diff --git a/.github/workflows/build_test_deploy_all_wheels.yml b/.github/workflows/build_test_deploy_all_wheels.yml index 383b459a..e8c5dba2 100644 --- a/.github/workflows/build_test_deploy_all_wheels.yml +++ b/.github/workflows/build_test_deploy_all_wheels.yml @@ -13,15 +13,15 @@ jobs: - os: macOS-ARM runner: [self-hosted, macOS, ARM64] archs: arm64 - cibw_build: cp39-macosx_arm64 cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64 + cibw_build: cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64 cp313-macosx_arm64 - os: manylinux runner: [self-hosted, Ubuntu, Native] archs: auto - cibw_build: cp39-manylinux_x86_64 cp310-manylinux_x86_64 cp311-manylinux_x86_64 cp312-manylinux_x86_64 + cibw_build: cp310-manylinux_x86_64 cp311-manylinux_x86_64 cp312-manylinux_x86_64 cp313-manylinux_x86_64 - os: windows runner: [self-hosted, Windows] archs: auto - cibw_build: cp39-win_amd64 cp310-win_amd64 cp311-win_amd64 cp312-win_amd64 + cibw_build: cp310-win_amd64 cp311-win_amd64 cp312-win_amd64 cp313-win_amd64 steps: - uses: actions/checkout@v4 @@ -29,10 +29,10 @@ jobs: - uses: actions/setup-python@v5 with: python-version: | - 3.9 3.10 3.11 - 3.12 + 3.12 + 3.13 - name: Install cibuildwheel and nox run: | @@ -52,6 +52,7 @@ jobs: env: CIBW_BUILD: ${{ matrix.cibw_build }} CIBW_ARCHS: ${{ matrix.archs }} + MACOSX_DEPLOYMENT_TARGET: "14.0" CIBW_BEFORE_ALL_LINUX: > sed -i 's/mirrorlist/#mirrorlist/g' /etc/yum.repos.d/CentOS-*.repo && sed -i 's|#baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' /etc/yum.repos.d/CentOS-*.repo && diff --git a/.github/workflows/build_wheels.yml b/.github/workflows/build_wheels.yml index 6476c9a3..9ab8ea28 100644 --- a/.github/workflows/build_wheels.yml +++ b/.github/workflows/build_wheels.yml @@ -13,27 +13,27 @@ jobs: - os: macOS-ARM runner: [self-hosted, macOS, ARM64] archs: arm64 - cibw_build: cp39-macosx_arm64 cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64 + cibw_build: cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64 cp313-macosx_arm64 - os: manylinux runner: [self-hosted, Ubuntu, Native] archs: auto - cibw_build: cp39-manylinux_x86_64 cp310-manylinux_x86_64 cp311-manylinux_x86_64 cp312-manylinux_x86_64 + cibw_build: cp310-manylinux_x86_64 cp311-manylinux_x86_64 cp312-manylinux_x86_64 cp313-manylinux_x86_64 - os: windows runner: [self-hosted, Windows] archs: auto - cibw_build: cp39-win_amd64 cp310-win_amd64 cp311-win_amd64 cp312-win_amd64 + cibw_build: cp310-win_amd64 cp311-win_amd64 cp312-win_amd64 cp313-win_amd64 steps: - uses: actions/checkout@v4 - uses: actions/setup-python@v5 with: - python-version: 3.9 # Works as bootstrap for cibuildwheel + python-version: 3.10 # Works as bootstrap for cibuildwheel - name: Install cibuildwheel and nox run: | python -m pip install --upgrade pip - python -m pip install cibuildwheel==2.16.2 + python -m pip install cibuildwheel==2.21.3 python -m pip install nox - name: Build sdist (only on Windows) @@ -45,6 +45,7 @@ jobs: env: CIBW_BUILD: ${{ matrix.cibw_build }} CIBW_ARCHS: ${{ matrix.archs }} + MACOSX_DEPLOYMENT_TARGET: "14.0" - name: Test wheels (only on macOS ARM64) if: matrix.os == 'macOS-ARM' diff --git a/.github/workflows/buildtest_mac_arm_wheels.yml b/.github/workflows/buildtest_mac_arm_wheels.yml index 4be1da32..7431d8a9 100644 --- a/.github/workflows/buildtest_mac_arm_wheels.yml +++ b/.github/workflows/buildtest_mac_arm_wheels.yml @@ -7,24 +7,33 @@ jobs: runs-on: [self-hosted, macOS, ARM64] steps: - name: Checkout - uses: actions/checkout@v3 - + uses: actions/checkout@v4 + with: + fetch-depth: 0 - name: Setup Python uses: actions/setup-python@v5 with: - python-version: "3.10" - + python-version: | + 3.10 + 3.11 + 3.12 + 3.13 - name: Install dependencies run: | python -m pip install --upgrade pip python -m pip install --upgrade nox - python -m pip install cibuildwheel==2.16.2 + python -m pip install cibuildwheel==2.21.3 + python -m pip install setuptools==73.0.1 + - name: Run Nox Quick-Tests + run: | + python -m nox --sessions test_source clear_wheelhouse - name: Build wheels run: python -m cibuildwheel --output-dir wheelhouse # to supply options, put them in 'env', like: env: - CIBW_BUILD: cp39-macosx_arm64 cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64 cp313-macosx_arm64 + CIBW_BUILD: cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64 cp313-macosx_arm64 CIBW_ARCHS: arm64 + MACOSX_DEPLOYMENT_TARGET: "14.0" - name: Test wheels run: python -m nox --sessions test_wheel diff --git a/.github/workflows/buildtest_manylinux_wheels.yml b/.github/workflows/buildtest_manylinux_wheels.yml index b3984f50..c55afe7d 100644 --- a/.github/workflows/buildtest_manylinux_wheels.yml +++ b/.github/workflows/buildtest_manylinux_wheels.yml @@ -13,7 +13,7 @@ jobs: # Used to host cibuildwheel - uses: actions/setup-python@v5 with: - python-version: 3.9 + python-version: 3.10 - name: Install cibuildwheel run: python -m pip install cibuildwheel==2.16.2 @@ -21,7 +21,7 @@ jobs: - name: Build wheels run: python -m cibuildwheel --output-dir wheelhouse env: - CIBW_BUILD: cp39-manylinux_x86_64 cp310-manylinux_x86_64 cp311-manylinux_x86_64 cp312-manylinux_x86_64 cp313-manylinux_x86_64 + CIBW_BUILD: cp310-manylinux_x86_64 cp311-manylinux_x86_64 cp312-manylinux_x86_64 cp313-manylinux_x86_64 # to supply options, put them in 'env', like: # env: # CIBW_SOME_OPTION: value diff --git a/.github/workflows/buildtest_windows_x86.yml b/.github/workflows/buildtest_windows_x86.yml index fae66bf9..40842dd8 100644 --- a/.github/workflows/buildtest_windows_x86.yml +++ b/.github/workflows/buildtest_windows_x86.yml @@ -11,7 +11,7 @@ jobs: fetch-depth: 0 - uses: actions/setup-python@v5 with: - python-version: 3.9 + python-version: 3.10 - name: Build sdist run: | python -m pip install --upgrade pip @@ -33,10 +33,10 @@ jobs: - uses: actions/setup-python@v5 with: python-version: | - 3.9 3.10 3.11 3.12 + 3.13 - name: Install cibuildwheel run: python -m pip install cibuildwheel==2.16.2 @@ -44,7 +44,7 @@ jobs: - name: Build wheels run: python -m cibuildwheel --output-dir wheelhouse env: - CIBW_BUILD: cp39-win_amd64 cp310-win_amd64 cp311-win_amd64 cp312-win_amd64 cp313-win_amd64 + CIBW_BUILD: cp310-win_amd64 cp311-win_amd64 cp312-win_amd64 cp313-win_amd64 # to supply options, put them in 'env', like: # env: # CIBW_SOME_OPTION: value diff --git a/.github/workflows/nanopyx_night_mechanic.yml b/.github/workflows/nanopyx_night_mechanic.yml index ba2f7fe5..25717815 100644 --- a/.github/workflows/nanopyx_night_mechanic.yml +++ b/.github/workflows/nanopyx_night_mechanic.yml @@ -29,15 +29,15 @@ jobs: - uses: actions/setup-python@v5 with: python-version: | - 3.9 3.10 3.11 3.12 + 3.13 - name: Run Nox Quick-Tests run: | python -m pip install --upgrade pip python -m pip install --upgrade nox - python -m pip install cibuildwheel==2.16.2 + python -m pip install cibuildwheel==2.21.3 python -m nox --sessions test_source clear_wheelhouse build_wheel build_sdist test_wheel env: LOG_LEVEL: ${{ github.event.inputs.logLevel }} @@ -58,15 +58,15 @@ jobs: - uses: actions/setup-python@v5 with: python-version: | - 3.9 3.10 3.11 3.12 + 3.13 - name: Run Nox Quick-Tests run: | python -m pip install --upgrade pip python -m pip install --upgrade nox - python -m pip install cibuildwheel==2.16.2 + python -m pip install cibuildwheel==2.21.3 python -m pip install setuptools==73.0.1 python -m nox --sessions test_source clear_wheelhouse build_wheel build_sdist test_wheel env: @@ -92,11 +92,12 @@ jobs: 3.10 3.11 3.12 + 3.13 - name: Install dependencies run: | python -m pip install --upgrade pip python -m pip install --upgrade nox - python -m pip install cibuildwheel==2.16.2 + python -m pip install cibuildwheel==2.21.3 python -m pip install setuptools==73.0.1 - name: Run Nox Quick-Tests run: | @@ -107,8 +108,9 @@ jobs: run: python -m cibuildwheel --output-dir wheelhouse # to supply options, put them in 'env', like: env: - CIBW_BUILD: cp39-macosx_arm64 cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64 + CIBW_BUILD: cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64 cp313-macosx_arm64 CIBW_ARCHS: arm64 + MACOSX_DEPLOYMENT_TARGET: "14.0" - name: Test wheels run: python -m nox --sessions test_wheel \ No newline at end of file diff --git a/.github/workflows/nanopyx_oncall_all_os.yml b/.github/workflows/nanopyx_oncall_all_os.yml index 2eb74443..e5c3ca61 100644 --- a/.github/workflows/nanopyx_oncall_all_os.yml +++ b/.github/workflows/nanopyx_oncall_all_os.yml @@ -25,10 +25,10 @@ jobs: - uses: actions/setup-python@v5 with: python-version: | - 3.9 3.10 3.11 3.12 + 3.13 - name: Run Nox Quick-Tests run: | python -m pip install --upgrade pip @@ -53,10 +53,10 @@ jobs: - uses: actions/setup-python@v5 with: python-version: | - 3.9 3.10 3.11 3.12 + 3.13 - name: Run Nox Quick-Tests run: | python -m pip install --upgrade pip @@ -81,15 +81,15 @@ jobs: - uses: actions/setup-python@v5 with: python-version: | - 3.9 3.10 3.11 3.12 + 3.13 - name: Install dependencies run: | python -m pip install --upgrade pip python -m pip install --upgrade nox - python -m pip install cibuildwheel==2.16.2 + python -m pip install cibuildwheel==2.21.3 - name: Test Source run: python -m nox --sessions test_source env: diff --git a/.github/workflows/nanopyx_oncall_mechanic.yml b/.github/workflows/nanopyx_oncall_mechanic.yml index ad81563e..ba7a29b1 100644 --- a/.github/workflows/nanopyx_oncall_mechanic.yml +++ b/.github/workflows/nanopyx_oncall_mechanic.yml @@ -38,10 +38,10 @@ jobs: - uses: actions/setup-python@v5 with: python-version: | - 3.9 3.10 3.11 3.12 + 3.13 - name: Run Nox Quick-Tests run: | python -m pip install --upgrade pip diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index ff9c08c6..dfccac4f 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -65,7 +65,7 @@ Ready to contribute? Here's how to set up **nanopyx** for local development. Before you submit a pull request, check that it meets these guidelines: - The pull request should pass every existing test. -- The pull request should work for Python 3.8, 3.9 and 3.10 +- The pull request should work for Python 3.10, 3.11, 3.12, and 3.13 - If the pull request adds functionality, new automated tests should be included in the pull request covering the new functionality - Please ensure pytest coverage at least stays the same before you submit a pull request. - The core development team reserves the right to reject pull requests, particularly if these only entail cosmetic changes to the code such as orthographic correction or the addition of type hint to variables. diff --git a/README.md b/README.md index eb870d2e..bde3f961 100644 --- a/README.md +++ b/README.md @@ -16,7 +16,7 @@ Nanoscopy Python library (NanoPyx, the successor to NanoJ) - focused on light microscopy and super-resolution imaging -WARNING: Currently stable and working for Python 3.9 to 3.12. For Python 3.13, it is possible to use it if you build numpy<2 from source but it is not officially supported (Yet!) +⚠️ **Python 3.10+ Required**: NanoPyx v2.0+ supports Python 3.10-3.13 with NumPy 2.x compatibility. --- @@ -87,7 +87,7 @@ pip install napari-nanopyx ## Installation -`NanoPyx` is compatible and tested with Python 3.9, 3.10, 3.11 and 3.12 in MacOS, Windows and Linux. Installation time depends on your hardware and internet connection, but should take around 5 minutes. +`NanoPyx` is compatible and tested with Python 3.10, 3.11, 3.12, and 3.13 in macOS, Windows and Linux. Installation time depends on your hardware and internet connection, but should take around 5 minutes. You can install `NanoPyx` via [pip]: diff --git a/notebooks/eSRRFandQC.ipynb b/notebooks/eSRRFandQC.ipynb index 3f00df8e..5e2ac7bf 100644 --- a/notebooks/eSRRFandQC.ipynb +++ b/notebooks/eSRRFandQC.ipynb @@ -50,12 +50,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "cdd9b61d", "metadata": { "cellView": "form" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cupy implementation is not available. Make sure you have the right version of Cupy and CUDA installed.\n" + ] + } + ], "source": [ "#@title Install NanoPyx, import necessary libraries and connect to Google Drive\n", "import sys\n", @@ -113,7 +121,22 @@ "metadata": { "cellView": "form" }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "bfb9d1b8649e421d97415f0b91544fe6", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(Button(description='Use Own data', layout=Layout(width='50%'), style=ButtonStyle()), Button(des…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "#@title Load image stack\n", "# Create a GUI\n", @@ -209,12 +232,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "322720a0", "metadata": { "cellView": "form" }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9ef4e6c84f7f41468a928a3849bc09b8", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(FloatSlider(value=1.5, description='Ring Radius:', layout=Layout(width='50%'), max=3.0, min=0.1…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# @title Create eSRRF GUI\n", "gui_esrrf = EasyGui(\"esrrf\")\n", @@ -348,12 +386,98 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "a93a23e6", "metadata": { "cellView": "form" }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "3c9d73a06084425080dc8f2f54b8856f", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(Checkbox(value=True, description='Save output', layout=Layout(width='50%'), style=CheckboxStyle…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# @title Create Error Map GUI\n", "gui_error = EasyGui(\"Error\")\n", @@ -519,12 +643,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "7b737a13", "metadata": { "cellView": "form" }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "27f12067a8df4180886f5b23a8c1bb79", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntSlider(value=100, description='Pixel Size:', layout=Layout(width='50%'), max=1000, style=Sli…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "#@title create FRC GUI for original image\n", "gui_frc = EasyGui(\"FRC\")\n", @@ -595,12 +743,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "ad9d9488", "metadata": { "cellView": "form" }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "3cc0da530f4d43bd9d6a7d0c3831c7bc", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntSlider(value=100, description='Pixel Size:', layout=Layout(width='50%'), max=1000, style=Sli…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "#@title create FRC GUI for SR image\n", "gui_frc_esrrf = EasyGui(\"FRC\")\n", @@ -672,12 +844,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "ef3bf607", "metadata": { "cellView": "form" }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "651d0c7aa51a4ab291304f758f09135f", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntSlider(value=100, description='Pixel Size:', layout=Layout(width='50%'), max=1000, style=Sli…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "#@title Create Decorrelation Analysis GUI for eSRRF data\n", "gui_decorr = EasyGui(\"DecorrAnalysis\")\n", @@ -750,12 +946,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "d667d440", "metadata": { "cellView": "form" }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "0a78b3f6d56f4c3093078c861ed3b973", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntSlider(value=100, description='Pixel Size:', layout=Layout(width='50%'), max=1000, style=Sli…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "#@title Create Decorrelation Analysis GUI for eSRRF data\n", "gui_decorr_esrrf = EasyGui(\"DecorrAnalysis\")\n", @@ -808,9 +1028,35 @@ "gui_decorr_esrrf.show()\n", "\n" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "586f7398", + "metadata": {}, + "outputs": [], + "source": [] } ], - "metadata": {}, + "metadata": { + "kernelspec": { + "display_name": "nanopyxnpy2", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, "nbformat": 4, "nbformat_minor": 5 } diff --git a/noxfile.py b/noxfile.py index fda65790..1d664093 100644 --- a/noxfile.py +++ b/noxfile.py @@ -6,7 +6,7 @@ import nox DIR = Path(__file__).parent.resolve() -PYTHON_ALL_VERSIONS = ["3.9", "3.10", "3.11", "3.12"] +PYTHON_ALL_VERSIONS = ["3.10", "3.11", "3.12", "3.13"] PYTHON_DEFAULT_VERSION = "3.10" # Platform logic diff --git a/pyproject.toml b/pyproject.toml index a19c8a29..36cff653 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,10 +1,10 @@ [build-system] requires = [ - "setuptools>=42, <74", + "setuptools>=42", "wheel>=0.38.4", "build>=0.10.0", - "cython>=0.29.0", - "numpy>=1.19.0", + "cython>=3.0.0", + "numpy>=2.0.0", "mako", ] @@ -15,7 +15,7 @@ build-backend = "setuptools.build_meta" name = "nanopyx" description = "Nanoscopy Python library (NanoPyx, the successor to NanoJ) - focused on light microscopy and super-resolution imaging" readme = "README.md" -requires-python = ">=3.9" +requires-python = ">=3.10" license = { file = "LICENSE.txt" } keywords = [ "NanoJ", @@ -32,14 +32,18 @@ authors = [ maintainers = [{ name = "Bruno Saraiva", email = "bruno.msaraiva2@gmail.com" }] classifiers = [ "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", ] dependencies = [ "liquid_engine", "mako>=1.3.0", - "cython>=0.29.32", - "numpy>=1.22,<2", + "cython>=3.0.0", + "numpy>=1.22", "scipy>=1.8", "tifffile>=2022.5.4", "scikit-image>=0.19.2", @@ -66,7 +70,7 @@ all = ["nanopyx[developer,test,jupyter,doc, optional]"] developer = ["pyx2pxd>=0.1.1", "black>=23.1.0", "flake8>=6.0.0"] test = [ "nox>=2022.11.21", - "pytest==7.2", # required to work with pytest-cython (https://github.com/lgpage/pytest-cython/issues/58) + "pytest>=7.2", "pytest-cov>= 4.0.0", "pytest-icdiff>=0.6", # https://github.com/hjwp/pytest-icdiff "pytest-clarity>=1.0.1", # https://pypi.org/project/pytest-clarity/ @@ -74,12 +78,12 @@ test = [ "pytest-plt>=1.1.0", "pytest-xdist>=3.1.0", "pytest-sugar>=0.9.6", - "pytest-cython>=0.2.0", "nanopyx[jupyter]", "nanopyx[optional]", ] -optional=["numba", "dask<2024.2.0", "dask_image", "transonic"] +optional=["dask<2024.2.0", "dask_image", "transonic"] cuda = ["cupy"] # should be manually installed by users according to their CUDA version https://docs.cupy.dev/en/stable/install.html +numba=["numba"] # moved to manual install as numba may not be fully supported in the latest Python versions jupyter = [ "nbformat>=4.2.0", "seaborn>=0.12.1", @@ -141,7 +145,7 @@ reportUndefinedVariable = false reportMissingImports = false [tool.pytest.ini_options] -addopts = "--cov=nanopyx --plots --doctest-modules --doctest-cython --ignore-glob=run*Tools.py --ignore=setup.py --ignore=notebooks/ --ignore=src/scripts --ignore=src/notebookchef --ignore=tests/notebooks --cov-report term-missing" +addopts = "--cov=nanopyx --plots --doctest-modules --ignore-glob=run*Tools.py --ignore=setup.py --ignore=notebooks/ --ignore=src/scripts --ignore=src/notebookchef --ignore=tests/notebooks --cov-report term-missing" timeout = 6001 plt_dirname = "tests_plots" doctest_encoding = "latin1" @@ -170,7 +174,7 @@ omit = [ [tool.cibuildwheel] # https://cibuildwheel.readthedocs.io/en/stable/options/ skip = ["pp*", "*musllinux*"] -build = ["cp39-*", "cp310-*", "cp311-*", "cp312-*"] +build = ["cp310-*", "cp311-*", "cp312-*", "cp313-*"] # it is not possible to test arm64 and the arm64 part of a universal2 wheel on this CI platform test-skip = ["*arm64"] # build-frontend = "pip" @@ -206,12 +210,8 @@ test-requires = ["nanopyx[test]"] # #repair-wheel-command = "delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel}" # repair-wheel-command = "delocate-wheel -w {dest_dir} -v {wheel}" -# [tool.cibuildwheel.macos.environment] -# CMAKE_OSX_ARCHITECTURES = "arm64;x86_64" -# MACOSX_DEPLOYMENT_TARGET = "11" -# LDFLAGS="-L/usr/local/lib" -# CXX="/usr/local/opt/llvm/bin/clang++" -# CC="/usr/local/opt/llvm/bin/clang" +[tool.cibuildwheel.macos.environment] +MACOSX_DEPLOYMENT_TARGET = "14.0" [tool.cibuildwheel.windows] archs = ["AMD64"] diff --git a/setup.py b/setup.py index 8bcb0fc9..f8eb9dec 100644 --- a/setup.py +++ b/setup.py @@ -22,7 +22,7 @@ ] EXTRA_LING_ARGS = [] -VERSION = "1.3.3" # sets version number for whole package +VERSION = "2.0.0" # sets version number for whole package def run_command(command: str) -> str: @@ -117,10 +117,9 @@ def search_for_c_files_referrenced_in_pyx_text(text: str): if sys.platform == "win32": - from distutils import msvccompiler + # distutils.msvccompiler removed in Python 3.12+, no longer needed from platform import architecture - VC_VERSION = msvccompiler.get_build_version() ARCH = "x64" if architecture()[0] == "64bit" else "x86" INCLUDE_DIRS += [] LIBRARY_DIRS += [] diff --git a/src/nanopyx/__init__.py b/src/nanopyx/__init__.py index 77035398..875e1d01 100644 --- a/src/nanopyx/__init__.py +++ b/src/nanopyx/__init__.py @@ -3,9 +3,14 @@ """ import os -import pkg_resources # part of setuptools -__version__ = pkg_resources.require("NanoPyx")[0].version +try: + from importlib.metadata import version +except ImportError: + # Python < 3.8 fallback (though we require 3.10+) + from importlib_metadata import version + +__version__ = version("nanopyx") from . import core, data, methods # noqa: F401 diff --git a/src/nanopyx/core/analysis/decorr_imagej.pyx b/src/nanopyx/core/analysis/decorr_imagej.pyx index d6f55dfa..a27aeb86 100644 --- a/src/nanopyx/core/analysis/decorr_imagej.pyx +++ b/src/nanopyx/core/analysis/decorr_imagej.pyx @@ -277,7 +277,7 @@ cdef class DecorrAnalysis: cdef float[:, :] _compute_d(self): cdef float[:] coef, kc, a, dg, result, results_gm, results_max - cdef complex[:, :] fft + cdef double complex[:, :] fft cdef float[:, :] d_curve, img_ref, blurred, mask, fft_real, fft_imag cdef float[:, :, :] normalized_fft cdef int count = 0 @@ -309,7 +309,7 @@ cdef class DecorrAnalysis: blurred = np.copy(self.img_ref) blurred = gaussian_filter(blurred, sig) blurred = np.copy(self.img_ref) - blurred - fft = np.fft.fftshift(np.fft.fft2(blurred)) + fft = np.fft.fftshift(np.fft.fft2(blurred)).astype(np.complex128) fft_real = np.real(fft).astype(np.float32) fft_imag = np.imag(fft).astype(np.float32) normalized_fft = _normalizeFFT(fft_real, fft_imag) @@ -409,7 +409,7 @@ cdef class DecorrAnalysis: cdef _run_analysis(self): cdef float[:] out - cdef complex[:, :] img_fft + cdef double complex[:, :] img_fft cdef float[:, :] img_ref, img_f, temp, fft_real, fft_imag cdef float resolution img_ref = np.copy(self.img) @@ -423,7 +423,7 @@ cdef class DecorrAnalysis: img_f = _apodize_edges(img_f) temp = self._get_preprocessed_image(img_f) self.img_ref = np.copy(temp) - img_fft = np.fft.fftshift(np.fft.fft2(temp)) + img_fft = np.fft.fftshift(np.fft.fft2(temp)).astype(np.complex128) fft_real = np.real(img_fft).astype(np.float32) fft_imag = np.imag(img_fft).astype(np.float32) fft_real[fft_real.shape[0]//2, fft_real.shape[1]//2] = 0 diff --git a/src/nanopyx/core/generate/simulate_particle_field.pyx b/src/nanopyx/core/generate/simulate_particle_field.pyx index 3e7c8d68..5efc58a4 100644 --- a/src/nanopyx/core/generate/simulate_particle_field.pyx +++ b/src/nanopyx/core/generate/simulate_particle_field.pyx @@ -77,7 +77,7 @@ def simulate_particle_field_based_on_2D_PDF(image_pdf, cdef float[:] _xp = xp # xp exists in python land, _xp in c land as memoryview cdef float[:] _yp = yp # same as above - cdef np.ndarray[np.int32_t, ndim=1] particles_not_set, particles_set + cdef int[:] particles_not_set, particles_set cdef int n_particles = 0 cdef int previous_n_particles = 0 @@ -88,7 +88,7 @@ def simulate_particle_field_based_on_2D_PDF(image_pdf, # start by creating the minimal pool of particles with tqdm(total=max_particles, desc="Generating particles", unit="particles") as progress_bar: while 1: - particles_not_set = np.nonzero(xp < 0)[0].astype(np.int32) # get the index for the parciles not yet set + particles_not_set = np.nonzero(xp < 0)[0].astype(np.int32) # get the index for the particles not yet set with nogil: for p in prange(particles_not_set.shape[0]): _get_particle_candidate(_image_pdf, p, _xp, _yp, _min_distance) # find some particles diff --git a/src/nanopyx/core/transform/_interpolation.pyx b/src/nanopyx/core/transform/_interpolation.pyx index 2b979b20..dea4b771 100644 --- a/src/nanopyx/core/transform/_interpolation.pyx +++ b/src/nanopyx/core/transform/_interpolation.pyx @@ -162,8 +162,8 @@ cdef float[:, :] _fht_space_interpolation_c(float[:, :] img, int intFactor, bint working_img = img # Forward FFT (use complex128 for accuracy) - cdef complex[:, :] F = fft.fft2(np.asarray(working_img)) - cdef complex[:, :] Fshift = fft.fftshift(F) + cdef double complex[:, :] F = fft.fft2(np.asarray(working_img)).astype(np.complex128) + cdef double complex[:, :] Fshift = fft.fftshift(F).astype(np.complex128) cdef int h = Fshift.shape[0] cdef int w = Fshift.shape[1] @@ -181,7 +181,7 @@ cdef float[:, :] _fht_space_interpolation_c(float[:, :] img, int intFactor, bint FInt[yROI:yROI + h, xROI:xROI + w] = Fshift # Inverse transform - cdef complex[:, :] result = fft.ifft2(fft.ifftshift(FInt)) + cdef double complex[:, :] result = fft.ifft2(fft.ifftshift(FInt)).astype(np.complex128) cdef float[:, :] output = np.real(result).astype(np.float32) # Scale to match input range (robust to constant images)