Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
1279 lines
37 KiB
1279 lines
37 KiB
"""
|
|
**********
|
|
Matplotlib
|
|
**********
|
|
|
|
Draw networks with matplotlib.
|
|
|
|
See Also
|
|
--------
|
|
|
|
matplotlib: http://matplotlib.org/
|
|
|
|
pygraphviz: http://pygraphviz.github.io/
|
|
|
|
"""
|
|
from numbers import Number
|
|
import networkx as nx
|
|
from networkx.drawing.layout import (
|
|
shell_layout,
|
|
circular_layout,
|
|
kamada_kawai_layout,
|
|
spectral_layout,
|
|
spring_layout,
|
|
random_layout,
|
|
planar_layout,
|
|
)
|
|
|
|
__all__ = [
|
|
"draw",
|
|
"draw_networkx",
|
|
"draw_networkx_nodes",
|
|
"draw_networkx_edges",
|
|
"draw_networkx_labels",
|
|
"draw_networkx_edge_labels",
|
|
"draw_circular",
|
|
"draw_kamada_kawai",
|
|
"draw_random",
|
|
"draw_spectral",
|
|
"draw_spring",
|
|
"draw_planar",
|
|
"draw_shell",
|
|
]
|
|
|
|
|
|
def draw(G, pos=None, ax=None, **kwds):
|
|
"""Draw the graph G with Matplotlib.
|
|
|
|
Draw the graph as a simple representation with no node
|
|
labels or edge labels and using the full Matplotlib figure area
|
|
and no axis labels by default. See draw_networkx() for more
|
|
full-featured drawing that allows title, axis labels etc.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
pos : dictionary, optional
|
|
A dictionary with nodes as keys and positions as values.
|
|
If not specified a spring layout positioning will be computed.
|
|
See :py:mod:`networkx.drawing.layout` for functions that
|
|
compute node positions.
|
|
|
|
ax : Matplotlib Axes object, optional
|
|
Draw the graph in specified Matplotlib axes.
|
|
|
|
kwds : optional keywords
|
|
See networkx.draw_networkx() for a description of optional keywords.
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.dodecahedral_graph()
|
|
>>> nx.draw(G)
|
|
>>> nx.draw(G, pos=nx.spring_layout(G)) # use spring layout
|
|
|
|
See Also
|
|
--------
|
|
draw_networkx()
|
|
draw_networkx_nodes()
|
|
draw_networkx_edges()
|
|
draw_networkx_labels()
|
|
draw_networkx_edge_labels()
|
|
|
|
Notes
|
|
-----
|
|
This function has the same name as pylab.draw and pyplot.draw
|
|
so beware when using `from networkx import *`
|
|
|
|
since you might overwrite the pylab.draw function.
|
|
|
|
With pyplot use
|
|
|
|
>>> import matplotlib.pyplot as plt
|
|
>>> G = nx.dodecahedral_graph()
|
|
>>> nx.draw(G) # networkx draw()
|
|
>>> plt.draw() # pyplot draw()
|
|
|
|
Also see the NetworkX drawing examples at
|
|
https://networkx.github.io/documentation/latest/auto_examples/index.html
|
|
"""
|
|
try:
|
|
import matplotlib.pyplot as plt
|
|
except ImportError as e:
|
|
raise ImportError("Matplotlib required for draw()") from e
|
|
except RuntimeError:
|
|
print("Matplotlib unable to open display")
|
|
raise
|
|
|
|
if ax is None:
|
|
cf = plt.gcf()
|
|
else:
|
|
cf = ax.get_figure()
|
|
cf.set_facecolor("w")
|
|
if ax is None:
|
|
if cf._axstack() is None:
|
|
ax = cf.add_axes((0, 0, 1, 1))
|
|
else:
|
|
ax = cf.gca()
|
|
|
|
if "with_labels" not in kwds:
|
|
kwds["with_labels"] = "labels" in kwds
|
|
|
|
draw_networkx(G, pos=pos, ax=ax, **kwds)
|
|
ax.set_axis_off()
|
|
plt.draw_if_interactive()
|
|
return
|
|
|
|
|
|
def draw_networkx(G, pos=None, arrows=True, with_labels=True, **kwds):
|
|
"""Draw the graph G using Matplotlib.
|
|
|
|
Draw the graph with Matplotlib with options for node positions,
|
|
labeling, titles, and many other drawing features.
|
|
See draw() for simple drawing without labels or axes.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
pos : dictionary, optional
|
|
A dictionary with nodes as keys and positions as values.
|
|
If not specified a spring layout positioning will be computed.
|
|
See :py:mod:`networkx.drawing.layout` for functions that
|
|
compute node positions.
|
|
|
|
arrows : bool, optional (default=True)
|
|
For directed graphs, if True draw arrowheads.
|
|
Note: Arrows will be the same color as edges.
|
|
|
|
arrowstyle : str, optional (default='-|>')
|
|
For directed graphs, choose the style of the arrowsheads.
|
|
See :py:class: `matplotlib.patches.ArrowStyle` for more
|
|
options.
|
|
|
|
arrowsize : int, optional (default=10)
|
|
For directed graphs, choose the size of the arrow head head's length and
|
|
width. See :py:class: `matplotlib.patches.FancyArrowPatch` for attribute
|
|
`mutation_scale` for more info.
|
|
|
|
with_labels : bool, optional (default=True)
|
|
Set to True to draw labels on the nodes.
|
|
|
|
ax : Matplotlib Axes object, optional
|
|
Draw the graph in the specified Matplotlib axes.
|
|
|
|
nodelist : list, optional (default G.nodes())
|
|
Draw only specified nodes
|
|
|
|
edgelist : list, optional (default=G.edges())
|
|
Draw only specified edges
|
|
|
|
node_size : scalar or array, optional (default=300)
|
|
Size of nodes. If an array is specified it must be the
|
|
same length as nodelist.
|
|
|
|
node_color : color or array of colors (default='#1f78b4')
|
|
Node color. Can be a single color or a sequence of colors with the same
|
|
length as nodelist. Color can be string, or rgb (or rgba) tuple of
|
|
floats from 0-1. If numeric values are specified they will be
|
|
mapped to colors using the cmap and vmin,vmax parameters. See
|
|
matplotlib.scatter for more details.
|
|
|
|
node_shape : string, optional (default='o')
|
|
The shape of the node. Specification is as matplotlib.scatter
|
|
marker, one of 'so^>v<dph8'.
|
|
|
|
alpha : float, optional (default=None)
|
|
The node and edge transparency
|
|
|
|
cmap : Matplotlib colormap, optional (default=None)
|
|
Colormap for mapping intensities of nodes
|
|
|
|
vmin,vmax : float, optional (default=None)
|
|
Minimum and maximum for node colormap scaling
|
|
|
|
linewidths : [None | scalar | sequence]
|
|
Line width of symbol border (default =1.0)
|
|
|
|
width : float, optional (default=1.0)
|
|
Line width of edges
|
|
|
|
edge_color : color or array of colors (default='k')
|
|
Edge color. Can be a single color or a sequence of colors with the same
|
|
length as edgelist. Color can be string, or rgb (or rgba) tuple of
|
|
floats from 0-1. If numeric values are specified they will be
|
|
mapped to colors using the edge_cmap and edge_vmin,edge_vmax parameters.
|
|
|
|
edge_cmap : Matplotlib colormap, optional (default=None)
|
|
Colormap for mapping intensities of edges
|
|
|
|
edge_vmin,edge_vmax : floats, optional (default=None)
|
|
Minimum and maximum for edge colormap scaling
|
|
|
|
style : string, optional (default='solid')
|
|
Edge line style (solid|dashed|dotted,dashdot)
|
|
|
|
labels : dictionary, optional (default=None)
|
|
Node labels in a dictionary keyed by node of text labels
|
|
|
|
font_size : int, optional (default=12)
|
|
Font size for text labels
|
|
|
|
font_color : string, optional (default='k' black)
|
|
Font color string
|
|
|
|
font_weight : string, optional (default='normal')
|
|
Font weight
|
|
|
|
font_family : string, optional (default='sans-serif')
|
|
Font family
|
|
|
|
label : string, optional
|
|
Label for graph legend
|
|
|
|
kwds : optional keywords
|
|
See networkx.draw_networkx_nodes(), networkx.draw_networkx_edges(), and
|
|
networkx.draw_networkx_labels() for a description of optional keywords.
|
|
|
|
Notes
|
|
-----
|
|
For directed graphs, arrows are drawn at the head end. Arrows can be
|
|
turned off with keyword arrows=False.
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.dodecahedral_graph()
|
|
>>> nx.draw(G)
|
|
>>> nx.draw(G, pos=nx.spring_layout(G)) # use spring layout
|
|
|
|
>>> import matplotlib.pyplot as plt
|
|
>>> limits = plt.axis("off") # turn of axis
|
|
|
|
Also see the NetworkX drawing examples at
|
|
https://networkx.github.io/documentation/latest/auto_examples/index.html
|
|
|
|
See Also
|
|
--------
|
|
draw()
|
|
draw_networkx_nodes()
|
|
draw_networkx_edges()
|
|
draw_networkx_labels()
|
|
draw_networkx_edge_labels()
|
|
"""
|
|
try:
|
|
import matplotlib.pyplot as plt
|
|
except ImportError as e:
|
|
raise ImportError("Matplotlib required for draw()") from e
|
|
except RuntimeError:
|
|
print("Matplotlib unable to open display")
|
|
raise
|
|
|
|
valid_node_kwds = (
|
|
"nodelist",
|
|
"node_size",
|
|
"node_color",
|
|
"node_shape",
|
|
"alpha",
|
|
"cmap",
|
|
"vmin",
|
|
"vmax",
|
|
"ax",
|
|
"linewidths",
|
|
"edgecolors",
|
|
"label",
|
|
)
|
|
|
|
valid_edge_kwds = (
|
|
"edgelist",
|
|
"width",
|
|
"edge_color",
|
|
"style",
|
|
"alpha",
|
|
"arrowstyle",
|
|
"arrowsize",
|
|
"edge_cmap",
|
|
"edge_vmin",
|
|
"edge_vmax",
|
|
"ax",
|
|
"label",
|
|
"node_size",
|
|
"nodelist",
|
|
"node_shape",
|
|
"connectionstyle",
|
|
"min_source_margin",
|
|
"min_target_margin",
|
|
)
|
|
|
|
valid_label_kwds = (
|
|
"labels",
|
|
"font_size",
|
|
"font_color",
|
|
"font_family",
|
|
"font_weight",
|
|
"alpha",
|
|
"bbox",
|
|
"ax",
|
|
"horizontalalignment",
|
|
"verticalalignment",
|
|
)
|
|
|
|
valid_kwds = valid_node_kwds + valid_edge_kwds + valid_label_kwds
|
|
|
|
if any([k not in valid_kwds for k in kwds]):
|
|
invalid_args = ", ".join([k for k in kwds if k not in valid_kwds])
|
|
raise ValueError(f"Received invalid argument(s): {invalid_args}")
|
|
|
|
node_kwds = {k: v for k, v in kwds.items() if k in valid_node_kwds}
|
|
edge_kwds = {k: v for k, v in kwds.items() if k in valid_edge_kwds}
|
|
label_kwds = {k: v for k, v in kwds.items() if k in valid_label_kwds}
|
|
|
|
if pos is None:
|
|
pos = nx.drawing.spring_layout(G) # default to spring layout
|
|
|
|
draw_networkx_nodes(G, pos, **node_kwds)
|
|
draw_networkx_edges(G, pos, arrows=arrows, **edge_kwds)
|
|
if with_labels:
|
|
draw_networkx_labels(G, pos, **label_kwds)
|
|
plt.draw_if_interactive()
|
|
|
|
|
|
def draw_networkx_nodes(
|
|
G,
|
|
pos,
|
|
nodelist=None,
|
|
node_size=300,
|
|
node_color="#1f78b4",
|
|
node_shape="o",
|
|
alpha=None,
|
|
cmap=None,
|
|
vmin=None,
|
|
vmax=None,
|
|
ax=None,
|
|
linewidths=None,
|
|
edgecolors=None,
|
|
label=None,
|
|
):
|
|
"""Draw the nodes of the graph G.
|
|
|
|
This draws only the nodes of the graph G.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
pos : dictionary
|
|
A dictionary with nodes as keys and positions as values.
|
|
Positions should be sequences of length 2.
|
|
|
|
ax : Matplotlib Axes object, optional
|
|
Draw the graph in the specified Matplotlib axes.
|
|
|
|
nodelist : list, optional
|
|
Draw only specified nodes (default G.nodes())
|
|
|
|
node_size : scalar or array
|
|
Size of nodes (default=300). If an array is specified it must be the
|
|
same length as nodelist.
|
|
|
|
node_color : color or array of colors (default='#1f78b4')
|
|
Node color. Can be a single color or a sequence of colors with the same
|
|
length as nodelist. Color can be string, or rgb (or rgba) tuple of
|
|
floats from 0-1. If numeric values are specified they will be
|
|
mapped to colors using the cmap and vmin,vmax parameters. See
|
|
matplotlib.scatter for more details.
|
|
|
|
node_shape : string
|
|
The shape of the node. Specification is as matplotlib.scatter
|
|
marker, one of 'so^>v<dph8' (default='o').
|
|
|
|
alpha : float or array of floats
|
|
The node transparency. This can be a single alpha value (default=None),
|
|
in which case it will be applied to all the nodes of color. Otherwise,
|
|
if it is an array, the elements of alpha will be applied to the colors
|
|
in order (cycling through alpha multiple times if necessary).
|
|
|
|
cmap : Matplotlib colormap
|
|
Colormap for mapping intensities of nodes (default=None)
|
|
|
|
vmin,vmax : floats
|
|
Minimum and maximum for node colormap scaling (default=None)
|
|
|
|
linewidths : [None | scalar | sequence]
|
|
Line width of symbol border (default =1.0)
|
|
|
|
edgecolors : [None | scalar | sequence]
|
|
Colors of node borders (default = node_color)
|
|
|
|
label : [None| string]
|
|
Label for legend
|
|
|
|
Returns
|
|
-------
|
|
matplotlib.collections.PathCollection
|
|
`PathCollection` of the nodes.
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.dodecahedral_graph()
|
|
>>> nodes = nx.draw_networkx_nodes(G, pos=nx.spring_layout(G))
|
|
|
|
Also see the NetworkX drawing examples at
|
|
https://networkx.github.io/documentation/latest/auto_examples/index.html
|
|
|
|
See Also
|
|
--------
|
|
draw()
|
|
draw_networkx()
|
|
draw_networkx_edges()
|
|
draw_networkx_labels()
|
|
draw_networkx_edge_labels()
|
|
"""
|
|
from collections.abc import Iterable
|
|
|
|
try:
|
|
import matplotlib.pyplot as plt
|
|
from matplotlib.collections import PathCollection
|
|
import numpy as np
|
|
except ImportError as e:
|
|
raise ImportError("Matplotlib required for draw()") from e
|
|
except RuntimeError:
|
|
print("Matplotlib unable to open display")
|
|
raise
|
|
|
|
if ax is None:
|
|
ax = plt.gca()
|
|
|
|
if nodelist is None:
|
|
nodelist = list(G)
|
|
|
|
if len(nodelist) == 0: # empty nodelist, no drawing
|
|
return PathCollection(None)
|
|
|
|
try:
|
|
xy = np.asarray([pos[v] for v in nodelist])
|
|
except KeyError as e:
|
|
raise nx.NetworkXError(f"Node {e} has no position.") from e
|
|
except ValueError as e:
|
|
raise nx.NetworkXError("Bad value in node positions.") from e
|
|
|
|
if isinstance(alpha, Iterable):
|
|
node_color = apply_alpha(node_color, alpha, nodelist, cmap, vmin, vmax)
|
|
alpha = None
|
|
|
|
node_collection = ax.scatter(
|
|
xy[:, 0],
|
|
xy[:, 1],
|
|
s=node_size,
|
|
c=node_color,
|
|
marker=node_shape,
|
|
cmap=cmap,
|
|
vmin=vmin,
|
|
vmax=vmax,
|
|
alpha=alpha,
|
|
linewidths=linewidths,
|
|
edgecolors=edgecolors,
|
|
label=label,
|
|
)
|
|
ax.tick_params(
|
|
axis="both",
|
|
which="both",
|
|
bottom=False,
|
|
left=False,
|
|
labelbottom=False,
|
|
labelleft=False,
|
|
)
|
|
|
|
node_collection.set_zorder(2)
|
|
return node_collection
|
|
|
|
|
|
def draw_networkx_edges(
|
|
G,
|
|
pos,
|
|
edgelist=None,
|
|
width=1.0,
|
|
edge_color="k",
|
|
style="solid",
|
|
alpha=None,
|
|
arrowstyle="-|>",
|
|
arrowsize=10,
|
|
edge_cmap=None,
|
|
edge_vmin=None,
|
|
edge_vmax=None,
|
|
ax=None,
|
|
arrows=True,
|
|
label=None,
|
|
node_size=300,
|
|
nodelist=None,
|
|
node_shape="o",
|
|
connectionstyle=None,
|
|
min_source_margin=0,
|
|
min_target_margin=0,
|
|
):
|
|
"""Draw the edges of the graph G.
|
|
|
|
This draws only the edges of the graph G.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
pos : dictionary
|
|
A dictionary with nodes as keys and positions as values.
|
|
Positions should be sequences of length 2.
|
|
|
|
edgelist : collection of edge tuples
|
|
Draw only specified edges(default=G.edges())
|
|
|
|
width : float, or array of floats
|
|
Line width of edges (default=1.0)
|
|
|
|
edge_color : color or array of colors (default='k')
|
|
Edge color. Can be a single color or a sequence of colors with the same
|
|
length as edgelist. Color can be string, or rgb (or rgba) tuple of
|
|
floats from 0-1. If numeric values are specified they will be
|
|
mapped to colors using the edge_cmap and edge_vmin,edge_vmax parameters.
|
|
|
|
style : string
|
|
Edge line style (default='solid') (solid|dashed|dotted,dashdot)
|
|
|
|
alpha : float
|
|
The edge transparency (default=None)
|
|
|
|
edge_ cmap : Matplotlib colormap
|
|
Colormap for mapping intensities of edges (default=None)
|
|
|
|
edge_vmin,edge_vmax : floats
|
|
Minimum and maximum for edge colormap scaling (default=None)
|
|
|
|
ax : Matplotlib Axes object, optional
|
|
Draw the graph in the specified Matplotlib axes.
|
|
|
|
arrows : bool, optional (default=True)
|
|
For directed graphs, if True draw arrowheads.
|
|
Note: Arrows will be the same color as edges.
|
|
|
|
arrowstyle : str, optional (default='-|>')
|
|
For directed graphs, choose the style of the arrow heads.
|
|
See :py:class: `matplotlib.patches.ArrowStyle` for more
|
|
options.
|
|
|
|
arrowsize : int, optional (default=10)
|
|
For directed graphs, choose the size of the arrow head head's length and
|
|
width. See :py:class: `matplotlib.patches.FancyArrowPatch` for attribute
|
|
`mutation_scale` for more info.
|
|
|
|
connectionstyle : str, optional (default=None)
|
|
Pass the connectionstyle parameter to create curved arc of rounding
|
|
radius rad. For example, connectionstyle='arc3,rad=0.2'.
|
|
See :py:class: `matplotlib.patches.ConnectionStyle` and
|
|
:py:class: `matplotlib.patches.FancyArrowPatch` for more info.
|
|
|
|
label : [None| string]
|
|
Label for legend
|
|
|
|
min_source_margin : int, optional (default=0)
|
|
The minimum margin (gap) at the begining of the edge at the source.
|
|
|
|
min_target_margin : int, optional (default=0)
|
|
The minimum margin (gap) at the end of the edge at the target.
|
|
|
|
Returns
|
|
-------
|
|
matplotlib.collection.LineCollection
|
|
`LineCollection` of the edges
|
|
|
|
list of matplotlib.patches.FancyArrowPatch
|
|
`FancyArrowPatch` instances of the directed edges
|
|
|
|
Depending whether the drawing includes arrows or not.
|
|
|
|
Notes
|
|
-----
|
|
For directed graphs, arrows are drawn at the head end. Arrows can be
|
|
turned off with keyword arrows=False. Be sure to include `node_size` as a
|
|
keyword argument; arrows are drawn considering the size of nodes.
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.dodecahedral_graph()
|
|
>>> edges = nx.draw_networkx_edges(G, pos=nx.spring_layout(G))
|
|
|
|
>>> G = nx.DiGraph()
|
|
>>> G.add_edges_from([(1, 2), (1, 3), (2, 3)])
|
|
>>> arcs = nx.draw_networkx_edges(G, pos=nx.spring_layout(G))
|
|
>>> alphas = [0.3, 0.4, 0.5]
|
|
>>> for i, arc in enumerate(arcs): # change alpha values of arcs
|
|
... arc.set_alpha(alphas[i])
|
|
|
|
Also see the NetworkX drawing examples at
|
|
https://networkx.github.io/documentation/latest/auto_examples/index.html
|
|
|
|
See Also
|
|
--------
|
|
draw()
|
|
draw_networkx()
|
|
draw_networkx_nodes()
|
|
draw_networkx_labels()
|
|
draw_networkx_edge_labels()
|
|
"""
|
|
try:
|
|
import matplotlib.pyplot as plt
|
|
from matplotlib.colors import colorConverter, Colormap, Normalize
|
|
from matplotlib.collections import LineCollection
|
|
from matplotlib.patches import FancyArrowPatch
|
|
import numpy as np
|
|
except ImportError as e:
|
|
raise ImportError("Matplotlib required for draw()") from e
|
|
except RuntimeError:
|
|
print("Matplotlib unable to open display")
|
|
raise
|
|
|
|
if ax is None:
|
|
ax = plt.gca()
|
|
|
|
if edgelist is None:
|
|
edgelist = list(G.edges())
|
|
|
|
if len(edgelist) == 0: # no edges!
|
|
if not G.is_directed() or not arrows:
|
|
return LineCollection(None)
|
|
else:
|
|
return []
|
|
|
|
if nodelist is None:
|
|
nodelist = list(G.nodes())
|
|
|
|
# FancyArrowPatch handles color=None different from LineCollection
|
|
if edge_color is None:
|
|
edge_color = "k"
|
|
|
|
# set edge positions
|
|
edge_pos = np.asarray([(pos[e[0]], pos[e[1]]) for e in edgelist])
|
|
|
|
# Check if edge_color is an array of floats and map to edge_cmap.
|
|
# This is the only case handled differently from matplotlib
|
|
if (
|
|
np.iterable(edge_color)
|
|
and (len(edge_color) == len(edge_pos))
|
|
and np.alltrue([isinstance(c, Number) for c in edge_color])
|
|
):
|
|
if edge_cmap is not None:
|
|
assert isinstance(edge_cmap, Colormap)
|
|
else:
|
|
edge_cmap = plt.get_cmap()
|
|
if edge_vmin is None:
|
|
edge_vmin = min(edge_color)
|
|
if edge_vmax is None:
|
|
edge_vmax = max(edge_color)
|
|
color_normal = Normalize(vmin=edge_vmin, vmax=edge_vmax)
|
|
edge_color = [edge_cmap(color_normal(e)) for e in edge_color]
|
|
|
|
if not G.is_directed() or not arrows:
|
|
edge_collection = LineCollection(
|
|
edge_pos,
|
|
colors=edge_color,
|
|
linewidths=width,
|
|
antialiaseds=(1,),
|
|
linestyle=style,
|
|
transOffset=ax.transData,
|
|
alpha=alpha,
|
|
)
|
|
|
|
edge_collection.set_cmap(edge_cmap)
|
|
edge_collection.set_clim(edge_vmin, edge_vmax)
|
|
|
|
edge_collection.set_zorder(1) # edges go behind nodes
|
|
edge_collection.set_label(label)
|
|
ax.add_collection(edge_collection)
|
|
|
|
return edge_collection
|
|
|
|
arrow_collection = None
|
|
|
|
if G.is_directed() and arrows:
|
|
# Note: Waiting for someone to implement arrow to intersection with
|
|
# marker. Meanwhile, this works well for polygons with more than 4
|
|
# sides and circle.
|
|
|
|
def to_marker_edge(marker_size, marker):
|
|
if marker in "s^>v<d": # `large` markers need extra space
|
|
return np.sqrt(2 * marker_size) / 2
|
|
else:
|
|
return np.sqrt(marker_size) / 2
|
|
|
|
# Draw arrows with `matplotlib.patches.FancyarrowPatch`
|
|
arrow_collection = []
|
|
mutation_scale = arrowsize # scale factor of arrow head
|
|
|
|
# FancyArrowPatch doesn't handle color strings
|
|
arrow_colors = colorConverter.to_rgba_array(edge_color, alpha)
|
|
for i, (src, dst) in enumerate(edge_pos):
|
|
x1, y1 = src
|
|
x2, y2 = dst
|
|
shrink_source = 0 # space from source to tail
|
|
shrink_target = 0 # space from head to target
|
|
if np.iterable(node_size): # many node sizes
|
|
source, target = edgelist[i][:2]
|
|
source_node_size = node_size[nodelist.index(source)]
|
|
target_node_size = node_size[nodelist.index(target)]
|
|
shrink_source = to_marker_edge(source_node_size, node_shape)
|
|
shrink_target = to_marker_edge(target_node_size, node_shape)
|
|
else:
|
|
shrink_source = shrink_target = to_marker_edge(node_size, node_shape)
|
|
|
|
if shrink_source < min_source_margin:
|
|
shrink_source = min_source_margin
|
|
|
|
if shrink_target < min_target_margin:
|
|
shrink_target = min_target_margin
|
|
|
|
if len(arrow_colors) == len(edge_pos):
|
|
arrow_color = arrow_colors[i]
|
|
elif len(arrow_colors) == 1:
|
|
arrow_color = arrow_colors[0]
|
|
else: # Cycle through colors
|
|
arrow_color = arrow_colors[i % len(arrow_colors)]
|
|
|
|
if np.iterable(width):
|
|
if len(width) == len(edge_pos):
|
|
line_width = width[i]
|
|
else:
|
|
line_width = width[i % len(width)]
|
|
else:
|
|
line_width = width
|
|
|
|
arrow = FancyArrowPatch(
|
|
(x1, y1),
|
|
(x2, y2),
|
|
arrowstyle=arrowstyle,
|
|
shrinkA=shrink_source,
|
|
shrinkB=shrink_target,
|
|
mutation_scale=mutation_scale,
|
|
color=arrow_color,
|
|
linewidth=line_width,
|
|
connectionstyle=connectionstyle,
|
|
linestyle=style,
|
|
zorder=1,
|
|
) # arrows go behind nodes
|
|
|
|
# There seems to be a bug in matplotlib to make collections of
|
|
# FancyArrowPatch instances. Until fixed, the patches are added
|
|
# individually to the axes instance.
|
|
arrow_collection.append(arrow)
|
|
ax.add_patch(arrow)
|
|
|
|
# update view
|
|
minx = np.amin(np.ravel(edge_pos[:, :, 0]))
|
|
maxx = np.amax(np.ravel(edge_pos[:, :, 0]))
|
|
miny = np.amin(np.ravel(edge_pos[:, :, 1]))
|
|
maxy = np.amax(np.ravel(edge_pos[:, :, 1]))
|
|
|
|
w = maxx - minx
|
|
h = maxy - miny
|
|
padx, pady = 0.05 * w, 0.05 * h
|
|
corners = (minx - padx, miny - pady), (maxx + padx, maxy + pady)
|
|
ax.update_datalim(corners)
|
|
ax.autoscale_view()
|
|
|
|
ax.tick_params(
|
|
axis="both",
|
|
which="both",
|
|
bottom=False,
|
|
left=False,
|
|
labelbottom=False,
|
|
labelleft=False,
|
|
)
|
|
|
|
return arrow_collection
|
|
|
|
|
|
def draw_networkx_labels(
|
|
G,
|
|
pos,
|
|
labels=None,
|
|
font_size=12,
|
|
font_color="k",
|
|
font_family="sans-serif",
|
|
font_weight="normal",
|
|
alpha=None,
|
|
bbox=None,
|
|
horizontalalignment="center",
|
|
verticalalignment="center",
|
|
ax=None,
|
|
):
|
|
"""Draw node labels on the graph G.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
pos : dictionary
|
|
A dictionary with nodes as keys and positions as values.
|
|
Positions should be sequences of length 2.
|
|
|
|
labels : dictionary, optional (default=None)
|
|
Node labels in a dictionary keyed by node of text labels
|
|
Node-keys in labels should appear as keys in `pos`.
|
|
If needed use: `{n:lab for n,lab in labels.items() if n in pos}`
|
|
|
|
font_size : int
|
|
Font size for text labels (default=12)
|
|
|
|
font_color : string
|
|
Font color string (default='k' black)
|
|
|
|
font_family : string
|
|
Font family (default='sans-serif')
|
|
|
|
font_weight : string
|
|
Font weight (default='normal')
|
|
|
|
alpha : float or None
|
|
The text transparency (default=None)
|
|
|
|
horizontalalignment : {'center', 'right', 'left'}
|
|
Horizontal alignment (default='center')
|
|
|
|
verticalalignment : {'center', 'top', 'bottom', 'baseline', 'center_baseline'}
|
|
Vertical alignment (default='center')
|
|
|
|
ax : Matplotlib Axes object, optional
|
|
Draw the graph in the specified Matplotlib axes.
|
|
|
|
|
|
Returns
|
|
-------
|
|
dict
|
|
`dict` of labels keyed on the nodes
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.dodecahedral_graph()
|
|
>>> labels = nx.draw_networkx_labels(G, pos=nx.spring_layout(G))
|
|
|
|
Also see the NetworkX drawing examples at
|
|
https://networkx.github.io/documentation/latest/auto_examples/index.html
|
|
|
|
See Also
|
|
--------
|
|
draw()
|
|
draw_networkx()
|
|
draw_networkx_nodes()
|
|
draw_networkx_edges()
|
|
draw_networkx_edge_labels()
|
|
"""
|
|
try:
|
|
import matplotlib.pyplot as plt
|
|
except ImportError as e:
|
|
raise ImportError("Matplotlib required for draw()") from e
|
|
except RuntimeError:
|
|
print("Matplotlib unable to open display")
|
|
raise
|
|
|
|
if ax is None:
|
|
ax = plt.gca()
|
|
|
|
if labels is None:
|
|
labels = {n: n for n in G.nodes()}
|
|
|
|
text_items = {} # there is no text collection so we'll fake one
|
|
for n, label in labels.items():
|
|
(x, y) = pos[n]
|
|
if not isinstance(label, str):
|
|
label = str(label) # this makes "1" and 1 labeled the same
|
|
t = ax.text(
|
|
x,
|
|
y,
|
|
label,
|
|
size=font_size,
|
|
color=font_color,
|
|
family=font_family,
|
|
weight=font_weight,
|
|
alpha=alpha,
|
|
horizontalalignment=horizontalalignment,
|
|
verticalalignment=verticalalignment,
|
|
transform=ax.transData,
|
|
bbox=bbox,
|
|
clip_on=True,
|
|
)
|
|
text_items[n] = t
|
|
|
|
ax.tick_params(
|
|
axis="both",
|
|
which="both",
|
|
bottom=False,
|
|
left=False,
|
|
labelbottom=False,
|
|
labelleft=False,
|
|
)
|
|
|
|
return text_items
|
|
|
|
|
|
def draw_networkx_edge_labels(
|
|
G,
|
|
pos,
|
|
edge_labels=None,
|
|
label_pos=0.5,
|
|
font_size=10,
|
|
font_color="k",
|
|
font_family="sans-serif",
|
|
font_weight="normal",
|
|
alpha=None,
|
|
bbox=None,
|
|
horizontalalignment="center",
|
|
verticalalignment="center",
|
|
ax=None,
|
|
rotate=True,
|
|
):
|
|
"""Draw edge labels.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
pos : dictionary
|
|
A dictionary with nodes as keys and positions as values.
|
|
Positions should be sequences of length 2.
|
|
|
|
ax : Matplotlib Axes object, optional
|
|
Draw the graph in the specified Matplotlib axes.
|
|
|
|
alpha : float or None
|
|
The text transparency (default=None)
|
|
|
|
edge_labels : dictionary
|
|
Edge labels in a dictionary keyed by edge two-tuple of text
|
|
labels (default=None). Only labels for the keys in the dictionary
|
|
are drawn.
|
|
|
|
label_pos : float
|
|
Position of edge label along edge (0=head, 0.5=center, 1=tail)
|
|
|
|
font_size : int
|
|
Font size for text labels (default=12)
|
|
|
|
font_color : string
|
|
Font color string (default='k' black)
|
|
|
|
font_weight : string
|
|
Font weight (default='normal')
|
|
|
|
font_family : string
|
|
Font family (default='sans-serif')
|
|
|
|
bbox : Matplotlib bbox
|
|
Specify text box shape and colors.
|
|
|
|
clip_on : bool
|
|
Turn on clipping at axis boundaries (default=True)
|
|
|
|
horizontalalignment : {'center', 'right', 'left'}
|
|
Horizontal alignment (default='center')
|
|
|
|
verticalalignment : {'center', 'top', 'bottom', 'baseline', 'center_baseline'}
|
|
Vertical alignment (default='center')
|
|
|
|
ax : Matplotlib Axes object, optional
|
|
Draw the graph in the specified Matplotlib axes.
|
|
|
|
Returns
|
|
-------
|
|
dict
|
|
`dict` of labels keyed on the edges
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.dodecahedral_graph()
|
|
>>> edge_labels = nx.draw_networkx_edge_labels(G, pos=nx.spring_layout(G))
|
|
|
|
Also see the NetworkX drawing examples at
|
|
https://networkx.github.io/documentation/latest/auto_examples/index.html
|
|
|
|
See Also
|
|
--------
|
|
draw()
|
|
draw_networkx()
|
|
draw_networkx_nodes()
|
|
draw_networkx_edges()
|
|
draw_networkx_labels()
|
|
"""
|
|
try:
|
|
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
except ImportError as e:
|
|
raise ImportError("Matplotlib required for draw()") from e
|
|
except RuntimeError:
|
|
print("Matplotlib unable to open display")
|
|
raise
|
|
|
|
if ax is None:
|
|
ax = plt.gca()
|
|
if edge_labels is None:
|
|
labels = {(u, v): d for u, v, d in G.edges(data=True)}
|
|
else:
|
|
labels = edge_labels
|
|
text_items = {}
|
|
for (n1, n2), label in labels.items():
|
|
(x1, y1) = pos[n1]
|
|
(x2, y2) = pos[n2]
|
|
(x, y) = (
|
|
x1 * label_pos + x2 * (1.0 - label_pos),
|
|
y1 * label_pos + y2 * (1.0 - label_pos),
|
|
)
|
|
|
|
if rotate:
|
|
# in degrees
|
|
angle = np.arctan2(y2 - y1, x2 - x1) / (2.0 * np.pi) * 360
|
|
# make label orientation "right-side-up"
|
|
if angle > 90:
|
|
angle -= 180
|
|
if angle < -90:
|
|
angle += 180
|
|
# transform data coordinate angle to screen coordinate angle
|
|
xy = np.array((x, y))
|
|
trans_angle = ax.transData.transform_angles(
|
|
np.array((angle,)), xy.reshape((1, 2))
|
|
)[0]
|
|
else:
|
|
trans_angle = 0.0
|
|
# use default box of white with white border
|
|
if bbox is None:
|
|
bbox = dict(boxstyle="round", ec=(1.0, 1.0, 1.0), fc=(1.0, 1.0, 1.0))
|
|
if not isinstance(label, str):
|
|
label = str(label) # this makes "1" and 1 labeled the same
|
|
|
|
t = ax.text(
|
|
x,
|
|
y,
|
|
label,
|
|
size=font_size,
|
|
color=font_color,
|
|
family=font_family,
|
|
weight=font_weight,
|
|
alpha=alpha,
|
|
horizontalalignment=horizontalalignment,
|
|
verticalalignment=verticalalignment,
|
|
rotation=trans_angle,
|
|
transform=ax.transData,
|
|
bbox=bbox,
|
|
zorder=1,
|
|
clip_on=True,
|
|
)
|
|
text_items[(n1, n2)] = t
|
|
|
|
ax.tick_params(
|
|
axis="both",
|
|
which="both",
|
|
bottom=False,
|
|
left=False,
|
|
labelbottom=False,
|
|
labelleft=False,
|
|
)
|
|
|
|
return text_items
|
|
|
|
|
|
def draw_circular(G, **kwargs):
|
|
"""Draw the graph G with a circular layout.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
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.
|
|
"""
|
|
draw(G, circular_layout(G), **kwargs)
|
|
|
|
|
|
def draw_kamada_kawai(G, **kwargs):
|
|
"""Draw the graph G with a Kamada-Kawai force-directed layout.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
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.
|
|
"""
|
|
draw(G, kamada_kawai_layout(G), **kwargs)
|
|
|
|
|
|
def draw_random(G, **kwargs):
|
|
"""Draw the graph G with a random layout.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
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.
|
|
"""
|
|
draw(G, random_layout(G), **kwargs)
|
|
|
|
|
|
def draw_spectral(G, **kwargs):
|
|
"""Draw the graph G with a spectral 2D layout.
|
|
|
|
Using the unnormalized Laplacian, the layout shows possible clusters of
|
|
nodes which are an approximation of the ratio cut. The positions are the
|
|
entries of the second and third eigenvectors corresponding to the
|
|
ascending eigenvalues starting from the second one.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
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.
|
|
"""
|
|
draw(G, spectral_layout(G), **kwargs)
|
|
|
|
|
|
def draw_spring(G, **kwargs):
|
|
"""Draw the graph G with a spring layout.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
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.
|
|
"""
|
|
draw(G, spring_layout(G), **kwargs)
|
|
|
|
|
|
def draw_shell(G, **kwargs):
|
|
"""Draw networkx graph with shell layout.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
|
|
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.
|
|
"""
|
|
nlist = kwargs.get("nlist", None)
|
|
if nlist is not None:
|
|
del kwargs["nlist"]
|
|
draw(G, shell_layout(G, nlist=nlist), **kwargs)
|
|
|
|
|
|
def draw_planar(G, **kwargs):
|
|
"""Draw a planar networkx graph with planar layout.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A planar networkx graph
|
|
|
|
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.
|
|
"""
|
|
draw(G, planar_layout(G), **kwargs)
|
|
|
|
|
|
def apply_alpha(colors, alpha, elem_list, cmap=None, vmin=None, vmax=None):
|
|
"""Apply an alpha (or list of alphas) to the colors provided.
|
|
|
|
Parameters
|
|
----------
|
|
|
|
colors : color string, or array of floats
|
|
Color of element. Can be a single color format string (default='r'),
|
|
or a sequence of colors with the same length as nodelist.
|
|
If numeric values are specified they will be mapped to
|
|
colors using the cmap and vmin,vmax parameters. See
|
|
matplotlib.scatter for more details.
|
|
|
|
alpha : float or array of floats
|
|
Alpha values for elements. This can be a single alpha value, in
|
|
which case it will be applied to all the elements of color. Otherwise,
|
|
if it is an array, the elements of alpha will be applied to the colors
|
|
in order (cycling through alpha multiple times if necessary).
|
|
|
|
elem_list : array of networkx objects
|
|
The list of elements which are being colored. These could be nodes,
|
|
edges or labels.
|
|
|
|
cmap : matplotlib colormap
|
|
Color map for use if colors is a list of floats corresponding to points
|
|
on a color mapping.
|
|
|
|
vmin, vmax : float
|
|
Minimum and maximum values for normalizing colors if a color mapping is
|
|
used.
|
|
|
|
Returns
|
|
-------
|
|
|
|
rgba_colors : numpy ndarray
|
|
Array containing RGBA format values for each of the node colours.
|
|
|
|
"""
|
|
from itertools import islice, cycle
|
|
|
|
try:
|
|
import numpy as np
|
|
from matplotlib.colors import colorConverter
|
|
import matplotlib.cm as cm
|
|
except ImportError as e:
|
|
raise ImportError("Matplotlib required for draw()") from e
|
|
|
|
# If we have been provided with a list of numbers as long as elem_list,
|
|
# apply the color mapping.
|
|
if len(colors) == len(elem_list) and isinstance(colors[0], Number):
|
|
mapper = cm.ScalarMappable(cmap=cmap)
|
|
mapper.set_clim(vmin, vmax)
|
|
rgba_colors = mapper.to_rgba(colors)
|
|
# Otherwise, convert colors to matplotlib's RGB using the colorConverter
|
|
# object. These are converted to numpy ndarrays to be consistent with the
|
|
# to_rgba method of ScalarMappable.
|
|
else:
|
|
try:
|
|
rgba_colors = np.array([colorConverter.to_rgba(colors)])
|
|
except ValueError:
|
|
rgba_colors = np.array([colorConverter.to_rgba(color) for color in colors])
|
|
# Set the final column of the rgba_colors to have the relevant alpha values
|
|
try:
|
|
# If alpha is longer than the number of colors, resize to the number of
|
|
# elements. Also, if rgba_colors.size (the number of elements of
|
|
# rgba_colors) is the same as the number of elements, resize the array,
|
|
# to avoid it being interpreted as a colormap by scatter()
|
|
if len(alpha) > len(rgba_colors) or rgba_colors.size == len(elem_list):
|
|
rgba_colors = np.resize(rgba_colors, (len(elem_list), 4))
|
|
rgba_colors[1:, 0] = rgba_colors[0, 0]
|
|
rgba_colors[1:, 1] = rgba_colors[0, 1]
|
|
rgba_colors[1:, 2] = rgba_colors[0, 2]
|
|
rgba_colors[:, 3] = list(islice(cycle(alpha), len(rgba_colors)))
|
|
except TypeError:
|
|
rgba_colors[:, -1] = alpha
|
|
return rgba_colors
|
|
|