# This code is part of KQCircuits
# Copyright (C) 2021 IQM Finland Oy
#
# This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public
# License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied
# warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along with this program. If not, see
# https://www.gnu.org/licenses/gpl-3.0.html.
#
# The software distribution should follow IQM trademark policy for open-source software
# (meetiqm.com/developers/osstmpolicy). IQM welcomes contributions to the code. Please see our contribution agreements
# for individuals (meetiqm.com/developers/clas/individual) and organizations (meetiqm.com/developers/clas/organization).
import importlib
import networkx as nx
from kqcircuits.defaults import default_netlist_ignore_connections
spec = importlib.util.find_spec("matplotlib")
matplotlib_exists = spec is not None
if matplotlib_exists:
from matplotlib import pyplot as plt
[docs]
def network_as_graph(network):
"""
Import KQC netlist as networkx graph.
Each element is added as a node, identified by the subcircuit id used in the netlist.
For each node, the data dictionary contains the following items:
* cell_name: identifies the PCell, for example ``Waveguide Coplanar$1``.
Multiple nodes can point to the same PCell, if it has identical parameters.
* cell_type: The PCell full name, for example ``Waveguide Coplanar``
* location: A list [x, y] specifying the element coordinates in um.
* instance_name: The instance name of the PCell instance, may be an empty string
* name: A unique name for this instance. Equal to instance_name if that exists, made
unique by appending a numbered suffix if needed. If the instance name is empty,
a string containing the subcircuit_id.
* properties: A dictionary containing the PCell properties associated with this instance
Args:
network: dictionary of netlist data obtained by loading the netlist json file
Returns. Networkx Graph
"""
edges = []
used_subcircuit_ids = set()
used_names = set()
# Add all edges from the netlist
for net in network["nets"].values():
if len(net) >= 2:
for i, net_i in enumerate(net):
for net_j in net[i + 1 :]:
reasons_to_ignore_connections = [
(a, b)
for a, b in default_netlist_ignore_connections
if (net_i["pin"] == a and net_j["pin"] == b) or (net_i["pin"] == b and net_j["pin"] == a)
]
if len(reasons_to_ignore_connections) > 0:
continue
edges.append([net_i["subcircuit_id"], net_j["subcircuit_id"]])
used_subcircuit_ids.add(net_i["subcircuit_id"])
used_subcircuit_ids.add(net_j["subcircuit_id"])
graph = nx.Graph()
graph.add_edges_from(edges)
# Add data to the nodes
for subcircuit_id in used_subcircuit_ids:
subcircuit = network["subcircuits"][str(subcircuit_id)]
graph.nodes[subcircuit_id]["cell_name"] = subcircuit["cell_name"]
graph.nodes[subcircuit_id]["cell_type"] = subcircuit["cell_name"].split("$")[0].replace("*", " ")
graph.nodes[subcircuit_id]["location"] = [
subcircuit["subcircuit_location"]["x"],
subcircuit["subcircuit_location"]["y"],
]
if "instance_name" in subcircuit and subcircuit["instance_name"] is not None:
instance_name = subcircuit["instance_name"]
else:
instance_name = ""
base_name = instance_name if instance_name != "" else str(subcircuit_id)
# Define a unique name by suffixing with a number if needed
name = base_name
i = 0
while name in used_names:
i += 1
name = f"{base_name}_{i}"
used_names.add(base_name)
graph.nodes[subcircuit_id]["instance_name"] = instance_name
graph.nodes[subcircuit_id]["name"] = name
graph.nodes[subcircuit_id]["properties"] = subcircuit.get("properties", {})
return graph
[docs]
def draw_graph(graph, with_labels=True, with_position=True, figsize=(8, 8), export_path=None):
"""
Draw a netlist graph
Args:
graph: Networkx Graph with data structures as loaded by ``network_as_graph``
with_labels: if True, the unique ``name`` of each node will be shown as label
with_position: if True, the nodes will be positioned as they are physically located on the chip.
If False, a spring layout will be used to position the nodes.
figsize: Figure size to pass to matplotlib, default (8, 8)
export_path: Path to export image to, or None to show interactive plot
"""
if not matplotlib_exists:
return
plt.figure(figsize=figsize)
if with_position:
pos = {node: data["location"] for node, data in graph.nodes(data=True)}
else:
pos = nx.spring_layout(graph)
labels = {node: data["name"] for node, data in graph.nodes(data=True)}
nx.draw(graph, pos=pos, labels=labels, with_labels=with_labels)
if export_path is not None:
plt.savefig(export_path)
else:
plt.show()