X-Git-Url: http://git.onelab.eu/?a=blobdiff_plain;f=src%2Fnepi%2Futil%2Fnetgraph.py;h=4b8c06c5e4b37493a66e9fd6300e2d24cf6aa0e3;hb=8ad1108c60ab8bcbbc08e7c53714edfd59d4e9cb;hp=6d68622651b298251b769466ba333f67e7e3c775;hpb=cfad7039f174589e1ad108dd38c61f7988d631f1;p=nepi.git diff --git a/src/nepi/util/netgraph.py b/src/nepi/util/netgraph.py index 6d686226..4b8c06c5 100644 --- a/src/nepi/util/netgraph.py +++ b/src/nepi/util/netgraph.py @@ -19,6 +19,7 @@ import ipaddr import networkx +import math import random class TopologyType: @@ -69,10 +70,18 @@ class NetGraph(object): :param version: IP version for IP address assignment. :type version: int - :param assign_st: Select source and target nodes on the graph. :type assign_st: bool + :param sources_targets: dictionary with the list of sources (key = + "sources") and list of targets (key = "targets") if defined, ignore + assign_st + :type sources_targets: dictionary of lists + + :param leaf_source: if True, random sources will be selected only + from leaf nodes. + :type leaf_source: bool + NOTE: Only point-to-point like network topologies are supported for now. (Wireless and Ethernet networks were several nodes share the same edge (hyperedge) can not be modeled for the moment). @@ -99,9 +108,13 @@ class NetGraph(object): self.assign_p2p_ips(network = network, prefix = prefix, version = version) - if kwargs.get("assign_st"): + sources_targets = kwargs.get("sources_targets") + if sources_targets: + [self.set_source(n) for n in sources_targets["sources"]] + [self.set_target(n) for n in sources_targets["targets"]] + elif kwargs.get("assign_st"): self.select_target_zero() - self.select_random_leaf_source() + self.select_random_source(is_leaf = kwargs.get("leaf_source")) @property def topology(self): @@ -151,24 +164,13 @@ class NetGraph(object): prev = c c += 1 - # node ids are int, make them str - g = networkx.Graph() - g.add_nodes_from(map(lambda nid: str(nid), graph.nodes())) - g.add_edges_from(map(lambda t: (str(t[0]), str(t[1])), - graph.edges())) - - return g + return graph def add_node(self, nid): - nid = str(nid) - if nid not in self.topology: self.topology.add_node(nid) def add_edge(self, nid1, nid2): - nid1 = str(nid1) - nid2 = str(nid2) - self.add_node(nid1) self.add_node( nid2) @@ -314,27 +316,28 @@ class NetGraph(object): if self.topology.node[nid].get("source")] def select_target_zero(self): - """ Marks the node 0 as target + """ Mark the node 0 as target """ - self.set_target("0") + nid = 0 if 0 in self.topology.nodes() else "0" + self.set_target(nid) - def select_random_leaf_source(self): - """ Marks a random leaf node as source. + def select_random_source(self, **kwargs): + """ Mark a random node as source. """ # The ladder is a special case because is not symmetric. if self.topo_type == TopologyType.LADDER: total_nodes = self.order/2 - leaf1 = str(total_nodes - 1) - leaf2 = str(nodes - 1) + leaf1 = total_nodes + leaf2 = total_nodes - 1 leaves = [leaf1, leaf2] source = leaves.pop(random.randint(0, len(leaves) - 1)) else: # options must not be already sources or targets options = [ k for k,v in self.topology.degree().iteritems() \ - if v == 1 and not self.topology.node[k].get("source") \ + if (not kwargs.get("is_leaf") or v == 1) \ + and not self.topology.node[k].get("source") \ and not self.topology.node[k].get("target")] - source = options.pop(random.randint(0, len(options) - 1)) self.set_source(source)