Question

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

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

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

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

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.

The question is:

1. Is there a standard way to do plots like this in any of the tools?
2. If not, how should I go about plotting this data (pointers to relevant tools/documentation/functions/examples which do something-kinda-like the thing described here)?

Answer 1

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()