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Current state of the simulation
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@@ -13,15 +13,25 @@ class GaussianNoise(Transform):
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self.__mu = mu
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self.__sigma = sigma
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def __call__(self, t: float, x: ArrayLike) -> ArrayLike:
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assert np.shape(self.__mu) == np.shape(x), "Mu and x have to match in shape."
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def __call__(self, _: float, x: ArrayLike) -> ArrayLike:
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if np.isscalar(x):
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noise = np.random.normal(0, 1)
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x += self.__sigma * noise + self.__mu
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else:
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dim = len(x)
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if np.isscalar(self.__sigma):
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sigma = np.identity(dim) * self.__sigma
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else:
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sigma = self.__sigma
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if np.isscalar(self.__mu):
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mu = np.ones(dim)
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else:
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mu = self.__mu
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noise = np.random.normal(0, 1, np.shape(x))
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x += self.__sigma @ noise + self.__mu
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x += sigma @ noise + mu
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return x
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