Plotting labeled intervals in matplotlib/gnuplot

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()