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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 invert_projection(self, X, identities):
 """ Calculate the inverted projection. The inverted projectio of a SOM is created by association each weight with the input which matches it the most, thus giving a good approximation of the "influence" of each input item. Works best for symbolic (instead of continuous) input data. Parameters X : numpy array Input data identities : list A list of names for each of the input data. Must be the same length as X. Returns ------- m : numpy array An array with the same shape as the map """

        distances = self.transform(X)

        if len(distances) != len(identities):
            raise ValueError("X and identities are not the same length: "
                             "{0} and {1}".format(len(X), len(identities)))

        node_match = []

        for d in distances.__getattribute__(self.argfunc)(0):
            node_match.append(identities[d])

        return np.array(node_match)