"""
**********
Matplotlib
**********
Draw networks with matplotlib (pylab).
See Also
--------
matplotlib: http://matplotlib.sourceforge.net/
pygraphviz: http://networkx.lanl.gov/pygraphviz/
"""
__author__ = """Aric Hagberg (hagberg@lanl.gov)"""
# Copyright (C) 2004-2010 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov>
# All rights reserved.
# BSD license.
__all__ = ['draw',
'draw_networkx',
'draw_networkx_nodes',
'draw_networkx_edges',
'draw_networkx_labels',
'draw_networkx_edge_labels',
'draw_circular',
'draw_random',
'draw_spectral',
'draw_spring',
'draw_shell',
'draw_graphviz']
import networkx as nx
from networkx.drawing.layout import shell_layout,\
circular_layout,spectral_layout,spring_layout,random_layout
def draw(G, pos=None, ax=None, hold=None, **kwds):
"""Draw the graph G with Matplotlib (pylab).
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 networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in specified Matplotlib axes.
hold: bool, optional
Set the Matplotlib hold state. If True subsequent draw
commands will be added to the current 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.
Good alternatives are:
With pylab:
>>> import pylab as P #
>>> import networkx as nx
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G) # networkx draw()
>>> P.draw() # pylab draw()
With pyplot
>>> import matplotlib.pyplot as plt
>>> import networkx as nx
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G) # networkx draw()
>>> plt.draw() # pyplot draw()
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
print "Matplotlib unable to open display"
raise
cf=pylab.gcf()
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()
# allow callers to override the hold state by passing hold=True|False
b = pylab.ishold()
h = kwds.pop('hold', None)
if h is not None:
pylab.hold(h)
try:
draw_networkx(G,pos=pos,ax=ax,**kwds)
ax.set_axis_off()
pylab.draw_if_interactive()
except:
pylab.hold(b)
raise
pylab.hold(b)
return
def draw_networkx(G, pos=None, ax=None, 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 networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in the specified Matplotlib axes.
with_labels: bool, optional
Set to True (default) to draw labels on the nodes.
nodelist: list, optional
Draw only specified nodes (default G.nodes())
edgelist: list
Draw only specified edges(default=G.edges())
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 string, or array of floats
Node color. 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.
node_shape: string
The shape of the node. Specification is as matplotlib.scatter
marker, one of 'so^>v<dph8' (default='o').
alpha: float
The node transparency (default=1.0)
cmap: Matplotlib colormap
Colormap for mapping intensities of nodes (default=None)
vmin,vmax: floats
Minimum and maximum for node colormap scaling (default=None)
width`: float
Line width of edges (default =1.0)
edge_color: color string, or array of floats
Edge color. Can be a single color format string (default='r'),
or a sequence of colors with the same length as edgelist.
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
Colormap for mapping intensities of edges (default=None)
edge_vmin,edge_vmax: floats
Minimum and maximum for edge colormap scaling (default=None)
style: string
Edge line style (default='solid') (solid|dashed|dotted,dashdot)
labels: dictionary
Node labels in a dictionary keyed by node of text labels (default=None)
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')
Notes
-----
Any keywords not listed above are passed through to draw_networkx_nodes(),
draw_networkx_edges(), and draw_networkx_labels(). For finer control
of drawing you can call those functions directly.
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G)
>>> nx.draw(G,pos=nx.spring_layout(G)) # use spring layout
>>> import pylab
>>> limits=pylab.axis('off') # turn of axis
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
See Also
--------
draw()
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
draw_networkx_edge_labels()
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
print "Matplotlib unable to open display"
raise
if pos is None:
pos=nx.drawing.spring_layout(G) # default to spring layout
node_collection=draw_networkx_nodes(G, pos, **kwds)
edge_collection=draw_networkx_edges(G, pos, **kwds)
if with_labels:
draw_networkx_labels(G, pos, **kwds)
pylab.draw_if_interactive()
def draw_networkx_nodes(G, pos,
nodelist=None,
node_size=300,
node_color='r',
node_shape='o',
alpha=1.0,
cmap=None,
vmin=None,
vmax=None,
ax=None,
linewidths=None,
**kwds):
"""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.
If not specified a spring layout positioning will be computed.
See networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in the specified Matplotlib axes.
nodelist: list, optional
Draw only specified nodes (default G.nodes())
edgelist: list
Draw only specified edges(default=G.edges())
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 string, or array of floats
Node color. 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.
node_shape: string
The shape of the node. Specification is as matplotlib.scatter
marker, one of 'so^>v<dph8' (default='o').
alpha: float
The node transparency (default=1.0)
cmap: Matplotlib colormap
Colormap for mapping intensities of nodes (default=None)
vmin,vmax: floats
Minimum and maximum for node colormap scaling (default=None)
width`: float
Line width of edges (default =1.0)
Notes
-----
Any keywords not listed above are passed through to Matplotlib's
scatter function.
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> nodes=nx.draw_networkx_nodes(G,pos=nx.spring_layout(G))
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
See Also
--------
draw()
draw_networkx()
draw_networkx_edges()
draw_networkx_labels()
draw_networkx_edge_labels()
"""
try:
import matplotlib.pylab as pylab
import numpy
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
print "Matplotlib unable to open display"
raise
if ax is None:
ax=pylab.gca()
if nodelist is None:
nodelist=G.nodes()
if not nodelist or len(nodelist)==0: # empty nodelist, no drawing
return None
try:
xy=numpy.asarray([pos[v] for v in nodelist])
except KeyError,e:
raise nx.NetworkXError('Node %s has no position.'%e)
except ValueError:
raise nx.NetworkXError('Bad value in node positions.')
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)
# pylab.axes(ax)
pylab.sci(node_collection)
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,
edge_cmap=None,
edge_vmin=None,
edge_vmax=None,
ax=None,
arrows=True,
**kwds):
"""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.
If not specified a spring layout positioning will be computed.
See networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in the specified Matplotlib axes.
alpha: float
The edge transparency (default=1.0)
width`: float
Line width of edges (default =1.0)
edge_color: color string, or array of floats
Edge color. Can be a single color format string (default='r'),
or a sequence of colors with the same length as edgelist.
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
Colormap for mapping intensities of edges (default=None)
edge_vmin,edge_vmax: floats
Minimum and maximum for edge colormap scaling (default=None)
style: string
Edge line style (default='solid') (solid|dashed|dotted,dashdot)
Notes
-----
For directed graphs, "arrows" (actually just thicker stubs) are drawn
at the head end. Arrows can be turned off with keyword arrows=False.
Yes, it is ugly but drawing proper arrows with Matplotlib this
way is tricky.
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> edges=nx.draw_networkx_edges(G,pos=nx.spring_layout(G))
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
See Also
--------
draw()
draw_networkx()
draw_networkx_nodes()
draw_networkx_labels()
draw_networkx_edge_labels()
"""
try:
import matplotlib
import matplotlib.pylab as pylab
import matplotlib.cbook as cb
from matplotlib.colors import colorConverter,Colormap
from matplotlib.collections import LineCollection
import numpy
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
print "Matplotlib unable to open display"
raise
if ax is None:
ax=pylab.gca()
if edgelist is None:
edgelist=G.edges()
if not edgelist or len(edgelist)==0: # no edges!
return None
# set edge positions
edge_pos=numpy.asarray([(pos[e[0]],pos[e[1]]) for e in edgelist])
if not cb.iterable(width):
lw = (width,)
else:
lw = width
if not cb.is_string_like(edge_color) \
and cb.iterable(edge_color) \
and len(edge_color)==len(edge_pos):
if numpy.alltrue([cb.is_string_like(c)
for c in edge_color]):
# (should check ALL elements)
# list of color letters such as ['k','r','k',...]
edge_colors = tuple([colorConverter.to_rgba(c,alpha)
for c in edge_color])
elif numpy.alltrue([not cb.is_string_like(c)
for c in edge_color]):
# If color specs are given as (rgb) or (rgba) tuples, we're OK
if numpy.alltrue([cb.iterable(c) and len(c) in (3,4)
for c in edge_color]):
edge_colors = tuple(edge_color)
else:
# numbers (which are going to be mapped with a colormap)
edge_colors = None
else:
raise ValueError('edge_color must consist of either color names or numbers')
else:
if cb.is_string_like(edge_color) or len(edge_color)==1:
edge_colors = ( colorConverter.to_rgba(edge_color, alpha), )
else:
raise ValueError('edge_color must be a single color or list of exactly m colors where m is the number or edges')
edge_collection = LineCollection(edge_pos,
colors = edge_colors,
linewidths = lw,
antialiaseds = (1,),
linestyle = style,
transOffset = ax.transData,
)
edge_collection.set_zorder(1) # edges go behind nodes
ax.add_collection(edge_collection)
# Note: there was a bug in mpl regarding the handling of alpha values for
# each line in a LineCollection. It was fixed in matplotlib in r7184 and
# r7189 (June 6 2009). We should then not set the alpha value globally,
# since the user can instead provide per-edge alphas now. Only set it
# globally if provided as a scalar.
if cb.is_numlike(alpha):
edge_collection.set_alpha(alpha)
# need 0.87.7 or greater for edge colormaps
mpl_version=matplotlib.__version__
if mpl_version.endswith('.svn'):
mpl_version=matplotlib.__version__[0:-4]
elif mpl_version.endswith('svn'):
mpl_version=matplotlib.__version__[0:-3]
elif mpl_version.endswith('pre'):
mpl_version=matplotlib.__version__[0:-3]
if map(int,mpl_version.split('.'))>=[0,87,7]:
if edge_colors is None:
if edge_cmap is not None: assert(isinstance(edge_cmap, Colormap))
edge_collection.set_array(numpy.asarray(edge_color))
edge_collection.set_cmap(edge_cmap)
if edge_vmin is not None or edge_vmax is not None:
edge_collection.set_clim(edge_vmin, edge_vmax)
else:
edge_collection.autoscale()
# pylab.axes(ax)
pylab.sci(edge_collection)
# else:
# sys.stderr.write(\
# """matplotlib version >= 0.87.7 required for colormapped edges.
# (version %s detected)."""%matplotlib.__version__)
# raise UserWarning(\
# """matplotlib version >= 0.87.7 required for colormapped edges.
# (version %s detected)."""%matplotlib.__version__)
arrow_collection=None
if G.is_directed() and arrows:
# a directed graph hack
# draw thick line segments at head end of edge
# waiting for someone else to implement arrows that will work
arrow_colors = edge_colors
a_pos=[]
p=1.0-0.25 # make head segment 25 percent of edge length
for src,dst in edge_pos:
x1,y1=src
x2,y2=dst
dx=x2-x1 # x offset
dy=y2-y1 # y offset
d=numpy.sqrt(float(dx**2+dy**2)) # length of edge
if d==0: # source and target at same position
continue
if dx==0: # vertical edge
xa=x2
ya=dy*p+y1
if dy==0: # horizontal edge
ya=y2
xa=dx*p+x1
else:
theta=numpy.arctan2(dy,dx)
xa=p*d*numpy.cos(theta)+x1
ya=p*d*numpy.sin(theta)+y1
a_pos.append(((xa,ya),(x2,y2)))
arrow_collection = LineCollection(a_pos,
colors = arrow_colors,
linewidths = [4*ww for ww in lw],
antialiaseds = (1,),
transOffset = ax.transData,
)
arrow_collection.set_zorder(1) # edges go behind nodes
ax.add_collection(arrow_collection)
# update view
minx = numpy.amin(numpy.ravel(edge_pos[:,:,0]))
maxx = numpy.amax(numpy.ravel(edge_pos[:,:,0]))
miny = numpy.amin(numpy.ravel(edge_pos[:,:,1]))
maxy = numpy.amax(numpy.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()
# if arrow_collection:
return edge_collection
def draw_networkx_labels(G, pos,
labels=None,
font_size=12,
font_color='k',
font_family='sans-serif',
font_weight='normal',
alpha=1.0,
ax=None,
**kwds):
"""Draw node labels on the graph G
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 networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in the specified Matplotlib axes.
alpha: float
The text transparency (default=1.0)
labels: dictionary
Node labels in a dictionary keyed by node of text labels (default=None)
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')
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> labels=nx.draw_networkx_labels(G,pos=nx.spring_layout(G))
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
See Also
--------
draw()
draw_networkx()
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_edge_labels()
"""
try:
import matplotlib.pylab as pylab
import matplotlib.cbook as cb
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
print "Matplotlib unable to open display"
raise
if ax is None:
ax=pylab.gca()
if labels is None:
labels=dict(zip(G.nodes(),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 cb.is_string_like(label):
label=str(label) # this will cause "1" and 1 to be labeled the same
t=ax.text(x, y,
label,
size=font_size,
color=font_color,
family=font_family,
weight=font_weight,
horizontalalignment='center',
verticalalignment='center',
transform = ax.transData,
clip_on=True,
)
text_items[n]=t
return text_items
def draw_networkx_edge_labels(G, pos,
edge_labels=None,
font_size=10,
font_color='k',
font_family='sans-serif',
font_weight='normal',
alpha=1.0,
bbox=None,
ax=None,
**kwds):
"""Draw edge labels.
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 networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in the specified Matplotlib axes.
alpha: float
The text transparency (default=1.0)
labels: dictionary
Node labels in a dictionary keyed by edge two-tuple of text
labels (default=None), Only labels for the keys in the dictionary
are drawn.
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)
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
http://networkx.lanl.gov/gallery.html
See Also
--------
draw()
draw_networkx()
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
"""
try:
import matplotlib.pylab as pylab
import matplotlib.cbook as cb
import numpy
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
print "Matplotlib unable to open display"
raise
if ax is None:
ax=pylab.gca()
if edge_labels is None:
labels=dict(zip(G.edges(),[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+x2)/2, (y1+y2)/2)
angle=numpy.arctan2(y2-y1,x2-x1)/(2.0*numpy.pi)*360 # degrees
# 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=numpy.array((x,y))
trans_angle=ax.transData.transform_angles(numpy.array((angle,)),
xy.reshape((1,2)))[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 cb.is_string_like(label):
label=str(label) # this will cause "1" and 1 to be labeled the same
t=ax.text(x, y,
label,
size=font_size,
color=font_color,
family=font_family,
weight=font_weight,
horizontalalignment='center',
verticalalignment='center',
rotation=trans_angle,
transform = ax.transData,
bbox = bbox,
zorder = 1,
clip_on=True,
)
text_items[(n1,n2)]=t
return text_items
def draw_circular(G, **kwargs):
"""Draw the graph G with a circular layout"""
draw(G,circular_layout(G),**kwargs)
def draw_random(G, **kwargs):
"""Draw the graph G with a random layout."""
draw(G,random_layout(G),**kwargs)
def draw_spectral(G, **kwargs):
"""Draw the graph G with a spectral layout."""
draw(G,spectral_layout(G),**kwargs)
def draw_spring(G, **kwargs):
"""Draw the graph G with a spring layout"""
draw(G,spring_layout(G),**kwargs)
def draw_shell(G, **kwargs):
"""Draw networkx graph with shell layout"""
nlist = kwargs.get('nlist', None)
if nlist != None:
del(kwargs['nlist'])
draw(G,shell_layout(G,nlist=nlist),**kwargs)
def draw_graphviz(G, prog="neato", **kwargs):
"""Draw networkx graph with graphviz layout"""
pos=nx.drawing.graphviz_layout(G,prog)
draw(G,pos,**kwargs)
def draw_nx(G,pos,**kwds):
"""For backward compatibility; use draw or draw_networkx"""
draw(G,pos,**kwds)
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