def draw_chimera(G, **kwargs):
"""Draws graph G in a Chimera cross topology.
If `linear_biases` and/or `quadratic_biases` are provided, these
are visualized on the plot.
Parameters
----------
G : NetworkX graph
Should be a Chimera graph or a subgraph of a Chimera graph.
linear_biases : dict (optional, default {})
A dict of biases associated with each node in G. Should be of
form {node: bias, ...}. Each bias should be numeric.
quadratic_biases : dict (optional, default {})
A dict of biases associated with each edge in G. Should be of
form {edge: bias, ...}. Each bias should be numeric. Self-loop
edges (i.e., :math:`i=j`) are treated as linear biases.
kwargs : optional keywords
See networkx.draw_networkx() for a description of optional keywords,
with the exception of the `pos` parameter which is not used by this
function. If `linear_biases` or `quadratic_biases` are provided,
any provided `node_color` or `edge_color` arguments are ignored.
Examples
--------
>>> # Plot 2x2 Chimera unit cells
>>> import networkx as nx
>>> import dwave_networkx as dnx
>>> import matplotlib.pyplot as plt # doctest: +SKIP
>>> G = dnx.chimera_graph(2, 2, 4)
>>> dnx.draw_chimera(G) # doctest: +SKIP
>>> plt.show() # doctest: +SKIP
"""
draw_qubit_graph(G, chimera_layout(G), **kwargs)
def draw_pegasus(G, crosses=False, **kwargs):
"""Draws graph G in a Pegasus topology.
If ``linear_biases`` and/or ``quadratic_biases`` are provided, these
are visualized on the plot.
Parameters
----------
G : NetworkX graph
A Pegasus graph or a subgraph of a Pegasus graph, as produced by
the :func:`dwave_networkx.pegasus_graph` function.
linear_biases : dict (optional, default {})
Biases as a dict, of form {node: bias, ...}, where keys are
nodes in G and biases are numeric.
quadratic_biases : dict (optional, default {})
Biases as a dict, of form {edge: bias, ...}, where keys are
edges in G and biases are numeric. Self-loop
edges (i.e., :math:`i=j`) are treated as linear biases.
crosses: boolean (optional, default False)
If True, :math:`K_{4,4}` subgraphs are shown in a cross
rather than L configuration. Ignored if G is defined with
``nice_coordinates=True``.
kwargs : optional keywords
See networkx.draw_networkx() for a description of optional keywords,
with the exception of the ``pos`` parameter, which is not used by this
function. If ``linear_biases`` or ``quadratic_biases`` are provided,
any provided ``node_color`` or ``edge_color`` arguments are ignored.
Examples
--------
This example plots a Pegasus graph with size parameter 2.
>>> import networkx as nx
>>> import dwave_networkx as dnx
>>> import matplotlib.pyplot as plt # doctest: +SKIP
>>> G = dnx.pegasus_graph(2)
>>> dnx.draw_pegasus(G) # doctest: +SKIP
>>> plt.show() # doctest: +SKIP
"""
draw_qubit_graph(G, pegasus_layout(G, crosses=crosses), **kwargs)
def draw_pegasus(G, crosses=False, **kwargs):
"""Draws graph G in a Pegasus topology.
If `linear_biases` and/or `quadratic_biases` are provided, these
are visualized on the plot.
Parameters
----------
G : NetworkX graph
Should be a Pegasus graph or a subgraph of a Pegasus graph,
a product of dwave_networkx.pegasus_graph.
linear_biases : dict (optional, default {})
A dict of biases associated with each node in G. Should be of
form {node: bias, ...}. Each bias should be numeric.
quadratic_biases : dict (optional, default {})
A dict of biases associated with each edge in G. Should be of
form {edge: bias, ...}. Each bias should be numeric. Self-loop
edges (i.e., :math:`i=j`) are treated as linear biases.
crosses: boolean (optional, default False)
If crosses is True, K_4,4 subgraphs are shown in a cross
rather than L configuration. Ignored if G was defined with
nice_coordinates=True.
kwargs : optional keywords
See networkx.draw_networkx() for a description of optional keywords,
with the exception of the `pos` parameter which is not used by this
function. If `linear_biases` or `quadratic_biases` are provided,
any provided `node_color` or `edge_color` arguments are ignored.
Examples
--------
>>> # Plot a Pegasus graph with size parameter 2
>>> import networkx as nx
>>> import dwave_networkx as dnx
>>> import matplotlib.pyplot as plt
>>> G = dnx.pegasus_graph(2)
>>> dnx.draw_pegasus(G)
>>> plt.show()
"""
draw_qubit_graph(G, pegasus_layout(G, crosses=crosses), **kwargs)
def draw_zephyr(G, **kwargs):
"""Draws graph G in a Zephyr topology.
If ``linear_biases`` and/or ``quadratic_biases`` are provided, these
are visualized on the plot.
Parameters
----------
G : NetworkX graph
A Zephyr graph or a subgraph of a Zephyr graph, as produced by
the :func:`dwave_networkx.zephyr_graph` function.
linear_biases : dict (optional, default {})
Biases as a dict, of form {node: bias, ...}, where keys are
nodes in G and biases are numeric.
quadratic_biases : dict (optional, default {})
Biases as a dict, of form {edge: bias, ...}, where keys are
edges in G and biases are numeric. Self-loop
edges (i.e., :math:`i=j`) are treated as linear biases.
kwargs : optional keywords
See :func:`~networkx.drawing.nx_pylab.draw_networkx` for a description of
optional keywords, with the exception of the ``pos`` parameter, which is
unsupported. If the ``linear_biases`` or ``quadratic_biases`` parameters
are provided, any provided ``node_color`` or ``edge_color`` arguments are
ignored.
Examples
--------
This example plots a Zephyr graph with size parameter 2.
>>> import networkx as nx
>>> import dwave_networkx as dnx
>>> import matplotlib.pyplot as plt # doctest: +SKIP
>>> G = dnx.zephyr_graph(2)
>>> dnx.draw_zephyr(G) # doctest: +SKIP
>>> plt.show() # doctest: +SKIP
"""
draw_qubit_graph(G, zephyr_layout(G), **kwargs)