numpy 2

.github/workflows/build.yml

@@ -27,10 +27,10 @@ jobs:
     runs-on: [self-hosted, python, cuda]
     strategy:
       matrix:
-        python-version: [3.11]
-        numpy-version: [1.25]
+        python-version: [3.12]
+        numpy-version: [2]
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with: {fetch-depth: 0, submodules: recursive}
     - id: reqs
       name: set requirements
@@ -67,12 +67,12 @@ jobs:
       matrix:
         include:
         - {python-version: '3.10', numpy-version: 1.23}
-        - {python-version: 3.12, numpy-version: 1.26}
+        - {python-version: 3.12, numpy-version: 2}
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with: {fetch-depth: 0, submodules: recursive}
     - name: set requirements
-      run: sed -ri -e '/ python /d' -e 's/(.* numpy) .*/\1=${{ matrix.numpy-version }}/' -e 's/=cuda*//' -e '/tigre/d' scripts/requirements-test.yml
+      run: sed -ri -e '/ python /d' -e 's/(.* numpy) .*/\1=${{ matrix.numpy-version }}/' -e 's/ cuda*//' -e '/tigre/d' scripts/requirements-test.yml
     - uses: conda-incubator/setup-miniconda@v3
       with:
         python-version: ${{ matrix.python-version }}
@@ -94,12 +94,12 @@ jobs:
       run: |
         if ${{ startsWith(github.ref, 'refs/tags') || github.event_name == 'workflow_dispatch' }}; then
           echo "python-version=['3.10', 3.11]" >> $GITHUB_OUTPUT
-          echo "numpy-version=[1.23, 1.24, 1.25, 1.26]" >> $GITHUB_OUTPUT
+          echo "numpy-version=['2.0', 2.1, 2.2, 2.3, 2.4]" >> $GITHUB_OUTPUT
           echo "os=['ubuntu', 'windows']" >> $GITHUB_OUTPUT
           include_max=true
         else
           echo "python-version=['3.10']" >> $GITHUB_OUTPUT
-          echo "numpy-version=[1.23]" >> $GITHUB_OUTPUT
+          echo "numpy-version=[2]" >> $GITHUB_OUTPUT
           if ${{ github.ref == 'refs/heads/master' }}; then
             echo "os=['ubuntu', 'windows']" >> $GITHUB_OUTPUT
             include_max=true
@@ -109,8 +109,8 @@ jobs:
           fi
         fi
         if $include_max; then
-          echo "include=[{'python-version': 3.12, 'os': 'ubuntu'}, {'python-version': 3.12, 'os': 'windows'}]" >> $GITHUB_OUTPUT
-          echo "include-numpy=[{'python-version': 3.12, 'numpy-version': 1.26, 'os': 'ubuntu'}, {'python-version': 3.12, 'numpy-version': 1.26, 'os': 'windows'}]" >> $GITHUB_OUTPUT
+          echo "include=[{'python-version': 3.13, 'os': 'ubuntu'}, {'python-version': 3.13, 'os': 'windows'}]" >> $GITHUB_OUTPUT
+          echo "include-numpy=[{'python-version': 3.13, 'numpy-version': 2, 'os': 'ubuntu'}, {'python-version': 3.13, 'numpy-version': 2, 'os': 'windows'}]" >> $GITHUB_OUTPUT
         else
           echo "include=[]" >> $GITHUB_OUTPUT
           echo "include-numpy=[]" >> $GITHUB_OUTPUT
@@ -125,7 +125,7 @@ jobs:
         os: ${{ fromJson(needs.conda-matrix.outputs.os) }}
         include: ${{ fromJson(needs.conda-matrix.outputs.include) }}
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         fetch-depth: 0
         submodules: recursive
@@ -158,15 +158,15 @@ jobs:
         os: ${{ fromJson(needs.conda-matrix.outputs.os) }}
         include: ${{ fromJson(needs.conda-matrix.outputs.include-numpy) }}
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
     - uses: conda-incubator/setup-miniconda@v3
       with:
         python-version: ${{ matrix.python-version }}
         mamba-version: "*"
         channels: conda-forge
         conda-remove-defaults: "true"
     - run: conda install boa
-    - uses: actions/download-artifact@v4
+    - uses: actions/download-artifact@v5
       with:
         name: cil-py${{ matrix.python-version }}-${{ matrix.os }}
         path: dist
@@ -180,13 +180,13 @@ jobs:
     runs-on: ubuntu-latest
     needs: conda-test
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
     - uses: conda-incubator/setup-miniconda@v3
       with:
         mamba-version: "*"
         channels: conda-forge
         conda-remove-defaults: "true"
-    - uses: actions/download-artifact@v4
+    - uses: actions/download-artifact@v5
       with: {pattern: cil-py*-*, path: dist, merge-multiple: true}
     - run: mamba install anaconda-client
     - name: anaconda upload -c ccpi
@@ -205,7 +205,7 @@ jobs:
     defaults: {run: {shell: 'bash -el {0}', working-directory: docs}}
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         fetch-depth: 0
         submodules: recursive
@@ -218,7 +218,7 @@ jobs:
         conda-remove-defaults: "true"
     - uses: ruby/setup-ruby@v1
       with:
-        ruby-version: '3.2'
+        ruby-version: '3.4.8'
         bundler-cache: true
         cache-version: 0
     - name: install dependencies
@@ -229,7 +229,7 @@ jobs:
         conda list
     - run: pip install ..
     - name: checkout docs
-      uses: actions/checkout@v4
+      uses: actions/checkout@v5
       with:
         path: docs/build
         ref: gh-pages
@@ -262,7 +262,7 @@ jobs:
       contents: read
       packages: write
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         fetch-depth: 0
         submodules: recursive
@@ -293,6 +293,7 @@ jobs:
         cache-from: type=gha
         cache-to: type=gha,mode=max
         context: .
+        target: cil
         load: true
         tags: tomographicimaging/cil:test
     - name: test

.gitignore

@@ -3,5 +3,6 @@ __pycache__/
 /Wrappers/Python/cil-*.dist-info/
 /Wrappers/Python/cil/include/
 /Wrappers/Python/cil/lib/
+/Wrappers/Python/build/
 *.vscode*
 *.egg*

CHANGELOG.md

@@ -16,6 +16,10 @@
     - cvxpy maximum version set to 1.7.5 to fix #2303 (#2304)
     - Update to TomoPhantom v3.0 (#2287)
     - Handle regularisation toolkit CPU only package error message (#2302)
+    - Added support for numpy 2
+      - Update to CCPi-Regularisation toolkit 25.0.0
+    - Added support for python 3.13
+    - Added support for astra-toolbox 2.4
   - Documentation:
     - Render the user showcase notebooks in the documentation (#2189)
   - Enhancements:

Dockerfile

@@ -3,31 +3,54 @@
 # - https://github.com/TomographicImaging/CIL#installation-of-cil
 # consumers:
 # - harbor.stfc.ac.uk/imaging-tomography/cil
-FROM jupyter/tensorflow-notebook:ubuntu-22.04
+ARG BASE_IMAGE=quay.io/jupyter/tensorflow-notebook:cuda-python-3.12
+FROM ${BASE_IMAGE} AS base
 LABEL org.opencontainers.image.source=https://github.com/TomographicImaging/CIL
 # tigre: BSD-3-Clause, astra-toolbox: GPL-3.0
 LABEL org.opencontainers.image.licenses="Apache-2.0 AND BSD-3-Clause AND GPL-3.0"
 
 # CUDA-specific packages
-ARG CIL_EXTRA_PACKAGES="tigre=2.6 astra-toolbox=2.1.0=cuda*"
+ARG CIL_EXTRA_PACKAGES="ccpi/label/dev::tigre astra-toolbox::astra-toolbox ccpi::ccpi-regulariser cuda-version>=12"
 # build & runtime dependencies
 # TODO: sync scripts/create_local_env_for_cil_development.sh, scripts/requirements-test.yml, recipe/meta.yaml (e.g. missing libstdcxx-ng _openmp_mutex pip)?
 # vis. https://github.com/TomographicImaging/CIL/pull/1590
-COPY --chown="${NB_USER}" scripts/requirements-test.yml environment.yml
-# channel_priority: https://stackoverflow.com/q/58555389
-RUN sed -ri '/tigre|astra-toolbox| python /d' environment.yml \
-  && for pkg in 'jupyter-server-proxy>4.1.0' $CIL_EXTRA_PACKAGES; do echo "  - $pkg" >> environment.yml; done \
-  && conda config --env --set channel_priority strict \
-  && for ch in defaults nvidia ccpi https://software.repos.intel.com/python/conda conda-forge; do conda config --env --add channels $ch; done \
-  && mamba env update -n base \
+USER root
+COPY scripts/requirements-test.yml /opt/environment.yml
+RUN sed -ri -e '/tigre| python |cuda/d' /opt/environment.yml \
+  && for pkg in 'jupyter-server-proxy>4.1.0' $CIL_EXTRA_PACKAGES; do echo "  - $pkg" >> /opt/environment.yml; done \
+  && mamba env update -n base --file /opt/environment.yml \
   && mamba clean -a -y -f \
-  && rm environment.yml \
   && fix-permissions "${CONDA_DIR}" /home/${NB_USER}
 
 # NB: trailing `/` is required
 ENV TENSORBOARD_PROXY_URL=/user-redirect/proxy/6006/
 
+FROM base AS dev
+RUN apt-get update -qq && apt-get install -yqq --no-install-recommends \
+  bash-completion \
+  && rm -rf /var/lib/apt/lists/*
+COPY docs/docs_environment.yml .
+RUN mamba install conda-merge \
+  && conda-merge /opt/environment.yml docs_environment.yml > environment.yml \
+  && mamba env update -n base --file environment.yml \
+  && mamba clean -a -y -f \
+  && rm {docs_,}environment.yml \
+  && fix-permissions "${CONDA_DIR}" /home/${NB_USER}
+# https://github.com/rbenv/rbenv
+RUN apt-get update -qq && apt-get install -yqq --no-install-recommends \
+  zlib1g-dev libffi-dev libyaml-dev \
+  && rm -rf /var/lib/apt/lists/*
+USER ${NB_USER}
+ENV RBENV_VERSION=3.4.8
+RUN git clone https://github.com/rbenv/rbenv.git ~/.rbenv \
+  && ~/.rbenv/bin/rbenv init \
+  && export PATH="$HOME/.rbenv/bin:$PATH" \
+  && git clone https://github.com/rbenv/ruby-build.git "$(rbenv root)"/plugins/ruby-build \
+  && rbenv install $RBENV_VERSION && rbenv global $RBENV_VERSION
+
+FROM base AS cil
 # build & install CIL
-COPY --chown="${NB_USER}" . src
+COPY . src
 RUN pip install ./src && rm -rf src \
   && fix-permissions "${CONDA_DIR}" /home/${NB_USER}
+USER ${NB_USER}

README.md

@@ -19,7 +19,7 @@ Binary installation of CIL can be achieved with `conda`.
 We recommend using either [`miniconda`](https://docs.conda.io/projects/miniconda/en/latest) or [`miniforge`](https://github.com/conda-forge/miniforge), which are both minimal installers for `conda`. We also recommend a `conda` version of at least `23.10` for quicker installation.
 
 #### Create a conda environment with CIL
-We maintain an environment file with the required packages to run the [CIL demos](https://github.com/TomographicImaging/CIL-Demos) which you can use to create a new environment. This will have specific and tested versions of all dependencies that are outlined in the table below: 
+We maintain an environment file with the required packages to run the [CIL demos](https://github.com/TomographicImaging/CIL-Demos) which you can use to create a new environment. This will have specific and tested versions of all dependencies that are outlined in the table below:
 
 ```sh
 conda env create -f https://tomographicimaging.github.io/scripts/env/cil_demos.yml
@@ -47,13 +47,13 @@ While building the CIL package we test with specific versions of dependencies. T
 
 | Package | Tested Version |  Conda install command | Description | License |
 |----|----|--------|--------|----|
-| [Python](https://www.python.org/) | 3.10 - 3.12 | `"python>=3.10,<=3.12"` || [PSF-2.0](https://docs.python.org/3/license.html) |
-| [Numpy](https://github.com/numpy/numpy) | 1.23 - 1.26 | `"numpy>=1.23,<2"` || [BSD-3-Clause](https://numpy.org/doc/stable/license.html) |
-| [IPP](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ipp.html#gs.gxwq5p) | 2021.12 | `-c https://software.repos.intel.com/python/conda ipp=2021.12` | The Intel Integrated Performance Primitives Library (required for the CIL recon class). | [ISSL](http://www.intel.com/content/www/us/en/developer/articles/license/end-user-license-agreement.html) |
+| [Python](https://www.python.org/) | 3.10 - 3.13 | `"python>=3.10,<=3.13"` || [PSF-2.0](https://docs.python.org/3/license.html) |
+| [Numpy](https://github.com/numpy/numpy) | 2.0 - 2.4 | `"numpy>=2,<=2.4"` || [BSD-3-Clause](https://numpy.org/doc/stable/license.html) |
+| [IPP](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ipp.html#gs.gxwq5p) | 2021.12 | `-c https://tomography.stfc.ac.uk/conda ipp=2021.12` | The Intel Integrated Performance Primitives Library (required for the CIL recon class). | [ISSL](http://www.intel.com/content/www/us/en/developer/articles/license/end-user-license-agreement.html) |
 |--|--| **Optional dependencies** |--|--|
-| [ASTRA toolbox](http://www.astra-toolbox.com) | 2.1 | CPU: `conda-forge::astra-toolbox=2.1=py*` <br> GPU: `conda-forge::astra-toolbox=2.1=cuda*` | CT projectors, FBP and FDK. | [GPL-3.0](https://github.com/astra-toolbox/astra-toolbox/blob/master/COPYING) |
-| [TIGRE](https://github.com/CERN/TIGRE) | 2.6 | `ccpi::tigre=2.6` | CT projectors, FBP and FDK. | [BSD-3-Clause](https://github.com/CERN/TIGRE/blob/master/LICENSE.txt) |
-| [CCPi Regularisation Toolkit](https://github.com/TomographicImaging/CCPi-Regularisation-Toolkit) | 24.0.1 | `ccpi::ccpi-regulariser=24.0.1` | Toolbox of regularisation methods. | [Apache-2.0](https://github.com/TomographicImaging/CCPi-Regularisation-Toolkit/blob/master/LICENSE) |
+| [ASTRA toolbox](http://www.astra-toolbox.com) | 2.1 - 2.4 | `astra-toolbox::astra-toolbox=2.4` | CT projectors, FBP and FDK. | [GPL-3.0](https://github.com/astra-toolbox/astra-toolbox/blob/master/COPYING) |
+| [TIGRE](https://github.com/CERN/TIGRE) | 3.1 | `ccpi/label/dev::tigre=3.1.*` | CT projectors, FBP and FDK. | [BSD-3-Clause](https://github.com/CERN/TIGRE/blob/master/LICENSE.txt) |
+| [CCPi Regularisation Toolkit](https://github.com/TomographicImaging/CCPi-Regularisation-Toolkit) | 25.0.0 | CPU: `ccpi::ccpi-regulariser=25.0.0=cpu*` <br> GPU: `ccpi::ccpi-regulariser=25.0.0=cuda*` | Toolbox of regularisation methods. | [Apache-2.0](https://github.com/TomographicImaging/CCPi-Regularisation-Toolkit/blob/master/LICENSE) |
 | [TomoPhantom](https://github.com/dkazanc/TomoPhantom) | [3.0.3](https://github.com/dkazanc/TomoPhantom/releases/tag/v3.0) | `ccpi::tomophantom=3.0.3` | Generates phantoms to use as test data. | [Apache-2.0](https://github.com/dkazanc/TomoPhantom/blob/master/LICENSE) |
 | [ipykernel](https://github.com/ipython/ipykernel) || `ipykernel` | Provides the IPython kernel to run Jupyter notebooks. | [BSD-3-Clause](https://github.com/ipython/ipykernel/blob/main/LICENSE) |
 | [ipywidgets](https://github.com/jupyter-widgets/ipywidgets) || `ipywidgets` | Enables visualisation tools within jupyter noteboooks. | [BSD-3-Clause](https://github.com/jupyter-widgets/ipywidgets/blob/main/LICENSE) |
@@ -62,7 +62,6 @@ While building the CIL package we test with specific versions of dependencies. T
 |[olefile](https://github.com/decalage2/olefile)|>= 0.46|`olefile>=0.46`|Package to process Microsoft OLE2 files, used to read ZEISS data files.|[BSD-style (custom)](https://github.com/decalage2/olefile?tab=License-1-ov-file)|
 |[dxchange](https://github.com/data-exchange/dxchange)|>= 0.2.1|`dxchange>=0.2.1`|Provides an interface with TomoPy for loading tomography data.|[BSD-style (custom)](https://github.com/data-exchange/dxchange?tab=License-1-ov-file)|
 
-
 ### Docker
 
 Finally, CIL can be run via a Jupyter Notebook enabled Docker container:

Wrappers/Python/cil/framework/acquisition_data.py

@@ -27,7 +27,7 @@
 class AcquisitionData(DataContainer, Partitioner):
     """
     DataContainer for holding 2D or 3D sinogram
-    
+
     Parameters
     ----------
     array : numpy.ndarray or DataContainer
@@ -36,10 +36,10 @@ class AcquisitionData(DataContainer, Partitioner):
         If True, the array will be deep copied. If False, the array will be shallow copied.
     geometry : AcquisitionGeometry
         The geometry of the data. If the dtype of the array and geometry are different, the geometry dtype will be overridden.
-    
+
     **kwargs:
         dtype : numpy.dtype
-            Specify the data type of the AcquisitionData array, this is useful if you pass None to array and want to over-ride the dtype of the geometry. 
+            Specify the data type of the AcquisitionData array, this is useful if you pass None to array and want to over-ride the dtype of the geometry.
             If an array is passed, dtype must match the dtype of the array.
 
     """
@@ -84,7 +84,7 @@ def __init__(self,
             if dtype is None:
                 dtype = geometry.dtype
             array = numpy.empty(geometry.shape, dtype)
-    
+
         elif issubclass(type(array) , DataContainer):
             array = array.as_array()
 
@@ -107,12 +107,12 @@ def __eq__(self, other):
         '''
         Check if two AcquisitionData objects are equal. This is done by checking if the geometry, data and dtype are equal.
         Also, if the other object is a numpy.ndarray, it will check if the data and dtype are equal.
-        
+
         Parameters
         ----------
         other: AcquisitionData or numpy.ndarray
             The object to compare with.
-        
+
         Returns
         -------
         bool
@@ -123,12 +123,12 @@ def __eq__(self, other):
             if numpy.array_equal(self.as_array(), other.as_array()) \
                 and self.geometry == other.geometry \
                 and self.dtype == other.dtype:
-                return True 
+                return True
         elif numpy.array_equal(self.as_array(), other) and self.dtype==other.dtype:
             return True
         else:
             return False
-        
+
     def _get_slice(self, **kwargs):
         '''
         Functionality of get_slice
@@ -165,8 +165,8 @@ def _get_slice(self, **kwargs):
             return out
         else:
             return AcquisitionData(out.array, deep_copy=False, geometry=geometry_new)
-        
-    
+
+
     def get_slice(self, *args, **kwargs):
         '''
         Returns a new AcquisitionData of a single slice in the requested direction.
@@ -205,10 +205,10 @@ def get_slice(self, *args, **kwargs):
                 raise TypeError(f"Cannot use 'projection' for geometries that use angles. Use 'angle' instead.")
             elif key not in AcquisitionDimension and key != 'force':
                 raise TypeError(f"'{key}' not in allowed labels {AcquisitionDimension}.")
-            
+
         if args:
             warnings.warn("Positional arguments for get_slice are deprecated. Use keyword arguments instead.", DeprecationWarning, stacklevel=2)
-            
+
             num_args = len(args)
 
             if num_args > 0:

Wrappers/Python/cil/framework/block.py

@@ -733,9 +733,7 @@ def __neg__(self):
         return -1 * self
 
     def dot(self, other):
-#
-        tmp = [ self.containers[i].dot(other.containers[i]) for i in range(self.shape[0])]
-        return sum(tmp)
+        return sum(self.containers[i].dot(other.containers[i]) for i in range(self.shape[0]))
 
     def __len__(self):