# TranPy
Machine learning tool for power system transient stability analysis with a simple, sklearn-style API.
## Quick Start
```bash
pip install tranpy
```
```python
from tranpy.datasets import load_newengland
from tranpy.models import SVMClassifier
X_train, X_test, y_train, y_test = load_newengland(test_size=0.2, random_state=42)
model = SVMClassifier(kernel='rbf')
model.fit(X_train, y_train)
accuracy = model.score(X_test, y_test)
print(f"Accuracy: {accuracy:.4f}")
results = model.evaluate(X_test, y_test, verbose=True)
```
### XAI
```python
from tranpy.explainers import SHAPExplainer
# Create explainer
explainer = SHAPExplainer(model, X_train, X_test)
# Generate global explanations
shap_values = explainer.explain_global()
# Visualize
explainer.plot_summary(save_path='shap_summary.png')
# Important features
top_features = explainer.get_top_features(n_features=10)
print(top_features)
``
Check out the [examples/](examples/) directory for Jupyter notebooks:
- `01_load_dataset.ipynb`
- `02_train_models.ipynb`
- `03_explainability.ipynb`
- `04_generate_data.ipynb` - > Requires PowerFactory local installation
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"description": "# TranPy\n\nMachine learning tool for power system transient stability analysis with a simple, sklearn-style API.\n\n## Quick Start\n\n```bash\npip install tranpy\n```\n\n```python\nfrom tranpy.datasets import load_newengland\nfrom tranpy.models import SVMClassifier\n\nX_train, X_test, y_train, y_test = load_newengland(test_size=0.2, random_state=42)\nmodel = SVMClassifier(kernel='rbf')\nmodel.fit(X_train, y_train)\n\naccuracy = model.score(X_test, y_test)\nprint(f\"Accuracy: {accuracy:.4f}\")\n\nresults = model.evaluate(X_test, y_test, verbose=True)\n```\n\n### XAI \n\n```python\nfrom tranpy.explainers import SHAPExplainer\n\n# Create explainer\nexplainer = SHAPExplainer(model, X_train, X_test)\n\n# Generate global explanations\nshap_values = explainer.explain_global()\n\n# Visualize\nexplainer.plot_summary(save_path='shap_summary.png')\n\n# Important features\ntop_features = explainer.get_top_features(n_features=10)\nprint(top_features)\n``\n\nCheck out the [examples/](examples/) directory for Jupyter notebooks:\n\n- `01_load_dataset.ipynb`\n- `02_train_models.ipynb`\n- `03_explainability.ipynb`\n- `04_generate_data.ipynb` - > Requires PowerFactory local installation\n\n\n",
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