Example #1
0
    def _connect_burrow_to_structure(self, contour, structure):
        """ extends the burrow contour such that it connects to the ground line 
        or to other burrows """

        outline = geometry.Polygon(contour)

        # determine burrow points close to the structure
        dist = structure.distance(outline)
        conn_points = []
        while len(conn_points) == 0:
            dist += self.params['burrows/width']/2
            conn_points = [point for point in contour
                           if structure.distance(geometry.Point(point)) < dist]
        
        conn_points = np.array(conn_points)

        # cluster the points to detect multiple connections 
        # this is important when a burrow has multiple exits to the ground
        if len(conn_points) >= 2:
            dist_max = self.params['burrows/width']
            data = cluster.hierarchy.fclusterdata(conn_points, dist_max,
                                                  method='single', 
                                                  criterion='distance')
        else:
            data = np.ones(1, np.int)
            
        burrow_width_min = self.params['burrows/width_min']
        for cluster_id in np.unique(data):
            p_exit = conn_points[data == cluster_id].mean(axis=0)
            p_ground = curves.get_projection_point(structure, p_exit)
            
            line = geometry.LineString((p_exit, p_ground))
            tunnel = line.buffer(distance=burrow_width_min/2,
                                 cap_style=geometry.CAP_STYLE.flat)

            # add this to the burrow outline
            outline = outline.union(tunnel.buffer(0.1))
        
        # get the contour points
        outline = regions.get_enclosing_outline(outline)
        outline = regions.regularize_linear_ring(outline)
        contour = np.array(outline.coords)
        
        # fill the burrow mask, such that this extension does not have to be
        # done next time again
        cv2.fillPoly(self.burrow_mask, [np.asarray(contour, np.int32)], 1) 

        return contour
Example #2
0
    def connect_burrow_chunks(self, burrow_chunks):
        """ takes a list of burrow chunks and connects them such that in the
        end all burrow chunks are connected to the ground line. """
        if len(burrow_chunks) == 0:
            return []
        
        dist_max = self.params['burrows/chunk_dist_max']

        # build the contour profiles of the burrow chunks        
        linear_rings = [geometry.LinearRing(c) for c in burrow_chunks]
        
        # handle all burrows close to the ground
        connected, disconnected = [], []
        for k, ring in enumerate(linear_rings):
            ground_dist = self.ground.linestring.distance(ring)
            if ground_dist < dist_max:
                # burrow is close to ground
                if 1 < ground_dist:
                    burrow_chunks[k] = \
                        self._connect_burrow_to_structure(burrow_chunks[k],
                                                          self.ground.linestring)
                connected.append(k)
            else:
                disconnected.append(k)
                
        assert (set(connected) | set(disconnected)) == set(range(len(burrow_chunks)))

        # calculate distances to other burrows
        burrow_dist = np.empty([len(burrow_chunks)]*2)
        np.fill_diagonal(burrow_dist, np.inf)
        for x, contour1 in enumerate(linear_rings):
            for y, contour2 in enumerate(linear_rings[x+1:], x+1):
                dist = contour1.distance(contour2)
                burrow_dist[x, y] = dist
                burrow_dist[y, x] = dist
        
        # handle all remaining chunks, which need to be connected to other chunks
        while connected and disconnected:
            # find chunks which is closest to all the others
            dist = burrow_dist[disconnected, :][:, connected]
            k1, k2 = np.unravel_index(dist.argmin(), dist.shape)
            if dist[k1, k2] > dist_max:
                # don't connect structures that are too far from each other
                break
            c1, c2 = disconnected[k1], connected[k2]
            # k1 is chunk to connect, k2 is closest chunk to connect it to

            # connect the current chunk to the other structure
            structure = geometry.LinearRing(burrow_chunks[c2])
            enlarged_chunk = self._connect_burrow_to_structure(burrow_chunks[c1], structure)
            
            # merge the two structures
            poly1 = geometry.Polygon(enlarged_chunk)
            poly2 = regions.regularize_polygon(geometry.Polygon(structure))
            poly = poly1.union(poly2).buffer(0.1)
            
            # find and regularize the common contour
            contour = regions.get_enclosing_outline(poly)
            contour = regions.regularize_linear_ring(contour)
            contour = contour.coords
            
            # replace the current chunk by the merged one
            burrow_chunks[c1] = contour
            
            # replace all other burrow chunks with the same id
            id_c2 = id(burrow_chunks[c2])
            for k, bc in enumerate(burrow_chunks):
                if id(bc) == id_c2:
                    burrow_chunks[k] = contour
            
            # mark the cluster as connected
            del disconnected[k1]
            connected.append(c1)

        # return the unique burrow structures
        burrows = []
        connected_chunks = (burrow_chunks[k] for k in connected) 
        for contour in unique_based_on_id(connected_chunks):
            contour = regions.regularize_contour_points(contour)
            try:
                burrow = Burrow(contour)
            except ValueError:
                continue
            else:
                if burrow.area >= self.params['burrows/area_min']:
                    burrows.append(burrow)
        
        return burrows