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trade one problem for another
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ngm/__init__.py

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@@ -65,7 +65,7 @@ def get_R(beta: np.ndarray, n: np.ndarray, n_vax: np.ndarray, ve: float) -> np.n
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s_i = n
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s_vax = (n - n_vax * ve) / n
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return beta * (s_i / n.sum()) * s_vax
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return (beta.T * ((s_i / n.sum()) * s_vax)).T
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def dominant_eigen(X: np.ndarray, norm: str = "L1") -> DominantEigen:

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