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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 apply_karhunen_loeve_scaling(self):
 """apply karhuene-loeve scaling to the jacobian matrix. Note ---- This scaling is not necessary for analyses using Schur's complement, but can be very important for error variance analyses. This operation effectively transfers prior knowledge specified in the parcov to the jacobian and reset parcov to the identity matrix. """

        cnames = copy.deepcopy(self.jco.col_names)
        self.__jco *= self.fehalf
        self.__jco.col_names = cnames
        self.__parcov = self.parcov.identity