On Wed, Sep 21, 2011 at 9:28 PM, Benjamin Root <ben.r...@ou.edu> wrote:
> On Wed, Sep 21, 2011 at 2:00 PM, Armando Serrano Lombillo <
> arser...@gmail.com> wrote:
>
>> Hello I have a dat set like this one
>> a=[[x1, y1, cat1], [x2, y2, cat1], ..., [x8, y8, cat1], [x9, y9, cat2],
>> ..., [x34, y34, cat2], [x35, y35, cat3],...]
>> and I don't know beforehand how many diffferent categories there will be
>> or how long they will be.
>>
>> I would like to make a plot like this:
>> ax.plot(a[0:i1, 0], a[0:i1, 1], label=cat1)
>> ax.plot(a[i1:i2, 0], a[i1:i2, 1], label=cat2)
>> ax.plot(a[i2:i3, 0], a[i2:i3, 1], label=cat3)
>> ...
>>
>> where i1, i2... are the indices where the data set changes fomt cat1 to
>> cat2, cat2 to cat3...
>>
>> Does anybody see an easy way of coding this?
>>
>> Thanks,
>> Armando.
>>
>
> Maybe something like this? (Warning: untested!)
>
> from collections import OrderedDict
> b = OrderedDict()
> for index, coords in enumerate(a) :
> b[coords[2]] = index + 1
>
> a = np.array([[c[0], c[1]] for c in a])
>
> prevIndex = 0
> for cat, curIndex in b.iteritems() :
> ax.plot(a[prevIndex:curIndex, 0], a[prevIndex:curIndex, 1], label=cat)
> prevIndex = curIndex
>
> The ordered dictionary may or may not be available in whatever version of
> python you use, but it guarantees the order.
>
> I hope that helps!
> Ben Root
>
>
Ok, thanks Ben, I was thinking that maybe with some numpy array manipulation
there might have been a straightforward way I wasn't seeing.
Armando.
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