[SciPy-user] NaN's in numpy (and Scipy)

Alan Jackson alan at ajackson.org
Sun Jan 7 20:08:08 CST 2007


Thanks! That looks like it could be what I need. 

On Sun, 07 Jan 2007 3:50:07 +0000
v-nijs at kellogg.northwestern.edu wrote:

> Alan,
> 
> There is an ediff1d() function in numpy that you could use.
> 
> >>> b = numpy.ediff1d(a,to_end=a[-1]-a[-2])
> 
> Or if you want to specify nan's at the beginning (or end):
> 
> >>> b = numpy.ediff1d(a,to_begin=numpy.nan)
> 
> Not sure what that will do with your masked-arrays however.
> 
> I need this function in my own time-series program as well so I was happy to find this function myself.
> 
> Vincent
> 
> 
> ==============Original message text===============
> On Sun, 07 Jan 2007 12:56:56 am +0000 Pierre GM wrote:
> 
> On Saturday 06 January 2007 19:22, Alan Jackson wrote:
> > Well for one it seems a shame to carry around the extra storage when 99.9%
> > of my data is not missing.
> 
> Booleans aren't that large.
> 
> > With normal arrays this could be done with
> > b = concatenate((a[1:]-a[:-1],[a[-1]-a[-2]] )) or something close to that,
> > I'm writing from memory.  With masked arrays, you seem to lose the
> > 'maskedness' when they are only one-d, so the concatenate fails and you
> > have to fiddle about a bit to get it to work right. In my mind, it should
> > "just work", so that the code looks the same in either case, but I couldn't
> > get it to do that.
> 
> Are you sure you use the concatenate function from numpy.core.ma ? 
> And not the one from numpy ?
> 
> Because if you do use the one from numpy, you get a warning that the data is 
> masked in one or more location, and you end up with a basic ndarray, True. In 
> the new implementation, you raise an exception (not an helpful one, but I 
> can't control that)
> 
> >>>import  numpy as N
> >>>import numpy.core.ma as ma
> >>>x = ma.array([1,2,3], mask=[0,0,1])
> >>>print ma.concatenate([x,x])
> [1 2 -- 1 2 --]
> >>>N.concatenate([x,x])
> [1 2 3 1 2 3]
> 
> Now, with the new implementation
> >>>import maskedarray as MA\
> >>>x=MA.array([1,2,3], mask=[0,0,1])
> >>>print MA.concatenate([x,x])
> [1 2 -- 1 2 --]
> >>>N.concatenate([x,x])
> AttributeError: 'NoneType' object has no attribute 'shape'
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> 
> 
> 
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