这不是一个完整的答案,但是作为评论发布太长了,所以我将其作为答案发布。随意扩展/编辑它。
不久前(嗯,五年多以前)我尝试过将python-igraph 和matplotlib 结合起来,总体结论是可以将两者结合起来,但方式相当复杂。
首先,只有当您使用 Cairo 作为 matplotlib 的绘图后端时,该组合才有效,因为 python-igraph 使用 Cairo 作为图形绘图后端(并且它不支持任何其他绘图后端)。
接下来,关键技巧是您可以以某种方式提取 Matplotlib 图形的 Cairo 曲面,然后将此曲面作为绘图目标传递给 igraph 的 plot() 函数 - 在这种情况下,igraph 不会创建单独的图形,而是刚开始在给定的表面上绘图。然而,在我尝试这个的时候,Matplotlib 中没有公共 API 可以从图形中提取开罗表面,所以我不得不求助于未记录的 Matplotlib 属性和函数,所以整个事情非常脆弱,它取决于很大程度上依赖于我使用的特定版本的 Matplotlib - 但它确实有效。
整个过程总结在igraph-help邮件列表上的this thread。在线程中,我提供了以下 Python 脚本作为概念验证,为了完整起见,我将其复制在这里:
from matplotlib.artist import Artist
from igraph import BoundingBox, Graph, palettes
class GraphArtist(Artist):
"""Matplotlib artist class that draws igraph graphs.
Only Cairo-based backends are supported.
"""
def __init__(self, graph, bbox, palette=None, *args, **kwds):
"""Constructs a graph artist that draws the given graph within
the given bounding box.
`graph` must be an instance of `igraph.Graph`.
`bbox` must either be an instance of `igraph.drawing.BoundingBox`
or a 4-tuple (`left`, `top`, `width`, `height`). The tuple
will be passed on to the constructor of `BoundingBox`.
`palette` is an igraph palette that is used to transform
numeric color IDs to RGB values. If `None`, a default grayscale
palette is used from igraph.
All the remaining positional and keyword arguments are passed
on intact to `igraph.Graph.__plot__`.
"""
Artist.__init__(self)
if not isinstance(graph, Graph):
raise TypeError("expected igraph.Graph, got %r" % type(graph))
self.graph = graph
self.palette = palette or palettes["gray"]
self.bbox = BoundingBox(bbox)
self.args = args
self.kwds = kwds
def draw(self, renderer):
from matplotlib.backends.backend_cairo import RendererCairo
if not isinstance(renderer, RendererCairo):
raise TypeError("graph plotting is supported only on Cairo backends")
self.graph.__plot__(renderer.gc.ctx, self.bbox, self.palette, *self.args, **self.kwds)
def test():
import math
# Make Matplotlib use a Cairo backend
import matplotlib
matplotlib.use("cairo.pdf")
import matplotlib.pyplot as pyplot
# Create the figure
fig = pyplot.figure()
# Create a basic plot
axes = fig.add_subplot(111)
xs = range(200)
ys = [math.sin(x/10.) for x in xs]
axes.plot(xs, ys)
# Draw the graph over the plot
# Two points to note here:
# 1) we add the graph to the axes, not to the figure. This is because
# the axes are always drawn on top of everything in a matplotlib
# figure, and we want the graph to be on top of the axes.
# 2) we set the z-order of the graph to infinity to ensure that it is
# drawn above all the curves drawn by the axes object itself.
graph = Graph.GRG(100, 0.2)
graph_artist = GraphArtist(graph, (10, 10, 150, 150), layout="kk")
graph_artist.set_zorder(float('inf'))
axes.artists.append(graph_artist)
# Save the figure
fig.savefig("test.pdf")
print "Plot saved to test.pdf"
if __name__ == "__main__":
test()
一个警告:我没有测试上面的代码,我现在不能测试它,因为我的机器上现在没有 Matplotlib。它曾经在五年前与当时的 Matplotlib 版本 (0.99.3) 一起工作。如果不进行重大修改,它现在可能无法运行,但它显示了总体思路,希望它不会太复杂而无法适应。
如果您设法使它适合您,请随时编辑我的帖子。