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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 array(self) -> numpy.ndarray: """The aggregated data of all logged |IOSequence| objects contained in one single |numpy.ndarray| object. The documentation on |NetCDFVariableAgg.shape| explains how |NetCDFVariableAgg.array| is structured. This first example confirms that, under default configuration (`timeaxis=1`), the first axis corresponds to the location, while the second one corresponds to time: array([[ 12. , 13. , 14. , 15. ], [ 16.5, 18.5, 20.5, 22.5], [ 25. , 28. , 31. , 34. ]]) When using the first axis as the "timeaxis", the resulting |NetCDFVariableAgg.array| is the transposed: array([[ 12. , 16.5, 25. ], [ 13. , 18.5, 28. ], [ 14. , 20.5, 31. ], [ 15. , 22.5, 34. ]]) """

        array = numpy.full(self.shape, fillvalue, dtype=float)
        for idx, subarray in enumerate(self.arrays.values()):
            array[self.get_timeplaceslice(idx)] = subarray
        return array