AttributeError: module 'networkx' has no attribute 'draw_graphviz'解决方案_network' object has no attribute 'draw

环境：

Python2.7 （64）、ubuntu环境下

被运行的代码来自《Python自然语言处理》的P185-186，代码如下：

P185-186.py

import networkx as nx
import matplotlib
from nltk.corpus import wordnet as wn
 
def traverse(graph, start, node):
    graph.depth[node.name] = node.shortest_path_distance(start)
    for child in node.hyponyms():
        graph.add_edge(node.name, child.name) 
        traverse(graph, start, child) 
def hyponym_graph(start):
    G = nx.Graph() 
    G.depth = {}
    traverse(G, start, start)
    return G
def graph_draw(graph):
    nx.draw_graphviz(graph,
        node_size = [16 * graph.degree(n) for n in graph],
        node_color = [graph.depth[n] for n in graph],
        with_labels = False)
    matplotlib.pyplot.show()
 
if __name__=='__main__':
    dog=wn.synset('dog.n.01')
    graph=hyponym_graph(dog)
    graph_draw(graph)

代码无法运行，直接报错：

AttributeError: module 'networkx' has no attribute 'draw_graphviz'

非常坑，消耗了我好几个小时，stackflow上面也没有答案，本文末尾的参考链接3中直接放弃了draw_graphviz这个函数，把draw_graphviz改为draw。

最终解决方案如下：

一、

apt-get install graphviz
apt-get install graphviz-dev
apt-get install graphviz-doc

pip install pygraphviz
pip install networkx
pip install matplotlib

把本文末尾的参考链接2中的nx_pylab.py(因为是doc里面的源码，所以要把所有的[doc]def改为def)

覆盖以下路径中的nx_pylab.py

/home/appleyuchi/.virtualenvs/python2.7/lib/python2.7/site-packages/networkx/drawing

（注意，不要使用github中的nx_pylab.py，这个太旧了，没有draw_graphviz函数，所以不行）

当然到这里，还是没完，这个时候，重新运行上面的P185-186.py，错误会变成：

AttributeError: module 'networkx.drawing' has no attribute 'graphviz_layout'

继续修改

draw_graphviz，换了一种import那个 graphviz_layout的方法就好了。

修改好的nx_pylab.py

"""
**********
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']
 
 
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
 
    if 'with_labels' not in kwds:
        kwds['with_labels'] = 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
 
 
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()
 
 
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.
       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 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
    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
    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
 
 
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.
       Positions should be sequences of length 2.
    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
    Returns
    -------
    matplotlib.collection.LineCollection
        `LineCollection` of the edges
    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
 
 
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
       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
    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.
    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
    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
 
 
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
       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
       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)
    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
    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
 
 
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_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 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, 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_graphviz(G, prog="neato", **kwargs):
    from nx_agraph import graphviz_layout
    """Draw networkx graph with graphviz layout.
    Parameters
    ----------
    G : graph
       A networkx graph
    prog : string, optional
      Name of Graphviz layout program
    **kwargs : optional keywords
       See networkx.draw_networkx() for a description of optional keywords.
    """
    # pos = nx.drawing.graphviz_layout(G, prog)
    pos=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")

最终结果:

注意，以上方法对python3.x无效，请知悉。

几个重要的参考链接：

参考链接:

1

https://networkx.github.io/documentation/networkx-1.9/_modules/networkx/drawing/nx_pylab.html#draw_graphviz

2
https://github.com/networkx/networkx/blob/master/networkx/drawing/nx_pylab.py

3

https://stackoverflow.com/questions/41047362/python-networkx-error-module-networkx-drawing-has-no-attribute-graphviz-layo