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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 _replace_zeros(arr, default_min_value):
 """Substitute 0s in the list with a near-zero value. Parameters arr : numpy.array(float) default_min_value : float If the smallest non-zero element in `arr` is greater than the default, use the default instead. Returns numpy.array(float) """

    min_nonzero_value = min(default_min_value, np.min(arr[arr > 0]))
    closest_to_zero = np.nextafter(min_nonzero_value, min_nonzero_value - 1)
    arr[arr == 0] = closest_to_zero
    return arr