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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 filter_above_threshold( self, key_fn, value_dict, threshold, default_value=0.0):
 """The code for filtering by gene or transcript expression was pretty much identical aside from which identifier you pull off an effect. So, factored out the common operations for filtering an effect collection into this helper method. Parameters key_fn : callable Given an element of this collection, returns a key into `value_dict` value_dict : dict Dict from keys returned by `extract_key_fn` to float values threshold : float Only keep elements whose value in `value_dict` is above this threshold. default_value : float Value to use for elements whose key is not in `value_dict` """

        def filter_fn(x):
            key = key_fn(x)
            value = value_dict.get(key, default_value)
            return value > threshold
        return self.filter(filter_fn)