python - 如何在matplotlib中绘制范围条形图？

Question

我正在尝试使用 matplotlib 绘制类似于以下内容的图:

但是，我不太确定要使用哪种类型的图表。我的数据具有以下形式，其中起始 x 位置是大于或等于 0 的正值:

<item 1><start x position><end x position>
<item 2><start x position><end x position>

查看文档，我发现有 barh和 errorbar ，但我不确定是否可以使用带有起始偏移量的 barh 。考虑到我的数据类型，最好的方法是什么？我对这个库不太熟悉，所以我希望能获得一些见解。

Answer 1

开胃菜

注释代码

据我所知，最直接的方法是直接在 matplotlib 上绘制矩形。 Canvas 使用 patches matplotlib的模块

简单的实现如下

import matplotlib.pyplot as plt
import matplotlib.patches as patches

def plot_rect(data, delta=0.4):
    """data is a dictionary, {"Label":(low,hi), ... }
    return a drawing that you can manipulate, show, save etc"""

    yspan = len(data)
    yplaces = [.5+i for i in range(yspan)]
    ylabels = sorted(data.keys())

    fig = plt.figure()
    ax = fig.add_subplot(111)
    ax.set_yticks(yplaces)
    ax.set_yticklabels(ylabels)
    ax.set_ylim((0,yspan))

    # later we'll need the min and max in the union of intervals
    low, hi =  data[ylabels[0]]
    for pos, label in zip(yplaces,ylabels):
        start, end = data[label]
        ax.add_patch(patches.Rectangle((start,pos-delta/2.0),end-start,delta))
        if start<low : low=start
        if end>hi : hi=end

    # little small trick, draw an invisible line so that the x axis
    # limits are automatically adjusted...
    ax.plot((low,hi),(0,0))

    # now get the limits as automatically computed
    xmin, xmax = ax.get_xlim()
    # and use them to draw the hlines in your example
    ax.hlines(range(1,yspan),xmin,xmax)
    # the vlines are simply the x grid lines
    ax.grid(axis='x')
    # eventually return what we have done
    return ax

# this is the main script, note that we have imported pyplot as plt

# the data, inspired by your example, 
data = {'A':(1901,1921),
        'B':(1917,1935),
        'C':(1929,1948),
        'D':(1943,1963),
        'E':(1957,1983),
        'F':(1975,1991),
        'G':(1989,2007)}

# call the function and give its result a name
ax = plot_rect(data)
# so that we can further manipulate it using the `axes` methods, e.g.
ax.set_xlabel('Whatever')
# finally save or show what we have
plt.show()

我们的痛苦的结果已经在这篇文章的第一段中展示了......

附录

假设您觉得蓝色是一种非常暗淡的颜色......

patches您放置在绘图中的内容可以作为绘图的属性(恰本地命名为 patches ...)进行访问，并且也可以进行修改，例如

ax = plot_rect(data)
ax.set_xlabel('Whatever')
for rect in ax.patches:
    rect.set(facecolor=(0.9,0.9,0.2,1.0), # a tuple, RGBA
          edgecolor=(0.6,0.2,0.3,1.0),
          linewidth=3.0)
plt.show()

在我的 VH 看来，自定义绘图功能对于描绘情节来说应该是最不重要的，因为这种后期制作通常在 matplotlib 中非常容易。 .