NetworkX

Source code for networkx.drawing.nx_pylab

"""
**********
Matplotlib
**********

Draw networks with matplotlib.

See Also
--------

matplotlib:     http://matplotlib.sourceforge.net/

pygraphviz:     http://networkx.lanl.gov/pygraphviz/

"""
#    Copyright (C) 2004-2012 by
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
#    All rights reserved.
#    BSD license.
import networkx as nx
from networkx.drawing.layout import shell_layout,\
    circular_layout,spectral_layout,spring_layout,random_layout
__author__ = """Aric Hagberg (hagberg@lanl.gov)"""
__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']

[docs]def draw(G, pos=None, ax=None, hold=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 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. With pyplot use >>> 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.pyplot as plt except ImportError: raise ImportError("Matplotlib required for draw()") 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() # allow callers to override the hold state by passing hold=True|False b = plt.ishold() h = kwds.pop('hold', None) if h is not None: plt.hold(h) try: draw_networkx(G,pos=pos,ax=ax,**kwds) ax.set_axis_off() plt.draw_if_interactive() except: plt.hold(b) raise plt.hold(b) return
[docs]def draw_networkx(G, pos=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. 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 string, or array of floats, (default='r') Node color. Can be a single color format string, 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, optional (default='o') The shape of the node. Specification is as matplotlib.scatter marker, one of 'so^>v<dph8'. alpha : float, optional (default=1.0) The node 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 string, or array of floats (default='r') Edge color. Can be a single color format string, 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, 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 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 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.pyplot as plt 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) plt.draw_if_interactive()
[docs]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, label = 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()) 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) linewidths : [None | scalar | sequence] Line width of symbol border (default =1.0) label : [None| string] Label for legend 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.pyplot as plt import numpy except ImportError: raise ImportError("Matplotlib required for draw()") except RuntimeError: print("Matplotlib unable to open display") raise if ax is None: ax=plt.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 as 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, label=label) node_collection.set_zorder(2) return node_collection
[docs]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, label=None, **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. edgelist : collection of edge tuples Draw only specified edges(default=G.edges()) 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. style : string Edge line style (default='solid') (solid|dashed|dotted,dashdot) alpha : float The edge transparency (default=1.0) 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. label : [None| string] Label for legend 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.pyplot as plt 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=plt.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 edge_collection.set_label(label) 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) 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() 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 arrow_collection.set_label(label) 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
[docs]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. labels : dictionary, optional (default=None) Node labels in a dictionary keyed by node of text labels 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 The text transparency (default=1.0) ax : Matplotlib Axes object, optional Draw the graph in the specified Matplotlib axes. 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.pyplot as plt 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=plt.gca() if labels is None: labels=dict( (n,n) for n in G.nodes()) # set optional alignment horizontalalignment=kwds.get('horizontalalignment','center') verticalalignment=kwds.get('verticalalignment','center') 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=horizontalalignment, verticalalignment=verticalalignment, transform = ax.transData, clip_on=True, ) text_items[n]=t return text_items
[docs]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=1.0, bbox=None, ax=None, rotate=True, **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) 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) 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.pyplot as plt 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=plt.gca() if edge_labels is None: labels=dict( ((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: 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] 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 cb.is_string_like(label): label=str(label) # this will cause "1" and 1 to be labeled the same # set optional alignment horizontalalignment=kwds.get('horizontalalignment','center') verticalalignment=kwds.get('verticalalignment','center') t=ax.text(x, y, label, size=font_size, color=font_color, family=font_family, weight=font_weight, horizontalalignment=horizontalalignment, verticalalignment=verticalalignment, rotation=trans_angle, transform = ax.transData, bbox = bbox, zorder = 1, clip_on=True, ) text_items[(n1,n2)]=t return text_items
[docs]def draw_circular(G, **kwargs): """Draw the graph G with a circular layout.""" draw(G,circular_layout(G),**kwargs)
[docs]def draw_random(G, **kwargs): """Draw the graph G with a random layout.""" draw(G,random_layout(G),**kwargs)
[docs]def draw_spectral(G, **kwargs): """Draw the graph G with a spectral layout.""" draw(G,spectral_layout(G),**kwargs)
[docs]def draw_spring(G, **kwargs): """Draw the graph G with a spring layout.""" draw(G,spring_layout(G),**kwargs)
[docs]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)
[docs]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) # fixture for nose tests def setup_module(module): from nose import SkipTest try: import matplotlib as mpl mpl.use('PS',warn=False) import matplotlib.pyplot as plt except: raise SkipTest("matplotlib not available")