[Numpy-discussion] Possible example application of the array interface
Bruce Southey
bsouthey at gmail.com
Wed Apr 6 11:38:37 CDT 2005
Hi,
I don't see that it is feasible to link R and numerical python in this
way. As you point out, R objects (R is an object orientated language)
uses a lot of meta-data. Then there is the IEEE stuff (NaN etc) that
would also need to be handled in numerical python.
You probably could get RPy or RSPython to use numerical python rather
than just baisc Python.
What statistical functions would you want in numerical python?
Regards
Bruce
On Apr 6, 2005 12:10 PM, Michael Sorich <mike_lists at yahoo.com.au> wrote:
> I think that this is a great idea! While I have a
> strong preference for python, I generally use R for
> statistical analyses due to the large number of mature
> libraries available. There are also some aspects of
> the R data types (eg data-frames and column/row names
> for 2D arrays) that are really nice for spreadsheet
> like data. I hope that scipy.base record arrays will
> be as easily manipulated as data-frames are.
>
> While RPy works well for small simple problems, there
> are data conversion limitations between R and Python.
> If one could efficiently convert between the major R
> data types and python scipy.base data types without
> loss of data, it would become possible to do most of
> the data manipulation in python and freely mix in R
> functions when required. This may encourage the use of
> python for the development of statistical routines.
>
> From my meager understanding of RPy:
>
> R vectors are converted to python lists. It may make
> more sense to convert them to an array (either stdlib
> or scipy.base version) - without copying data if
> possible.
>
> R arrays and matrices are converted to Numeric arrays.
> Eg
>
> In [8]: r.array([1,2,3,4,5,6],dim=[2,3])
> Out[8]:
> array([[1, 3, 5],
> [2, 4, 6]])
>
> However, column and row names (or dimnames for arrays
> with >2 dimensions) are lost in R->Py conversion. I do
> not know whether these conversions require copying of
> the data.
>
> R data-frames are currently converted to python
> dictionaries and I don't think that there is any
> simple way to convert a python object to an R data
> frame. This is the biggest limitation of rpy in my
> opinion.
>
> In [16]:
> r.data_frame(col1=[1,2,3,4],col2=['one','two','three','four'])
> Out[16]: {'col2': ['one', 'two', 'three', 'four'],
> 'col1': [1, 2, 3, 4]}
>
> If it were possible to convert between an R data-frame
> and a scipy.base record array without copying or
> losing data, RPy would become more useful.
>
> I wish I understood C, scipy.base and R well enough to
> give this a go. However, this is Way over my head!
>
> Mike
>
> --- Magnus Lie Hetland <magnus at hetland.org> wrote:
> > I was just thinking about some experimental designs,
> > and whether I
> > could, perhaps, do the statistics in Python. I
> > remembered having used
> > RPy [1] briefly at some time (there may be other
> > similar bindings out
> > there -- I don't remember) and started thinking
> > about whether I could,
> > perhaps, combine it with numpy in some way. My first
> > thought was to
> > reimplement the relevant statistical functions; then
> > I thought about
> > how to convert data back and forth -- but then it
> > occurred to me that
> > R also uses arrays extensively, and that it could,
> > perhaps, be
> > possible to expose those (through something like
> > RPy) through the
> > array interface/protocol!
> >
> > This would be (IMO) a good example of the benefits
> > of the array
> > protocol; it's not a matter of "getting yet another
> > array module". RPy
> > is an external library/language with *lots* of
> > features that might be
> > useful to numpy users, many of which aren't likely
> > to be implemented
> > in Python for quite a while, I'd guess (unless,
> > perhaps, someone
> > writes a translator from R, which I'm sure is
> > doable).
> >
> > I don't know enough (at least yet ;) about the
> > implementation of RPy
> > and the R library to say for sure whether this would
> > even be possible,
> > but it does seem like it could be really useful...
> >
> > [1] rpy.sf.net
> >
> > --
> > Magnus Lie Hetland Fall seven
> > times, stand up eight
> > http://hetland.org
> > [Japanese proverb]
> >
> >
> >
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