient to RAS` determines whether the layer should be converted to the RAS coordinate system. Regardless of the format of the medical image data, the coordinate system is mostly the LPS coordinate system. Bioxel, however, are in the RAS coordinate system and therefore need to be transformed in most cases.
+
+## Adding Volume Data to an existing container
+
+In 3D view or outliner panel, select the container and right click, Bioxel Nodes > Add Volume Data to Container.
+The import settings are the same as for the first time import.

docs/index.md

@@ -0,0 +1,76 @@
+[中文文档](https://uj6xfhbzp0.feishu.cn/wiki/Qx3VwHuNPimeI8kr6nDcvl1DnHf?from=from_copylink)
+
+# Bioxel Nodes
+
+[![For Blender](https://img.shields.io/badge/Blender-orange?style=for-the-badge&logo=blender&logoColor=white&color=black)](https://blender.org/)
+![GitHub License](https://img.shields.io/github/license/OmooLab/BioxelNodes?style=for-the-badge&labelColor=black)
+![GitHub Release](https://img.shields.io/github/v/release/OmooLab/BioxelNodes?style=for-the-badge&labelColor=black)
+![GitHub Repo stars](https://img.shields.io/github/stars/OmooLab/BioxelNodes?style=for-the-badge&labelColor=black)
+
+[![Discord](https://img.shields.io/discord/1265129134397587457?style=for-the-badge&logo=discord&label=Discord&labelColor=white&color=black)](https://discord.gg/pYkNyq2TjE)
+
+Bioxel Nodes is a Blender addon for scientific volumetric data visualization. It using Blender's powerful **Geometry Nodes** and **Cycles** to process and render volumetric data.
+
+![cover](https://omoolab.github.io/BioxelNodes/latest/assets/cover.png)
+
+-   Realistic rendering result, also support EEVEE NEXT.
+-   Support multiple formats.
+-   Support 4D volumetric data.
+-   All kinds of cutters.
+-   Simple and powerful nodes.
+-   Based on blender natively, can work without addon.
+
+**Read the [getting started](https://omoolab.github.io/BioxelNodes/latest/installation) to begin your journey into visualizing volumetric data!**
+
+Welcome to our [discord server](https://discord.gg/pYkNyq2TjE), if you have any problems with this add-on.
+
+## Support Multiple Formats
+
+| Format | EXT                                      | Test    |
+| ------ | ---------------------------------------- | ------- |
+| DICOM  | .dcm, .DCM, .DICOM, .ima, .IMA           | ✅ pass |
+| BMP    | .bmp, .BMP                               | ✅ pass |
+| JPEG   | .jpg, .JPG, .jpeg, .JPEG                 | ✅ pass |
+| PNG    | .png, .PNG                               | ✅ pass |
+| TIFF   | .tif, .TIF, .tiff, .TIFF                 | ✅ pass |
+| Nifti  | .nia, .nii, .nii.gz, .hdr, .img, .img.gz | ✅ pass |
+| Nrrd   | .nrrd, .nhdr                             | ✅ pass |
+| HDF5   | .hdf, .h4, .hdf4, .he2, .h5, .hdf5, .he5 | ✅ pass |
+| OME    | .ome.tiff, .ome.tif                      | ✅ pass |
+| MRC    | .mrc, .mrc.gz, .map, .map.gz             | ✅ pass |
+
+## Support 4D volumetric data
+
+![4d](https://omoolab.github.io/BioxelNodes/latest/assets/4d-time.gif)
+
+🥰 4D volumetric data can also be imported into Blender.
+
+## Support EEVEE NEXT
+
+![eevee](https://omoolab.github.io/BioxelNodes/latest/assets/eevee.gif)
+
+👍 EEVEE NEXT is absolutely AWESOME! Bioxel Nodes is fully support EEVEE NEXT now! However, there are some limitations:
+
+1. Only one cutter supported.
+2. EEVEE result is not that great as Cycles does.
+
+## Known Limitations
+
+-   Only works with Cycles CPU , Cycles GPU (OptiX), EEVEE
+-   Section surface cannot be generated when convert to mesh (will be supported soon)
+
+## Compatible to Newer Version
+
+**v0.3.x is not compatible to v0.2.x, Updating this addon may break old files. Read the following carefully before upgradation**
+
+Before upgradation, you need to ask yourself whether this project file will be modified again or not, if it's an archived project file, I would recommend that you run **Bioxel Nodes > Save Staged Data** to make the addon nodes permanent. In this way, there will be no potential problem with the nodes not functioning due to the addon update.
+
+After the addon update, your old project files may not work either, this may be because you had executed **Save Staged Data**. If so, you need to execute **Bioxel Nodes > Relink Nodes to Addon** to relink them to make sure that the addon's new functionality and the addon nodes are synchronized.
+
+Also, the older shaders are not based on OSL, so if you find that you can't render volumes, you need to turn on **Open Shading Language (OSL)** in the Render Settings.
+
+## Roadmap
+
+-   Better multi-format import experience
+-   One-click bake model with texture
+-   AI Segmentation to Generate Labels

docs/installation.md

@@ -0,0 +1,27 @@
+# Installation
+
+> **Currently only support Blender 4.1 or above, make sure you have the correct version of Blender.**
+
+## For Blender 4.2 or higher
+
+The most recommended way is to open **Edit > Preferences > Extension**, enter "bio" in the search box and click **Install**. since the addon is quite large (20MB) you may need to wait a while!
+
+![extension](assets/installation_extension.png)
+
+Thats it!
+
+> If it cannot be enable, reboot blender or install again as administrator
+
+Also, you can do it maually. Download the **Extension** version `BioxelNodes_Extension_{version}.zip` from https://github.com/OmooLab/BioxelNodes/releases/latest  
+In Blender, **Edit > Preferences > Extensions > Install from Disk**, select the zip file you just downloaded.
+
+## For Blender 4.1
+
+Download the **Addon** version `BioxelNodes_Addon_{version}.zip` from https://github.com/OmooLab/BioxelNodes/releases/latest  
+In Blender, Edit > Preferences > Add-ons > Install, select the zip file you just downloaded.
+
+The add-on requires a third-party python dependency called SimpleITK, click `Install SimpleITK` button below to install the dependency. After clicking, blender may get stuck, it is downloading and installing, just wait for a moment. After that, click `Reboot Blender` button.
+
+![dependency](assets/installation_dependency.png)
+
+This step may have failed due to network factors, just click "Set PyPI Mirror" to change the mirror.