Or make a stairstep, if each time has a finite duration.   like the following 
(though I am sure there are some inelegant code in there. 

data = np.arange(10)
mask = [0,0,0,1,1,0,1,0,0,0]
x = np.ma.masked_array(data, mask)
t = arange(-0.5,shape(x)[0]-0.5,1.)

xx=ma.zeros((2,10))
xx[0,:]=x
xx[1,:]=x
tt=0.*xx
tt[0,:]=t
tt[1,:]=t+0.9999999
tt=reshape(tt,(20),order='F')
xx=reshape(xx,(20),order='F')
plot(tt,xx)

On Jul 17, 2013, at  7:45 AM, Gregorio Bastardo <gregorio.basta...@gmail.com> 
wrote:

> Hi,
> 
> The following example demonstrates the problem, value 5 could not be
> seen w/o marker:
> 
> data = np.arange(10)
> mask = [0,0,0,1,1,0,1,0,0,0]
> x = np.ma.masked_array(data, mask)
> plot(x)
> plot(x, '+')
> 
> In my datasets, isolated unmasked values are rare, but placing a
> marker to spot them makes the whole graph cluttered. I do realize that
> at least 2 valid points are needed for a line segment, but still, is
> there any way to visualize these isolated unmasked values w/o a
> marker?
> 
> Thanks,
> Gregorio
> 
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--
Jody Klymak    
http://web.uvic.ca/~jklymak/





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