text stringlengths 0 93.6k |
|---|
# LOG.error("ERROR messages are printed") |
# LOG.warning("WARNING messages are printed") |
# LOG.info("INFO message are printed") |
# LOG.debug("DEBUG messages are printed") |
# If the user needs a detailed topology, use "record" shapes and draw |
# individual ports on each shape. |
# Otherwise, use "rectangle" shapes with multiple connections. |
# |
# Unfortunately, a detailed topology is not supported by Gephi. |
# Disabling by default. |
detailed = options.detailed_topo |
# If enabled, HCAs (nodes) connected on the same switches are grouped in |
# the same cluster. Unfortunately only 'dot' supports clustering at the |
# moment, so I disable it by default. |
useClusters = options.use_clusters |
exportGexf = options.export_gexf |
# Read the topology and build the graph in an OrderedDict |
topology_file = options.topo_file |
topology = OrderedDict() |
num_of_switches = 0 |
num_of_hcas = 0 |
current_node = "" |
with open(topology_file, mode='r', buffering=1) as f: |
for line in f: |
line = line.strip() |
isinstance(line, str) |
if line: |
r = quick_regexp() |
# This regexp will read the name of nodes and the number of |
# ports (Switches or HCAs) |
if r.search( |
r"^(\w+)\s+(\d+)\s+\"(.+?)\"\s+#\s+\"(.+?)\"", line): |
current_node = r.groups[2] |
topology[current_node] = OrderedDict() |
topology[current_node]['number_of_ports'] = int( |
r.groups[1]) |
if len(r.groups) == 4: |
# If we have a label, keep track of it |
topology[current_node]['label'] = r.groups[3] |
if r.groups[0] == 'Switch': |
topology[current_node]['node_type'] = 'switch' |
num_of_switches = num_of_switches + 1 |
else: |
topology[current_node]['node_type'] = 'hca' |
num_of_hcas = num_of_hcas + 1 |
# This regexp will read the port lines from a dump |
if r.search(r"^\[(\d+)\].*?\"(.+?)\"\[(\d+)\]", line): |
local_port = int(r.groups[0]) |
connected_to_remote_host = r.groups[1] |
connected_to_remote_port = int(r.groups[2]) |
topology[current_node][local_port] = { |
connected_to_remote_host: connected_to_remote_port} |
# if len(topology) > 1000 and detailed: |
# LOG.warn( |
# ("The provided network contains %d nodes (too many) and you" |
# " have chosen to draw a detailed topology.\n" |
# "If the drawing state takes much longer than anticipated," |
# " please run the program again with the detailed topology" |
# " switch turned off."), len(topology)) |
# print_(topology) |
G = pgv.AGraph(name="Fat-tree", strict=False) |
################ |
# Graphviz attribute list! |
# www.graphviz.org/doc/info/attrs.html |
################ |
# Graph attributes |
G.graph_attr['rankdir'] = 'TB' # TB, BT, LR, RL |
G.graph_attr['ranksep'] = 1.0 |
# G.graph_attr['nodesep'] = 0.0 |
# Type of the edges: (line, false), (spline, true), (none, ""), |
# curved, polyline, ortho |
G.graph_attr['splines'] = 'line' |
# Do not allow nodes to overlap. Scale makes the compilation very fast |
# but spreads the graph! |
G.graph_attr['overlap'] = 'scale' |
# The size of the output image in inches. Use a multiple of 7.75 and 10.25 |
# http://stackoverflow.com/questions/3489451/how-to-set-the-width-and-heigth-of-the-ouput-image-in-pygraphviz |
G.graph_attr['size'] = "{},{}!".format(7.75 * 12, 10.25 * 12) |
if options.optimize_black_bg: |
G.graph_attr['bgcolor'] = '#000000' |
# Node Attributes |
G.node_attr['style'] = 'filled' |
G.node_attr['margin'] = 0.2 |
G.node_attr['fontsize'] = 24 |
# Edge Attributes |
G.edge_attr['penwidth'] = 4 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.