Re: [Matplotlib-users] Splitting arrays into chunks that satisfy a condition?

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) [go...@jp...]
Sent: Friday, August 02, 2013 11:16 AM
To: Benjamin Root
Cc: Drain, Theodore R (392P); mat...@li...
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...@ou...<mailto:ben...@ou...>> wrote:

On Fri, Aug 2, 2013 at 1:36 PM, Drain, Theodore R (392P) <the...@jp...<mailto:the...@jp...>> 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