在matplotlib/gnuplot中绘制标记的间隔 [英] Plotting labeled intervals in matplotlib/gnuplot

问题描述

我有一个数据样本，如下所示:

I have a data sample which looks like this:

a 10:15:22 10:15:30 OK
b 10:15:23 10:15:28 OK
c 10:16:00 10:17:10 FAILED
b 10:16:30 10:16:50 OK

我想要的是通过以下方式绘制以上数据:

What I want is to plot the above data in the following way:

captions ^
  |
c |         *------*
b |   *---*    *--*
a | *--*
  |___________________
                     time >

线的颜色取决于数据点的OK/FAILED状态.标签(a/b/c/...)可以重复也可以不重复.

With the color of lines depending on the OK/FAILED status of the data point. Labels (a/b/c/...) may or may not repeat.

正如我从 gnuplot 和 matplotlib 的文档中收集的那样，这种类型的绘图在后者中应该更容易处理，因为它不是标准绘图，并且会需要一些预处理.

As I've gathered from documentation for gnuplot and matplotlib, this type of a plot should be easier to do in the latter as it's not a standard plot and would require some preprocessing.

问题是:

1. 在任何一种工具中都可以使用这种标准方法来绘制类似的图吗?
2. 如果没有，我应该如何绘制这些数据(指向相关工具/文档/功能/示例的指针，它们执行类似此处所述的操作)?

推荐答案

已更新:现在包括处理数据样本并使用mpl date功能.

Updated: Now includes handling the data sample and uses mpl dates functionality.

import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, MinuteLocator, SecondLocator
import numpy as np
from StringIO import StringIO
import datetime as dt

### The example data
a=StringIO("""a 10:15:22 10:15:30 OK
b 10:15:23 10:15:28 OK
c 10:16:00 10:17:10 FAILED
b 10:16:30 10:16:50 OK
""")

#Converts str into a datetime object.
conv = lambda s: dt.datetime.strptime(s, '%H:%M:%S')

#Use numpy to read the data in. 
data = np.genfromtxt(a, converters={1: conv, 2: conv},
                     names=['caption', 'start', 'stop', 'state'], dtype=None)
cap, start, stop = data['caption'], data['start'], data['stop']

#Check the status, because we paint all lines with the same color 
#together
is_ok = (data['state'] == 'OK')
not_ok = np.logical_not(is_ok)

#Get unique captions and there indices and the inverse mapping
captions, unique_idx, caption_inv = np.unique(cap, 1, 1)

#Build y values from the number of unique captions.
y = (caption_inv + 1) / float(len(captions) + 1)

#Plot function
def timelines(y, xstart, xstop, color='b'):
    """Plot timelines at y from xstart to xstop with given color."""   
    plt.hlines(y, xstart, xstop, color, lw=4)
    plt.vlines(xstart, y+0.03, y-0.03, color, lw=2)
    plt.vlines(xstop, y+0.03, y-0.03, color, lw=2)

#Plot ok tl black    
timelines(y[is_ok], start[is_ok], stop[is_ok], 'k')
#Plot fail tl red
timelines(y[not_ok], start[not_ok], stop[not_ok], 'r')

#Setup the plot
ax = plt.gca()
ax.xaxis_date()
myFmt = DateFormatter('%H:%M:%S')
ax.xaxis.set_major_formatter(myFmt)
ax.xaxis.set_major_locator(SecondLocator(interval=20)) # used to be SecondLocator(0, interval=20)

#To adjust the xlimits a timedelta is needed.
delta = (stop.max() - start.min())/10

plt.yticks(y[unique_idx], captions)
plt.ylim(0,1)
plt.xlim(start.min()-delta, stop.max()+delta)
plt.xlabel('Time')
plt.show()

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