Completed documentation #79
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| name: CI | |
| on: | |
| push: | |
| branches: ["main"] | |
| pull_request: | |
| branches: ["**"] | |
| env: | |
| PYTHON_VERSION: "3.12" | |
| jobs: | |
| lint: | |
| runs-on: ubuntu-22.04 | |
| steps: | |
| - name: Checkout code | |
| uses: actions/checkout@v4 | |
| - name: Set up Python | |
| uses: actions/setup-python@v5 | |
| with: | |
| python-version: ${{ env.PYTHON_VERSION }} | |
| - name: Install dependencies (pinned by tests/constraints.txt) | |
| run: | | |
| python -m pip install --upgrade pip | |
| pip install -r requirements.txt -c tests/constraints.txt | |
| - name: Run formatter | |
| run: black --check . | |
| # - name: Run linter | |
| # run: flake8 . | |
| test: | |
| runs-on: ubuntu-22.04 | |
| needs: lint # only run tests if lint passes | |
| steps: | |
| - name: Checkout code | |
| uses: actions/checkout@v4 | |
| - name: Set up Python | |
| uses: actions/setup-python@v5 | |
| with: | |
| python-version: ${{ env.PYTHON_VERSION }} | |
| - name: Install dependencies (pinned by tests/constraints.txt) | |
| run: | | |
| python -m pip install --upgrade pip | |
| pip install -r requirements.txt -c tests/constraints.txt | |
| - name: Report SVI calibration (Linux) | |
| run: | | |
| PYTHONPATH=. python - <<'PY' | |
| import pandas as pd | |
| import numpy as np | |
| import scipy | |
| from oipd import VolCurve, MarketInputs | |
| print("numpy", np.__version__) | |
| print("scipy", scipy.__version__) | |
| print("pandas", pd.__version__) | |
| df = pd.read_csv("tests/data/AAPL_data.csv") | |
| df = df[df["expiration"] == "2026-01-16"] | |
| market = MarketInputs( | |
| valuation_date=pd.Timestamp("2025-01-15"), | |
| risk_free_rate=0.045, | |
| underlying_price=220.0, | |
| ) | |
| column_mapping = { | |
| "strike": "strike", | |
| "last_price": "last_price", | |
| "type": "option_type", | |
| "bid": "bid", | |
| "ask": "ask", | |
| "expiration": "expiry", | |
| } | |
| def run_fit(): | |
| vc = VolCurve(method="svi") | |
| vc.method_options = {"random_seed": 42} | |
| vc.fit(df, market, column_mapping=column_mapping) | |
| params = {k: vc.params.get(k) for k in ("a", "b", "rho", "m", "sigma", "forward", "maturity_years")} | |
| diagnostics = getattr(vc, "diagnostics", None) | |
| diag = None | |
| if diagnostics is not None: | |
| diag = { | |
| "objective": getattr(diagnostics, "objective", None), | |
| "rmse_weighted": getattr(diagnostics, "rmse_weighted", None), | |
| "rmse_unweighted": getattr(diagnostics, "rmse_unweighted", None), | |
| "envelope_violations_pct": getattr(diagnostics, "envelope_violations_pct", None), | |
| "chosen_start_origin": getattr(diagnostics, "chosen_start_origin", None), | |
| } | |
| return params, diag | |
| params_1, diag_1 = run_fit() | |
| params_2, diag_2 = run_fit() | |
| print("SVI params run1", params_1) | |
| print("SVI params run2", params_2) | |
| if diag_1 is not None: | |
| print("SVI diagnostics run1", diag_1) | |
| if diag_2 is not None: | |
| print("SVI diagnostics run2", diag_2) | |
| diffs = {k: None for k in params_1.keys()} | |
| for k in params_1.keys(): | |
| v1 = params_1.get(k) | |
| v2 = params_2.get(k) | |
| try: | |
| diffs[k] = float(abs(v1 - v2)) | |
| except Exception: | |
| diffs[k] = None | |
| print("SVI param abs diff", diffs) | |
| PY | |
| - name: Run tests | |
| run: pytest |