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

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 nximport matplotlibfrom nltk.corpus import wordnet as wndef 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 Gdef 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 <[e-mail]>#    Dan Schult <[e-mail]>#    Pieter Swart <[e-mail]>#    All rights reserved.#    BSD license.import networkx as nxfrom networkx.drawing.layout import shell_layout,\    circular_layout,spectral_layout,spring_layout,random_layout__author__ = """Aric Hagberg ([e-mail])"""__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)    returndef 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_collectiondef 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_collectiondef 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_itemsdef 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_itemsdef 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 testsdef 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