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update sd assumption

feature/notebook
Michael Pilosov 3 years ago
parent
commit
a8c0ad14ac
  1. 5
      main.py

5
main.py

@ -10,7 +10,8 @@ from scipy.stats import norm
def train(data):
D = pd.DataFrame(data)
D["qoi"] = D["obs"].apply(lambda o: np.sum(o, axis=0) / np.sqrt(len(o)))
sd = np.array([1.0, 0.25, 0.5, 0.1])
D["qoi"] = D["obs"].apply(lambda o: np.sum(o, axis=0) / sd / np.sqrt(len(o)))
D["i"] = D["lam"].apply(lambda l: norm.pdf(l).prod())
D["o"] = D["qoi"].apply(lambda q: norm.pdf(q).prod())
Q = np.array(D["qoi"].to_list()).reshape(-1, 4)
@ -19,6 +20,7 @@ def train(data):
D["u"] = D["i"] * D["o"] / D["p"]
mud_point_idx = D["u"].argmax()
mud_point = D["lam"].iloc[mud_point_idx]
print(f"MUD Point ({mud_point_idx}: {mud_point}")
return mud_point
@ -44,5 +46,4 @@ def test(decision=np.array([-0.09, -0.71, -0.43, -0.74]), seed=1992):
if __name__ == "__main__":
data = pickle.load(open("data.pkl", "rb"))
mud_point = train(data)
print(f"MUD Point: {mud_point}")
test(mud_point)

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