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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 _h_function(self,h):
 """ private method exponential variogram "h" function Parameters h : (float or numpy.ndarray) distance(s) Returns ------- h_function : float or numpy.ndarray the value of the "h" function implied by the ExpVario """

        return self.contribution * np.exp(-1.0 * h / self.a)