Merge branch 'release/v0.2.3'

colour-science · Dec 2, 2022 · 4479502 · 4479502
2 parents c78eb63 + a2ecf0e
commit 4479502
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diff --git a/.github/workflows/continuous-integration-documentation.yml b/.github/workflows/continuous-integration-documentation.yml
@@ -7,8 +7,8 @@ jobs:
     name: ${{ matrix.os }} - Python ${{ matrix.python-version }}
     strategy:
       matrix:
-        os: [ubuntu-20.04]
-        python-version: [3.8]
+        os: [ubuntu-22.04]
+        python-version: [3.11]
       fail-fast: false
     runs-on: ${{ matrix.os }}
     steps:
@@ -31,8 +31,7 @@ jobs:
         sudo apt-get --yes install latexmk texlive-full
     - name: Install Poetry
       run: |
-        curl -L https://raw.githubusercontent.com/sdispater/poetry/master/get-poetry.py -o get-poetry.py
-        python get-poetry.py
+        curl -sSL https://install.python-poetry.org | POETRY_HOME=$HOME/.poetry python3 -
         echo "$HOME/.poetry/bin" >> $GITHUB_PATH
       shell: bash
     - name: Install Package Dependencies

diff --git a/.github/workflows/continuous-integration-quality-unit-tests.yml b/.github/workflows/continuous-integration-quality-unit-tests.yml
@@ -7,8 +7,8 @@ jobs:
     name: ${{ matrix.os }} - Python ${{ matrix.python-version }}
     strategy:
       matrix:
-        os: [macOS-latest, ubuntu-20.04, windows-latest]
-        python-version: [3.8, 3.9, '3.10']
+        os: [macOS-latest, ubuntu-22.04, windows-latest]
+        python-version: [3.9, '3.10', 3.11]
       fail-fast: false
     runs-on: ${{ matrix.os }}
     steps:
@@ -22,14 +22,17 @@ jobs:
         echo "CI_SHA=${{ github.sha }}" >> $GITHUB_ENV
         echo "COVERALLS_REPO_TOKEN=${{ secrets.COVERALLS_REPO_TOKEN }}" >> $GITHUB_ENV
       shell: bash
+    - name: Set up Python 3.9 for Pre-Commit
+      uses: actions/setup-python@v1
+      with:
+        python-version: 3.9
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v1
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install Poetry
       run: |
-        curl -L https://raw.githubusercontent.com/sdispater/poetry/master/get-poetry.py -o get-poetry.py
-        python get-poetry.py --version 1.1.12
+        curl -sSL https://install.python-poetry.org | POETRY_HOME=$HOME/.poetry python3 -
         echo "$HOME/.poetry/bin" >> $GITHUB_PATH
       shell: bash
     - name: Install Package Dependencies

diff --git a/.github/workflows/continuous-integration-static-type-checking.yml b/.github/workflows/continuous-integration-static-type-checking.yml
@@ -8,20 +8,22 @@ jobs:
     strategy:
       matrix:
         os: [macOS-latest]
-        python-version: [3.9]
+        python-version: [3.11]
       fail-fast: false
     runs-on: ${{ matrix.os }}
     steps:
     - uses: actions/checkout@v1
     - name: Environment Variables
       run: |
-        echo "CI_PACKAGE=colour" >> $GITHUB_ENV
+        echo "CI_PACKAGE=colour_demosaicing" >> $GITHUB_ENV
       shell: bash
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v1
       with:
         python-version: ${{ matrix.python-version }}
-    - name: Static Type Checking
+    - name: Install Package Dependencies
       run: |
         pip install -r requirements.txt
-        mypy --install-types --non-interactive --show-error-codes --warn-unused-ignores --warn-redundant-casts -p $CI_PACKAGE
+    - name: Static Type Checking
+      run: |
+        mypy --install-types --non-interactive --show-error-codes --warn-unused-ignores --warn-redundant-casts $CI_PACKAGE
diff --git a/.gitignore b/.gitignore
@@ -1,12 +1,16 @@
+*.egg-info
 *.pyc
+*.pyo
 .DS_Store
 .coverage
 .dmypy.json
+.fleet
 .idea
-.ipynb_checkpoints/
+.ipynb_checkpoints
 .mypy_cache
-.vscode
 .sandbox
+.vs
+.vscode
 
 __pycache__
 

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -1,20 +1,25 @@
 repos:
 -   repo: https://github.com/asottile/pyupgrade
-    rev: v2.34.0
+    rev: v3.2.2
     hooks:
     -   id: pyupgrade
-        args: [--py38-plus]
+        args: [--py39-plus]
 -   repo: https://github.com/ikamensh/flynt/
-    rev: '0.76'
+    rev: '0.77'
     hooks:
     -   id: flynt
 -   repo: https://github.com/psf/black
-    rev: 22.3.0
+    rev: 22.10.0
     hooks:
     - id: black
-      language_version: python3.8
+      language_version: python3.9
+-   repo: https://github.com/keewis/blackdoc
+    rev: v0.3.8
+    hooks:
+    - id: blackdoc
+      language_version: python3.9
 -   repo: https://github.com/PyCQA/flake8
-    rev: 4.0.1
+    rev: 6.0.0
     hooks:
     -   id: flake8
 -   repo: https://github.com/pycqa/pydocstyle

diff --git a/.readthedocs.yaml b/.readthedocs.yaml
@@ -3,7 +3,7 @@ version: 2
 build:
   os: ubuntu-20.04
   tools:
-    python: "3.8"
+    python: "3.11"
 
 sphinx:
    configuration: docs/conf.py

diff --git a/CONTRIBUTORS.rst b/CONTRIBUTORS.rst
@@ -4,7 +4,7 @@ Contributors
 Development & Technical Support
 -------------------------------
 
--   **Thomas Mansencal**, *Lead Pipeline Developer @ WetaFX*
+-   **Thomas Mansencal**, *Technology Supervisor @ Wētā FX*
 
     Project coordination, overall development.
 

diff --git a/colour_demosaicing/__init__.py b/colour_demosaicing/__init__.py
@@ -42,19 +42,19 @@
     "mosaicing_CFA_Bayer",
 ]
 
-RESOURCES_DIRECTORY: str = os.path.join(os.path.dirname(__file__), "resources")
-EXAMPLES_RESOURCES_DIRECTORY: str = os.path.join(
-    RESOURCES_DIRECTORY, "colour-demosaicing-examples-datasets"
+ROOT_RESOURCES: str = os.path.join(os.path.dirname(__file__), "resources")
+ROOT_RESOURCES_EXAMPLES: str = os.path.join(
+    ROOT_RESOURCES, "colour-demosaicing-examples-datasets"
 )
-TESTS_RESOURCES_DIRECTORY: str = os.path.join(
-    RESOURCES_DIRECTORY, "colour-demosaicing-tests-datasets"
+ROOT_RESOURCES_TESTS: str = os.path.join(
+    ROOT_RESOURCES, "colour-demosaicing-tests-datasets"
 )
 
 __application_name__ = "Colour - Demosaicing"
 
 __major_version__ = "0"
 __minor_version__ = "2"
-__change_version__ = "2"
+__change_version__ = "3"
 __version__ = ".".join(
     (__major_version__, __minor_version__, __change_version__)
 )

diff --git a/colour_demosaicing/bayer/demosaicing/bilinear.py b/colour_demosaicing/bayer/demosaicing/bilinear.py
@@ -55,7 +55,7 @@ def demosaicing_CFA_Bayer_bilinear(
     Notes
     -----
     -   The definition output is not clipped in range [0, 1] : this allows for
-        direct HDRI / radiance image generation on *Bayer* CFA data and post
+        direct HDRI image generation on *Bayer* CFA data and post
         demosaicing of the high dynamic range data as showcased in this
         `Jupyter Notebook <https://github.com/colour-science/colour-hdri/\
 blob/develop/colour_hdri/examples/\
@@ -69,8 +69,11 @@ def demosaicing_CFA_Bayer_bilinear(
     --------
     >>> import numpy as np
     >>> CFA = np.array(
-    ...     [[0.30980393, 0.36078432, 0.30588236, 0.3764706],
-    ...      [0.35686275, 0.39607844, 0.36078432, 0.40000001]])
+    ...     [
+    ...         [0.30980393, 0.36078432, 0.30588236, 0.3764706],
+    ...         [0.35686275, 0.39607844, 0.36078432, 0.40000001],
+    ...     ]
+    ... )
     >>> demosaicing_CFA_Bayer_bilinear(CFA)
     array([[[ 0.69705884,  0.17941177,  0.09901961],
             [ 0.46176472,  0.4509804 ,  0.19803922],
@@ -82,9 +85,12 @@ def demosaicing_CFA_Bayer_bilinear(
             [ 0.15294118,  0.4509804 ,  0.59705884],
             [ 0.07647059,  0.18431373,  0.90000002]]])
     >>> CFA = np.array(
-    ...     [[0.3764706, 0.360784320, 0.40784314, 0.3764706],
-    ...      [0.35686275, 0.30980393, 0.36078432, 0.29803923]])
-    >>> demosaicing_CFA_Bayer_bilinear(CFA, 'BGGR')
+    ...     [
+    ...         [0.3764706, 0.360784320, 0.40784314, 0.3764706],
+    ...         [0.35686275, 0.30980393, 0.36078432, 0.29803923],
+    ...     ]
+    ... )
+    >>> demosaicing_CFA_Bayer_bilinear(CFA, "BGGR")
     array([[[ 0.07745098,  0.17941177,  0.84705885],
             [ 0.15490197,  0.4509804 ,  0.5882353 ],
             [ 0.15196079,  0.27450981,  0.61176471],

diff --git a/colour_demosaicing/bayer/demosaicing/malvar2004.py b/colour_demosaicing/bayer/demosaicing/malvar2004.py
@@ -58,7 +58,7 @@ def demosaicing_CFA_Bayer_Malvar2004(
     Notes
     -----
     -   The definition output is not clipped in range [0, 1] : this allows for
-        direct HDRI / radiance image generation on *Bayer* CFA data and post
+        direct HDRI image generation on *Bayer* CFA data and post
         demosaicing of the high dynamic range data as showcased in this
         `Jupyter Notebook <https://github.com/colour-science/colour-hdri/\
 blob/develop/colour_hdri/examples/\
@@ -71,8 +71,11 @@ def demosaicing_CFA_Bayer_Malvar2004(
     Examples
     --------
     >>> CFA = np.array(
-    ...     [[0.30980393, 0.36078432, 0.30588236, 0.3764706],
-    ...      [0.35686275, 0.39607844, 0.36078432, 0.40000001]])
+    ...     [
+    ...         [0.30980393, 0.36078432, 0.30588236, 0.3764706],
+    ...         [0.35686275, 0.39607844, 0.36078432, 0.40000001],
+    ...     ]
+    ... )
     >>> demosaicing_CFA_Bayer_Malvar2004(CFA)
     array([[[ 0.30980393,  0.31666668,  0.32941177],
             [ 0.33039216,  0.36078432,  0.38112746],
@@ -84,9 +87,12 @@ def demosaicing_CFA_Bayer_Malvar2004(
             [ 0.3379902 ,  0.36078432,  0.3754902 ],
             [ 0.37769609,  0.39558825,  0.40000001]]])
     >>> CFA = np.array(
-    ...     [[0.3764706, 0.360784320, 0.40784314, 0.3764706],
-    ...      [0.35686275, 0.30980393, 0.36078432, 0.29803923]])
-    >>> demosaicing_CFA_Bayer_Malvar2004(CFA, 'BGGR')
+    ...     [
+    ...         [0.3764706, 0.360784320, 0.40784314, 0.3764706],
+    ...         [0.35686275, 0.30980393, 0.36078432, 0.29803923],
+    ...     ]
+    ... )
+    >>> demosaicing_CFA_Bayer_Malvar2004(CFA, "BGGR")
     array([[[ 0.35539217,  0.37058825,  0.3764706 ],
             [ 0.34264707,  0.36078432,  0.37450981],
             [ 0.36568628,  0.39607844,  0.40784314],
@@ -157,13 +163,13 @@ def demosaicing_CFA_Bayer_Malvar2004(
     del GR_GB, Rg_RB_Bg_BR, Rg_BR_Bg_RB, Rb_BB_Br_RR
 
     # Red rows.
-    R_r = np.transpose(np.any(R_m == 1, axis=1)[np.newaxis]) * ones(R.shape)
+    R_r = np.transpose(np.any(R_m == 1, axis=1)[None]) * ones(R.shape)
     # Red columns.
-    R_c = np.any(R_m == 1, axis=0)[np.newaxis] * ones(R.shape)
+    R_c = np.any(R_m == 1, axis=0)[None] * ones(R.shape)
     # Blue rows.
-    B_r = np.transpose(np.any(B_m == 1, axis=1)[np.newaxis]) * ones(B.shape)
+    B_r = np.transpose(np.any(B_m == 1, axis=1)[None]) * ones(B.shape)
     # Blue columns
-    B_c = np.any(B_m == 1, axis=0)[np.newaxis] * ones(B.shape)
+    B_c = np.any(B_m == 1, axis=0)[None] * ones(B.shape)
 
     del R_m, B_m
 

diff --git a/colour_demosaicing/bayer/demosaicing/menon2007.py b/colour_demosaicing/bayer/demosaicing/menon2007.py
@@ -74,7 +74,7 @@ def demosaicing_CFA_Bayer_Menon2007(
     Notes
     -----
     -   The definition output is not clipped in range [0, 1] : this allows for
-        direct HDRI / radiance image generation on *Bayer* CFA data and post
+        direct HDRI image generation on *Bayer* CFA data and post
         demosaicing of the high dynamic range data as showcased in this
         `Jupyter Notebook <https://github.com/colour-science/colour-hdri/\
 blob/develop/colour_hdri/examples/\
@@ -87,8 +87,11 @@ def demosaicing_CFA_Bayer_Menon2007(
     Examples
     --------
     >>> CFA = np.array(
-    ...     [[ 0.30980393,  0.36078432,  0.30588236,  0.3764706 ],
-    ...      [ 0.35686275,  0.39607844,  0.36078432,  0.40000001]])
+    ...     [
+    ...         [0.30980393, 0.36078432, 0.30588236, 0.3764706],
+    ...         [0.35686275, 0.39607844, 0.36078432, 0.40000001],
+    ...     ]
+    ... )
     >>> demosaicing_CFA_Bayer_Menon2007(CFA)
     array([[[ 0.30980393,  0.35686275,  0.39215687],
             [ 0.30980393,  0.36078432,  0.39607844],
@@ -100,9 +103,12 @@ def demosaicing_CFA_Bayer_Menon2007(
             [ 0.30588236,  0.36078432,  0.39019609],
             [ 0.32156864,  0.3764706 ,  0.40000001]]])
     >>> CFA = np.array(
-    ...     [[ 0.3764706 ,  0.36078432,  0.40784314,  0.3764706 ],
-    ...      [ 0.35686275,  0.30980393,  0.36078432,  0.29803923]])
-    >>> demosaicing_CFA_Bayer_Menon2007(CFA, 'BGGR')
+    ...     [
+    ...         [0.3764706, 0.36078432, 0.40784314, 0.3764706],
+    ...         [0.35686275, 0.30980393, 0.36078432, 0.29803923],
+    ...     ]
+    ... )
+    >>> demosaicing_CFA_Bayer_Menon2007(CFA, "BGGR")
     array([[[ 0.30588236,  0.35686275,  0.3764706 ],
             [ 0.30980393,  0.36078432,  0.39411766],
             [ 0.29607844,  0.36078432,  0.40784314],
@@ -160,9 +166,9 @@ def demosaicing_CFA_Bayer_Menon2007(
     del d_H, d_V, G_H, G_V
 
     # Red rows.
-    R_r = np.transpose(np.any(R_m == 1, axis=1)[np.newaxis]) * ones(R.shape)
+    R_r = np.transpose(np.any(R_m == 1, axis=1)[None]) * ones(R.shape)
     # Blue rows.
-    B_r = np.transpose(np.any(B_m == 1, axis=1)[np.newaxis]) * ones(B.shape)
+    B_r = np.transpose(np.any(B_m == 1, axis=1)[None]) * ones(B.shape)
 
     k_b = as_float_array([0.5, 0, 0.5])
 
@@ -248,26 +254,28 @@ def refining_step_Menon2007(
     Examples
     --------
     >>> RGB = np.array(
-    ...     [[[0.30588236, 0.35686275, 0.3764706],
-    ...       [0.30980393, 0.36078432, 0.39411766],
-    ...       [0.29607844, 0.36078432, 0.40784314],
-    ...       [0.29803923, 0.37647060, 0.42352942]],
-    ...      [[0.30588236, 0.35686275, 0.3764706],
-    ...       [0.30980393, 0.36078432, 0.39411766],
-    ...       [0.29607844, 0.36078432, 0.40784314],
-    ...       [0.29803923, 0.37647060, 0.42352942]]])
+    ...     [
+    ...         [
+    ...             [0.30588236, 0.35686275, 0.3764706],
+    ...             [0.30980393, 0.36078432, 0.39411766],
+    ...             [0.29607844, 0.36078432, 0.40784314],
+    ...             [0.29803923, 0.37647060, 0.42352942],
+    ...         ],
+    ...         [
+    ...             [0.30588236, 0.35686275, 0.3764706],
+    ...             [0.30980393, 0.36078432, 0.39411766],
+    ...             [0.29607844, 0.36078432, 0.40784314],
+    ...             [0.29803923, 0.37647060, 0.42352942],
+    ...         ],
+    ...     ]
+    ... )
     >>> RGB_m = np.array(
-    ...     [[[0, 0, 1],
-    ...       [0, 1, 0],
-    ...       [0, 0, 1],
-    ...       [0, 1, 0]],
-    ...      [[0, 1, 0],
-    ...       [1, 0, 0],
-    ...       [0, 1, 0],
-    ...       [1, 0, 0]]])
-    >>> M = np.array(
-    ...     [[0, 1, 0, 1],
-    ...      [1, 0, 1, 0]])
+    ...     [
+    ...         [[0, 0, 1], [0, 1, 0], [0, 0, 1], [0, 1, 0]],
+    ...         [[0, 1, 0], [1, 0, 0], [0, 1, 0], [1, 0, 0]],
+    ...     ]
+    ... )
+    >>> M = np.array([[0, 1, 0, 1], [1, 0, 1, 0]])
     >>> refining_step_Menon2007(RGB, RGB_m, M)
     array([[[ 0.30588236,  0.35686275,  0.3764706 ],
             [ 0.30980393,  0.36078432,  0.39411765],
@@ -310,13 +318,13 @@ def refining_step_Menon2007(
 
     # Updating of the red and blue components in the green locations.
     # Red rows.
-    R_r = np.transpose(np.any(R_m == 1, axis=1)[np.newaxis]) * ones(R.shape)
+    R_r = np.transpose(np.any(R_m == 1, axis=1)[None]) * ones(R.shape)
     # Red columns.
-    R_c = np.any(R_m == 1, axis=0)[np.newaxis] * ones(R.shape)
+    R_c = np.any(R_m == 1, axis=0)[None] * ones(R.shape)
     # Blue rows.
-    B_r = np.transpose(np.any(B_m == 1, axis=1)[np.newaxis]) * ones(B.shape)
+    B_r = np.transpose(np.any(B_m == 1, axis=1)[None]) * ones(B.shape)
     # Blue columns.
-    B_c = np.any(B_m == 1, axis=0)[np.newaxis] * ones(B.shape)
+    B_c = np.any(B_m == 1, axis=0)[None] * ones(B.shape)
 
     R_G = R - G
     B_G = B - G