Okay??
That does seem to work... I guess I'd better go read up on index_tricks.py ?
Thanks.
Alan G Isaac wrote:
>
x1,y1,x2,y2 =np.random.random((4,20))
data = dict(var1=(x1,y1), var2=(x2,y2))
a = np.c_[[d for xy in data.values() for d in xy]]
a
> array([[ 0.66613738, 0.
washakie wrote:
> DataDict={var1:(x1,y1),var2:(x2,y2),var3:(x3,y3)} ; where the x and y's are
> generally lists.
You might be able to use numpy record arrays (recarray). There are lots
of good reasons to use numpy arrays other than plotting.
-Chris
--
Christopher Barker, Ph.D.
Oceanographe
On Fri, 13 Jun 2008, washakie apparently wrote:
> DataDict={var1:(x1,y1),var2:(x2,y2),var3:(x3,y3)} ; where
> the x and y's are generally lists.
> Now that's nice, because I can cycle through the DataDict.keys() to batch
> plot, etc. But how can I convert the whole dict into
> a single array (
Hello, I've started to use the convention of making dictionaries to hold my
datasets. But I haven't settled on an approach yet, and would like input
from people for how they a) handle their arrays of data, and b) how to
create pylab arrays from lists of lists, etc.
What I generally have is:
Data
