Merge branch 'main' into some-devops

Author: drbenvincent

.github/workflows/ci.yml

@@ -14,9 +14,9 @@ jobs:
         python-version: ["3.8", "3.9", "3.10"]
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
       - name: Run lint
@@ -29,9 +29,9 @@ jobs:
         python-version: ["3.8", "3.9", "3.10"]
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - name: Set up Python
-        uses: actions/setup-python@v3
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
       - name: Run doctests

.github/workflows/release.yml

@@ -12,10 +12,10 @@ jobs:
     name: Build source distribution
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
         with:
           fetch-depth: 0
-      - uses: actions/setup-python@v4
+      - uses: actions/setup-python@v5
         with:
           python-version: 3.8
       - name: Build the sdist and the wheel
@@ -40,7 +40,7 @@ jobs:
           echo "Checking import and version number (on release)"
           venv-bdist/bin/python -c "import causalpy; assert causalpy.__version__ == '${{  github.ref_name }}' if '${{ github.ref_type }}' == 'tag' else causalpy.__version__; print(causalpy.__version__)"
           cd ..
-      - uses: actions/upload-artifact@v3
+      - uses: actions/upload-artifact@v4
         with:
           name: artifact
           path: dist/*
@@ -60,7 +60,7 @@ jobs:
           user: __token__
           password: ${{ secrets.TEST_PYPI_API_TOKEN }}
           repository_url: https://test.pypi.org/legacy/
-      - uses: actions/setup-python@v4
+      - uses: actions/setup-python@v5
         with:
           python-version: 3.8
       - name: Test pip install from test.pypi

CONTRIBUTING.md

@@ -62,16 +62,17 @@ For more instructions see the [Pull request checklist](#pull-request-checklist)
     Install the package (in editable mode) and its development dependencies. The `--no-deps` flag is used to avoid installing the dependencies of `CausalPy` as they are already installed when installing the development dependencies. This can end up interfering with the conda-only install of pymc.
 
     ```bash
-    pip install -e . --no-deps
+    pip install --no-deps -e .
     ```
 
 	Install development dependencies
 
-	```
+	```bash
 	pip install 'causalpy[dev]'
 	pip install 'causalpy[docs]'
 	pip install 'causalpy[test]'
 	pip install 'causalpy[lint]'
+	pip install 'pylint'
 	```
 
 	It may also be necessary to [install](https://pandoc.org/installing.html) `pandoc`. On a mac, run `brew install pandoc`.

Makefile

@@ -21,5 +21,4 @@ test:
 	pytest
 
 uml:
-	pip install pylint
 	pyreverse -o png causalpy --output-directory docs/source/_static --ignore tests

README.md

@@ -178,7 +178,7 @@ Interrupted time series analysis is appropriate when you have a time series of o
 
 | Frequentist | Bayesian |
 |--|--|
-| coming soon | ![](https://raw.githubusercontent.com/pymc-labs/CausalPy/main/docs/source/_static/interrupted_time_series_pymc.svg) |
+| ![](https://raw.githubusercontent.com/pymc-labs/CausalPy/main/docs/source/_static/interrupted_time_series_skl.svg) | ![](https://raw.githubusercontent.com/pymc-labs/CausalPy/main/docs/source/_static/interrupted_time_series_pymc.svg) |
 
 > The data, pre-treatment model fit, and counterfactual are plotted (top). The causal impact is shown as a blue shaded region. The Bayesian analysis shows shaded Bayesian credible regions of the model fit and counterfactual. Also shown is the causal impact (middle) and cumulative causal impact (bottom).
 

causalpy/skl_experiments.py

@@ -475,7 +475,10 @@ def plot(self, round_to=None):
         )
         ax.annotate(
             "causal\nimpact",
-            xy=(1.05, np.mean([self.y_pred_counterfactual, self.y_pred_treatment[1]])),
+            xy=(
+                1.05,
+                np.mean([self.y_pred_counterfactual[0], self.y_pred_treatment[1]]),
+            ),
             xycoords="data",
             xytext=(5, 0),
             textcoords="offset points",