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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 in_hull_volume(self):
 r""" Work out the voxels inside the convex hull of the voronoi vertices of each pore """

        i = self.network['pore.internal']
        s = self.network['pore.surface']
        d = self.network['pore.delaunay']
        Ps = self.network.pores()[np.logical_and(d, np.logical_or(i, s))]
        inds = self.network._map(ids=self['pore._id'][Ps], element='pore',
                                 filtered=True)
        # Get the fiber image
        self._get_fiber_image(inds)
        hull_image = np.ones_like(self._fiber_image, dtype=np.uint16)*-1
        self._hull_image = hull_image
        for pore in Ps:
            logger.info("Processing Pore: "+str(pore+1)+" of "+str(len(Ps)))
            verts = self['pore.vertices'][pore]
            verts = np.asarray(unique_list(np.around(verts, 6)))
            verts /= self.network.resolution
            self.inhull(verts, pore)
        self._process_pore_voxels()