On Wed, May 21, 2014 at 12:38 PM, alex <argri...@ncsu.edu> wrote:
> > years = [2004,2005,2006,2007]
> >
> > dates = [20040501,20050601,20060801,20071001]
> >
> > for x in years:
> >
> > print 'year ',x
> >
> > xy = np.array([x*1.0e-4 for x in dates]).astype(np.int)
> >
> > print 'year ',x
>
did you mean that to be "print 'year' xy" I then get:
year 2004
year [2004 2005 2006 2007]
year 2005
year [2004 2005 2006 2007]
year 2006
year [2004 2005 2006 2007]
year 2007
year [2004 2005 2006 2007]
or di you really want something like:
In [35]: %paste
years = [2004,2005,2006,2007]
dates = [20040501,20050601,20060801,20071001]
for x, d in zip(years, dates):
print 'year ', x
print 'date', d
print int (d*1.0e-4)
print 'just date:', d - x*1e4
## -- End pasted text --
year 2004
date 20040501
2004
just date: 501.0
year 2005
date 20050601
2005
just date: 601.0
year 2006
date 20060801
2006
just date: 801.0
year 2007
date 20071001
2007
just date: 1001.0
but using floating point for this is risky anyway, why not:
In [47]: d
Out[47]: 20071001
In [48]: d // 10000
Out[48]: 2007
i.e integer division.
-Chris
> > ==
> >
>
>
> It seems like a misunderstanding of Python scoping, or just an
> oversight in your code, or I'm not understanding your question. Would
> you expect the following code to print the same value twice in each
> iteration?
>
> for x in (1, 2, 3):
> print x
> dummy = [x*x for x in (4, 5, 6)]
> print x
> print
>
>
> > Or is this a recipe to blow up a power plant?
>
> Now we're on the lists...
>
>
> Cheers!
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>
--
Christopher Barker, Ph.D.
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chris.bar...@noaa.gov
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