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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 integrate(self, min, max, attr=None, info={}):
 """ Calculate the total number of points between [min, max). If attr is given, also calculate the sum of the weight. This is a M log(N) operation, where M is the number of min/max queries and N is number of points. """

        if numpy.isscalar(min):
            min = [min for i in range(self.ndims)]
        if numpy.isscalar(max):
            max = [max for i in range(self.ndims)]

        min = numpy.array(min, dtype='f8', order='C')
        max = numpy.array(max, dtype='f8', order='C')

        if (min).shape[-1] != self.ndims:
            raise ValueError("dimension of min does not match Node")
        if (max).shape[-1] != self.ndims:
            raise ValueError("dimension of max does not match Node")
        min, max = broadcast_arrays(min, max)
        return _core.KDNode.integrate(self, min, max, attr, info)