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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 _setup(self):
 """ Set the binning info we need from the `edges` """

        dtype = [('inv', 'f8'), ('min', 'f8'), ('max', 'f8'),('N', 'i4'), ('spacing','object')]
        dtype        = numpy.dtype(dtype)
        self._info   = numpy.empty(self.Ndim, dtype=dtype)
        self.min     = self._info['min']
        self.max     = self._info['max']
        self.N       = self._info['N']
        self.inv     = self._info['inv']
        self.spacing = self._info['spacing']

        for i, dim in enumerate(self.dims):

            self.N[i] = len(self.edges[i])-1
            self.min[i] = self.edges[i][0]
            self.max[i] = self.edges[i][-1]

            # determine the type of spacing
            self.spacing[i] = None
            lin_diff = numpy.diff(self.edges[i])
            with numpy.errstate(divide='ignore', invalid='ignore'):
                log_diff = numpy.diff(numpy.log10(self.edges[i]))
            if numpy.allclose(lin_diff, lin_diff[0]):
                self.spacing[i] = 'linspace'
                self.inv[i] = self.N[i] * 1.0 / (self.max[i] - self.min[i])
            elif numpy.allclose(log_diff, log_diff[0]):
                self.spacing[i] = 'logspace'
                self.inv[i] = self.N[i] * 1.0 / numpy.log10(self.max[i] / self.min[i])

        self.shape = self.N + 2

        # store Rmax
        self.Rmax = self.max[0]