MAINT: Merge update_docs branch

.github/workflows/python-test-latest.yml

@@ -40,6 +40,8 @@ jobs:
 
     steps:
     - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+      with:
+        persist-credentials: false
 
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0

.github/workflows/python-test.yml

@@ -40,12 +40,8 @@ jobs:
 
     steps:
     - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
-      # fetch-depth: '0' is needed to fetch tags for hatch-vcs (and thus setuptools-scm)
-      # to generate the version correctly; only really needed for jobs that would build and
-      # upload to pypi, so ignore it since fetching the entire git history can take much longer
-      # than the default of fetching just the last commit
-      #with:
-        #fetch-depth: '0'
+      with:
+        persist-credentials: false
 
     - name: Set up Python
       uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
@@ -81,6 +77,8 @@ jobs:
 
     steps:
     - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+      with:
+        persist-credentials: false
 
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
@@ -113,6 +111,8 @@ jobs:
 
     steps:
     - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+      with:
+        persist-credentials: false
 
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
@@ -124,3 +124,32 @@ jobs:
 
     - name: Lint
       run: ruff check .
+
+  doctest:
+
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        # only test earliest and latest supported Python versions since the examples should
+        # be fairly simple
+        python-version: ['3.9', '3.13']
+
+    steps:
+    - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+      with:
+        persist-credentials: false
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install dependencies
+      # TODO will need to think of how to handle doctests when they rely on optional dependencies
+      run: |
+        python -m pip install --upgrade pip
+        python -m pip install ".[test, doctest]"
+
+    - name: Run doctests
+      run: pytest pybaselines --doctest-modules

docs/algorithms/classification.rst

@@ -17,6 +17,8 @@ method. The plot below shows such an example.
 
 .. plot::
    :align: center
+   :include-source: False
+   :show-source-link: True
 
     import numpy as np
     import matplotlib.pyplot as plt
@@ -75,6 +77,8 @@ points, and then iteratively fitting a polynomial to the interpolated baseline.
 .. plot::
    :align: center
    :context: reset
+   :include-source: False
+   :show-source-link: True
 
     import numpy as np
     import matplotlib.pyplot as plt
@@ -206,6 +210,8 @@ the noise's standard deviation as belonging to the baseline.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -234,6 +240,8 @@ of the median of the noise's standard deviation distribution.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -263,6 +271,8 @@ threshold, and peak regions are iteratively interpolated until the baseline is b
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -291,6 +301,8 @@ other points have a weight of 0.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     scales = np.arange(2, 40)
     # to see contents of create_data function, look at the top-most algorithm's code
@@ -327,6 +339,8 @@ a weight of 0.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -369,6 +383,8 @@ peak positions.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -397,6 +413,8 @@ slightly reduced, as seen below.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)

docs/algorithms/misc.rst

@@ -25,6 +25,8 @@ with user interfaces and is not encouraged otherwise.
 
 .. plot::
    :align: center
+   :include-source: False
+   :show-source-link: True
 
     import numpy as np
     import matplotlib.pyplot as plt
@@ -81,6 +83,8 @@ as sparse.
 .. plot::
    :align: center
    :context: reset
+   :include-source: False
+   :show-source-link: True
 
     import numpy as np
     import matplotlib.pyplot as plt
@@ -205,6 +209,8 @@ of the beads function.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the second-to-top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)

docs/algorithms/morphological.rst

@@ -13,6 +13,8 @@ below. The algorithms in this section use these operations to estimate the basel
 .. plot::
    :align: center
    :context: reset
+   :include-source: False
+   :show-source-link: True
 
     import numpy as np
     import matplotlib.pyplot as plt
@@ -80,6 +82,8 @@ method.
 .. plot::
    :align: center
    :context: reset
+   :include-source: False
+   :show-source-link: True
 
     import numpy as np
     import matplotlib.pyplot as plt
@@ -212,6 +216,8 @@ erosion and dilation of the opening to create the baseline.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -235,6 +241,8 @@ create the baseline.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -252,6 +260,8 @@ kernel, to produce a smooth baseline.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -276,6 +286,8 @@ and opening of either the data (first iteration) or previous iteration's baselin
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -294,6 +306,8 @@ resembles rolling a ball across the data.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -315,6 +329,8 @@ then smooths the result with a moving average.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -340,6 +356,8 @@ tophat (Top-hat Transformation)
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -367,6 +385,8 @@ Finally, a penalized spline is fit to the smoothed data with the assigned weight
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -419,11 +439,11 @@ linear equations:
 
 .. math::
 
-    (I + 2 \gamma D_d^{\top} D_d) s^n = y - v^{n-1}
+    (I + 2 \gamma D_d^{\mathsf{T}} D_d) s^n = y - v^{n-1}
 
 .. math::
 
-    (I + 2 \alpha I + 2 \beta D_d^{\top} D_d) v^n = y - s^n + 2 \alpha Op
+    (I + 2 \alpha I + 2 \beta D_d^{\mathsf{T}} D_d) v^n = y - s^n + 2 \alpha Op
 
 where :math:`I` is the identity matrix and :math:`D_d` is the matrix version
 of :math:`\Delta^d`, which is also the d-th derivative of the identity matrix.
@@ -433,6 +453,8 @@ multipliers.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)
@@ -452,6 +474,8 @@ of the jbcd function.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the second-to-top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)

docs/algorithms/optimizers.rst

@@ -26,6 +26,8 @@ An example of data with added baseline and Gaussian peaks is shown below.
 
 .. plot::
    :align: center
+   :include-source: False
+   :show-source-link: True
 
     import numpy as np
     import matplotlib.pyplot as plt
@@ -88,6 +90,8 @@ added linear regions is selected as the optimal parameter.
 .. plot::
    :align: center
    :context: reset
+   :include-source: False
+   :show-source-link: True
 
     import numpy as np
     import matplotlib.pyplot as plt
@@ -225,6 +229,8 @@ algorithm versus the individual baselines from the mpls method.
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     x = np.linspace(1, 1000, 500)
     signal = (
@@ -283,6 +289,8 @@ the name).
 .. plot::
    :align: center
    :context: close-figs
+   :include-source: False
+   :show-source-link: True
 
     # to see contents of create_data function, look at the top-most algorithm's code
     figure, axes, handles = create_plots(data, baselines)