使用NetworkX绘制彩色的树 [英] Drawing colored trees with NetworkX

问题描述

注意-这是对上一个问题的完整重写，我认为这太复杂了.它提供了一个简单得多的版本，如果我能解决的话，将会取得进展.

NOTE -- This is a complete rewrite of the previous question, which I think was too complex. It presents a much simpler version which, if I can solve, will result in progress.

我已经从以下SO答案中修改了我的代码:有没有办法保证NetworkX的分层输出?

I have adapted my code from this SO answer: Is there a way to guarantee hierarchical output from NetworkX?

通过以下非常简单的代码，我得到了奇怪的着色行为.

With the following very simple code, I get strange coloring behavior.

import networkx as nx
import matplotlib.pyplot as plt

G = nx.DiGraph()
G.add_node("ROOT")

for i in xrange(1):
    for j in range(1):
        G.add_node(str(j)+"_%i" % i, )        
        if j ==0:
            G.add_edge("ROOT", str(j)+"_%i" % i)
        else:
            G.add_edge(str(j-1)+"_%i" %i, str(j)+"_%i" % i)

pos=nx.graphviz_layout(G,prog='dot')

for i in xrange(1):
    nodelist = ['ROOT']
    for j in range(1):
        nodelist.append(str(j)+"_%i" % i )
    nx.draw_networkx_nodes(G,pos, nodelist=nodelist, cmap=plt.get_cmap('Set3'), node_color=[0,1])
nx.draw_networkx_edges(G, pos,arrows=True)

limits=plt.axis('off')          

我给node_color赋什么值似乎无关紧要，仅取决于这些值是否不同.例如，使用node_color = [0,1]时，我得到的行为与[0,.1]或[0,1000]时完全相同. (为什么?颜色图的取值在0到1之间).

It seems to NOT matter what values I give for the node_color, only whether the values are different or not. For example, with node_color = [0,1], I get the exact same behavior as when it is [0,.1], or [0,1000]. (Why? The colormap takes values between 0 and 1).

但是，如果我更改颜色图，则颜色也会更改.例如:

However if I change the colormap, the colors DO change. For example:

如果我设置node_color = [3,3](或任何两个相同的值)，我总是得到相同的东西，节点的颜色相同.

And if I set node_color = [3,3] (or any two values which are the same), I always get the same thing, the nodes are colored identically.

有什么想法我在这里做错了吗?

Any ideas what I'm doing wrong here?

推荐答案

在进入颜色图之前，将节点颜色值标准化为间隔[0，1].据推测，这意味着要使用整个颜色范围，而与给定值的范围无关.要使用不同的缩放间隔，可以设置vmin和vmax参数:

Before getting to the colormap, the node color values are normalized to the interval [0, 1]. This is presumably meant to use the full range of colors, regardless of the range of the values given. To use a different interval for scaling, you can set the vmin and vmax parameters:

nx.draw_networkx_nodes(G,pos, nodelist, cmap=plt.get_cmap('Set3'),
                       node_color=[0,1], vmin=0, vmax=100)

---

详细说明:

---

A detailed explanation:

根据node_color 参数的描述. nx_pylab.draw_networkx_nodes.html?highlight = node_color"rel =" nofollow> draw_networkx_nodes()文档:

From the description of the node_color parameter in the draw_networkx_nodes() docs:

如果是数值 指定它们将使用cmap和 vmin，vmax参数.有关更多详细信息，请参见matplotlib.scatter.

If numeric values are specified they will be mapped to colors using the cmap and vmin,vmax parameters. See matplotlib.scatter for more details.

不幸的是，这些文档不能很好地描述vmin和vmax的行为.但是对matplotlib.scatter的引用确实更详细地介绍了它: >

Unfortunately, these docs don't do a good job of describing the behaviour of vmin and vmax. But the reference for matplotlib.scatter does cover it more thouroughly:

vmin和vmax与范数结合使用以对亮度数据进行归一化. 如果任何一个都不为，则使用颜色阵列的最小值和最大值.

vmin and vmax are used in conjunction with norm to normalize luminance data. If either are None, the min and max of the color array is used.

因此，默认情况下，所传递的node_color数组的最小值在颜色图上映射为0，最大值为1.使用线性映射将介于两者之间的所有内容映射到间隔[0.0,1.0](此方法被称为 normalization 或 功能缩放 ) .以下是一些示例，从node_color到色图域中的点:

So, the minimum of the node_color array you pass is, by default, mapped to 0 on the colormap, and the maximum to 1. Everything in between is mapped to the interval [0.0,1.0] using a linear mapping (this is called normalization or feature scaling). Here are some examples, going from node_color to points in the colormap's domain:

• [0，0.1]→[0，1]
• [0，1000]→[0，1]
• [0，200，1000]→[0，0.2，1]
• [10、15、20]→[0、0.5、1]
• [0，0]→[0,0] (或者可能是[1,1]；我实际上没有运行它)

• [0, 0.1] → [0, 1]
• [0, 1000] → [0, 1]
• [0, 200, 1000] → [0, 0.2, 1]
• [10, 15, 20] → [0, 0.5, 1]
• [0, 0] → [0,0] (or it could be [1,1]; I didn't actually run this)

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