Merge pull request #407 from arthurmello/api-stability-test

Add test for API stability for a CausalPy example in Causal Inference and Discovery in Python by Aleksander Molak

causalpy/data/gt_social_media_data.csv

@@ -0,0 +1,182 @@
+date,twitter,linkedin,tiktok,instagram
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causalpy/tests/test_api_stability.py

@@ -0,0 +1,57 @@
+#   Copyright 2024 The PyMC Labs Developers
+#
+#   Licensed under the Apache License, Version 2.0 (the "License");
+#   you may not use this file except in compliance with the License.
+#   You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
+"""
+Tests API stability for specific external calls
+"""
+
+import matplotlib.pyplot as plt
+import pandas as pd
+
+import causalpy as cp
+from causalpy.experiments.prepostfit import SyntheticControl
+from causalpy.pymc_models import WeightedSumFitter
+
+sample_kwargs = {"tune": 20, "draws": 20, "chains": 2, "cores": 2}
+
+
+def test_causal_inference_and_discovery_with_python_example():
+    """Test example used in Alexander Molak's book 'Causal Inference and Discovery in Python'
+    Chapter 11 (pages 304-307)
+    """
+    data = pd.read_csv(r"./causalpy/data/gt_social_media_data.csv")
+    data.index = pd.to_datetime(data["date"])
+    data = data.drop("date", axis=1)
+    treatment_index = pd.to_datetime("2022-10-28")
+
+    # Build the model
+    model = cp.pymc_models.WeightedSumFitter(sample_kwargs=sample_kwargs)
+    assert isinstance(
+        model, WeightedSumFitter
+    ), "model is not an instance of WeightedSumFitter"
+
+    formula = "twitter ~ 0 + tiktok + linkedin + instagram"
+
+    # Run the experiment and plot results
+    results = cp.pymc_experiments.SyntheticControl(
+        data,
+        treatment_index,
+        formula=formula,
+        model=model,
+    )
+    assert isinstance(
+        results, SyntheticControl
+    ), "results is not an instance of SyntheticControl"
+
+    fig, ax = results.plot()
+    assert isinstance(fig, plt.Figure)