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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def masked(self) -> np.ndarray: """Axis expression evaluated, and masked with NaN shared from data channels."""

        arr = self[:]
        arr.shape = self.shape
        arr = wt_kit.share_nans(arr, *self.parent.channels)[0]
        return np.nanmean(
            arr, keepdims=True, axis=tuple(i for i in range(self.ndim) if self.shape[i] == 1)
        )