Thanks! Either of those looks like it will work. I'll play w/ both of them to
see which fits better w/ my existing code.
Ted
________________________________
From: Goodman, Alexander (398J-Affiliate) [good...@jpl.nasa.gov]
Sent: Friday, August 02, 2013 11:16 AM
To: Benjamin Root
Cc: Drain, Theodore R (392P); matplotlib-users@lists.sourceforge.net
Subject: Re: [Matplotlib-users] Splitting arrays into chunks that satisfy a
condition?
Hi Ted,
As far as actually splitting up a numpy array into contiguous chunks fulfilling
a condition, there is a very good solution posted on stackoverflow:
http://stackoverflow.com/questions/4494404/find-large-number-of-consecutive-values-fulfilling-condition-in-a-numpy-array
If you use the contiguous_regions function from the first answer, this code
should give you what you want:
xneg = [x[slice(*reg)] for reg in contiguous_regions(z < 0)]
xpos = [x[slice(*reg)] for reg in contiguous_regions(z >= 0)]
Thanks,
Alex
On Fri, Aug 2, 2013 at 10:45 AM, Benjamin Root
<ben.r...@ou.edu<mailto:ben.r...@ou.edu>> wrote:
On Fri, Aug 2, 2013 at 1:36 PM, Drain, Theodore R (392P)
<theodore.r.dr...@jpl.nasa.gov<mailto:theodore.r.dr...@jpl.nasa.gov>> wrote:
I have three arrays (x,y,z). I want plot x vs y and draw the line segments
differently depending on whether or not z is positive or negative. So I'm
trying to split the x,y arrays into chunks depending on the value of z. Using
numpy.where, I can find the indeces in z that satisfy a condition but I can't
figure out an efficient way (other than brute force) to split the array up into
continuous chunks. Does anyone know of a numpy trick that would help with this?
Here's a simple example:
# index: 0 1 2 3 4 5 6 7 8 9
z=numpy.array([-1,-1,-1, 1, -1,-1,-1, 1,1,1] )
x=numpy.array([-2,-3,-4, 2, -5,-6,-7, 3,4,5] )
# Want: xneg = [ x[0:3], x[4:7] ], xpos = [ x[3:4], x[7:10] ]
xneg = [ [-2,-3,-4], [-5,-6,-7] ]
xpos = [ [ 2 ], [ 3, 4, 5 ] ]
idxneg = numpy.where( z < 0 )[0]
# == [ 0,1,2, 4,5,6 ]
idxpos = numpy.where( z >= 0 )[0]
# == [ 3, 7,8,9 ]
Thanks,
Ted
One way I would go about it is to do this:
z1 = numpy.where(z < 0, z, numpy.nan)
z2 = numpy.where(z >= 0, z, numpy.nan)
And then plot those against x. matplotlib ignores nans and would break up the
line where-ever a nan shows up (assuming that is the effect you want).
Cheers!
Ben Root
--
Alex Goodman
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